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How to Think Clearly In The Era Of AI: Full Course (5 Hours)

Nick Saraev · 65,068 words · 296 min read

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Intro

0:00So this video is 5 hours long and by the

0:03end of it you will understand how to

0:05think clearly in a world that explicitly

0:08profits out of you not doing so. I'm not

0:12a big productivity guy. I am a business

0:14owner who shares what I've learned on

0:15the internet. Uh I've made over a

0:17million dollars a year in profit for the

0:19last 3 years and I've made almost $5

0:21million in the last 12 months. I say all

0:24of this because I firmly believe that

0:26once you figure out how to think

0:28clearly, you will learn as well how to

0:30act clearly. And so it is the thinking

0:33clearly that is the foundation behind

0:36being effective in a lot of real world

0:38settings. In my case, you know,

0:39entrepreneurship, but in your case,

0:41maybe something else. So in my view,

0:43over the course of the last maybe 2 or 3

0:44years, AI and other algorithms have

0:47negatively impacted our ability to think

0:49for ourselves. One of the goals of my

0:51course as somebody that talks a lot

0:53about AI is to help people take some of

0:55their ability to think back from these

0:57models and hopefully get to a place

0:59where you can both think deeply for

1:01yourself and achieve the myriad gains

1:04that thinking deeply gives you while

1:06also being able to utilize this

1:07technology effectively because I believe

1:09it does have the promise to be used very

1:11effectively. Now you guys won't know

1:12this if you watch my channel often but

1:14before I went into business I actually

1:16studied behavioral neuroscience for

1:17around 5 years at a research university.

1:19And during this time I worked in a

1:21variety of labs. We performed

1:23experiments on animals to determine how

1:26various things affected their ability to

1:28literally think. In the literature, this

1:30is referred to as their cognition. Uh I

1:32changed stuff like their eating

1:34schedules. I changed who they got to

1:36hang out with. I changed the lighting in

1:38their cages. I changed how they were

1:40trained and so on and so forth. And so a

1:42lot of the principles that I'm going to

1:43be talking about in this course are

1:45taken directly from my time back in

1:47university. Lastly, before we get into

1:49the course, I want to make it clear that

1:50this is not AI slop. Um, I wrote all of

1:52this myself using the same principles

1:54that I'm going to share with you. I had

1:56Claude Fable generate diagrams based on

1:58the data, but all the words are mine and

2:00I poured many, many hours into this

2:02because I frankly think it is probably

2:04one of the most valuable things that I

2:05could share with you. So, without

2:06further ado, let me show you how to

2:08think clearly. First, a lot of these

2:09terms will probably seem kind of

2:11senseless to you at face value, and I'll

2:13do my best to explain them, but you're

2:14going to learn them later on in the

2:16course. There's no way that you can't.

2:18I'm planning on going in depth into both

2:20research and then practical applications

2:22of all this stuff. The whole idea being

2:24that you walk away with both deep

2:26underlying theory which will allow you

2:27to categorize problems in real life into

2:29the bins that I provide you, but also

2:32actionables aka real strategies and

2:34immediately implementable techniques

2:36that you guys could take immediately

2:37after this course to go and solve

2:38problems that you're struggling with.

2:40What I'm going to do is frontload with

2:42the hardware sections of the course and

2:44then finally we'll chat software before

2:46running you guys through those

2:47immediately actionable skills. So here

What this course covers

2:49is the outline of our course. I'm going

2:52to start with the biological basis of

2:53cognition. Then we'll talk about

2:55scientifically defining self-control.

2:57Afterwards we'll talk a concept called

2:59choice architecture. Then I'll discuss

3:02friction in action and behavior.

3:04Afterwards we'll start optimizing our

3:06biology. Then we'll optimize our

3:09environment, our workspace, our virtual

3:11environment, and so on. Then I'll cover

3:13a concept the ancient Greeks talked

3:14about called accasia, which is where you

3:16know something but you cannot do it and

3:18how to solve that. We'll then run

3:20through expected value methodology and

3:22how to use it to accomplish tasks. I'll

3:25then cover local and global maxim, which

3:27is a mental model handed to me by

3:29calculus and optimization math.

3:31Afterwards, we'll cover what is called

3:33attentional residue. I'll talk about

3:35models like the map versus the

3:37territory. Extremely important. You'll

3:39learn about Ulyses or Adysius contracts

3:41for people here that have seen the

3:42Odyssey recently. I'll then talk power

3:45law. I'll talk the chain law. I'll teach

3:47you guys about opportunity cost.

3:49Incentives, what's called good heart. If

3:51you guys haven't heard of Chesterton's

3:53fence, which is a strong thinking

3:54technique, I'll run you guys through

3:56Chesterton's fence. I'll then talk about

3:58Beijian theorem and Beijian probability

4:00theory in natural frequencies. This is a

4:02very strong way to solve problems.

4:05You'll learn firmmy approximates which

4:06are ways of estimating magnitudes and

4:09sizes. I'll run you guys through hourly

4:11rate and offload rules, planning

4:14fallacies, and how to multiply your way

4:16out of them. I'll cover the explore

4:18exploit trade-off, which is increasingly

4:20relevant with AI agents and models. And

4:22then finally, we'll actually cover these

4:24immediately actionable techniques like

4:25taps, noticing. I'll show you guys how

4:28to run what are called premortems. I'll

4:30then show you guys how to use five

4:32minute timers in a very strategic and

4:34tactical way to solve problems using

4:36structured decision-m and then finally

4:38at the end of this course I'm going to

4:39show you guys how to use AI

4:41intelligently and not be overwhelmed or

4:43destroyed cognitively by these models.

4:45Now, that's obviously a lot of

4:47information and because of that, I

4:48should take a moment to discuss how best

4:50to take this course and actually cram it

4:52in your brain because as you guys will

4:54find the sort of meta planning, even a

4:56few moments of that significantly

4:57improves the ability of your brain to

4:59consolidate this information into

5:01something useful over time. So, how do

How to take this course

5:03you actually take this course? Well, I

5:04would recommend you start by watching or

5:07listening to the course passively at

5:091.5x speed. Now, this will obviously

5:11take you a lot of time, but not as much

5:14time as if you played it at 1x. After

5:16you're done, I would watch the course at

5:181x speed. So, that actually slow it

5:20down. After every section, you guys will

5:22find that I've added these action

5:24questions down to the bottom. Now, I

5:27like to do that because quizzes, short

5:29little questions that you answer, force

5:31you to retrieve information from the

5:33various corners of your mind that we've

5:34just stuffed it in. And what you'll find

5:36is encoding or putting information into

5:38the system is quite different from

5:39retrieval, which is getting information

5:41out of the system. It's important that

5:42you experiment and practice both if you

5:45really want to consolidate concepts. So

5:46I'd recommend after you play it back at

5:481x speed, answer those action questions

5:51if you really want to get the most out

5:52of the material. Finally, this entire

5:55document is available just in the link

5:56in the description. So you guys can

5:57download it and then keep it as a

5:59companion guide uh for the short term,

6:01for the long term, for a study partner

6:03or whatever it is that you want.

The biological basis of cognition

6:05So, let's talk about the biological

6:06basis of cognition, shall we? For those

6:09of you guys that don't know, thinking,

6:10it's also referred to as cognition. Uh,

6:12it is a biological process and

6:14understanding that biological process is

6:16very important if you want to learn how

6:18to optimize it. I'm not going to sit

6:20here and then pretend to give you guys,

6:21you know, a biology or a neurobiology

6:23101. So, I'm going to spare you most of

6:25the details and instead I just want to

6:27leave you with probably the most useful

6:28definition I found so far back when I

6:31was pursuing work in a cognitive

6:32sciences lab in university which I I did

6:34not end up getting but this was still

6:36useful nonetheless. Now cognition your

6:39ability to think is composed of three

6:40parts. You have your attention, you have

6:43your working memory and then you have

6:45your executive function. Now put another

6:48way any thought that you have even the

6:50thoughts that you are having right now

6:51as you are watching this course is a

6:53byproduct of three things. The first is

6:55attention itself and a good way of

6:58picturing attention is like a gatekeeper

7:00that lets in a small slice of the

7:03incredible amount of sensory information

7:05that is constantly flooding in from the

7:06outside world. Think things like the

7:09feeling of the headphones in your ear if

7:11you are wearing them or where your

7:13computer is or your wrists on the desk

7:15or the various background noises

7:17outside, wind, flapping of birds, sounds

7:20from your family members, whatever it

7:22is. All of this is currently flooding

7:24into your brain constantly. Yet, you're

7:26not constantly aware of it. Why? Well,

7:29that's because attention is like a

7:31spotlight. Your brain can put that

7:33spotlight on the things that it wants

7:34you to attend to. And so attention is a

7:37gatekeeper like that spotlight that

7:40chooses what it is in our environment

7:41we're actually going to be lighting.

7:44Working memory is the next step. And

7:46that is like a workbench. If you guys

7:48have ever worked with any sort of heavy

7:49machinery or tools, you'll know that

7:51that workbench, you know, can typically

7:53hold a few things simultaneously. And

7:55the whole idea of a workbench is you put

7:58something on the workbench, you work on

8:00it, you get rid of it, you finish it,

8:02and then you put it out away. You clear

8:05the workbench so that somebody else or

8:07let's say you in the future can put new

8:09items on the workbench and then repeat

8:10that process again. That is what working

8:13memory is and that's an excellent way of

8:15conceptualizing it. The next is

8:17executive function. The best way I found

8:19of conceptualizing executive function is

8:22like a foreman or a general contractor

8:24if you guys have experience with

8:25construction. These are the people that

8:28ultimately decide what goes on the

8:29workbench and who works on the

8:31workbench. You have all these things

8:32that are constantly flooding into your

8:34working memory from your attention

8:36because it is the gatekeeper that

8:37permits things. Well, the executive

8:39function is the foreman that decides

8:41what gets thrown out, when you should

8:43stop one task and move to another, etc.

8:46They are the project managers of your

8:48thinking. Now, the problem is the

8:51majority of human beings currently

8:53operate with next to no attention, very

8:56poor working memory, and not very

8:58functional executive function.

9:01In practice, this leads to you feeling

9:03fuzzy all the time. You know, you you

9:05really struggle focusing on anything

9:07that is actually important. You struggle

9:09with carrying an idea through to its

9:10logical conclusion. A lot of the time

9:12things probably feel confusing or

9:14unnecessarily difficult and things like

9:17maybe this course just feel like they're

9:18happening a little bit too quickly. This

9:21often frustrates you constantly and it

9:22also leads to a relatively emotionally

9:24fragile state which I'll cover more in

9:26the course. So, how do you actually fix

9:28this? I mean, it sounds like a pretty

9:30big problem, right? We have attention,

9:31we have working memory, we have

9:33executive function. These are obviously

9:35deep cognitive science concepts, and

9:37you're learning them for the first time.

9:39Just like a video game character creator

9:41screen, you can actually just pour bonus

9:44stats from various hardware and software

9:47optimizations that I will teach you in

9:49this course directly into these skills

9:51of your attention, your working memory,

9:53and then your executive function. You

9:56know, we can find hardware improvements

9:58through things like health optimization,

10:01better nutrition, circadian rhythm

10:03optimization and so on. And then in time

10:06we can distribute these free wins to

10:09parts like your attention, working

10:10memory and executive function to allow

10:12you to level up each of these. Then we

10:14can also take various software wins

10:16which are problem solving techniques and

10:18so on and so forth to also fundamentally

10:20improve your executive function as well.

10:22And that is simply all we are going to

10:23be doing today. I'm going to be going

10:25through like a caveman, finding all the

10:28extra bonus stats that you're probably

10:29leaving on the table, and we're just

10:30going to combine them to make the best

10:32video game character you've ever seen.

10:34So, let's cover a little bit about the

10:35biology behind the brain. Now, if you

10:37didn't already know, the human brain is

10:40extremely expensive. By weight, the

10:42brain makes up around 2% of our total

10:45body weight, but at the same time, it

10:47consumes approximately 20% of our body's

10:50energy at rest. That means that per unit

10:53weight, the brain is actually the most

10:55metabolically expensive tissue in the

10:58entire body. And you can see that with

11:00this graph right over here. Despite

11:03having a small share of body mass, only

11:05around 2% or so. It includes over 20% of

11:10all resting energy usage. And obviously,

11:12this is very disproportionate. A very,

11:15very light organ, but one that requires

11:17a lot of energy to fuel. Now because of

Why your brain is stingy with energy

11:19this incredible amount of energy per

11:21unit, there are two major implications

11:24and frames that I want you to think

11:25about this course through. The first is

11:28that if something is expensive

11:30energetically, then evolution and other

11:32pressures will always force it to

11:34minimize costs and the brain is no

11:37exception to that. That means that the

11:39brain will always prefer a habit to a

11:41decision. It'll prefer, you know, a

11:44guess to a calculation. it'll prefer,

11:47you know, the old to the new and so on.

11:50You can think of this as the brain

11:52budgeting its energy, you know, like a

11:54spreadsheet or something like that,

11:55trying to spend as little energy as

11:56humanly possible, assuming energy is a

11:58resource. Now, many of the techniques

12:00that I'm going to be discussing with you

12:02guys, things like chunking or

12:03implementation intentions, uh, and so on

12:06and so forth, they work because they

12:08exploit this inherent stinginess which

12:10is currently operating by default, but

12:12which you can actually learn to utilize

12:14to think more clearly and be more

12:15effective. Now, much more surprising

12:18than that is that the brain's energy

12:20consumption is actually fixed. What I

12:23mean by this is throughout the day

12:25there's actually no statistically

12:26significant increase in whole brain

12:28energy consumption during difficult

12:30tasks versus simple and easy tasks. At

12:33most any local energy consumption

12:35difference caps out at around 5% or so.

12:39Now this has interesting implications

12:40because it means that from a metabolic

12:42perspective you burn just as much energy

12:44solving a calculus problem and really

12:47racking your brain with it than you

12:49would if you were to just stare at the

12:50window. [gasps] Now, this I think is at

12:54the core of why it makes sense to

12:57improve your ability to think and be

12:58effective because the core reality is

13:01from a metabolic perspective, your brain

13:03is going to be burning those calories

13:04anyway. Why not use those calories as

13:07efficiently and as effectively as

13:09possible? Part of me feels like as an

13:11animal, I have a moral and ethical duty

13:13to use every one of those damn calories

13:15in a way such that I positively impact

13:17the world. And I think that if you guys

13:20understand that perspective, it'll

13:21probably inherently motivate you to

13:22learn how to do that as well.

13:25Now, there's this notion of willpower,

13:27which is the idea that there's a certain

13:28amount of effort you can apply to

13:30thinking, and that it is a naturally

13:31depletable resource.

13:34Well, think about it from this

13:35perspective. Looking out the window and

13:37then doing a bunch of extremely

13:39economically valuable work consumes the

13:41same amount of energy. So, where is that

13:43depletable resource? The science doesn't

13:46actually check out with that

13:47explanation. And I'm going to explain to

13:48you guys in a moment how you guys can

13:49use a better concept of willpower to

13:51actually get things done. Anyway, for

13:54now, just know that the brain is

13:56expensive. It is always on. It's also

13:58very stingy and it budgets its energy as

14:00much as possible, typically by reducing

14:02the total capacity at all times. All of

14:05this puts you under a very strong

14:06constraint or optimization pressure,

14:08which you know, if you want to think

14:10clearly, you have to maneuver.

Working memory and the four-chunk limit

14:13Okay, now that we've covered the brain

14:14in general, let's cover probably the

14:16most important singular component of the

14:17brain that most people would say is

14:20responsible for how clearly you think.

14:22That's called your working memory. Now,

14:25if I asked you to repeat a sequence of

14:2612 random digits immediately, like if I

14:29just gave you a random list of 12

14:31numbers and then had you walk away from

14:33the computer and come back a minute

14:34later and then repeat them, would you be

14:35able to do so? Statistically, no. Very

14:38few people can. Now, it's not because

14:41you're dumb, although that may have

14:42something to do with it. It's because of

14:44the incredibly small and natural size of

14:47a human being's working memory. I'm

14:49going to show you guys how you guys can

14:51increase or improve the size of your

14:53working memory in a moment. The current

14:55consensus in psychology, which is

14:57supported by many, many studies, is that

14:59you can hold approximately three to five

15:02meaningful items in your working memory

15:05at any one moment in time. because it's

15:07a range of three to five. Most

15:09researchers will round this down to

15:10about four. For those in not in the

15:13know, a meaningful item is also referred

15:15to as a chunk. And a chunk is any unit

15:18of information that your memory stores.

15:21For instance, how many chunks would

15:23these letters be? E I L N D A E. Well,

15:31if it's not clear, that is eight chunks

15:34long because it's eight letters. Given

15:36the previous cap on 3 to five items

15:38stored approximately four, statistically

15:40if you were to walk away from the

15:42computer for a second and then come back

15:43afterwards most of you guys would not

15:45actually be able to repeat those

15:46letters. And the reason why is simply we

15:48do not have the working memory capacity.

15:50There are only so many things we can

15:52store on our workbench at once.

15:55But the magic here is the meaningful

15:58part of meaningful items. Now, if you

16:02took those letters above, e i l n d a e,

16:06and then you reorganize them into

16:08something meaningful, you can actually

16:09get a word out of them. For instance, if

16:11you reorganize e i l n d a, you'll find

16:15that putting the letters together

16:16magically, it turns into the word

16:18deadline. Now, if I flash the word

16:21deadline on the screen for just a second

16:23and then I asked you guys a moment

16:24later, hey, what word flashed on the

16:26screen? Not a very tough question to

16:28answer, right? It's the word deadline,

16:30obviously. Of course, I'd get it right.

Chunking and meaning

16:32So, that takes me to an interesting

16:34idea. Why can't you remember eight

16:37letters by themselves like e i l n dae?

16:40But when you organize all of those

16:42letters into a word that it becomes

16:44really easy. Well, it's because of

16:46meaning. Meaning is a layer that

16:48inherently organizes information into

16:50higher and higher levels of abstraction.

16:53Which means rather than store the base

16:54data of E I L N D AE into your working

16:58memory each as an individual chunk, you

17:00can actually just zoom out or reorganize

17:03the information a little bit into

17:04something that makes sense and then

17:05store the entire thing as a single chunk

17:08instead.

17:10Now this continues up the ladder of

17:12abstraction, reducing chunk size the

17:14entire time, which as you get good at

17:16things allows you to store more and more

17:17information in your working memory at

17:18once. Put another way, it allows you to

17:20zoom out and see more of the picture at

17:22once. And as you guys know, seeing a lot

17:25of the picture at once is how you make

17:27good decisions and think clearly. So for

17:30example, let's say I had this sequence

17:33here. You tarindula

17:37data at face value. If you guys are

17:40listening and not watching, we have 22

17:42chunks here, 22 letters. Now, this is

17:44obviously a lot of data and the

17:46probability that you'd be able to

17:47memorize this whole long string of

17:49characters without spending a lot of

17:50time and energy invested on it is quite

17:52low. But if I reorganize that

17:55information, you'll find that those

17:57letters, if put in a specific way,

17:59actually mean quarterly tax deadline.

18:02And to an average adult, we're no longer

18:04at 22 chunks anymore. Quarterly means

18:07something. Tax seems means something.

18:10And deadline means something. which

18:12means we will have transformed these 22

18:14chunks into just three. Now, if I flash

18:18quarterly tax deadline on the screen and

18:19walked away, you'd probably be able to

18:21memorize that and be able to repeat that

18:23back to me in a few moments, right? Of

18:25course. But here's the really

18:27interesting part. You can actually go

18:28one level up and that is where a high

18:30degree of skill becomes important. If I

18:33put the term quarterly tax deadline, not

18:35in front of an average adult, but I put

18:37it in front of a specialized tax

18:39accountant, you know, who has spent

18:41years internalizing the concept of a

18:43quarterly tax deadline. To them, it's

18:47not even three chunks anymore. It's just

18:49one. Why? Because they are now storing

18:53quarterly tax deadline as a concept in

18:56and of itself. A quarterly tax deadline

18:59is not just the combination of three

19:01separate words, quarterly tax and

19:02deadline. It is a thing. It is a

19:05constant reoccurring thing in an average

19:07tax accountant's life. It's something

19:08they're always looking up to and forward

19:10to. They recognize that as a standalone

19:13idea. And that takes me to the following

19:16point. People who are exceptional at

19:19things can typically remember far more

19:21than an average adult so long as they

19:23are in their zone of competence. The

19:25reason why is because throughout their

19:26lives, they've applied meaning to larger

19:28and larger groups of information, which

19:30allows them to chunk larger amounts of

19:32data in any single time. A good example

19:36of this is a chess master. A world

19:38famous chess master can remember the

19:40positions of pieces on a board far

19:42better than you or I can. And it's not

19:45because their brains are inherently

19:46better than ours. They do not remember

19:49any more chunks, so to speak. What they

19:51do is they've simply combined all of the

19:53information into larger chunks

19:55themselves and then they store those

19:57fewer chunks in the same area that you

19:59and I have available to us. Whereas you

20:02might see 32 distinct pieces on a board,

20:05they would see only three or four

20:07distinct patterns and thus can store far

20:10more information with just four chunks

20:12than we can. Another example. Can you

20:16remember the following number?

20:18149217762001.

20:24Well, if I just said that to you guys

20:25and then walked away and came back in a

20:26minute and asked you to repeat it, the

20:28vast majority of you would not be able

20:29to do that. The reason why is because

20:31you're trying to remember 12 individual

20:33chunks.

20:34But for example, what if I told you that

20:37that number was actually just three

20:40chunks.

20:411492, which was the year that Columbus

20:44sailed to the New World, 1776, which is

20:47the year of the American Revolution, and

20:502001, which is the year that the Twin

20:51Towers fell. If I asked you to now

20:54repeat those numbers back to me,

20:56probably be far easier, right? Simply

20:58because you now know 1492, right? That's

21:01the year Columbus made it to the New

21:02World. 1776, right? That's the year of

21:04the American Revolution. In 2001, right,

21:07that's the year that the Twin Towers

21:08fell. I'm doing this obviously for an

21:10Americanric audience. I'm Canadian, but

21:12hopefully you'll bear with me. Okay. And

21:15so, as we see on this diagram here, we

21:18started with 12 items, which was vastly

21:20over our capacity. You know, 1492, 1776,

21:242001. Very, very difficult sort of to

21:26remember it as 14921776,2001.

21:30But because we're now applying meaning

21:32to this information, we're organizing it

21:34in a way that allows us to chunk them

21:35smaller and then store them all on our

21:37workbench simultaneously.

21:39Now, if I told you I was going to quiz

21:40you on this later, uh, you'd probably

21:42remember it for a week or more. And

21:43studies have shown things like that. You

21:46can be shown a long string of characters

21:47or numbers. You can then be told how the

21:50meaning organizes that into some sort of

21:52concept you understand. And a week, a

21:54month, a year later, people can still

21:56understand that information, which is

21:58obviously far more efficient, right? I

22:00mean, could you imagine working three

22:02times as hard to try and store 12 items

22:04in your working memory as somebody else

22:06who just knows a little bit more about

22:07the underlying patterns and facts and

22:09and let's say in this case, history and

22:12can turn them into just three chunks.

22:13Why would you work three times as hard

22:15if you don't have to? Well, this is a

22:16good example of exploiting that natural

22:18energy conservation concept of the

22:20brain.

22:22Now, this is just a very tiny example in

22:24the grand scheme of things. As I

22:26discussed with you guys earlier,

22:27cognition is composed of three parts. We

22:29have attention, working memory, and

22:31executive function. And what we just

22:33discussed together, chunking, is just

22:36one very small and tactical way to

22:38slightly improve the working memory

22:40stat. In reality, there are actually

22:42dozens, if not hundreds of different

22:44ways that you can improve each of these

22:46three stats. High performers in avenues

22:48where thinking is very essential. So,

22:50think things like poker or public

22:52speaking or business, memory,

22:55championships, and so on and so forth.

22:57They will take all of the techniques

22:59that I'm about to show you guys and

23:00apply them across the board in a very

23:02intelligent way so that they can achieve

23:04productivity and thinking gains of well

23:07over the 300% that we just saw with that

23:091492 1776 2001 example. And that's

23:13ultimately where we're getting to. In

23:15addition to talking about what they are,

23:16I'm also going to show you guys how you

23:18can apply them to real problems in your

23:20life. Until then, I want to talk to you

The rats and enriched environments

23:22guys a little bit more about the

23:23hardware to fully flesh out this idea of

23:26what thinking really means.

23:28Now, as mentioned, I spent about half a

23:30decade in behavioral neuroscience. And a

23:32lot of that time was spent volunteering

23:34and later working in laboratories whose

23:37whole goal was to manipulate the

23:39environment of animals, their food,

23:42their cage mates, the other animals

23:43around them, the time of day that their

23:45lights were on or off, uh their

23:47training, and a bunch of other things.

23:49and then immediately after test their

23:51resulting cognitive performance on big

23:54batteries of tests. And so you can think

23:56about this as you know I at the time was

23:58volunteering and then later paid

24:00specifically to analyze what inputs

24:03resulted in clearer or less clear

24:06thinking. And so the key takeaway I got

24:09from that experience was that

24:11counterintuitively rather than thinking

24:12clearly being very hard thinking clearly

24:14is actually quite easy. They're actually

24:17extremely simple and very mundane, but

24:20very powerful interventions that

24:22drastically improve animal performance.

24:24And I guarantee you, you will not have

24:26thought about more than half of them.

24:28And the most powerful and impressive

24:29ones to me were not the ones that

24:31required injections or supplementation

24:34or various drugs or treatments. The most

24:37powerful ones were always things like a

24:40few hours difference in the feeding

24:42times of the animals or which lights got

24:46turned off earlier or later than usual

24:48or which cage mates which other rats or

24:50mice did they get to play around with

24:52before they went to bed. And you'll find

24:55that all of these made a massive

24:56statistically significant difference in

24:59many cases between 30 to 50% of improved

25:01or impacted performance which turned

25:04them into basically different animals.

25:07And it all boiled down to simple changes

25:09that I don't think anybody here would

25:10probably bat their eyes at. These simple

25:12changes impacted their hardware. Now

25:15obviously it'd be unethical to perform

25:17these experiments at large on people.

25:19Okay? Okay, I'm sure some people have

25:20unfortunately, but it would be unethical

25:22to do this sort of thing obviously

25:24unless somebody explicitly opted into

25:25it. But with what limited research that

25:28you know neuroscientists have done, it

25:30is clear that human beings are quite

25:32similar to the animals studied in most

25:33of these experiments.

25:35Small changes in what you eat or the

25:38strength of the lights that you are

25:39exposed to or maybe the people in your

25:41periphery or your friends or maybe the

25:43colors in your environment. Believe it

25:45or not, all of these variables that you

25:47might not have otherwise noticed at all,

25:50if you stack them up, can actually make

25:51a massive difference to your ability to

25:53think clearly over time for your brain

25:56to basically function. Now, I'm going to

25:58run you guys through a bunch of examples

26:00of those in this section and then give

26:02you a big laundry list of all possible

26:04ways that you can optimize your biology

26:06or hardware for the purposes of

26:07thinking. And we're only going to do

26:09thinking in this course, so obviously

26:10you can optimize your biology for

26:11anything these days. Afterwards, I'm

26:14going to give you guys the programs that

26:16I talked about to stretch that hardware

26:17out as much as possible.

26:20So, if you guys didn't know, there's

26:22this very famous 1997 experiment where a

26:24bunch of adult mice were put into what

26:26they called an enriched environment,

26:28which is more or less a cage that

26:29contains more cage mates, a bunch of

26:31running wheels, a bunch of tunnels and

26:33toys, and so on and so forth. when they

26:35were compared to control mice and

26:37control just means like the default the

26:39mice that did not have all of this. Um

26:41what they found is that mice in the

26:43enriched environments showed massively

26:45increased granular cell layer thickness

26:48in an area of the brain called the

26:49dentate gyus which is the area of the

26:52brain that is typically responsible for

26:53new memory formation.

26:56The cool thing is this was achieved

26:57solely through housing. There were no

26:59drugs and no training involved, which

27:01means quite literally the only

27:02difference was that their environment

27:04was more stimulating in a positive sense

27:07than the mice that did not see these

27:08gains. And you can actually see on this

27:11graph here that the granular neurons in

27:14the dentate gyus index to 100 here in

27:16the standard cage were 100. In the

27:18enriched cage, which had all these extra

27:20things that I talked about, we hit 115.

27:24Now, what's important to note here is

27:25that the mice did not have to, you know,

27:27hustle and grind for these improvements.

27:29They did not have to wake up at 5, watch

27:31a bunch of Instagram inspirational Tik

27:33Toks, and go to the gym. Really, they

27:36didn't get more disciplined at all. They

27:38also did not have to watch super

27:39comprehensive courses on how to improve

27:41your hardware and your software. All

27:43that happened was they were by

27:45circumstance put into better enclosures.

27:48And as a result, their brains, their

27:50hardware followed suit and became

27:52better.

27:53Now, a similar study on human beings.

27:55There were 24 architects, uh,

27:57programmers, engineers, managers, just a

27:59bunch of knowledge workers basically

28:01that were put into a fake office for six

28:03full days. These had the exact same

28:06desks. They had the exact same

28:07co-workers as before. And to my

28:09knowledge, they were also doing the

28:10exact same work. The only thing that

28:13differed in that experiment was the air.

28:16how much of it came from outside, how

28:18much CO2 was inside of it, and how much

28:21offging there was, which is something

28:23called volatile organic compounds, which

28:26typically are gassed off of paint,

28:29carpets, furniture, and uh, you know,

28:31things like that, typically when they're

28:33purchased new. Now, every afternoon at 3

28:36p.m., these 24 knowledge workers took

28:39the exact same set of cognitive tests to

28:41evaluate their ability to think clearly.

28:44Well, the shocking result is that on the

28:47days with very clean and well ventilated

28:49air, the scores of these knowledge

28:51workers were literally double what they

28:54were on their normal office days. That's

28:57not 10% better. That is literally

28:59double. And the specific part of their

29:01thinking that improved the most was

29:02their strategy, their ability to plan,

29:05prioritize, and then sequence actions.

29:08All of which are executive function

29:10related. basically their ability to

29:12think clearly. There wasn't a single

29:14person in that room that slept more.

29:16Nobody took supplements or neutropics.

29:19Nobody tried harder. All of these people

29:21literally just breathed slightly

29:23different air and then became twice as

29:25good at certain batteries as a result,

29:28which is kind of nuts, right? And as a

29:30business owner, that's extremely

29:31attractive to me because it means I can

29:33achieve 200% output with the exact same

29:35input. You know, we define that as

29:38leverage. It's free money. If you can

29:40make 200% with a minor change that has

29:42no real other impact on my day-to-day,

29:45why the hell wouldn't I do it? In

29:47general terms, you guys might have also

29:48heard of this concept as lowhanging

29:50fruit. And when you have low hanging

29:51fruit, you should probably pluck it

29:53wherever possible. It's low hanging,

29:54right? That's what I'm going to be doing

29:57with you guys next with zero additional

29:59effort. I want you guys to be able to

30:00output twice as much as you are

30:02currently outputting. Or put another

30:04way, think twice as clearly. So our next

30:07few sections which are on the scientific

30:09definitions of willpower on choice

30:11architecture on friction on hardware

30:14optimization and on environment

30:16optimization you can think of as

30:17basically the human equivalent of

30:19designing a better cage like those

30:21workers were in or like those mice were

30:23in uh compared to their default

30:25counterparts.

30:27Now it's miraculous to me as somebody

30:29that's worked with modifying animal

30:30environments for performance reasons

30:32that human beings have as much control

30:33over our own environments as we do.

30:35Because if you think about it, you can

30:36quite literally design your world. You

30:39can, for instance, choose where to live.

30:42You can buy or build your own home. You

30:45can surround yourself voluntarily with

30:47better cagemates, which are things like

30:49family, friends, competitors, your

30:52spouse, and so on.

30:54When you do this and you actually design

30:57your environment or design your own

30:59cage, you'll find that for at least the

31:01hardware side of things, thinking

31:02clearly becomes way less a question of

31:05being really disciplined and using

31:07various structures to think and to guide

31:09your thinking and more really just a

31:11sense of minor engineering actions that

31:13you only really ever need to make once,

31:15which is when you make the decision to

31:17like move somewhere or I don't know buy

31:19a new house or associate with a person

31:21and not associate with another person.

31:24Okay. And that takes me to the first set

31:26of action questions in our course.

31:29First, what was that 12-digit number

31:31that I asked you to memorize from

31:32earlier? Actually, I want you to sit

31:34with it for a second and think, what was

31:38that 12digit number that I asked you to

31:40memorize from earlier?

31:42Second question is given the experiment

31:43on knowledge workers and CO2/organic

31:46compounds can you guys just off the top

31:49of your head without us going in depth

31:50on hardware optimizations think of any

31:52other biological limiters that you

31:54yourself might be facing and that's just

31:57right now without you having any

31:59extremely detailed list of of steps to

32:02optimize anything come to mind odds are

32:05that thing is probably pretty important

32:06to fix.

What willpower really is

32:08Okay, moving on to willpower. On a

32:10similar level, what the hell is

32:12willpower? Well, most people think of

32:15willpower as a reservoir. Every time

32:17that you use your self-control, they are

32:19withdrawing a small amount from their

32:21willpower reserve. Like, let's say you,

32:24you know, didn't hit snooze this morning

32:25even though you really wanted to, or you

32:28didn't check your phone even though you

32:29really wanted to, or somebody was rude

32:31to you, but you kind of buried it and

32:34were polite instead. The way that most

32:36people conceptualize willpower is that

32:38consumes a little bit of willpower, a

32:40unit here, a unit there. And then

32:42eventually what happens is at the end of

32:43the day your willpower reserve is low.

32:45Maybe because you've had a, you know, a

32:47lot of temptation fighting all day. And

32:49then because it's low, you know, if

32:50another temptation comes around or

32:52something happens that requires

32:54self-control, maybe you're you're more

32:55likely to give up, you know, and at some

32:57point you refill your willpower

32:59reservoir with sleep and then just

33:01refill or redo the process tomorrow.

33:05Now, what's interesting is, have you

33:07ever noticed how some people are capable

33:08of staying extremely clear-minded and

33:10self-controlled, whereas other people

33:13cannot? Why is this? Do you think it's

33:16because they have more willpower? Well,

33:18it's not really. The answer, which has

33:20been backed by a tremendous amount of

33:21science at this point, is not that some

33:23people have more willpower than others.

33:25It is that the people that you think

33:27have more willpower simply never have to

33:29fight the same level of temptation that

33:31you do in the first place. What I mean

33:33by this is people that maintain clear

33:36thinking and strong self-control usually

33:38just do not put themselves in situations

33:40where they have the opportunity to make

33:41a mistake at all. If you think about it

33:44logically, if you cannot make mistakes

33:46at all because that is not one of the

33:48possible moves available to you, like in

33:49a video game or a chessboard, well, news

33:52flash, you're probably going to make

33:53fewer mistakes, right? Because you

33:54simply can't make the move that leads to

33:56a mistake.

33:58Think bowling with the guardrails up. If

34:01you bowl with the guardrails up, landing

34:03in the gutters is simply not one of the

34:04possible mistakes. I mean, I guess it is

34:06technically a possible mistake, but

34:08damn, you'd have to screw up really hard

34:09to make it in the gutter. What happens

34:11when you bowl with the guardrails up is

34:13if you bowl and you're just a little bit

34:14off to a side, you knock off a guardrail

34:17and eventually end up virtually

34:19somewhere in the neighborhood of hitting

34:20the pin that you want.

34:22Now, in a similar vein, it turns out

34:24that the majority of the effort involved

34:25in resisting temptation or avoiding work

34:28that you have to do or some sort of

34:30similar issue like that really just

34:31boils down to you having to adjust to do

34:34work at times that are maybe less

34:38effective or profitable for you. To do

34:41things outside of a regular schedule. to

34:44do things at times that are closer to

34:45the end of the day when your quote

34:47unquote reserves have fallen low than at

34:49the beginning of the day when your quote

34:50unquote reserves are still high. I want

34:53to give you guys an example of this. A

34:55person that doesn't check their phone in

34:56the meeting, for instance, would

34:58commonly be referred to as resisting

34:59temptation. And that's good for them,

35:02right? But if you think about it

35:03logically, a lot of people don't check

35:05their phones during meetings. Do you

35:07know how most people do it? They just

35:09don't have their phones on them in the

35:11meeting. The people that don't check

35:12their phones in the meetings, that have

35:14them in their bags, constantly have to

35:16fight the temptation of pulling out

35:17their phone to check a text message or

35:18write something down. Whereas the people

35:20that simply do not have phones on them

35:22whatsoever, well, they never have to

35:23fight that temptation. Their phone is,

35:24you know, three doors down. It's

35:25impossible to get it without making a

35:26total ass of yourself.

35:29Basically, the people that don't check

35:31their phone in this example because they

35:33don't have their phone on them, they

35:34have adjusted and built their

35:37environment such that temptation never

35:39shows up in the first place. And this is

35:41a very small example of much larger

35:43sweeping lifestyle changes that I'm

35:45going to run through with you. Now, to

35:47be clear, this is probably not what is

35:49going on in your brain under the hood.

35:50There probably is not actually a

35:51reservoir of willpower. It's not like

35:53you're using up energy every time you

35:54say no to something. As mentioned, we

35:56use approximately the same amount of

35:57energy when staring out the window or,

35:59you know, working on a task. But I want

Asymmetric bets

36:01to introduce a concept to you today

36:03called asymmetric bets. If you assume

36:05that your willpower was limited and then

36:07acted according to that philosophy, that

36:10would probably lead you to reducing

36:11temptations more. Right? So even if you

36:14are wrong, you will have built yourself

36:16a better environment and probably some

36:18extra capacity now. Similarly, if you

36:22assume that your willpower was unlimited

36:23and that you could just rely on it every

36:25time because you're a badass MF, right?

36:28Well, you will fail in front of

36:29everybody at the worst possible time

36:31simply because that is the modus

36:33operandi with which you have lived your

36:35life. So logically then if you have

36:37possibility to believe one thing or the

36:39other thing and one thing leads to a

36:41universe where you are better off aka

36:43you resist temptation less because you

36:45just do not have the opportunity to

36:46resist temptation and the other one you

36:48resist temptation more which leads you

36:50to screwing up every now and then.

36:51Shouldn't you believe the univer believe

36:54in the story that results in the

36:55universe where you do not have to resist

36:56temptation at all? Obviously, right?

36:59This is a concept known as instrumental

37:01rationality, which we'll cover a little

37:03bit later. But basically, it is where

37:05you choose the most effective and useful

37:06belief system to achieve a goal, even if

37:08it slightly differs from reality. The

37:11takeaway is do not build resisting into

37:14any of the plans that you come up with.

37:16If one of the steps in your proposed

37:19plan, which we'll be doing a lot of

37:21later on, is you know, I just won't do

37:24that bad thing that I always do. Well,

37:26it's not a plan. It is a hope and it is

37:28quite unrealistic at that. Instead of

37:32eliminating X completely, what you

37:33should aim to do is just reduce X by

37:36reducing your access and opportunity to

37:38abuse X. If you remove some sort of

37:40temptation entirely, it will naturally

37:42go down for free and you will think more

37:44clearly as a result. Now, in terms of an

37:45actual immediately actionable example

37:47that you guys can do right now while

37:48watching this course to gain an

37:50additional 10 to 20% out of it, you guys

37:52probably have your phone in the room

37:53right now. And some of you may actually

37:55be listening or watching to this course

37:57on their phones. Now, by doing so, you

38:00are increasing the probability of

38:02picking up your phone for whatever

38:03reason and getting distracted by an

38:04order of magnitude, which is 10x or

38:06more. What I'd recommend you do right

38:09now is if you are watching me on the

38:12computer and your phone is somewhere in

38:14your periphery, I'd recommend you

38:16actually stop, go grab your phone, pick

38:18it up, move it to another room, and then

38:20place it somewhere where it isn't

38:21directly in your periphery. And if you

38:23are listening to me while on your phone,

38:26because this is your only access to

38:27media, then I would recommend you swipe

38:29down from the top, go to the do not

38:31disturb button, or the equivalent,

38:32depends on your operating system, and

38:34turn that on. If you just do that one

38:36thing right now, if you pre-commit, you

38:38will get 10 to 20% more out of this

38:40course. Imagine if I had two options

38:43available to you, kind of a red pill or

38:45blue pill like in the matrix. And on one

38:47hand, I had a dollar and on another hand

38:49I had a $110 and I said, "Hey brother,

38:52which one do you want? Do you want the

38:53dollar or do you want the$110?" What

38:55would the logical thing be to do in that

38:58scenario? It would obviously be to be

39:00like, "Hey, give me the freaking

39:01dollars." Obviously. Well, that is what

39:04I am offering you right now. You have

39:05the ability to design the future few

39:08hours that you will be listening to this

39:10and to maximize your engagement and

39:12minimize your distractability during

39:13that time period. And so, this is a

39:16great example of a bunch of techniques

39:17that we're going to line up back to back

39:19in order to help you think more clearly

39:21and get more done. But I'd recommend

39:23that you do so right now because if you

39:25do so, you won't be serendipitously

39:26distracted by like a rogue notification

39:28flavors. Yeah. You won't be randomly

39:31distracted by a friend of yours texting

39:32you a funny meme on Instagram, which you

39:34have because the damn default

39:35notifications always blow up your phone.

39:37You know, you won't have a little

39:38buzzing constantly occurring in the

39:39background, which pulls five or 6% of

39:41your cognitive capacity away from you

39:42like we'll learn about in the hardware

39:43optimization section. [sighs and gasps]

39:45Can you think of a freer? You're

39:47literally picking up a 100 gram object,

39:49moving it 10 meters to the right, and

39:50then immediately being 10 or 20% more

39:52effective. Okay, another good example of

39:55this which my family would probably hate

39:56is that I used to smoke weed uh mostly

39:59in social settings luckily and I did not

40:01really like what weed did to me. You

40:03know, I was I grew up in a British

40:05Columbia, you know, Vancouver. So I was

40:06I was smoking that BC bud for anybody in

40:08the know and I grew up in East Van. Um

40:10so there was a lot of it an abundance,

40:12let's say, in my periphery. So I tried

40:15many times after, you know, picking up

40:16the habit with my friends at parties and

40:18stuff like that to just quit many, many,

40:20many times. But I didn't really know

40:22half of what I know now. And back then,

40:24I tried to quit every time based on my

40:27willpower. Not shockingly, every one of

40:30my attempts failed. You know, I would do

40:32pretty well for like a week or two

40:34saying no and no and no. But then

40:36finally, one random night, I'd go with

40:37my friends and maybe I'd be a little bit

40:39sleepd deprived. Maybe I wouldn't have

40:40been entirely in my best state and

40:42somebody would have some weed on them

40:43and they'd offer some to me and then

40:44next thing you know, I was smoking.

40:47So eventually I identified a rule and

40:50the rule was when I hung out with person

40:52X or person Y, I would lead to smoking

40:55weed. And then when I did not hang out

40:57with person X or person Y, I would not.

41:00So logically, me being a, you know, I

41:03don't know, bright 18 or 19-year-old kid

41:05thought, hm, I wonder, can I use this

41:08rule not to smoke weed anymore? So what

41:11I did is I just stopped hanging out with

41:12the people that smoke weed. And

41:13miraculously, I stopped smoking weed.

41:15And it's been a hot minute, quite a

41:17while since the last time I did. If you

41:19think about it, this is a very simple

41:21and minor example of a deep part of me

41:23not wanting to engage in a habit that I

41:25had picked up just by happen stance that

41:26I then felt chained to for for quite a

41:28long time. We all have the ability to do

41:31so. We simply need to stop and observe

41:33and notice, which I'll cover in the

41:35software uh section, various things in

41:37our periphery that tend to lead to

41:39actions that we do not want. The second

41:41you've established an if then rule,

41:43everything becomes very very easy. So

41:46the key pattern is I put the work in

41:48before I got tempted, not during the

41:50temptation. I could have come up with a

41:52variety of things to say, maybe like I

41:54tell my friends, no, not tonight, guys.

41:56I got to wake up early tomorrow. But

41:58that works far less effectively than

42:00just building a rulein to eliminate the

42:02possibility of temptation in the first

42:04place.

42:06It sucks that we stop hanging out, by

42:07the way. you know, some of these people

42:08are pretty cool, but obviously my life

42:10is way better off. And I think that's a

42:11core thing to understand. Like, do you

42:13want your life to be better off or do

42:15you want to be dragged down to the level

42:17of everybody else? I don't necessarily

42:19want to do things like that. Um, maybe

42:22if you zoom out on a deep level, I don't

42:25want to. Maybe on a superficial level

42:27when I'm tempted and so on and so forth,

42:28I do. But I obviously like the deep

42:31version of myself more and that's

42:32ultimately who I'm I'm looking to better

42:34and self-actualize. So if you find your

42:35guyselves in similar situations, that's

42:38a very simple and easy hack to do. Okay,

42:40let's think of some action questions.

42:42Think of the last time this week that

42:44you lost to some sort of temptation.

42:46Maybe it is your phone. Maybe it is your

42:48food. Maybe it is skipping your workout.

42:50Whatever it is for your particular

42:51challenges. Was there a way that you

42:53think you could have reorganized your

42:55environment to avoid you doing the thing

42:56that you did not want to do? I'll give

42:59you guys an example. I had some junk

43:00food in the house because my girlfriend

43:01and I bought a bunch of these wonderful

43:03creamy all-d dressed potato chips from I

43:05think Miss Vicky's. And these things are

43:07incredible. They are so good. But one of

43:10my goals was not to eat these sorts of

43:11extremely ultrarocessed potato chips.

43:13Well, anyway, we had bought it earlier

43:15on in the week because we were

43:16celebrating something. I just got hungry

43:18one day. I opened up the cabinet and

43:20there it was. I ate it. If I had not had

43:22that at home, I obviously logically

43:24would not have eaten that bag of chips,

43:25right? I would not have just downed

43:261,200 calories worth of probably the

43:28most ultrarocessed fat known to man. Now

43:30listen, I'm not saying you have to, you

43:32know, live your life like a freaking a

43:34sack. You really don't. You can enjoy

43:35your life and have fun. And it's not the

43:37first time I had a crazy bag of chips.

43:39Not the last time. But the end result is

43:42I ended up doing something I didn't want

43:43to do, not because of intention, simply

43:46because of my environment. So why not

43:49only do the things that I actually want

43:50to do? And I have the power to do the

43:52things that I want to do. If I did want

43:54to have that bag of chips, I could have

43:56reconstructed my environment such that I

43:58got them when I wanted them, but I did

44:00not. So, at some level, a dumber,

44:04younger version of me or somebody else,

44:07the manufacturer of the chip, you know,

44:09and so on and so forth, essentially made

44:11me do something that I did not entirely

44:13want to do. So, think about an example

44:15like that from your own life. Do you

44:17have any? If so, consider them. Now,

44:18next, find some step in your plans that

44:21depends on you resisting something in

44:23the moment. Rewrite that step so nothing

44:26needs resisting at all. Maybe instead of

44:29you, I don't know, coming home from work

44:31or something and then having a big fat

44:34candy bar, remove the ability that you

44:37have to do that in the first place. So,

44:39let's talk phones. What is a phone

44:41really? Well, initially it was a tool

44:43used for making phone calls. Then it

44:46expanded into a tool used for both

44:47messaging and making phone calls. But

44:50eventually it exploded into a basically

44:52general purpose computer that could do

44:54everything from check your GPS route to

44:56video conference your friends to take

44:58photos and post them and more. How about

45:01social media? Social media initially

45:03started as a simple tool for messaging

45:05your friends. Think things like AOL chat

45:07rooms, IRC, and so on. Eventually, in

45:09the pursuit of increased functionality,

45:11it became a tool used for both messaging

45:12and then posting updates. Think things

45:14like MySpace with like your original

45:16pages. Eventually, like everything else,

45:20it exploded into an everything app where

45:22you can play games and you can even buy

45:24furniture. Have you ever asked yourself

45:26the question, who came up with all of

45:28that and why? Well, the unfortunate

Nobody is designing this for you

45:31reality is virtually all of the

45:32decisions around your virtual

45:34environment and your physical

45:35environment were made by other people

45:38for the express purpose of consuming

45:40more of your time, typically in an

45:43unproductive way. Think about it

45:45logically. You don't need to be able to

45:48play Farm Simulator 2000 on Facebook, do

45:51you? No. So, why does it exist? Well,

45:55it's because there was some smart person

45:57on Facebook's team that noticed that

45:59having games embedded in their little

46:00message box increases the average user

46:03time spent by, you know, 10% or 17% or

46:0625% or something. If you think about it,

46:09the vast majority of the time that you

46:10do something on the internet and really

46:11life in general, it is a decision that

46:14somebody made for you. This is called

Choice architecture

46:17choice architecture. Now, this term was

46:20coined in a book called Nudge. Really

46:22good book if you guys haven't heard of

46:23it before. And it basically means the

46:26way that you present options or the way

46:28that options are presented to you

46:31influences which options are chosen.

46:35Put another way, there is no single way

46:39to neutrally present more than one

46:42option. Anytime that you give somebody a

46:45choice between X or Y or A or B or C, in

46:49some way, shape or form, you will always

46:50be influencing their behavior logically.

46:54A good example of this is a cafeteria

46:55manager. A cafeteria manager can

46:57actually fundamentally change what

46:59people eat. Not by taking anything off

47:01the menu entirely, but simply by

47:02changing the way in which the food is

47:04presented or the story is shaped. For

47:07instance, if you have two items, a

47:09healthy bowl and then an unhealthy

47:10burrito. If a photo of the healthy bowl

47:12looks like crap and the photo of the

47:14unhealthy bowl, unhealthy burrito is

47:17high quality and attractive, people will

47:20eat way more of the unhealthy burrito.

47:22And if you think about it, that's a

47:24massive responsibility on behalf of the

47:26cafeteria manager because over 10 years

47:28or 20 years or 30 years or even 50

47:30years, that single action could

47:33theoretically lead to hundreds of times

47:35more heart attacks, strokes, deaths, and

47:38so on and so forth. If this is a really

47:40busy cafeteria with several hundred

47:42people visiting every day and you've

47:44nudged them even 30% more towards a very

47:47unhealthy food option or something like

47:49that, obviously people are going to eat

47:51way more of it and as a result screw

47:53their bodies up and that obviously has

47:54consequences, right? So what I mean to

47:57say here is that you are being

48:00manipulated constantly. Even the

48:02algorithm that led you to my video here

48:04today was in part some sort of

48:06manipulation.

48:08Now, in rare cases like the one that you

48:10guys currently have, manipulations can

48:12be positive and they can end up

48:14improving your life. But that is the

48:16exception and that is not the rule. The

48:18vast majority of the time, the 99.999%

48:20of the time, manipulations are actively

48:22detracting from your ability to think

48:24clearly because your ability to think

48:25clearly is tied to your ability to set

48:27intentions and then reason through those

48:28intentions. But if you are being led not

48:30by your own intentions, but by somebody

48:32else's, obviously you're not being led

48:34to your own ends. You are being led to

48:35someone others. A great example of this

Defaults and organ donation

48:38um from like a sociological perspective

48:40is organ donation. Some European

48:43countries run optin systems where you're

48:45not a donor unless you actually register

48:47to become a donor and then other ones

48:49run opt out systems which are where you

48:51are automatically a donor unless you

48:53register out of it. Now they compared

48:55the two groups of countries back in 2003

48:57and found an insane difference in total

49:00organ uh uh essentially defaults. Now in

49:03Germany which is an opt-in country only

49:0612% of people were registered as donors.

49:08In Austria which is right next door and

49:10which was an opt out uh uh region 99.98%

49:14of people registered to be an organ

49:16donor. Every single opt-in country was

49:19around 28% or less whereas every single

49:22opt out country was around 85% or more.

49:27And if you think about it, that is one

49:28of the clearest examples of how

49:30impactful choice architecture can be.

49:32These governments simply made a choice

49:34really early on. Should we default

49:36people into organ collection or should

49:38we allow people to make the choice about

49:40whether they want their organs collected

49:41or not? You know, basically opt in. The

49:43countries that said opt in have

49:45virtually no organ collection. The

49:47countries that say opt out have

49:48virtually all of the organ collection.

49:50And it is a hell of a power law

49:52difference here, which I'll cover later

49:53on. Now, these are societal level

49:55choices that are being made for you. And

49:57it shows clearly how much a single line

49:59on a piece of paper can impact things

50:00like your organ availability or more

50:03what people will do with your body after

50:04you die. And that takes me to this

50:07concept of default. If you think about

50:09it, autoplay is a default that is

50:12selected and defaulted to because it

50:13increases your watch time. Notifications

50:16on your phone are a default because they

50:18are selected to increase the total

50:20number of times you open an app.

50:22pre-selecting an annual plan when you

50:24are shopping around a SAS that is done

50:26to increase the total amount of money

50:28that you spend and your ultimate

50:30retention or churn and putting candy by

50:33a checkout is done to maximize the

50:35number of people who ultimately impulse

50:37buy because they're saying well I

50:39already got all that healthy stuff when

50:40I just throw in some candy too. It is

50:43not illegal right now to do this. It's

50:45just designing an environment in the

50:47service of a KPI. The issue is it's just

50:51not your KPI. Now, I don't mention any

50:54of this because I want to freak you the

50:55hell out or mislead you. I just want to

50:57offer a new lens to look at the world

50:59through. Next time that you're presented

51:01with some sort of choice, okay, just ask

51:04whose interests are being served by this

51:06choice. You know, if you have a choice

51:08between A or B, is that a choice you

51:11need to make at all? When you get a

51:13phone and all of your notifications are

51:15automatically defaulted to on, or you

51:17get a new Windows PC and you have a

51:18bunch of game apps that are auto

51:20pre-installed, why are they auto

51:22pre-installed? Why is all of that stuff

51:24set up the way that it is to begin with?

51:26It's not like phones evolved. There's

51:28something that a person put together.

51:30Same thing with Windows PCs. The reality

51:32is there's a complicated interconnected

51:34web of incentives at play, but the harsh

51:37reality is most of those incentives are

51:38not for you. They're against you.

51:42Now you can use this knowledge to design

51:44your own life. As mentioned, you guys

51:46can build defaults yourselves that

51:48overwrite the typical defaults of

51:50corporations and big organizations. And

51:52in doing so, you can have a lot more

51:54control over what it is that you do on a

51:56day-to-day basis. The math is very much

51:58in your favor. And it's another clear

52:00example of leverage if you think about

52:02it because you only ever have to make

52:04the decision one time while very

52:06clear-headed, maybe on a, you know,

52:07Sunday morning after you've had your cup

52:09of coffee. And despite you making that

52:11decision once, it will continue to pay

52:12dividends even, you know, at every other

52:146 a.m. morning when you don't get a lot

52:16of sleep, you're tired, you're lazy,

52:18maybe you're a little less caffeinated,

52:19whatever. The point that I'm making is

52:21you can make a default decision right

52:23now when you're in a strong state of

52:25mind and then force all future instances

52:28of you to do the default decision and

52:30basically just treat that as how things

52:32are.

52:34Okay? So, you know, if a default is set

52:36by a company and you do nothing, you get

52:38what they want. But if you set a default

52:41and you do nothing, you get what you

52:42want. So, maybe your laptop

52:44automatically opens the tab that you

52:46were on yesterday. And you know, usually

52:48before you go to bed, you're on some

52:50sort of entertainment website or social

52:52media. What that means is the default is

52:54when you go to your laptop in the

52:55morning, you are now seeing a bunch of

52:58social media. If there were two

53:00universes, one where you know you had

53:02that tab open and then another where you

53:04had a tab open with your work on it. You

53:06which of the two universes do you think

53:07you would do more work? Obviously the

53:09one where your tab is open with the work

53:11on it, right? You have the ability to

53:13control that. Tabs reopening are not a

53:16default setting. That is something that

53:18the people that designed these browsers

53:20did because they want to keep you on

53:21them for longer. Likewise, maybe your

53:24refrigerator is organized so that the

53:26worst snacks are at eye level. And so

53:28every time you open it, they're

53:29literally the very first thing that you

53:30see. Now, that is a default that you

53:33yourself probably unknowingly created.

53:35But it's also a default that you can

53:36change. How about your calendar, your

53:38virtual environment? Maybe it's bookable

53:4024/7, and the reason is you just never

53:43set your working hours, and that results

53:45in a variety of annoying ass

53:46notifications that come in throughout

53:47the day, and a bunch of people that come

53:48in and steal your time. Well, you have

53:50the ability to control that and change

53:52that right now. So, all these are

53:54defaults. They take you maybe a few

53:56moments, but the cool benefit here is if

53:58you change them, you get repeated gains

54:01literally every day until you die or

54:03until the company claws back that claws

54:04back that default.

Finding the defaults in your life

54:07How do you actually identify all the

54:08defaults in your life? Since obviously

54:10this is a okay list, but it's not an

54:12exhaustive one. Well, I use the

54:13following diagnostic tool to do this.

54:16For every transition in my day, I just

54:18ask myself, what happens if I do

54:20nothing? So for instance, at 5:00 a.m.

54:23in the morning when I access my

54:24computer, what happens by default if I

54:27do nothing? So a good example of, you

54:30know, environment design is what I have

54:32done to my computer at 5 a.m. when I

54:34access my computer. I open it up. There

54:36are no additional applications on my

54:38screen except for Chrome. So I will

54:40double click on Chrome. I then look at

54:42my bookmarks bar, which includes links

54:43to all of the work laid out in serial uh

54:46capacity. Literally 1 2 3 4 5. I then

54:49click one and then it opens the page

54:51that I have to start doing my work on.

54:53If I try and access any sites outside of

54:55these, my browser will actually block

54:57them until 3 p.m. So, what I mean by

54:59this is that that's a transition state

55:01for my day, right? I went from waking to

55:02working. What happens by default if I do

55:05nothing in this situation? Well, I work.

55:07I physically can not work. I basically

55:09have, if you think about it, gone onto

55:12like some sort of Wet n Wild tube ride

55:15or something and, you know, I've gone up

55:17to like the slide and I've entered the

55:19slide and the slide takes me to the end

55:22destination and there's nothing I can do

55:23about it. The cool thing is I'm the one

55:25that architected that slide and I'm the

55:27one that made it how I wanted it to be.

55:30as opposed to entering somebody else's

55:31slide which maybe had a lot of

55:33entertainment on it or distractions or

55:35things that reduced my capacity for

55:36attention, working memory or executive

55:38function. I got to do all of this

55:40myself.

55:42Similarly, since my phone is not in my

55:44room, you know, if I do nothing, I

55:45cannot check my phone easily without

55:47physically getting up and going

55:48somewhere else. Which if you think about

55:50it means that my default if I do nothing

55:52is I have very low usage of my phone.

55:54This graph here is quite important

55:56because if you notice that when you do

55:58nothing you achieve an outcome that is

56:00beneficial for somebody else like a

56:02company odds are that default is

56:04something that you need to change. Now

56:06if you do nothing and then you achieve a

56:08positive outcome that you like odds are

56:09you have in some way shape or form

56:11shaped that default and that is okay. So

56:14some action questions look at the last

56:1524 hours and list every point at which

56:18something happened because you did

56:19nothing. For instance, what did you

56:21open? What did you eat? What did you

56:24check? Ask yourself which of those

56:26defaults did you set and which ones did

56:28a company or an organization that is

56:30incentivized to make money off of you

56:32and your time set instead. Next, pick

56:35the single default that cost you the

56:37most each week and write down the

56:39one-time change that would change that.

56:42When will you make that change? By the

56:44way, I'll run you through a bunch of

56:45great ways to make changes in a moment.

Friction, the golden rule

56:48Okay, one final point before we begin

56:50the optimization of our hardware. The

56:52golden rule of this whole course, if you

56:54think about it, at a meta level, is

56:55friction. I've been dancing around that

56:57word for the last maybe 30 minutes or

56:59so. I say 15 here, but it took a little

57:01longer than I was expecting. But it's

57:03worth us clearly defining it before we

57:05move on. The way I define friction is

57:08it's a cost between a person and a

57:10behavior. This typically means an extra

57:12click. It means an extra step. Means an

57:15extra 10-ft walk down a hallway. Means

57:17having to put in an extra password, and

57:19so on and so forth. A great example of

57:21this is if you, a person, wants to go to

57:24the gym, which is a behavior. Friction

57:26is anything that makes it harder for you

57:28to go to the gym. For instance, your

57:31distance from the gym, like where you

57:33live versus where the gym is, that is

57:34friction. If you go to sign up to the

57:37gym, but the signup portal bugs out,

57:39that is friction. If there is a physical

57:42cost which is a little bit higher than

57:43you were anticipating, that is friction.

57:46In general, if you want to decrease a

57:48behavior, what you do is you add

57:49friction. If you want to increase a

57:51behavior, what you do is you remove

57:53friction. Because your brain, as

57:55mentioned, is extraordinarily energy

57:57conservative and it wants to conserve

57:58energy wherever possible because it

58:00consumes 20% of the entire body's energy

58:01reserves. It will do the rest. You

58:04simply need to make something a little

58:05bit harder and make the other thing,

58:07presumably the thing you want to do, a

58:08little bit easier. And your environment

58:10will start shaping your choices without

58:12you even noticing.

58:13The most important point about friction

58:15is that it is proportionate. For

58:16instance, the size of the friction

58:18scales typically with the size of your

58:20opportunity to engage in the behavior.

58:22So if you make something maybe three

58:23times as hard to do on average, you will

58:26do it maybe three times less. If going

58:28to the gym is now three times easier

58:31because maybe the gym has moved three

58:32times closer to you or maybe because I

58:34don't know you have a friend that picks

58:35you up in the morning and actually

58:36drives you and drops you off there like

58:37I used to have um then you will do it

58:39far more often. A good example of this

58:42is friction in food consumption. If you

58:43guys think back to our cafeteria example

58:45where we had a good-looking photo and

58:46then a bad looking photo of a bowl and a

58:48burrito and that impacted the uptake of

58:50food. Lots of studies have been done on

58:52the exact same idea except instead all

58:55about applying friction. What I mean by

58:58that is making something easier or

59:00making something a little bit harder. So

59:03in one of these studies they changed the

59:04distance of three foods in a cafeteria.

59:07There was a bowl of cherry tomatoes.

59:09There was a bowl of peas and then there

59:11was a bowl of carrots. Aside from that,

59:13they didn't change the signage or move

59:15any of the food at all. Here are some

59:18results. When they moved the cherry

59:19tomatoes 10 in further away, consumption

59:22of all cherry tomatoes dropped 9%. That

59:26means that by moving the cherry tomatoes

59:28literally less than 1 ft further from uh

59:31where they were before, people consumed

59:33approximately 9% less. When the peas

59:36were moved 10 in away, consumption

59:38dropped 13%. When the carrots were moved

59:4110 in away, consumption dropped 9%.

59:44Then the researchers went as far as to

59:46replace the serving utensils for the

59:48peas from a spoon, which is quite easy

59:50to use to grab peas, to tongs, which are

59:52hard to use and you can't really get too

59:53many. Total consumption of peas dropped

59:5616.5%.

59:58Now, this is a massive effect. Not to

1:00:00mention, all of this took only a few

1:00:02seconds to actually implement, right?

1:00:04Because look at this graph here. You

1:00:05could see food taken on baseline. The

1:00:08spoon at reach obviously allowed for

1:00:10baseline consumption. When you move

1:00:12something at 10 in, it reduced it by

1:00:1413.4% 8.9%. And then when you replaced

1:00:17your spoon with tongs, it reduced it by

1:00:1916.5%.

1:00:21All of this is pretty crazy to me.

1:00:23Here's a quote from an essay that was

1:00:25written back in 2009 by a really smart

1:00:27guy, uh, Scott Alexander. And I

1:00:29personally think about this quote all

1:00:30the time. The point is that you don't

1:00:32have to make things impossible to make

1:00:34them not happen. You just have to make

1:00:36them inconvenient. Even a trivial

1:00:39inconvenience, one that takes a second

1:00:41or two, is enough to stop the majority

1:00:43of people the majority of the time. So,

1:00:46what does this mean? Have you guys ever

1:00:48been in the following situation where

1:00:50you decided not to open an application

1:00:53because it signed you out? Have you ever

1:00:55not read some sort of report because

1:00:56maybe it was attached as an attachment

1:00:58or PDF rather than in the body of an

1:01:00email or an easy to click link? Or maybe

1:01:03have you ever not worked out because you

1:01:04went to your bag and then found that you

1:01:06just didn't have the stuff inside of the

1:01:07bag or you didn't have your shorts on or

1:01:09something like that? Realistically, none

1:01:11of these are real barriers. Like would

1:01:13this stuff have stopped Kangaskhan from

1:01:14conquering the known world? No, probably

1:01:16not. But they all still worked on you. A

1:01:20good model to internalize is that your

1:01:22mind is always calculating the startup

1:01:24cost to do anything in your environment,

1:01:26also known as the friction. So if you

1:01:29add or remove even a second of friction

1:01:31from a process, you can over a long

1:01:34enough time change your life completely.

1:01:36Like we talked about in the first

1:01:37section on the biological basis of

1:01:39cognition, executive function is very

1:01:41very expensive. You know, your working

1:01:43memory is also quite small, and you guys

1:01:45only really have enough space to attend

1:01:47to a couple of things in your

1:01:48environment at any one point in time.

1:01:50What that means is your brain, which is

1:01:52always looking for a way to minimize

1:01:53costs, will always default to not now as

1:01:56the most efficient option as opposed to

1:01:58the let me figure out how to take the

1:02:00first step option.

1:02:02The crazy thing is from the outside, it

1:02:03all looks like discipline. You know,

1:02:06when I used to be really poor, I would

1:02:08look at people that were making 10K a

1:02:10month or 20K a month or 15K a month or

1:02:13maybe even 100K per month, and I would

1:02:14always think, you know, these people,

1:02:16they're a different species. They're

1:02:17just built different, and I'll never be

1:02:19able to catch up. I looked at how much

1:02:20time and effort it took me to make

1:02:22$2,000. And then I looked at the guy

1:02:25making $10,000, and then I went, there's

1:02:27no way. I mean, that's five times the

1:02:29work. That's impossible. The harsh

1:02:31reality is those people are not doing

1:02:33five times the work. In fact, many of

1:02:35them were probably doing half of the

1:02:36work that I was doing, maybe even a

1:02:38quarter of the work that I was doing.

1:02:39The main difference was they had

1:02:41designed their environment to be able to

1:02:42do the things that actually make them

1:02:43money really easily and automatically.

1:02:46Whereas I, I was a door-to-d dooror

1:02:48salesman at the time, um, had to get up

1:02:50and push through a slog every single

1:02:52day. Many of the times when I would have

1:02:54to do this, I would not actually carry

1:02:56through with my core foundational

1:02:57revenue generating activity simply

1:02:59because of how hard I had made it for

1:03:00myself.

1:03:02So that takes me to a few action

1:03:03questions. The first is name one

1:03:06behavior that you want to do more of

1:03:08this month. How many steps currently sit

1:03:11between the thought and then the action?

1:03:14And what single change can cut down the

1:03:16number of steps so that instead of going

1:03:18to the gym requiring 10 things where you

1:03:20got to get put your shorts in your bag

1:03:22and get your shoes and get the

1:03:23basketball and walk out the house and

1:03:25take the bus, instead of all of those

1:03:27steps, what changes can you make that

1:03:28would bring that to just one?

1:03:31The other question is, name the behavior

1:03:32that ate the vast majority of your last

1:03:35week. What one step could put you in

1:03:38front of it that would force a conscious

Optimizing your hardware

1:03:40decision every time? It is now time to

1:03:42actually optimize our hardware. Before

1:03:45we get started, none of this is probably

1:03:46going to seem very fancy to you guys. I

1:03:48mean, if you think about it, we're going

1:03:49to talk about some very elementary and

1:03:50basic things here. So, things like food,

1:03:53uh, sleep, exercise, and so on and so

1:03:55forth. And these are all things that

1:03:56people have been realistically

1:03:57discussing for decades. But if you

1:03:59optimize them in the way that I will

1:04:00show you, most people that are taking

1:04:02this course can expect 40 to 80%

1:04:03improvements in cognitive function. And

1:04:05that is not a typo. I mean, we did the

1:04:07math. Um, that is literally 1.5 extra

1:04:09performance on a wide cognitive battery.

1:04:12To make it clear, I'm not a doctor and

1:04:14none of this is medical advice. What I

1:04:16have done is I've gone through all the

1:04:17currently available up-to-date

1:04:19literature, the meta analyses, and the

1:04:21randomized controlled trials on various

1:04:22biological interventions. I've also

1:04:24ranked them according to EV or expected

1:04:26value, which I will teach you guys how

1:04:27to do later. for the median person. And

1:04:29so if you're unsure about any of this, I

1:04:30would encourage you guys to talk to a

1:04:32qualified doctor or your LLM. With that

1:04:34out of the way, I've seen people spend

1:04:37tens of thousands of dollars on

1:04:39biohacking and cold plunges and crazy

1:04:42supplement stacks and neutropics and all

1:04:45this other stuff ultimately to ek out

1:04:47maybe 1 to 2% improvement in cognitive

1:04:50capacity. [snorts] These same people

1:04:52when asked, "Hey bro, how much sleep did

1:04:54you get last night?" will confidently

1:04:55turn around and tell you, I don't know,

1:04:57maybe like five or six hours. If you're

1:04:59one of those people, if you are

1:05:00currently focusing on trendy and super

1:05:02shiny objects or maybe all these bio

1:05:04hacks without actually having maxed out

1:05:07your health, the biological gold, which

1:05:09if you think about it is available to us

1:05:11all, very low hanging fruit, you're

1:05:12almost certainly wasting your time, and

1:05:14I recommend you stop it. I think about

1:05:16it like winning a minor skirmish and

1:05:17then losing a generational war, or maybe

1:05:19dodging a bullet just to get hit by a

1:05:21nuke. Do you guys remember the basis of

1:05:23cognition? It was attention, working

1:05:25memory, and then executive function.

1:05:27What I'm going to do is I'm going to

1:05:28show you guys how to use biological

1:05:29interventions to improve each of these

1:05:31in turn. To begin, I'm going to start by

Sleep, nutrition and exercise

1:05:33going through the three major drivers of

1:05:34clear thinking, which is sleep,

1:05:36nutrition, and exercise. And we're going

1:05:38to do that one at a time. For every one

1:05:40of these, I'm going to explain how it

1:05:41works, what you guys can do about it,

1:05:43and then also my own routine. And if

1:05:45something is not backed by hard evidence

1:05:46and it is just a suggestion, I will be

1:05:48sure to tell you because I don't want to

1:05:49mislead anyone or have you do things

1:05:51that is are not necessarily

1:05:52scientifically backed. So this graph

1:05:54shows where the effective sleep,

1:05:56nutrition, and exercise. These tend to

1:05:58be approximately 70 to 80% of all

1:06:00possible gains. Although there are some

1:06:01others that I'll cover too.

1:06:02Unfortunately, the attention currently

1:06:04goes towards flashy things like

1:06:05neutropics, uh cold plunges, supplement

1:06:07stacks, productivity apps, morning

1:06:09routines, biohacks, all that stuff.

1:06:11While some of these are important,

1:06:12they're typically more important

1:06:13important in concert with the former

1:06:15three. And it's also a good point to

1:06:17remember that um the whole point of this

1:06:19is none of these should really require a

1:06:20tremendous amount of willpower. That's

1:06:21the whole point, right? My goal is

1:06:23really to get most of these gains done

1:06:25without really adjusting by only really

1:06:28adjusting your schedule. Things like

1:06:30your light, uh your diet, your exercise,

1:06:32and some other stuff. And the plan is to

1:06:34make habits that clarify your thinking

1:06:37and turn those into defaults and then

1:06:39take those that ruin your thinking and

1:06:41make them like we saw uh with the

1:06:43European examples optins.

1:06:46The format typically is the title with

1:06:48the actional tip plus expected cognitive

1:06:50improvement. Any expected cognitive

1:06:52improvement is just what I've reasoned

1:06:53through first principles. Um as well as

1:06:55you know summarizing the literature and

1:06:57meta analyses on the subject. Um I also

1:06:59want you to know that these are not

1:07:00additive. So you're not just going to

1:07:02add the 10 to 15% with the 8% with the

1:07:0514%. These are all multiplicative. So

1:07:07think about it not as 10% plus 10%

1:07:09equals 20%, but 1.1 * 1.1 equals I don't

1:07:12know 1.11 or something. Okay. So the

1:07:15very first is to rule out a sleep

1:07:17disorder. Now logically you will sleep

1:07:20every night for the rest of your entire

1:07:21life. Right? Given how often you sleep,

1:07:24doesn't it make sense to ensure that you

1:07:25guys are sleeping well? If you think

1:07:27about it, that's a huge return on

1:07:28investment for just a few moments of

1:07:30your consideration, right? And the

1:07:31unfortunate news is a lot of people

1:07:33haven't spent more than 5 minutes

1:07:34thinking about something they are

1:07:35literally going to be forced to do for

1:07:37about a third of their life. So, first

Check for a sleep disorder first

1:07:39before proceeding to optimize anything,

1:07:41cuz I'm going to give you guys a big

1:07:41laundry list of sleep improvement

1:07:43techniques which have direct and

1:07:44measurable impacts on cognition, just

1:07:46make sure you don't have a sleep

1:07:47disorder because if you do, uh, no

1:07:49amount of the next few tips are going to

1:07:51help you given that the problem is

1:07:52mostly on the hardware level and not

1:07:53actually on anything else. The main one

1:07:56to look for, which unfortunately around

1:07:5730% of uh men in the United States are

1:07:59expected to have, is some form of sleep

1:08:01disordered breathing. This is an

1:08:03umbrella term that includes sleep apnnea

1:08:05as well as its less audible cousin

1:08:06called Us. As mentioned, 30% of men in

1:08:10the US are suspected to have one of

1:08:11these two and it's simply mostly a

1:08:14byproduct of weight at this point. Um,

1:08:16you know, the more you weigh, the more

1:08:17compression occurs around your trachea,

1:08:20the thing you use to breathe. And as a

1:08:21result, that compression leads you to

1:08:23not being able to breathe fully in the

1:08:25middle of the night when all of your

1:08:26muscles collapse. As a result, you

1:08:27typically have disordered sleeping. Now,

1:08:30essentially, this triggers the brain to

1:08:32wake you up partially, dozens of times

1:08:34per hour to fix the issue. You have to

1:08:36wake up a little bit to take a really

1:08:38deep breath or you start snoring a lot,

1:08:39which kind of wakes you up as well. And

1:08:41you don't remember any of it, but it

1:08:42still reduces your sleep effectiveness

1:08:44significantly. A very common thing to do

1:08:46is to spend around 8 hours in bed and

1:08:48then only get the equivalent of maybe 5

1:08:49hours of actual sleep. The symptoms are

1:08:52also quite vague. They're often

1:08:53misattributed as personality traits,

1:08:54which I find funny. You know, brain fog

1:08:57or waking up tired after 9 hours in bed

1:08:59or always being the sleepy person or the

1:09:01person that loves their coffee and so on

1:09:03and so forth. Um, all of this stuff is

1:09:06associated with sleep disordered

1:09:07breathing and it's not something that I

1:09:09would recommend. The whole reason why I

1:09:11spent a solid two minutes talking about

1:09:12this, by the way, is because I actually

1:09:13have that. And for many years, I

1:09:14attributed my groggginess in the

1:09:16mornings to a lack of discipline and a

1:09:17lack of routine. I also tried a bunch of

1:09:19different sleep hygiene protocols and

1:09:21medications. None of those worked until

1:09:23now. So, if you have any of these,

1:09:25snore, wake up tired, breathe through

1:09:27your mouth at night, you have a narrow

1:09:28jaw, maybe you drink an incredible

1:09:29amount of coffee or energy drinks, I

1:09:31would recommend getting a sleep study

1:09:32and and ruling it out. If you find out

1:09:34you have one and you do treat it, not

1:09:36only will you live many additional

1:09:37years, but you'll also think far more

1:09:38clearly. You'll also instantaneously

1:09:40basically, not actually, but almost

1:09:42become fitter, healthier, more vibrant.

1:09:44And it also costs you very little in the

1:09:46grand scheme of things. Think about that

1:09:48right now. If you had one and you

1:09:50figured it out, you've just gained 10%.

1:09:53Like the matrix pill analogy, you will

1:09:55have just taken the $110.

1:09:58Next is to sleep somewhere between 7 to

1:10:009 hours for another 10 to 20%. Sleep

1:10:03deprivation is super common. I would

1:10:04wager more than half of the people that

1:10:06are currently watching this course have

1:10:07some form of sleep deprivation,

1:10:08knowingly or otherwise. The major issue

1:10:11is it's not actually the sleep

1:10:12deprivation itself that's so dangerous,

1:10:14but the fact that it is invisible to us

1:10:16as humans because you don't know that

1:10:18you're suffering. And science has shown

1:10:20this many times. In this example, 48

1:10:22healthy adults were monitored in a lab

1:10:24for 2 weeks 24/7 and they restricted

1:10:26either 4, 6, or 8 hours in bed. So

1:10:29moderate, mild, or not at all uh sleepd

1:10:31deprived. Results were over two weeks

1:10:34that people in the six-hour group

1:10:35accumulated as much of a sleep deficit,

1:10:37aka impact of performance, as an entire

1:10:39one or two whole nights without sleeping

1:10:41at all. Yet, their perceived sleepiness,

1:10:44how they thought they were, did not

1:10:46change after the first few initial days.

1:10:49Which is interesting because the

1:10:50researchers found that subjects were

1:10:52unable to reliably detect their own

1:10:54impairment.

1:10:57You might be able to think, hey, you

1:10:58know, I can survive off 6 hours. No

1:11:00problem. I'm special. But logically

1:11:02speaking, the very instrument that you

1:11:04would use to determine that is the thing

1:11:06that is ultimately impaired. Right? So

1:11:08how the hell are you going to know? You

1:11:09can't. Our brain is ultimately the thing

1:11:11that we use to think through whether or

1:11:13not we are sleepd deprived. Now there

1:11:15are obviously a few people on Earth with

1:11:17a genetic mutation that allow them to

1:11:19sleep much less on average. They're

1:11:20pretty cool and you should look into

1:11:21that if you wanted to. Unfortunately,

1:11:23statistically you are almost certainly

1:11:24not one of them. So as a sensible

1:11:27person, try and fix this. What's really

1:11:29interesting is, you know, if you are

1:11:31sleeping six hours a night, as this

1:11:33graph shows right over here, um you

1:11:34could see that after, I don't know,

1:11:37maybe let's say a week or so, you say

1:11:41that you're sleepier,

1:11:45you say that you're less sleepy than you

1:11:47actually are. You essentially have more

1:11:51confidence than reality. And I don't

1:11:53mean that to mean not sleeping makes you

1:11:55super confident, you should go and do

1:11:56it. I mean, you think you are more

1:11:58capable than you realistically are, and

1:12:00as a result, you make a lot of strategic

1:12:02and tactical errors that you otherwise

1:12:04would not. I have a couple of really

1:12:05good friends that have probably been

1:12:06sleeping on somewhere between 5 to 6

1:12:08hours for better part of the last 3 or 4

1:12:09years. And I hate to say it, but I've

1:12:12watched them measurably degrade in their

1:12:14cognitive and and tactical capacities

1:12:16throughout that time. Despite repeated

1:12:18urgings, they continuously say things

1:12:19like, "Dude, it doesn't matter. I can't.

1:12:21No, man. I'm totally fine. I don't feel

1:12:23bad at all." Well, they're definitely on

1:12:24this side of the graph, if you catch my

1:12:26drift.

1:12:27Now worth noting any deficit here is

1:12:29dose dependent. So 6 hours for instance

1:12:31is worse than 8 hours. If you see four

1:12:32hours it's worse than 6 hours etc. Uh my

1:12:36recommendation is 7 to 9. I would

1:12:37consider that non-negotiable if you

1:12:39really are serious about improving this.

1:12:40Uh and you can do this easily by the

1:12:42way. All you have to do is set a bedtime

1:12:44alarm and then a wake up alarm at the

1:12:45same time every evening and morning for

1:12:47maybe a month or so. So let's say you go

1:12:49to bed at 10:00 and then you wake up at

1:12:516:00. You can actually stop right now

1:12:52and set alarms either on your phone or

1:12:54if you have one of those physical sort

1:12:55of wall clock alarms. Um, do that as

1:12:57well. The first few times your mornings

1:12:59and evenings are almost certainly going

1:13:00to be rough, but that's simply because

1:13:02you're not used to it. Over time, you'll

1:13:04begin getting tired right around the

1:13:05time that you're supposed to. And that's

1:13:07just because, like any animal, including

1:13:08the rats that were in the labs that I

1:13:10uh, you know, managed, uh, we thrive on

1:13:12regularity.

1:13:14Another easy 6 to 12% improvement is

1:13:17through improving your wake time. So

1:13:19this is a very powerful sleep tactic and

1:13:21it also costs you virtually nothing if

1:13:22you think about it from an ROI

1:13:23perspective. So I used to work with a

1:13:25lab that dealt with the neurobiology of

1:13:27sleep. We changed rat feeding, waking

1:13:29and light dark schedules pretty often.

1:13:31And to give you guys a rundown of the

1:13:33main concept there. It's called the

1:13:34circadian clock. Your circadian clock is

1:13:37just a system internal to your body that

1:13:39injects you with various chemicals at

1:13:42various parts of the day. So cortisol,

1:13:44adrenaline, and other wake up chemicals

1:13:46basically usually as you wake up. The

1:13:48idea behind that evolutionarily was

1:13:50you're waking up, you better get to it,

1:13:53right? Going to have to go out, find

1:13:54food, fend off saber-tooth tigers, do

1:13:56whatever the hell else. So cortisol and

1:13:59adrenaline naturally when they're

1:14:00applied at the right times are extremely

1:14:02valuable and they're also correlated

1:14:03with major improvements in cognition. I

1:14:05know that all the Tik Tok girlies are

1:14:06talking about reducing cortisol so their

1:14:08face looks less bloated or whatever, but

1:14:10uh cortisol is not inherently bad.

1:14:12Obviously, we have all of the chemicals

1:14:14we have in our body for a reason. So, if

1:14:16you've ever had a morning where you just

1:14:17feel on, a lot of those mornings are

1:14:20going to be because you just so happen

1:14:22to align your internal circadian clock

1:14:24with the time at which you are waking

1:14:25up. It's an easy 6 to 12% improvement to

1:14:28the clarity and rigor of your thinking

1:14:30virtually for free. Now, the issue for

1:14:32most people is that our circadian

1:14:34rhythms, you know, they need a couple of

1:14:35weeks of consistent sleep or wake cycles

1:14:38to lock on to a time. And unfortunately,

1:14:40most people do not actually wake up at

1:14:42the same time for many days in a row.

1:14:44Instead, they will wake up early Monday

1:14:46to Friday, but then they'll ruin it all

1:14:48on Saturday or Sunday on their days off,

1:14:49assuming they work a 9 to5 or something.

1:14:52The best and easiest way to fix this is

1:14:54simply to pick a consistent wake time

1:14:55and then stick to it every day of the

1:14:57week. That way, your body will naturally

1:14:59self-correct the energy boost period to

1:15:01occur right at the time that you wake

1:15:03up, or at least within an hour or so of

1:15:05that time. And this doesn't just improve

1:15:07your short-term or acute cognit

1:15:09cognitive capacity during that hour

1:15:11period. It will improve that throughout

1:15:12the day as well. The next is to cut

Cutting caffeine

1:15:15caffeine such that you are not taking it

1:15:1710 hours before bed. When you do this,

1:15:19you can expect a 3 to 8% improvement in

1:15:21your sleep, which will obviously roll

1:15:23over to your cognition as well. And it's

1:15:25another very easy hardware gain. The

1:15:27reality is most people who sleep at, you

1:15:29know, 10 p.m. or so will drink coffee

1:15:32after 12:00 p.m. What I mean by that is

1:15:34since caffeine has a very long halflife,

1:15:37aka how long it stays in somebody's

1:15:38system, doing this will directly and

1:15:40immediately impact the quality of your

1:15:41sleep because logically caffeine will

1:15:43still be floating around in your body,

1:15:44right? Lots of studies show that

1:15:46caffeine right before sleep impacts how

1:15:48much you actually get, which leads to

1:15:49the same problem that you would

1:15:50otherwise get with sleep deprivation. So

1:15:52in this study, people were given 400

1:15:54millig of caffeine 6 hours before their

1:15:56sleep. These folks literally lost a

1:15:58whole hour of measured sleep and they

1:16:00didn't even know it. Meaning that they

1:16:01were like those people in that study I

1:16:03talked about earlier accumulating

1:16:04impacts on their cognition and they were

1:16:06completely unaware of it the entire

1:16:07time. The major rule is if you go to bed

1:16:09at 10 p.m. you should stop caffeine

1:16:11consumption at noon and no later.

1:16:13Otherwise, you could see that despite

1:16:15the fact that, you know, you you drink

1:16:17it at 12, if you drink your I don't

1:16:19know, let's say 200 at about 10 pm or

1:16:22so, the average or typical person will

1:16:24still have approximately 50 milligs in

1:16:26their system, which is about a quarter

1:16:27of that coffee. [sighs] For those of you

1:16:29guys that haven't had 50 milligs of

1:16:30caffeine, that is pretty sizable. And to

1:16:32have that running around your system in

1:16:33the middle of the night, which is the

1:16:34direct opposite sort of thing you want

1:16:36in your system in the middle of the

1:16:37night, mind you, um is obviously not

1:16:38very good from a long-term health

1:16:40perspective.

1:16:42Next, get bright mornings and then dim

1:16:44evenings so that they're dark uh for an

1:16:46additional 3 to 8%. What I mean by that

1:16:49is circadian rhythms drive a lot of our

1:16:50behavior and our performance, right?

1:16:52Well, have you ever asked yourself how

1:16:53these things are set? The reality is

1:16:56they're set via light. So, there are

1:16:58tiny brain regions in your head which

1:16:59are activated by light which later

1:17:01entrain the rest of your brain and they

1:17:03also entrain those chemicals that we

1:17:04talked about earlier. So, if you want a

1:17:06consistent boost of energy as well as a

1:17:08far more predictable schedule, you have

1:17:10to get consistent morning light

1:17:12exposure. In general, what this looks

1:17:14like is about 10 minutes of natural

1:17:16sunlight within an hour or so of waking

1:17:17up. Even a cloudy day typically has a

1:17:20lot more light than, you know, your

1:17:21kitchen or an office. And so, my usual

1:17:24recommendation is unless you have a

1:17:26really big window or you have some sort

1:17:27of artificial light, which I'll show you

1:17:28guys in a moment, um you're going to

1:17:30want to go outside. And at night, you

1:17:32want the exact opposite. a couple of

1:17:34hours before bed, you want some sort of

1:17:35dim or warm or low inensity light and

1:17:38that will, you know, reverse that whole

1:17:39cortisol adrenaline thing that I talked

1:17:41about earlier and start bringing it

1:17:42down. A note on blue light, by the way,

1:17:45since I think many of us will probably

1:17:46have heard about blue light from pop

1:17:48science shows or YouTube channels or

1:17:50whatever. The idea of blue light making

1:17:52you unable to sleep is probably less of

1:17:54an issue than the actual content on the

1:17:55screen itself. Most of the time if

1:17:57you're scrolling around really late at

1:17:58night, you're doing so on social media

1:18:00platforms or some sort of feeds where

1:18:02that facilitate doom scrolls and that if

1:18:05you think about it is incentivized to

1:18:07show you guys highly engaging and

1:18:08controversial content just to sort of

1:18:10keep you going. These algorithms are

1:18:12tuned and they know your time zones.

1:18:13They will they will do stuff like this

1:18:14on purpose. I don't mean the algorithms

1:18:16themselves are evil. I just mean like

1:18:18their goal is to keep you on, right? So

1:18:19they will show you these terrible things

1:18:21in order to keep you awake and keep you

1:18:23scrolling. Obviously, the there's nobody

1:18:25uh there's no Facebook user like a

1:18:27person that can't fall asleep uh until 1

1:18:29or 2 a.m. in the morning, right? So,

1:18:32despite the fact that, you know, I think

1:18:33blue light at night is important, I

1:18:35think it's a lot less important than

1:18:36people make it out to be. And I think

1:18:37blue light blockers and stuff like that,

1:18:38while they help, they probably don't

1:18:40help in the capacity of, hey, I can wear

1:18:42blue light blockers and keep scrolling

1:18:44through gore and whatever the hell else

1:18:45on my ex account. You definitely should

1:18:47not be doing that regardless of of what

1:18:49it is that you are doing at night. My

1:18:51rule is I just stop looking at socials

1:18:53every night. I do so like a couple hours

1:18:54before I go to bed. And honestly, I try

1:18:56and not look at socials at all because

1:18:58they're just inherently terrible for

1:18:59you. Anyh who, another quick and easy

1:19:02way to gain somewhere between 2 to 6% to

1:19:05your um cognitive capacity is to sleep

1:19:07in a cold and a dark environment. So, in

1:19:10general, you want your bedroom to be

1:19:11cold, dark, and quiet. The majority of

1:19:13human beings sleep best at temperatures

1:19:15in the high teens. I'm Canadian, so in

1:19:17Celsius. And I do not know what that is

1:19:19for my Freedom Loving Brothers down

1:19:20south, unfortunately. But I know for us

1:19:22it's somewhere between like 18 to to 20

1:19:25degrees C. Personally, the way that I do

1:19:27it is I have a mattress topper called an

1:19:30eight sleep. And I'm not affiliated, but

1:19:32these guys are pretty cool. Sort of like

1:19:33water cooled. And what it does is um

1:19:36right before I fall asleep, it reduces

1:19:38the temperature of the bed to get me

1:19:40close to that 18 19° range. And then as

1:19:42I sleep, it modulates and mediates the

1:19:45temperature. So, it keeps me basically,

1:19:47according to known science, in like the

1:19:48optimal space of comfort to be able to

1:19:51sleep for longer. This is not cheap. I

1:19:53think this costs four grand or five

1:19:54grand or something like that, but if you

1:19:56can afford it, I would highly recommend

1:19:57it again because of the ROI. You're

1:19:59doing this every day for the rest of

1:20:00your life, you might as well get as much

1:20:02of an ROI as possible. Now, for those of

1:20:04you guys in maybe warmer climates, you

1:20:05know, I'm up here in Canada, so it gets

1:20:06pretty cold. Um, you can use an AC fan,

1:20:10blackout curtains, and so on and so

1:20:11forth. If you're somewhere really north,

1:20:13you might need a heater as well to get

1:20:15to that point. Another really easy hack

Bloodwork and deficiencies

1:20:18is just to understand whether or not you

1:20:20have any nutrient deficiencies or

1:20:22anything like that. Now, I understand

1:20:24this is not the most accessible to a lot

1:20:26of people, uh, especially those in like

1:20:27Commonwealth areas where maybe health is

1:20:29is public, but I would recommend at some

1:20:31point over a course of maybe a year or

1:20:33two, you should probably get some sort

1:20:34of blood test. If you think about it,

1:20:36your brain is fed by blood. It's the

1:20:38most metabolically active organ per unit

1:20:40mass. Around 2% of the mass and 20% of

1:20:42the energy, but it stores very little

1:20:44energy of its own, meaning that the

1:20:45quality of your blood is a very

1:20:47important part of your nutrition.

1:20:49Unfortunately, because our diets have

1:20:50all gotten very efficient. We eat

1:20:52ultrarocessed foods or we eat food of

1:20:55which natural minerals and so on and so

1:20:56forth have been stripped from, a lot of

1:20:58people end up deficient in one or more

1:21:00of these nutrients, which means they're

1:21:01sacrificing breadth of diversity of

1:21:03nutrients for the convenience of maybe

1:21:05the same thing every day. I'm guilty of

1:21:08this as well, by the way. Now, if you

1:21:10have a deficiency, a lot of the time it

1:21:11will manifest as things that look like,

1:21:13you know, a laziness or a lack of focus

1:21:16or unclear thinking, etc. Often to the

1:21:18tune of 10 to 15% or more if you have a

1:21:20nutrient deficiency. Um, you know, as

1:21:23mentioned, I'm not a doctor and I can't

1:21:24give you clear medical advice on this.

1:21:26So, do this if this sounds like it may

1:21:28or may not be something that you are

1:21:30experiencing. But some very common ones

1:21:32that a lot of people have are things

1:21:33like iron, especially in women. Um,

1:21:35feritin, uh, B12, especially if you

1:21:37don't eat a lot of meat or in a

1:21:39vegetarian or vegan diet, a vitamin D.

1:21:41If you live in Canada or other northern

1:21:42countries, northern latitudes, and it's

1:21:44between October and April, you probably

1:21:45have this unless you supplement. Uh, you

1:21:47know, underactive thyroid problems, and

1:21:49so on and so forth. These are all things

1:21:50that are worth at least thinking about

1:21:52and then cluing into to see whether or

1:21:54not there's something that you you might

1:21:55realistically have because all of them

1:21:57essentially unlock you a good 5 or 10%.

1:22:00I would also get some form of metabolic

1:22:02marker just to see how your blood sugar

1:22:03is doing. A lot of people probably eat

1:22:05these ultrarocessed foods and then

1:22:07result in chronically high blood sugar

1:22:09that leads to clarity of thought issues

1:22:11long before you develop things like

1:22:13diabetes and so on and so forth. And

1:22:15yeah, you guys can do this through, you

1:22:16know, a doctor's referral if you're in a

1:22:18public healthare place like I am, or you

1:22:19can pay out of pocket for insurance if

1:22:21you're somewhere private like the US or

1:22:22other places. The harsh reality is this

1:22:25is probably going to be a few hundred or

1:22:26maybe a couple hours of your time max,

1:22:28but it will pay dividends for the rest

1:22:29of your life as you get proactive about

1:22:31managing your health. Okay, so I have a

1:22:34standard panel over here that I would

1:22:36recommend you guys get at some point in

1:22:37time. All of this is super easy to see.

1:22:39Just get the results, then you can take

1:22:41them um to I don't know your own LLM.

1:22:44You take them to any doctor that you

1:22:45want to discuss these things, people you

1:22:47trust and so on and so forth. um for as

1:22:49mentioned proactive health purposes.

Cutting alcohol

1:22:52Another big thing I do is I cut alcohol.

1:22:54People that do typically see somewhere

1:22:55between a four to a 10% improvement on a

1:22:57variety of these batteries. Um if you're

1:22:59going to get anything done, you might as

1:23:01well finish with booze. And I don't say

1:23:03you have to abstain completely. I just

1:23:05mean if you want the best performance

1:23:06and you really want to maximize the

1:23:08clarity of your thinking, alcohol just

1:23:09is not is not for you. I want you to

1:23:12think about this from the perspective

1:23:13that I talked earlier. Everybody's like,

1:23:15"Oh, just have a drink. Why not?

1:23:18We didn't evolve with alcohol. It's not

1:23:20like alcohol, like alcohol was created,

1:23:23you know what I mean? Obviously, it was

1:23:24created through a bunch of natural

1:23:25fermentation processes that led people

1:23:27to, you know, smelling a bunch of very

1:23:29off smelling barley or whatever and then

1:23:32thinking, "Oh, maybe I'll put this in my

1:23:33mouth for whatever reason. Prehistoric

1:23:35people, man." But the point that I'm

1:23:37making is this is a default that was

1:23:39given to you. The whole idea of like

1:23:42going out to the bar or whatever, that

1:23:43was a default that was given to you. You

1:23:45can certainly enjoy it and you can like

1:23:47it. And if you find that you like it,

1:23:49you can turn it into something with

1:23:50intention, but so many people live lives

1:23:52of no intention whatsoever or they think

1:23:54they have to simply because of the

1:23:55people that they're surrounded with or

1:23:56the environments that they happen to

1:23:58grow up with. Um, take the permission

1:24:00from me. You don't have to do any of the

1:24:01stuff if you really don't want to. Most

1:24:03people don't actually even enjoy the

1:24:04taste of booze. It's one of those hidden

1:24:06secrets that nobody really likes talking

1:24:08about. So, anybody that's young that

1:24:10takes a sip of, I don't know, some super

1:24:12hard liquor and goes, "That smells and

1:24:14tastes like crap." You're not wrong. It

1:24:16does. It's just people tend to grow used

1:24:17to it and then eventually find joy in

1:24:18the suffering. Now, the main issue for

1:24:21us cognition interested types is not

1:24:23actually like things like liver disease

1:24:24and so on and so forth. What it is is

1:24:26it's sleep. Alcohol lets you fall asleep

1:24:29faster, which makes sense since it's a

1:24:31central nervous system depressant,

1:24:32right? but it does so at the cost of

1:24:34actually disrupting the second half of

1:24:36your night usually, which is where

1:24:38you're supposed to be in what's called

1:24:40REM sleep or rapid eye movement sleep.

1:24:42Um, this is critical for making you feel

1:24:45more rested the next morning. And since

1:24:47alcohol disrupts that, it interferes

1:24:49with your ability to feel rested and

1:24:50then also consolidate things like memory

1:24:52and so on and so forth. Basically, take

1:24:54things that were in your working memory

1:24:55during the day and then turn those in

1:24:57encode those into memories.

1:24:59So, even one or two drinks can massively

1:25:01impact your next day. I personally keep

1:25:03my alcohol consumption at zero. In the

1:25:05last eight years, I've probably had less

1:25:06than a dozen drinks. And virtually every

1:25:08one of those was at some quote unquote

1:25:10once in a lifetime opportunity, say half

1:25:13a beer at uh my best friend's wedding or

1:25:15something of that nature. And despite

1:25:17that being relatively small in the grand

1:25:19scheme of things, I still feel it the

1:25:20next morning. Okay. like alcohol. I'd

1:25:23highly recommend that you guys cut any

1:25:25sort of drug that may or may not be

1:25:27something that has been, you know,

1:25:28medically prescribed to you. A good

1:25:30example of that is cannabis or weed uh

1:25:32for 2 to 6%. So, if you're an active

1:25:34cannabis user, it's a very similar

1:25:36problem to alcohol, although it works

1:25:37through slightly different mechanisms.

1:25:39It can help people fall asleep faster,

1:25:41at least feel like they're falling

1:25:42asleep faster, but a lot of the time it

1:25:44does this at the expense of sleep

1:25:45quality. When I stopped smoking, I felt

1:25:48almost immediate improvements in just

1:25:50mental clarity, maybe 2 or 3 days. And

1:25:52this is an advantage I've never once let

1:25:54go of since then. Also, if you're at the

1:25:56point where maybe you need this to fall

1:25:57asleep, or at least you think you do,

1:25:59you really should urgently fix this. U

1:26:01because relying on any sort of drug to

1:26:02sleep is terrible, it's obviously bad

1:26:04and it's not where you want to go.

Protein, fiber and creatine

1:26:07Eating more protein and fiber for maybe

1:26:092 to 4% each is extremely important.

1:26:12Protein helps stabilize blood glucose

1:26:13levels as well as prolongs feelings of

1:26:15fullness, which is a side effect can

1:26:16help you lose weight if you guys are

1:26:18overweight. Also beneficial to cognition

1:26:20and then also has a tie-in to the sleep

1:26:21disordered breathing loop. Fiber slows

1:26:24down the absorption of sugar from other

1:26:26foods and also feeds your gut microbiome

1:26:28which is strongly associated with mood

1:26:30and cognitive function. And while all of

1:26:32this is very early on, I mean the

1:26:34research that I'm I'm talking about here

1:26:35has really only come out in the last

1:26:37couple of years, it is not

1:26:38insignificant. And there are a lot of

1:26:41suggestions that you know some major

1:26:43depressive disorders or uh you know a

1:26:45variety of like mental or disordered

1:26:47states of of thinking and so on and so

1:26:49forth are a result of a fractured gut

1:26:51microbiome. So you can fix that. Now I

1:26:54used to blow at fiber. I would eat maybe

1:26:565 to 10 grams in a good day. And just so

1:26:58you know, the recommended intake for

1:26:59somebody about my size is probably

1:27:00closer to 40 gram or so. When I

1:27:02corrected that by eating more fiber, I

1:27:04noticed an immediate improvement in

1:27:06sustained energy levels throughout the

1:27:07day, as well as just my my mood on a

1:27:09day-to-day basis. The next is to take

1:27:12creatine for around a 1 to 3%

1:27:13improvement in cognition, more if you

1:27:15are sleepd deprived because creatine

1:27:17acts as a buffer for sleep deprivation.

1:27:19Now, creatine is really the only

1:27:21supplement that has any real evidence

1:27:22support in the literature. Uh they've

1:27:24done lots of systematic reviews of

1:27:26randomized trials and it shows that

1:27:28creatine may improve reasoning in

1:27:30short-term memory specifically in people

1:27:33that do not have lots of creatine

1:27:35floating around in their bodies.

1:27:36Creatine comes from meat, typically red

1:27:38meat, so steaks and you know very fatty

1:27:41sort of gy meats as well, meaning

1:27:43vegetarians, vegans, and so on and so

1:27:45forth or people that have more

1:27:46pescatarian style diets typically do not

1:27:48get as much creatine. So when you

1:27:50supplement with creatine in that micro

1:27:52population, you typically have a more

1:27:53pronounced result than if you supplement

1:27:55with creatine in let's say a population

1:27:56that eats a lot of beef, but it's still

1:27:58present. It also seems to impact stress

1:28:00management um for the better, which I

1:28:02think is important. [gasps] Now, if

1:28:04you're going to take a supplement, and

1:28:05again, supplements are such a small

1:28:06portion of the total productivity and

1:28:08clarity of thought pie that I just want

1:28:10to make it clear that like they're good,

1:28:11but you shouldn't rely on them. You

1:28:13should probably take creatine. I'd

1:28:15recommend 3 to 5 grams a day. costs

1:28:17around 20 cents or so and there's

1:28:18virtually zero risk. Not completely zero

1:28:20risk. Obviously, if you are concerned,

1:28:22talk about it with your doctor. Uh but

1:28:24if you lift weights or have had a poor

1:28:25night's sleep, all of this is a

1:28:26no-brainer. It's basically as close to

1:28:28the Limitless pill as you'll ever get,

1:28:30which is disappointing, but you know,

1:28:32still pretty good. Now, for a massive

Raising your VO2 max

1:28:35upgrade, raise your V2 max and get 10 to

1:28:3820% better cognitive capacity. Now,

1:28:41exercise improves cognitive performance

1:28:42in a lot of ways. Cardio improves blood

1:28:45flow to the brain. It increases

1:28:46expression of what's called BDNF, which

1:28:48is a brain derived chemical promoting

1:28:49neurogenesis in the hippocampus, which

1:28:52is a region of the brain involved in

1:28:53memory. It also improves your insulin

1:28:55sensitivity and resistance. And then it

1:28:57improves sleep as well, which we've

1:28:58talked about. Now, we can't directly

1:29:00measure all of these effects in humans

1:29:02clearly since uh it is way easier to

1:29:04figure all this stuff out if you can

1:29:05just euthanize the animal and chop its

1:29:07brain in half. But scientists have been

1:29:09seeing this sort of thing in rodents for

1:29:10many decades. And there's also very

1:29:12strong evidence that all of this is

1:29:13directly causitive. Meaning that there

1:29:15is a if then loop behind exercise and

1:29:18then sustained cognitive performance and

1:29:20focus. If you literally just give

1:29:22animals access to a running wheel and

1:29:24then they tend to run more because it's

1:29:25in their environment. Um they get more

1:29:27neurons created in the memory centers of

1:29:29the brain. They also learn mazes much

1:29:31faster than sedentary, which means

1:29:33controls that don't move a lot. So if

1:29:35you're going to track just one part of

1:29:36your exercise, my recommendation is to

1:29:38track your V2 max. And this is something

1:29:39that I'm currently in the process of

1:29:41doing having started from relatively low

1:29:42V2 max due to both um some biological

1:29:45disadvantages I was given and then just

1:29:47a lack of you know cardiovascular

1:29:48exercise and I'm seeing massive

1:29:50improvements. It's also the gold

1:29:52standard for measuring cardiovascular

1:29:53fitness and it's also interestingly

1:29:55enough a much better predictor of

1:29:57longevity than almost any other risk

1:29:58factor. So for cognitive performance,

1:30:00it's a good proxy for your brain's

1:30:02ability to receive and then metabolize

1:30:04oxygen. Because the whole idea behind V2

1:30:06max is how much oxygen you can like

1:30:08actually take in per unit time. Given

1:30:10that, as we know, your brain is the most

1:30:11oxygen demanding and energy demanding

1:30:13organ of the body, kind of makes sense

1:30:15that becoming better at the process of

1:30:17taking in energy would improve your

1:30:18brain's ability to function, right? It's

1:30:21also a really good KPI. So you can

1:30:22measure this in a lab once every quarter

1:30:24costs a few hundred bucks. Or you can

1:30:26use an approximate estimate for maybe a

1:30:27smartwatch, a Whoop band, an Apple

1:30:29Watch, etc. Or you can also use a

1:30:30formula. There are a variety of them

1:30:32like the Cooper equation which helps you

1:30:34understand the direction uh of your

1:30:35health over time. Now another 5 to 10%

The REHIT protocol

1:30:39improvement here in using the reit

1:30:41protocol. Reit is a way to improve your

1:30:44V2 max in surprisingly little time. Now,

1:30:47because this is technically linked to

1:30:48the V2 max, I'm not saying that these

1:30:50two stack necessarily, but this is a

1:30:52cheap and easy way for you to improve

1:30:54that V2 max marker for virtually no

1:30:56effort. The way it works is rehit, which

1:30:59stands for reduced exertion

1:31:00high-intensity interval training is

1:31:02based off a study where a bunch of

1:31:04sedentary adults were given a bike and

1:31:05asked to pedal for three 10-minute

1:31:07sessions per week. Twice per session,

1:31:09they pedal as hard as they could for 10

1:31:11to 20 seconds. in total exerting maximum

1:31:13capacity for 40 to 60 seconds per

1:31:1510-minute session. After six weeks,

1:31:19their V2 max improved by 15% in men and

1:31:2212% in women. We also saw an improvement

1:31:24in insulin sensitivity of 28% in men. To

1:31:28be clear, these people did just one

1:31:32minute of hard work every time they

1:31:35worked out. The other 9 minutes was

1:31:38easy, slow pedaling. Which means that if

1:31:41you do the math on three times a week

1:31:43times six weeks, they spent 18 minutes

1:31:46in total working very hard over 6 weeks

1:31:50to improve their V2 max by 15%.

1:31:53Every session essentially improve their

1:31:55V2 max by almost 1%. Keeping in mind

1:31:58that these were sedentary adults, aka

1:32:00they probably had poor V2 maxes to begin

1:32:02with. If you are young, healthy, and

1:32:04somewhat fit, you're unlikely to get 1%

1:32:06improvement of V2 max per rehol. And

1:32:09obviously you have a massive decrease in

1:32:11the impact of this marginally as you do

1:32:13more, but it's still insane. So I'm

1:32:16starting to do this and I have been

1:32:17doing this now uh for maybe maybe a few

1:32:19weeks in total because I I've been

1:32:22traveling. Um this is usually two 20

1:32:25second sprints. Um I will do this just

1:32:27after every workout. So my protocol is a

1:32:29little bit different, but if you think

1:32:30about the total capacity and total

1:32:32impact of this, it's now 40 seconds 6

1:32:34days a week. um you know it is it's

1:32:36essentially equivalent to that same

1:32:37protocol in terms of total number of

1:32:39minutes of like extremely difficult

1:32:40work. I'd recommend you just tie this

1:32:43into like after your cardio uh after

1:32:44your exercise if you're doing strength

1:32:46training or something like that. Just do

1:32:48not allow yourself the decision about

1:32:50whether or not to do this. Just do it. I

1:32:51mean a 1% improvement of V2 max every

1:32:53workout for at least maybe the first 6

1:32:55to 8 weeks is probably the number one

1:32:57thing you can do for your cognition

1:32:59right now. aside from taking care of,

1:33:01you know, major health issues and sleep

1:33:03disordered breathing and nutrient

1:33:04deficiencies.

1:33:06Finally, I'd recommend you stack your

1:33:08defaults. What I mean by this is when

1:33:10you lock in even a few of these habits,

1:33:11you guys can eventually stack them

1:33:12together for far more efficiency. For

1:33:15instance, instead of just working out in

1:33:16a gym, which has limited light and which

1:33:18sometimes will make you feel pressured

1:33:19to do this in the afternoons or the

1:33:21evenings since it's an artificial

1:33:22environment, why don't you exercise

1:33:23outside in the mornings? This would give

1:33:25you immediate exposure to bright light

1:33:27should knock that out. You'd have a

1:33:28consistent wake up time as well, which

1:33:30knocked that out. And it would also give

1:33:31you, of course, your exercise. So, you

1:33:33knock that out. Even better if you pair

1:33:35it with a friend because now you also

1:33:36have the equivalent of a cage mate,

1:33:38which is a very important part of

1:33:39socialization and then cognitive

1:33:40improvement.

1:33:42All right, let's run through some acting

1:33:44action questions before talking about

1:33:46workspace design. Which of these three

1:33:48levers, sleep, nutrition, or exercise,

1:33:51is most broken for you right now? And

1:33:53what is the one probably pretty boring

1:33:55test? maybe a home sleep study or a

1:33:57blood panel or a V2 max measurement that

1:34:00you can do this week to find out for

1:34:01sure. Next, add up all of the

1:34:04percentages from your personal hardware

1:34:05lowhanging fruit. What gains would you

1:34:08say you are currently leaving on the

1:34:09table? And to be clear, I don't mean add

1:34:11as in the literal sense. I mean multiply

1:34:13them all together.

Workspace design and air quality

1:34:15All right, let's now talk about

1:34:16workspace design. You have in extremely

1:34:18lowhanging fruit by doing things like

1:34:20managing as mentioned your air quality,

1:34:23by managing your light intake and so on

1:34:25and so forth. And I wanted to give this

1:34:27section the time and energy that it

1:34:28deserved because I think most people are

1:34:29currently operating in sub-optimal

1:34:31environments. Now, a common part of your

1:34:33environment that most people just do not

1:34:34think about for the life of them is

1:34:36their air. Our metabolism currently runs

1:34:39on oxygen and output CO2. That may

1:34:42change when we get accepted into the

1:34:43organism, but for now, we run on oxygen

1:34:46and output CO2. And so, you should live

1:34:48with that in mind. What that means is

1:34:50when you're in a closed room, you are

1:34:52actively consuming all of the O2 in your

1:34:55room. And then you're pumping out in

1:34:57response the CO2. If your room

1:35:00ventilation is very poor, over time,

1:35:02what will occur is the balance of O2 and

1:35:04CO2 in that room will shift. And many

1:35:06studies have shown that a poor O2 or CO2

1:35:09ratio starts negatively impacting

1:35:10cognition right around when CO2 gets to

1:35:12about 800 parts per million. As a rule

1:35:15of thumb, air outside, like outside of

1:35:18your window, is 420 parts per million

1:35:20approximately. Whereas the ale that the

1:35:23air that you exhale is around 40,000

1:35:25parts per million. That means that in a

1:35:27small and relatively closed office, one

1:35:29that does not have any outdoor

1:35:30ventilation, CO2 levels can climb to as

1:35:33much as over 1,000 parts per million in

1:35:36just an hour or two unless you get some

1:35:38fresh air in there, especially when

1:35:39there are multiple people. Now, the

1:35:41worst thing is we don't notice this.

1:35:44Lots of studies have been performed on

1:35:45your ability to sense minor performance

1:35:47degradations like this, and the brain

1:35:49just virtually cannot. So, your brain

1:35:51thinks this is normal. You don't have a

1:35:52headache. you don't have any obvious

1:35:54sign that you are just slowly becoming a

1:35:55worse version of yourself. Um I like to

1:35:57think of it as a frog getting boiled.

1:35:59It's just now instead of water it is

1:36:00CO2. And you can actually see

1:36:03performance here. If this is your

1:36:05baseline reference at about 550 parts

1:36:07per million at some hypothetical office

1:36:10um this is when Allen at all in 2016 was

1:36:12studying a big group of office workers

1:36:14when CO2 went down to 94 or went up to

1:36:17945 parts per million. So almost double

1:36:19performance went down 15%. When it was

1:36:21at 1400 parts per million, where many

1:36:23people that are currently listening to

1:36:25this right now are currently living and

1:36:26existing, performance went down 50%.

1:36:29There are way too many people listening

1:36:31to this course right now that are

1:36:32probably in highly CO2 out environments

1:36:36that are significantly impacting their

1:36:37ability to perform certain cognitive

1:36:38function scores. Obviously, to be clear,

1:36:41a cognitive function score does not mean

1:36:42everything that you do. It's not going

1:36:44to impact your ability to, I don't know,

1:36:46let's say like pay attention to things

1:36:48or whatever, hear things, but it will

1:36:50impact your ability to think multiple

1:36:52levels deeper than you probably would

1:36:54assume was possible in a CO2

1:36:55environment. So, all this aside, you

1:36:58should get the air moving. My

1:36:59recommendation is to buy a $200 CO2

1:37:02monitor, which sounds like a lot, and

1:37:03I'm going to do a product placement

1:37:04here. I wasn't paid for this, but you

1:37:06know, this is what I have. And what this

1:37:08does is it says more or less what the

1:37:10current CO2 levels in the room are. And

1:37:12you guys could see mine are currently a

1:37:14little too high. I have 763 parts per

1:37:18million of CO2. And uh if I go any

1:37:20further, I'm going to have a little sad

1:37:21face on here. Now, this is pretty

1:37:23expensive. You don't have to get this

1:37:24specific one. I think this one was the

1:37:26air things or something like that. But

1:37:28um you there there variety of different

1:37:29ones that you can get. As long as it

1:37:31measures CO2 and parts per million, you

1:37:33know, do a quick little Google review or

1:37:34ask your agent, you're you're probably

1:37:36fine. Alternatively, just always have a

1:37:38little window cracked open to the

1:37:40outside world. like a fan is not enough

1:37:42because you're just recirculating the

1:37:43air. So, you can also prop your door

1:37:46open between work periods. That's

1:37:47something that I used to do when I would

1:37:49work in a closet. Thanks, Matt Larson.

1:37:51I'd also turn on the AC. Some buildings

1:37:53have like, you know, circulation that

1:37:55pulls air from the outside and then

1:37:56circulates it. Um, I personally prefer

1:37:59working with my door closed because of

1:38:00the noise. So that means that if I don't

1:38:02ventilate it a couple times a day, aka I

1:38:04open the door like once every four or

1:38:05five hours, this invariably leads to CO2

1:38:07levels above 1,200 parts per million

1:38:08before EOD, which if you think about it

1:38:10is now capable of resulting in like a

1:38:12probably a 30 to 40% decrease in

1:38:14cognitive function. Um, keep in mind

1:38:16that CO2 is also not distributed

1:38:18everywhere. Um, depending on its weight

1:38:19density and depending on the other

1:38:20things in the room, CO2 could sit in

1:38:22different places. But this is this is a

1:38:24fair proxy, I would say, for how good

1:38:26your brain is doing. I wish I could

1:38:28actually reprogram this so that I showed

1:38:30an additional uh metric and maybe I can

1:38:32that shows like percentage cognitive

1:38:34impact. Maybe you know as it rises to

1:38:36763 I'm already at 3 or 4% which you

1:38:38know if presented to me in this manner

1:38:40would alert my brain to being like holy

1:38:42crap dude you're doing something bad.

Removing intelligible speech

1:38:44Here's another really easy gain. Remove

1:38:46any intelligible speech in your

1:38:47environment for an improvement of 2 to

1:38:496%. Do not listen to podcasts, music

1:38:52with lyrics, or any family, friends,

1:38:55partners or colleagues while you work.

1:38:57It is okay to have instrumental music or

1:38:59brown noise or fans or rain or other

1:39:02masking sounds. But the key is anything

1:39:04that is intelligible will negatively

1:39:06impact your ability to think clearly

1:39:07over long periods of time. This is

1:39:09because when you talk, your brain will

1:39:11automatically try to figure out the

1:39:13meaning of what those words are. If I am

1:39:16hearing a bunch of other people say

1:39:17stuff, I will constantly be doing that

1:39:19background processing because attention

1:39:21as a gatekeeper is only so good. We're

1:39:23always going to be letting in stuff that

1:39:25we're not directly putting the spotlight

1:39:26on. simply by virtue of how attention

1:39:28grabbing it is. And if you think about

1:39:30it logically, you know, when you do

1:39:31this, it consumes a lot of cognitive

1:39:32resources. Even when speech is mostly

1:39:35unintelligible, even if it's just a

1:39:37bunch of murmuring through a a door or

1:39:39something like that, you still see

1:39:40performance decreases. And the second

1:39:43you follow a conversation, you actually

1:39:45have a major penalty to your reasoning,

1:39:46which um empirically ends up being

1:39:48somewhere between 40 4 to 45% or so,

1:39:51which is obviously a wide range, but it

1:39:52just depends on what task you're doing.

1:39:54tasks that involve, you know,

1:39:55verbalizing and reasoning through words

1:39:58tend to do way worse than those that

1:39:59maybe are more spatially based. Okay.

1:40:02[sighs and gasps]

1:40:03So, how exactly does this work? Well,

1:40:05speech tends to get impacted by

1:40:07intelligibility, not loudness, as we see

1:40:09here. So, one time, um, a client of mine

1:40:12was discussing low performance of their

1:40:13writing team. Um, and I love these guys

1:40:15to death. So, if any one of them are

1:40:16listening to me, um, just know that, you

1:40:18know, you guys you guys are the best.

1:40:20Uh, I visited their office and I noticed

1:40:22that all of the writers on their writing

1:40:23team sat next to each other on a big

1:40:25open floor plan and they also often

1:40:27spoke to each other and it was what you

1:40:29would call a tight-knit team. You know,

1:40:30people really liked each other and it

1:40:31was fun to go to work. However, I

1:40:33noticed that when a single person in the

1:40:35office spoke, everybody else could hear

1:40:38what that person was saying. Now,

1:40:40logically, and I didn't know what I know

1:40:42at the time, but I knew enough. This

1:40:44meant that all other performers in the

1:40:46office had a tax on their ability to

1:40:49write between four to 45% and I would

1:40:51guess probably closer to 45% because

1:40:53writing is obviously directly reasoning

1:40:55based. So what that means is obviously

1:40:58everybody in their office was constantly

1:41:00underperforming. Why? Because you know

1:41:01if it's an let's say it was an office of

1:41:0310 people if one person talks 10% of the

1:41:05time that is virtually literally the

1:41:08entire time that people are working

1:41:09they're going to have somebody saying

1:41:11something which will be impacting their

1:41:12ability to reason verbally. So what I

1:41:15did is I suggested they move their best

1:41:16writers the people that were performing

1:41:18the most to closed offices for a few

1:41:20weeks. Uh just a few weeks and they

1:41:22obliged and wouldn't you know it all of

1:41:23their KPIs massively skyrocketed like

1:41:26night and day. And I mean, sure, some of

1:41:28it probably made the environment a

1:41:30little bit sadder because now we didn't

1:41:31have a bunch of people together cracking

1:41:33jokes and shooting the but I'll be

1:41:34honest, the purpose of business is to be

1:41:36effective, right? They were currently

1:41:38not being very effective despite being

1:41:39all close-knit and stuff like that. So,

1:41:42you know, instead, they just hung out

1:41:43during lunch and had a blast. Then, I

1:41:45would not recommend you pay the verbal

1:41:47reasoning tax on intelligible speech in

1:41:49your environment. It is completely

1:41:50needless. Personally, I use a

1:41:52combination of foam earplugs and a

1:41:54closed door. And I know this sounds a

1:41:56little antisocial, but uh significantly

1:41:57improves my clarity of thought, and that

1:41:59is ultimately what we're going for here.

1:42:01So yeah, I mean, I don't have the

1:42:02earplugs with me. I would have shown

1:42:03them to you, but they're just bright

1:42:04orange, and I stick them in my ear

1:42:05before I start working.

Working next to a window

1:42:07Another easy 2 to 5% improvement is

1:42:09working next to a window. As mentioned,

1:42:11your circadian rhythm depends on your

1:42:13eyes receiving light. So to optimize

1:42:15this in your own workspace, my

1:42:16recommendation is have your desk near a

1:42:18window of some kind. So in my case, for

1:42:20instance, I have a big floor toseeiling

1:42:21window immediately to my left. Not only

1:42:23does this function as nice lighting for

1:42:24my face, it also improves my cognition.

1:42:28Now, moving your desk, if you think

1:42:29about it, is free, absolutely free

1:42:30leverage, but if you don't have a

1:42:32window, let's say you're working in one

1:42:33of those closet style, cave style

1:42:35offices, um what you can do is use a

1:42:37powerful lamp on your desk every

1:42:39morning, use it as an alternative, sit

1:42:41near that. Um for instance, I have a

1:42:4210,000 lux one right over here, which I

1:42:45don't know if I'll be able to pull in.

1:42:48Yes, I don't think you guys can see this

1:42:50really. It's just out of frame here.

1:42:51There it is. Anyway, it's a very big and

1:42:53very powerful light. Cost me 200 bucks

1:42:55or so. And I use it in the winters

1:42:57before I wake up. Um, I'll talk a little

1:42:59bit more about that later, but basically

1:43:00in northern environments just due to the

1:43:02way the Earth is tilted, you don't get

1:43:03anywhere near as much light in your

1:43:05average day uh until maybe 9 or 10 a.m.

1:43:07And most of the time I'm awake before

1:43:09that. So, if I want my circadian rhythm

1:43:10to get jump started, that's what I have

1:43:12to do. Next up, reduce clutter for 1 to

Reducing clutter

1:43:153%. Now, attention, as mentioned, is a

1:43:17spotlight, but it doesn't just

1:43:20illuminate things that are underneath

1:43:21that spotlight. The gatekeeper sometimes

1:43:23allows additional things into your

1:43:25working memory, even if you didn't want

1:43:26to. And unfortunately, as we know, the

1:43:28working memory is quite limited

1:43:29chunkwise. So, you can only keep a

1:43:31certain number of things in that puppy

1:43:32at any one time. Meaning, if you have a

1:43:35bunch of stuff in your environment, even

1:43:36clutter on your desk, some of that will

1:43:38enter your attention and thus your

1:43:40working memory without you wanting to.

1:43:43Now, just like intelligible speech,

1:43:45every object in your visual field is

1:43:47technically competing for some small

1:43:48share of your attention. If you have to

1:43:50constantly fight all of that off, it is

1:43:52consuming your resources. When you

1:43:54focus, your visual system has to spend

1:43:56effort suppressing all of the clutter in

1:43:58your environment, which is called biased

1:44:00competition. Meaning, if your desk is

1:44:02filled with papers, cables, mail, and

1:44:04other miscellaneous objects, your bra

1:44:05your brain actually spends energy every

1:44:06time you look at it, slightly

1:44:08classifying their location, their

1:44:09position, the way that they're oriented,

1:44:11and so on and so forth.

1:44:13So there's just no need to suffer that.

1:44:15And if you've ever wondered why really

1:44:16rich people's homes are typically quite

1:44:18clean, I think part of it is this. They

1:44:20likely don't know it at face value, but

1:44:22it is likely one of the major reasons.

1:44:24They just feel like they can focus more

1:44:25when they don't have clutter on their

1:44:26desks or on their kitchens or so on and

1:44:28so forth.

Batching notifications

1:44:30The next easy 3 to 6% has to do less

1:44:33with physical workspaces and more with

1:44:35virtual and digital workspaces. And this

1:44:37one is batching your notifications for

1:44:39an easy 3 to 6%.

1:44:41In case you didn't know, phones and

1:44:42computers are designed to capture and

1:44:44hold your attention. It's inherent part

1:44:46of the economic value model of companies

1:44:48that make them. The more time you spend

1:44:50on your phones and computers, the more

1:44:52money these companies will make. So,

1:44:54they set their defaults as high levels

1:44:57of notifications. These play into their

1:44:59incentives and then make them tons of

1:45:01money. What I'm going to do here is help

1:45:03you change those settings a single time

1:45:05and then gain clear thinking as a result

1:45:07and then be done with them for the rest

1:45:09of your life to easily and immediately

1:45:11pick 3 to 6% on the cognitive capacity

1:45:14side but probably far more than that on

1:45:16the general life happiness side. Now

1:45:18first every notification forces your

1:45:20brain to temporarily switch tasks

1:45:21between what it was doing and then the

1:45:22notification. As mentioned your

1:45:24attention and working memory is quite

1:45:26limited. So when something salient in

1:45:27your environment occurs like maybe a

1:45:29phone buzzing or maybe like I don't know

1:45:30your screen turning on in the corner

1:45:32your mind will actually attend to it

1:45:33whether you want to or not. This leads

1:45:35to a byproduct called attentional

1:45:37residue where even if you shift back to

1:45:40work okay if I see the notif and then I

1:45:42go back to my screen a part of my

1:45:44attention a part of my spotlight is just

1:45:46impossible to wrench away from my phone.

1:45:50That means I'm basically keeping track

1:45:52of it in case it buzzes again or in case

1:45:55it lights up again because, you know,

1:45:56evolutionarily I'm constantly keeping

1:45:58track of all the things in my

1:45:59environment that move in case it's a

1:46:00snake coiled up ready to attack me or

1:46:02something like that. Now, in the

1:46:04literature, this can cost you 10 to 15%

1:46:07of your cognitive capacity for as long

1:46:08as 20 freaking minutes. And many of you

1:46:11guys, unfortunately, get disrupted and

1:46:13distracted by notifications more than

1:46:15once every 20 minutes. Some people here

1:46:17probably get distracted by notes like

1:46:18every 3 minutes. Put it another way, you

1:46:21are basically like in my office example,

1:46:23permanently hobbling your ability to

1:46:25think clearly because you always have

1:46:26somebody saying something in the

1:46:27background. The good news is the fix is

1:46:30really easy. You just go through your

1:46:31phone, turn off all of the banners,

1:46:32bubbles, and sounds notice. And instead,

1:46:35you schedule your notifications to be

1:46:36delivered in two to three batches per

1:46:37day using the built-in and iOS feature

1:46:40called scheduled summary. Whereas in

1:46:42Android, you can just turn off all

1:46:43notifications and check your phone at

1:46:44specific times like 11 or 4 p.m. The way

1:46:47you do that is just by setting an alarm.

1:46:49So, you guys hearing me right? Instead

1:46:50of checking your phone randomly over the

1:46:52course of the day as follows. Okay,

1:46:5424-hour chunk. You're constantly just

1:46:56looking looking every couple of hours

1:46:58and then facing that 20 minutes of

1:47:01addentional residue afterwards. What you

1:47:03do is you choose the times to batch and

1:47:05check. Maybe you do two or three

1:47:07throughout the day. And now instead of

1:47:08constantly being in a state of 20%

1:47:10reduced performance for maybe 50% of the

1:47:12dice or 10 percent across the board,

1:47:14maybe you only have to suffer two or 3%

1:47:16while still getting the upsides of using

1:47:17this really cool technology to to stay

1:47:19in touch with people. So I run all my

1:47:21social media channels personally using

1:47:23the same principle. If you think about

1:47:24it, um, one major revenue driver of mine

1:47:26right now is I run Maker School, which

1:47:28is a community that guarantees your

1:47:29first customer for an AI or automation

1:47:31service in 90 days or I give you your

1:47:32money back. So there's lots of people in

1:47:35that freaking community. I mean, almost

1:47:372,500 right now. And they make posts all

1:47:39the time. Just like a social media

1:47:42notification. I could respond to their

1:47:44post every day, all day throughout the

1:47:46day. But instead, what I do is I batch

1:47:48it. What I'll do is I will check in at

1:47:50one or two intervals every day. I will

1:47:52then respond in bulk and then I do not

1:47:54let it eat up the rest of my day. So

1:47:56rather than me being constantly pulled

1:47:58away from what I'm doing and then having

1:47:59to go back to this thing, you know, I

1:48:01can just focus on the thing and get it

1:48:03done. This is obviously far more

1:48:05efficient than me checking in 40 times a

1:48:06day. And in addition to helping me think

1:48:08clearer throughout the rest of my day,

1:48:10it also probably saves you a lot of time

1:48:11because you're not constantly being

1:48:12pulled away and then working in an

1:48:14inefficient manner. Meaning you have

1:48:15both the direct gains in terms of

1:48:17performance improvements and you also

1:48:18have the indirect gains in terms of time

1:48:20improvements as well. Another really

Single-tasking your screen

1:48:22quick and easy hack is to single task

1:48:24your screen for 3 to 8%. Now, similarly

1:48:27to the clutter rule, right, we spend a

1:48:29lot of time in a virtual environment

1:48:30which is basically like our physical

1:48:32environment. Now this screen almost

1:48:33extends into three dimensions. I could

1:48:35see far past it. So similar to that

1:48:37rule, you should minimize clutter on

1:48:39your environment. The way that I do it

1:48:41is I go full screen with no other apps

1:48:43or tabs visible. This minimizes the

1:48:46attentional drag and forces me to

1:48:48actually just sit and focus on one task.

1:48:50For instance, while recording this

1:48:51video, I only have one window open. I do

1:48:53not have 45 different monitors blinking

1:48:56stock tickers at me and whatever the

1:48:58hell else. All I have is this.

1:48:59Therefore, all I can do is this. Couple

1:49:02exceptions. Obviously, if you guys are

1:49:03doing explicit design heavy work, if you

1:49:05guys are crazy active day traders or

1:49:08whatever the hell, if you need to

1:49:08constantly compare things between one

1:49:10screen and another, you know, there can

1:49:11be some value in having a few windows

1:49:13open, a few tabs, the visual ease of

1:49:16dragging and dropping stuff and looking

1:49:17and and so on and so forth probably does

1:49:18outweigh the cognitive impact.

1:49:20[sighs and gasps] However, all other

1:49:22times and in all other situations, I

1:49:24would close your email, your chat apps,

1:49:26and all of the 31 tabs you have open,

1:49:28unless you're explicitly working on

1:49:30getting those through. I'd also remove

1:49:32your URL bar, your taskbar, and give

1:49:34yourself nothing but the thing in front

1:49:35of you. What do I mean by URL bar? I

1:49:38mean, I would literally like go to the

1:49:39setting in the top right or top left

1:49:40hand corner of Chrome or or whatever

1:49:42operating system you're on and going

1:49:44into the view tab and saying turn off

1:49:45URL bar. I'd go down to the bottom, I'd

1:49:47say, turn off taskbar. I make it so that

1:49:49when I look at my screen, I only have

1:49:50the thing that I'm currently working on.

1:49:52It just makes you far more efficient.

1:49:53All right, that's it for the hardware

1:49:54portion. If you guys have followed along

1:49:56with everything up until now, you're

1:49:57probably looking at a stacked

1:49:59multiplicative improvement in the

1:50:00clarity of your thinking and your focus,

1:50:03right? So, combine those to the tune of

1:50:05about 150 to 200% or so. And obviously,

1:50:08you know, a lot of these are estimates.

1:50:10Of course, I just took what the science

1:50:12said and then gave them to you and told

1:50:14you to multiply them. I think um you

1:50:16have to infer the actual end impact on

1:50:20your own stats, if you want to call them

1:50:22that, of attention, working memory, and

1:50:24executive function through the lens of

1:50:26like your own problems and the own

1:50:28things that you struggle with. For

1:50:29instance, I think a lot of people here

1:50:31probably suffer from way worse than the

1:50:33800 parts per million CO2 issue. I think

1:50:36a lot of people probably have ambient

1:50:37problems with air quality, especially in

1:50:38like Southeast Asia, you know,

1:50:40Bangladesh, India, and so on and so

1:50:41forth. I think they're like different

1:50:44things that everybody gets to pluck out

1:50:46of that big list, but so long as you

1:50:48plucked out a couple of them, I think

1:50:49you'll probably be at least, you know,

1:50:5220 to 30% better, if not 50% or more.

1:50:55Um, and because all of those scale with

1:50:57the magnitude of your starting place if

1:50:59you're sleep disordered for instance,

1:51:01fixing your sleep will lead to a

1:51:02significant improvement in your hardware

1:51:04that, you know, a non-sleep disordered

1:51:06person would probably feel. And I think,

1:51:08you know, we all sort of carve out our

1:51:09own story there. So anyway, not bad for

1:51:12a bunch of low-hanging fruit, huh?

1:51:13That's about as free leverage as you

1:51:15could possibly find. From here on out,

1:51:17what I'm going to be doing is pivoting

1:51:18to software and creating a toolbox of

1:51:20processes and algorithms that help you

1:51:22think more clearly. A very interesting

1:51:24thing, software is infinitely more

1:51:27malleable and growable than hardware.

1:51:29Whereas our hardware, basically our

1:51:31attention, working memory, executive

1:51:32function are fairly fixed and can only

1:51:34be nudged or expanded slightly.

1:51:37Better software can provide algorithmic

1:51:39improvements to the tune of many

1:51:41thousands of percentage points. And I

1:51:43don't say that lightly. I think great

1:51:45thinkers are genuinely orders of

1:51:46magnitude faster and better than poor

1:51:48thinkers are. And it's all because they

1:51:50just apply the tools that I'm about to

1:51:51teach you. So some action questions just

1:51:53to wrap that up. Before we go into

1:51:55software, answer these two questions. Uh

1:51:57take an inventory of the room that you

1:51:59are in right now and apply the workspace

1:52:01design principles to it. What is your

1:52:03air like? Can you hear the people around

1:52:05you? What is in your direct field of

1:52:07view and how can you improve it? Next,

1:52:09open your phone. What notifications are

1:52:12asking for your attention? Turn them all

1:52:13off unless absolutely necessary.

Software: models as programs

1:52:17So on software, obviously the human mind

1:52:18and the computer are different things

1:52:20and you can't analogize them one to one.

1:52:22You know, one is silicon, the other is

1:52:23meat. But bear with me. Between 1988 and

1:52:272003, computers got around a thousand

1:52:29times faster via hardware. better

1:52:32memory, better processors, better

1:52:34architecture, and so on and so forth.

1:52:36And so, if you think about it, that's

1:52:37pretty incredible, right? But you know

1:52:38what is even more incredible? During

1:52:40that same time period, software

1:52:42algorithms got 10,000 times faster. Now,

1:52:46clearly software is a different beast

1:52:47entirely. Whereas, you could extract

1:52:49significant and fixed gains from

1:52:51improving your own hardware, having the

1:52:53right program to run on is an order of

1:52:56magnitude as powerful since it also

1:52:57allows you to consider problems from a

1:52:59fundamentally different lens. So imagine

1:53:01if you will that you were only ever

1:53:03taught addition. You know, no

1:53:04multiplication, no nothing. If I asked

1:53:07you, hey, can you add the number 10 to

1:53:09itself 100 times, aka 10 + 10 + 10 + 10

1:53:15all the way up to 100. How long would

1:53:17that take you? It would probably take

1:53:18you forever, right? It doesn't matter

1:53:20how fast you are at mental addition

1:53:22because fundamentally, the solution to

1:53:24adding a bunch of numbers together is

1:53:25slow and it's linear. And it' probably

1:53:28take you 3 or 4 minutes to actually go

1:53:30through the process of adding 10 to 10

1:53:32to 10 to 10 100 times to get to a

1:53:35th00and. There's also in a situation

1:53:37like that a much higher probability of

1:53:38error because maybe you just missed one

1:53:40or two of those 10 and now you think

1:53:42it's 980 whereas the actual answer is

1:53:44obviously a th00and. But imagine giving

1:53:46that same problem to somebody who has

1:53:48the multiplication program installed on

1:53:50their brain. Whereas person A might take

1:53:534 minutes to do it. Person B could

1:53:55literally do it in a second. Not only

1:53:57would they do it in a second, the error

1:53:58rate would be far, far lower. That's

1:54:01exactly what I intend to show you guys

1:54:02today. I intend to show you a set of

1:54:04operators that you could use to better

1:54:05understand, conceptualize, and then

1:54:07think through all of the problems in

1:54:08your own life. And the first is expected

Expected value

1:54:11value. Now, most decisions always get

1:54:13made based off of gut feeling. This is

1:54:15type one decision-m. In the average

1:54:18day-to-day life of a human, this is

1:54:19usually fine because the decisions that

1:54:22you get are things like, "What coffee

1:54:23did you want today?" Eh, I'm feeling

1:54:25like a latte. [gasps] Holy crap, is that

1:54:27my bus? Let me run over towards it. And

1:54:29so on and so forth. But you're here

1:54:31because you want to learn more than

1:54:32that. You want to learn how to think

1:54:33through decisions that ultimately impact

1:54:35the rest of your life. So that's things

1:54:38like, should I launch X product or

1:54:41should I spend the next 6 months of my

1:54:43life on Y pursuit? And these are nuance

1:54:46questions that have nuance answers. You

1:54:48know, gut feelings are ultimately a

1:54:50terrible way to make high-risisk, high

1:54:52impact decisions like that because gut

1:54:54feelings are always just yes or no.

1:54:55They're also not accountable at all, and

1:54:57they're also not interpretable. The

1:54:59whole go with your gut thing sounds nice

1:55:01in practice, but when you can't look

1:55:03back and say, "So, why the hell did I do

1:55:04that thing to begin with?" And your only

1:55:06answer is cuz my gut told me so.

1:55:08Obviously, that is not a very rigorous

1:55:10decision-making process that you can

1:55:11rely on for larger things. The solution

1:55:14to all this is expected value. It is the

1:55:16single most useful piece of arithmetic

1:55:18that I know and it'll take you literally

1:55:20just 1 minute once you've done it a

1:55:22couple of times. Now, expected value

1:55:25defined in as simple terms as possible

1:55:27is when you sum each possible outcome's

1:55:29value multiplied by its probability. And

1:55:32I know that sounds really mathematical.

1:55:34It's probably pretty intimidating to

1:55:35you, but it's actually very simple.

1:55:37Let's pretend that you and I are playing

1:55:39this game where we flip a coin and if it

1:55:41comes up heads, you get $3. And if it

1:55:43comes up tails, you lose $1. Now,

1:55:46logically, the coin flip has two

1:55:47outcomes, heads or tails, right? The

1:55:50probability of heads is 50%, and the

1:55:52probability of tails is 50%. So, there's

1:55:55nothing super crazy here just yet. Keep

1:55:57following along with me. In expected

1:55:59value terms, what you do to figure out

1:56:01the value of whether or not I should

1:56:02play this game is you multiply the

1:56:04probabilities of each outcome by their

1:56:06respected values. So for instance, a

1:56:09probability of 50% is equivalent to 0.5

1:56:12mathematically. So that's our

1:56:14probability. And we already know the

1:56:16value of the outcome, which is $3 for

1:56:18heads, right? Which means our equations

1:56:20look like this. If we wanted to figure

1:56:21out the outcome of heads, well, heads is

1:56:240.5 times the outcome, which is $3 means

1:56:27that the EV of heads is actually $1.50.

1:56:30Tails is 0.5 as well. But this has a

1:56:34value of minus1 cuz that's where you

1:56:36lose a dollar which means that the EV of

1:56:38tails is 0.5. Now if you wanted to get

1:56:40the expected value not of a specific uh

1:56:42head or tails but the whole game itself

1:56:45then what you would do is you would take

1:56:46the value of heads and add it to the

1:56:48value of tails. The value of heads is

1:56:50$1.50. The value of tails is minus50

1:56:54meaning the expected value is a dollar.

1:56:56What this means then is that the

1:56:59expected value of playing this game

1:57:01every time is a dollar. Meaning that if

1:57:04I play the game a thousand times and I

1:57:06zoomed out and asked myself how much

1:57:08money would I make if I played this game

1:57:10a thousand times, I would make

1:57:12approximately $1,000 cuz every time I

1:57:14play statistically I win a dollar. Now,

1:57:18while it's true that you probably won't

1:57:19make exactly $1,000 because of

1:57:21statistical chance, you know, I might

1:57:22have a lucky winning streak or I might

1:57:25make a bit over that, maybe $1,5 or $943

1:57:28or something. The more you zoom out, if

1:57:30it's 10,000 runs or 100,000 runs or a

1:57:32million runs, the closer I will get to

1:57:35that actual reality.

1:57:37Okay, so that is the hypothetical coin

1:57:39flip example, which I think people

1:57:40understand intuitively. Let's apply this

1:57:42to something that's a bit more real

1:57:44life, shall we? Let's say I run a small

1:57:47service company right now and I install

1:57:49solar panels. I've seen a bunch of cool

1:57:51new developments on Twitter and I'm

1:57:52trying to decide on whether I should

1:57:54start a big SAS company, which is new

1:57:55and exciting, or I should keep my small

1:57:57service agency running, which is small,

1:57:59old, and familiar.

1:58:01Instead of me just being like, what does

1:58:03my gut tell me? Man, I should go big or

1:58:05go home. I'm going to start the SAS. We

1:58:07can actually compute the expected values

1:58:08of both of these options using this new

1:58:10framework. So, let's say you do a bunch

1:58:12of research and you determine that the

1:58:13industry that you're trying to start a

1:58:14SAS in is willing to buy a company like

1:58:16yours for a billion dollars. Maybe

1:58:19that's the average sale value.

1:58:21Meanwhile, you also notice that the

1:58:22majority of companies that are started

1:58:24in this space fail miserably, meaning

1:58:26that your probability of success is very

1:58:28low. Maybe it's.1% or 1 in a,000. What

1:58:31that means is you have a 1 in1,000

1:58:33chance of making a billion dollars. Kind

1:58:35of how that works, right? So, keep that

1:58:38in mind. On the other hand, let's think

1:58:40about the SAS business, uh, the service

1:58:41business. Your current service business

1:58:43makes $500,000 a year. You do some

1:58:46market research and think about your

1:58:47business and you say, you know what,

1:58:48this is probably going to run for

1:58:49another 5 years minimum. And I give it a

1:58:5250% chance that I'm right there. Maybe

1:58:5350% of the time it'll run less than 5

1:58:55years. Maybe 50% of the time it'll run

1:58:56more than 5 years. Okay? So that means

1:58:59the expected value of starting a SAS

1:59:01versus your current company is as

1:59:03follows. The EV of the SAS is again

1:59:06equal to the value time the probability.

1:59:09So the EV of the SAS is again $1 billion

1:59:12time 1/1,000th of a you know odds. So a

1:59:16billion *1 1,000th is a million. That's

1:59:20just how that works. What that means is

1:59:22the expected value of doing the SAS is

1:59:25if you choose to make the SAS, it will

1:59:26make you a million dollars.

1:59:27Statistically, if you could zoom out and

1:59:29start a billion SASS on net, every one

1:59:33of those SASes would actually only make

1:59:34you a million dollars. Why? Because the

1:59:36vast majority of them would fail. Only a

1:59:38couple of them would win, and the ones

1:59:40that win on average would win

1:59:41approximately this much. Now, how about

1:59:43the expected value of your current

1:59:45company? The EV of this small business

1:59:47is again equal to the value times the

1:59:49probability. Well, I added an additional

1:59:51step here cuz I wanted the value to be

1:59:53non-trivial to compute. So in this case,

1:59:55I said the value was $500,000. But how

1:59:57many years would it run? Five. So we

1:59:59actually have to multiply these two

2:00:01numbers together. Which means the EV of

2:00:02the small business is actually 2.5

2:00:04million times our 50% probability that

2:00:06we'd actually still maintain the

2:00:07business for that 5 years. What we get

2:00:09is 2.5 *.5 or 1.25 million which if you

2:00:13think about it logically means that the

2:00:14you know small business makes us 1.25

2:00:17million. The SAS makes us 1 million. So

2:00:20in this example, the expected value of

2:00:22the SAS is actually lower than the

2:00:23expected value of the small business.

2:00:25Put in simple terms, the value of

2:00:27starting this big fancy company is not

2:00:29as high as the value of just continuing

2:00:31to work on on your SMB.

2:00:34Now, I know what you're thinking here as

2:00:35I go through this example. You're

2:00:36thinking, Nick, how the hell am I

2:00:38supposed to know the precise dollar

2:00:39amount or probability of every single

2:00:41decision that we're considering making?

2:00:42Uh, if you do know this somehow

2:00:44magically, give me a call. I have some

2:00:46work for you. The reality is, you will

2:00:47not know these numbers, and that is

2:00:49totally normal. The point of expected

2:00:51value is not meant to be taken

2:00:52literally. The point is it's meant to be

2:00:54a tool that you use to objectively

2:00:55evaluate multiple different object

2:00:58objects or options in concert. Rather

2:01:01than just going off of somebody's gut

2:01:02feeling, which is always the same

2:01:04circuit that was used by your animal

2:01:06ancestors, which is only yes or no, this

2:01:08actually lets you upgrade your software

2:01:10and apply a stronger, more rigorous

2:01:12decision-m uh process to the art of

2:01:14making decisions. And so instead of you

2:01:16just being like, I'm going to do this or

2:01:18I'm not going to do this, you now

2:01:19actually say, well,

2:01:21I predict that if I do this, I'll make

2:01:23this much money, that is now a

2:01:25falsifiable prediction. You can actually

2:01:27take that prediction, store it somewhere

2:01:30like in a journal, in a year from now,

2:01:32come back and update it based off of

2:01:34your actual experience. Likewise, you

2:01:36could share that prediction with other

2:01:37people, have them follow the same

2:01:39rigorous standardized thinking process,

2:01:41and in that way think far more clearly

2:01:43about whether or not something is likely

2:01:44to actually work. And the cool thing is

2:01:47in the case of the SAS example, we see

2:01:49how that an option that may seem sexy,

2:01:51exciting, and perhaps like the right gut

2:01:52feeling for most people, obviously, I

2:01:54want to go big or go home, that sounds

2:01:55fun, actually underperforms compared to,

2:01:57in this case, the very boring and very

2:01:59safe one.

2:02:01I want to talk about poker for a second.

2:02:03Professional poker players that are with

2:02:05me right now will probably have nodded

2:02:07along this whole time and been like,

2:02:08"Okay, get to the good part." The reason

2:02:10why is they already know expected value

2:02:12and they do that math in their heads

2:02:14constantly. I'd say that's actually one

2:02:15of the core skills of playing poker

2:02:17really well. Good poker players are

2:02:20always computing the expected values of

2:02:22their hands versus their competitor's

2:02:23hands at all possible times. And then

2:02:26the entire way you play is you just look

2:02:27for games where you have a slight edge,

2:02:29meaning the EV of you doing the I don't

2:02:32know, you know, folding or something is

2:02:33a little bit higher than the EV of you

2:02:35uh going all in. And as long as the

2:02:37expected values are positive, they will

2:02:39play around. And if the expected values

2:02:40are not positive, they'll stay out. So

2:02:42since the expected value is all about

2:02:44averaging outcomes over a long period of

2:02:45time, poker players that even have a

2:02:47slight edge, like they make like an

2:02:48expected value of like a dollar per hand

2:02:50or something, will typically come out on

2:02:52top over the long run. The issue is it

2:02:55won't be abundantly clear in your first

2:02:56few hands because you need to play

2:02:58enough times for the law of large

2:03:00numbers to work out in your favor, for

2:03:01statistics to kick in. And that's why

2:03:03having enough of a betting pile comes in

2:03:05handy because the more money you have to

2:03:07bet, the longer you can stay in the game

2:03:09enough for your fundamental expected

2:03:10value bets to pay off. This is the same

2:03:13thing, by the way, that underlies why

2:03:15people that have a lot of money tend to

2:03:16be a lot uh less risk averse. If you

2:03:20have a lot of money, if you have a big

2:03:21betting pile and you're confident that

2:03:23at some level the expected value of your

2:03:25decisions are right, you're okay wasting

2:03:27a bunch of that money on bets that may

2:03:29not pay off in the short term but will

2:03:30pay off in the long run. That's because

2:03:32your model of expected value is high. If

2:03:35you've ever wondered why some people go

2:03:37allin on stuff or spend tons of money on

2:03:39small things or I don't know venture

2:03:41capitalists give $50,000 to a 100

2:03:43different companies, that's because they

2:03:44compute the expected value of every one

2:03:46of these bets as just a little bit

2:03:48bigger than zero. Maybe it's, you know,

2:03:50$50,000 or something. And so in that

2:03:52way, they know they just need to do

2:03:54enough of these eventually they'll make

2:03:55$50,000 when they're $50,000, doubling

2:03:58their ROI. I mean VCs in particular,

2:04:00they want way more than a double, but

2:04:02you get my point. So all of that is to

2:04:04say your probabilities are estimates.

2:04:06You won't know them perfectly and that's

2:04:08totally okay. The key is just write them

2:04:10down. When you write 20%, that is

2:04:12something that is concrete and it is

2:04:13modifiable. If you just feel nah, it's

2:04:16risky. I don't want to do it. That is

2:04:18not concrete modifiable and you cannot

2:04:20use it to make good decisions.

The resulting trap

2:04:24I want to talk a sec for I want to talk

2:04:26for a sec about the resulting trap. Now,

2:04:28when people start learning about EV,

2:04:30they will often fall prey to the trap of

2:04:32resulting. The term was initially

2:04:34invented by Annie Duke, who was a former

2:04:36professional poker player back in a 2018

2:04:39book called Thinking in Bets. You guys

2:04:41might have read it. It's very popular

2:04:42when it came out. Um, the core idea is

2:04:45resulting is the tendency to evaluate

2:04:47the quality of a decision based on the

2:04:50decision's outcome.

2:04:52For instance, let's say you use expected

2:04:54value on a hypothetical decision between

2:04:56A or B. Here is the expected value of a.

2:04:59It is 2 *8 = 1.6. The expected value of

2:05:05b is 10 *2 which is equal to 2. If you

2:05:09think about it in our formula 2 here is

2:05:12the value.8

2:05:14is the probability. So for a there is a

2:05:1980% chance you will win a two meaning

2:05:21the value of this play is 1.6. For B,

2:05:26there is a 20% chance you'll win A 10,

2:05:28meaning the value of this play is two.

2:05:31So logically speaking, you know, A is a

2:05:33lot safer because there's much higher

2:05:35probability you'll win. With B, it's

2:05:37less likely you'll win, but when you do,

2:05:39you win big. And so that's how you sort

2:05:40of think about expected values. You

2:05:42think about it in terms of probabilities

2:05:43and outcomes. So in an environment like

2:05:46this where EVB is equal to two and EVA

2:05:48is equal to 1.6, logically, you should

2:05:50probably pick B, right? Because EVB is

2:05:51higher than EVA. But keep in mind the

2:05:54probability of 0.2 or 20%. Despite B

2:05:57being technically the right answer

2:05:59according to our formula, it'll actually

2:06:01only pay off 20% of the time. So if you

2:06:04choose B and then you don't get that 10

2:06:07payout, you will naturally consider it a

2:06:09dumb decision. You'll be like, man, I

2:06:11know it said the EV was two for B and

2:06:13that's why I picked it, but I just lost

2:06:16all my money or I don't know, I didn't

2:06:18make the two. What the hell? This is

2:06:21logically incorrect because B is in fact

2:06:23the right choice. It's just the right

2:06:26choice happens to lose 80% of the time.

2:06:28The thing is when you get the win, it'll

2:06:31pay out enough to reverse that trend 20%

2:06:33of the time. So real life is kind of

2:06:36like that because in real life you'll

2:06:38have a lot of decisions that you make

2:06:39that don't immediately pay off. You need

2:06:41to hit the net constantly in order to

2:06:43make them pay off. But if you start

2:06:45evaluating your decision-m based off the

2:06:47results you get on a small sample size,

2:06:49you will make incorrect inferences that

2:06:51lead obviously to incorrect conclusions.

2:06:54If you penalized yourself for every

2:06:55single decision you made that did not

2:06:56immediately pay off, you would probably

2:06:58quickly learn never to take a B sorted

2:07:00bet again, right? But that would be a

2:07:03major mistake. Likewise, a lot of people

2:07:05find the opposite. They might choose A

2:07:08and then they'll get like a little

2:07:09payout of two every time and then

2:07:10they'll say, "I'm a genius. Every time I

2:07:12do this, I win. I win. I win. So then

2:07:14you'll start logically thinking, well,

2:07:16it's smarter for me to continue taking A

2:07:17as opposed to B despite A paying a

2:07:19little bit less. That's fine. I'm making

2:07:20way more money. This is the same thing

2:07:23that happens in poker. If you folded a

2:07:24hand based on correct odds, and then the

2:07:26winning hand comes out anyway, you have

2:07:27not made a mistake. You had the right

2:07:29idea, the fold was the right move

2:07:31despite losing. The point is, you just

2:07:34need to zoom out and understand that

2:07:36this one time that I won or this one

2:07:38time that I lost is not actually

2:07:39representative of the whole thing. I see

2:07:42this, you know, B play a lot in

2:07:45business, specifically in cold outreach,

2:07:47because there's about a 20% chance that

2:07:48most people will see any sort of

2:07:50outreach that you send. And so, if I'm

2:07:52attempting to sell my product or service

2:07:53and I send an email to somebody, let's

2:07:54say, and they only had a 20% chance of

2:07:56looking at it, that means 80% of the

2:07:57time they see nothing. So, if I am new

2:08:00to this and I send out outreach and four

2:08:03times out of five people don't see it, I

2:08:04might think, "This sucks. I don't get

2:08:06anything out of it." It's simply because

2:08:08I do not have enough of a sample size to

2:08:11draw from for me to understand that well

2:08:13when you do get some something that pays

2:08:15off, boy, it pays off really big. Uh if

2:08:18you understood this on a visceral level,

2:08:20which you do after you usually get a

2:08:21couple of wins, uh the probability of

2:08:23you staying in the ring for longer goes

2:08:25way up.

2:08:26So zoom out, play a thousand hands or

2:08:29make a thousand decisions or start 100

2:08:31businesses or whatever. When you do

2:08:33this, you will easily be able to tell

2:08:34the difference between a good decision

2:08:36and a bad decision. Okay? So, here's a

2:08:38little decision matrix. If you had a

2:08:41good decision, but it was a bad outcome,

2:08:43that means that you just had bad luck

2:08:44and you should keep doing it. If you had

2:08:46a good decision and a good outcome, you

2:08:47obviously deserve the win. If you had a

2:08:48bad decision and a bad outcome, you

2:08:50obviously deserve the loss. But if you

2:08:51made a bad decision and got a good

2:08:52outcome, you got lucky and you should

2:08:54count that as a win.

2:08:56Here's another example for EV. If you

2:08:58guys were considering hiring a

2:08:59salesperson at a cost of 6K per month,

2:09:01and you believe there's a 60% chance

2:09:03they'll succeed and generate 15K in

2:09:05gross profit per month after a 3-month

2:09:06ramp, and a 40% chance that they will

2:09:08fail and generate $0 in gross profit

2:09:10before you fire them at the end of that

2:09:113-month ramp, resulting in an $18,000

2:09:14loss, should you hire the salesperson?

2:09:16Well, you can actually do expected value

2:09:18math by subtracting the two. So in the

2:09:20case of should I do X or should I do Y

2:09:23or rather just should I do X in general

2:09:25where X has two outcomes. The expected

2:09:26value of the decision is expected value

2:09:28of success assuming everything goes well

2:09:30minus the expected value of fail

2:09:31assuming things do not go well. So in

2:09:33our case here and I'm just going to bury

2:09:35the mathematics here because I know some

2:09:36people are probably listening as a

2:09:37podcast not necessarily watching it. EV

2:09:39success is equal to 9,000. EV fail is

2:09:43equal to 7,200. That means that EV

2:09:46success minus EV fail is equal to

2:09:48$1,800. That means that the value of

2:09:52making this decision is $1,800

2:09:54over that 3 months. That means basically

2:09:57if you make this decision from an

2:09:59expected value standpoint, you will gain

2:10:00$600 a month every month for those three

2:10:03months, which is obviously positive,

2:10:05right? Who doesn't want $600 for free?

2:10:08Now, I do a rough version of this

2:10:09expected value framework in my head for

2:10:11small stuff, and then I'll actually take

2:10:12it on paper, just like I did here for

2:10:14anything that costs me more than a few

2:10:15days or maybe $10,000 or so. What I have

2:10:18found is that writing the probability

2:10:19down influences my later decision-m far

2:10:21more than the actual arithmetic that I'm

2:10:23doing. It forces me to try my best at

2:10:25quantifying the odds, which is most the

2:10:27value. Literally just articulating how

2:10:29likely do I think this actually is. So,

2:10:32speaking of actual, let's do some action

2:10:35questions. Write an expected value

2:10:37calculation for a decision you've made

2:10:39in the last year with probabilities and

2:10:41payoffs. Then decide whether it was a

2:10:43good decision or a bad decision based on

2:10:45your expected value. Okay, let's talk

Power laws

2:10:48power laws for a second. Power laws like

2:10:50expected value are a cool framework that

2:10:52allow you to peek a little bit behind

2:10:55the curtain at probability theory and

2:10:57what I should probably be doing with my

2:10:59time. and they're at the core of what I

2:11:01would consider to be effective

2:11:02especially business decision-m in insert

2:11:05current year. So to make good decisions

2:11:07you must understand how the world is

2:11:09distributed. Most people have poor

2:11:11intuitions here. They will assume that

2:11:13things in life are distributed normally

2:11:15like height. Okay, for those of you guys

2:11:17that don't know, if you were to plot the

2:11:19height of a million random people, you

2:11:21would get a normal distribution or a

2:11:23bell curve distribution where the

2:11:26majority of people are going to be of

2:11:28average height and there'd be very few

2:11:30super short or super tall people. And

2:11:32for those of you guys that have never

2:11:33seen this before, what that distribution

2:11:34would look like would be like this. You

2:11:36know, around here zero, you would have

2:11:38the average height, which I don't know.

2:11:40I don't know the average height, but

2:11:41maybe for males it's like 57 or 5'8 or

2:11:44so. On the right hand side of the graph,

2:11:46you'd have a bunch of people that are

2:11:47taller. On the left hand side of the

2:11:49graph, you'd have a bunch of people that

2:11:50are shorter. And so, because human

2:11:52beings tend to intuitively understand

2:11:54that, you know, height is normally

2:11:55distributed, that most people are going

2:11:57to be here, like this is frequency,

2:11:58right? Number of people, and then this

2:12:00is the um standard deviation. Um they're

2:12:03going to assume everything in life is

2:12:04like this. But actually, very few things

2:12:06in life are like this. And that's the

2:12:08key because human intuition often

2:12:11assumes that distributions of like

2:12:13clients, videos, decisions, finances,

2:12:16and tasks are normally distributed. U

2:12:18they end up making a lot of bad

2:12:20mistakes. The reality is you cannot make

2:12:22good decisions merely by distributing

2:12:24your time or effort equally among

2:12:26candidate options. What you need to do

2:12:29is instead of normal distribution, look

2:12:31for a power distribution. And this is

2:12:34where the power law comes into play.

2:12:37So what is a power law? Well, in

2:12:39mathematics, a power law is a

2:12:40relationship between two variables where

2:12:42one is proportional to the other raised

2:12:44to some power. This is what it looks

2:12:46like mathematically. X is equal to Y

2:12:49raised to the N. Let's say

2:12:52this equation is less important than the

2:12:54graph. So when graphed it looks

2:12:56something like this. Generally speaking,

2:12:59okay, almost all power law graphs are

2:13:02going to look like this massive

2:13:03descending exponential. And the reason

2:13:06why is because on the left hand side of

2:13:07the exponential you have the outcome or

2:13:10impact of a thing typically the lowest

2:13:13frequency thing. What I mean by this is

2:13:16let me pretend for a moment that we are

2:13:18running a videography agency and we

2:13:21currently have 20 clients on our belt.

2:13:24You know we have client number one,

2:13:26client number two, client number three,

2:13:27client number four, all the way up to

2:13:28number 20. And on the left hand side of

2:13:30this graph we have the amount of money

2:13:31that every one of those clients has

2:13:32generated us. If you were to sort all of

2:13:35those clients based off of how much

2:13:36money they've paid you, the result would

2:13:39almost invariably look like this. And

2:13:40this is just a universal law of money

2:13:42and client relationships.

2:13:44[gasps and sighs] One of those clients

2:13:46would probably have paid you the vast

2:13:47majority of your wealth. The second

2:13:49client, descending order, would have

2:13:51paid you another big chunk. The third

2:13:53client would have paid you another big

2:13:54chunk. And the fourth client would have

2:13:55paid you the last big chunk. But all of

2:13:57the other 16 clients would have paid you

2:13:59virtually nothing. What that means is,

2:14:01okay, literally just client number one

2:14:04is probably equivalent to the bottom 16

2:14:06or so.

2:14:08Another way of conceptualizing this is

2:14:10having a few items carry the total.

2:14:14Now, the general rule is in life, um,

2:14:17aside from things like, you know, height

2:14:18and some biological principles, one item

2:14:21is typically responsible for a

2:14:22disproportionate share of whatever the

2:14:24outcome of interest is.

2:14:26For example, in business, a power law

2:14:27might look like a few products driving

2:14:29most of your revenue, a few clients

2:14:30comprising most of your MR, or you know,

2:14:32in investing, a few stocks driving most

2:14:34of your portfolio return.

The Pareto principle

2:14:36Many people here will probably have

2:14:38heard of this idea of this Pareto

2:14:39principle. It's a great example of the

2:14:41same concept where 80% of results are

2:14:44brought to you by 20% of causes. Uh,

2:14:47Pareto came up with this while studying

2:14:48the distribution of land in Italy way

2:14:50back in the day. I believe he noticed

2:14:51that 80% of the land was owned by 20% of

2:14:53the people, but I might be mistaken

2:14:55there. A more modern look at that might

2:14:57be companies like Microsoft because

2:14:59companies like Microsoft understand

2:15:01power laws and the Purto principle.

2:15:03Okay, what they do is they allocate the

2:15:05resources differently than if everything

2:15:08were normally distributed. For instance,

2:15:10Microsoft will identify the 20% of bugs

2:15:13in their software that cause 80% of

2:15:15customer complaints. They will then

2:15:17spend only 20% of their time on those

2:15:20bugs. Okay? Or rather 100% of the time

2:15:23on the 20% of the bugs. They will not

2:15:25distribute their time equally across all

2:15:27of the bugs because logically speaking,

2:15:28it is only a small portion of the bugs

2:15:30that actually lead to the most customer

2:15:32experience. What I mean by that is by

2:15:35focusing on the 20% of the bugs, they

2:15:37could reduce the number of crashes by

2:15:3880%.

2:15:40This number 20% is about four times

2:15:42smaller than this number 80%. which

2:15:44means they can spend four times fewer

2:15:46resources to affect a result that is

2:15:47equivalent or they could affect a result

2:15:49that is equivalent that is four times as

2:15:51large as they could if they were

2:15:52allocating the resources uniformly. So

2:15:55what that means is they just get to do a

2:15:56lot for very little and in business that

2:15:58is the whole game. It's literally all

2:15:59leverage.

2:16:01So the specific numbers will vary. It's

2:16:02not always 20 80 20. Um but the shape

2:16:06will be the same. I always encourage you

2:16:08guys to think of power law as a graph

2:16:10where the left hand side is really

2:16:12really big and it sort of goes inverse

2:16:14exponentially down.

2:16:16Now why do power laws matter? Well, they

2:16:18matter because they make the concept of

2:16:19averages basically completely useless.

2:16:22You know, if you guys ran a business and

2:16:23your clients were all normally

2:16:24distributed, that means that the highest

2:16:26paying client of yours might only be 30

2:16:28or 40% taller or bigger than average. So

2:16:32instead of maybe let's say you're

2:16:33selling a $5,000 a month product, maybe

2:16:35they would pay you $6,500, right? That

2:16:39would have a major impact on strategy,

2:16:40wouldn't it? If most clients tend to pay

2:16:42you the same amount, your primary way of

2:16:44growing your business is likely just

2:16:45getting as many clients as possible, and

2:16:48you would be happy to do so, even if

2:16:49quantity comes at the expense of

2:16:51quality. But if you understand the way

2:16:54the clients are really distributed, aka

2:16:56through a power law, you'd understand

2:16:58that in that world, 90% of your clients

2:17:01probably pay you very little money,

2:17:02maybe $2 or $3,000, whereas a single

2:17:04client might pay you way more, like 30,

2:17:07$40 or $50,000. That's just how it

2:17:09works. What that means is in this world

2:17:12clearly your goal is actually to avoid

2:17:14lowpaying $2,000 a month clients and

2:17:15instead orient your business and

2:17:17strategy such that you can find more of

2:17:18those 50,000 a month bangers since one

2:17:20of those clients are literally equal to

2:17:2225 of the others. Now this is true in my

2:17:25own business. One of my own portfolio

2:17:27companies makes about1 to$1.2 million a

2:17:29year at least that's their um run rate

2:17:31right now and a single client makes up

2:17:32over $800,000

2:17:34of that. That is literally the power law

2:17:37in action. And I can think about all of

2:17:39the other businesses I run. And you will

2:17:41see that same idea applied, although

2:17:43probably less starkly um in a variety of

2:17:46ways. And so this is not optimal for a

2:17:48variety of reasons. In business that

2:17:49it's called keyman risk or key client

2:17:51risk. If you have most of your earnings

2:17:53coming from one or two clients,

2:17:54obviously it's risky because if that

2:17:56client disappears, you are then kind of

2:17:58screwed, right? I would only have

2:17:59$400,000 a year or $40,000 a month

2:18:02versus about $100,000 a month. But it is

2:18:05what it is and that's just how it is.

2:18:08Similarly, in my media company, I have a

2:18:10small handful of courses that I make

2:18:12that drive the vast majority of my

2:18:13views. And most of the other videos,

2:18:15including many videos that I worked very

2:18:16hard on, are literal rounding errors

2:18:18beside them. Right? One of my courses

2:18:20drives over 10,000 views every 48 hours.

2:18:23A variety of my other ones, which I

2:18:25invested way more time and effort into,

2:18:26make me maybe 500. Simply, it is power

2:18:29law. You will always have one or two

2:18:31major levers that do most of the heavy

2:18:33lifting. You can think about this in

2:18:35technology as well. Your phone is a

2:18:37similar idea. A few apps eat the vast

2:18:39majority of your screen time. Meaning

2:18:41that blocking just one or two specific

2:18:42apps can achieve perhaps 80% of the

2:18:44screen reduction time if you just spent

2:18:45that time and energy finding that out.

2:18:48You can also think of it more

2:18:49philosophically in terms of how your

2:18:50days, months, and years go. Um,

2:18:52realistically, it's just a couple of key

2:18:54decisions that occur throughout the year

2:18:55that dictate the vast majority of how

2:18:57the year goes, right? It's like, should

2:18:58I have gone on this trip with this

2:19:00person? Should I have stayed with this

2:19:01person or broken up with this person?

2:19:03Should I have uh started a family with

2:19:04this person? Should I have, you know,

2:19:06called my uh grand uncle at that special

2:19:08time that I probably should have or

2:19:10something? Right? All of these things

2:19:12here um are the power law of your

2:19:15decisions. So the idea is strategically

2:19:17you want to find the 20% of decisions

2:19:19that you make that dictate the rest of

2:19:21your year and then spend all your time

2:19:22and energy making decisions like that.

2:19:25[clears throat]

2:19:26So how do you use the power law to

2:19:27actually make better decisions? As

2:19:29mentioned, first we find the items that

2:19:30make up that 20%. And this is much

2:19:33easier than most people think. You just

2:19:34have to look at your pre-existing

2:19:36distribution. So for whatever skill or

2:19:38business or avenue you are currently

2:19:39taking this course to improve on, I

2:19:41would enumerate all of my outputs. What

2:19:43I mean is all the things that we have

2:19:44produced. The 20% will always be at the

2:19:47top of the distribution if you sort it

2:19:48in descending order based off results.

2:19:50So on YouTube for instance, this would

2:19:53be the videos with the most views. In

2:19:55our time example, these would be the

2:19:56apps with the most usage. And in our

2:19:58life example, these would be the most

2:20:00impactful decisions that you've made in

2:20:01the last year, which would be really

2:20:03cool if you had on a journal or

2:20:04something. That way, you could review

2:20:05them. If you were eving all of the

2:20:08decisions that you made, you would have

2:20:09that written down on a piece of paper,

2:20:10and you could very easily go back and

2:20:12maybe filter and sort them through to

2:20:13determine which ones actually had large

2:20:15impacts. Now, once you identify the 20%,

2:20:18you have two choices. The first is you

2:20:20can double down on the winning 20%. For

2:20:23instance, if 80% of my views come from

2:20:25just three video formats, well, I could

2:20:27just make more of those three formats

2:20:28rather than innovating on a fourth,

2:20:29right? My second choice is to stop

2:20:32investing in the losing 80%. Logically,

2:20:35the losing 80% makes me just a few

2:20:37percentage points of the actual outcome.

2:20:39Why don't I just cut them off entirely

2:20:40or just stop adding resources to them?

2:20:42Doesn't really make much of a difference

2:20:43to me either way. Right? Now, this

2:20:45connects directly to the idea of

2:20:46opportunity cost and the hourly rate

2:20:48rule, which I'm going to cover in detail

2:20:49later. They're both very strong thinking

2:20:51frameworks because every hour that you

2:20:53spend on something that is in the tail

2:20:54of the power law, the tail is the really

2:20:57long skinny part at the end where

2:20:58there's very little outcome is an hour

2:21:00that you could have spent on something

2:21:02in the head, which is that really tall

2:21:03part, aka in the client example, the

2:21:06client that pays you $50,000 a month.

2:21:10I am going to continue producing long

2:21:12multi-hour videos like this one. Even

2:21:14though they require many times the

2:21:15effort of an average video, they are the

2:21:17head of my distribution. and the numbers

2:21:19taught me to focus my efforts on the

2:21:20head because I'm attempting to proceed

2:21:21logically via power law. If one does not

2:21:24pop for me, that is totally okay. Uh I

2:21:26trust that the expected value of the

2:21:28comprehensive course, you know, program

2:21:30is way better than the expected value of

2:21:32the shitty course or shitty short-term

2:21:34video program that a lot of other people

2:21:35on YouTube are doing. Another example is

The chain law

2:21:38inverting the power law. So in addition

2:21:41to there being, you know, a power law,

2:21:43there's also something called the chain

2:21:45law. And you can think of the chain law

2:21:47as the inverse of the power law. The

2:21:49power law says that, you know, the most

2:21:51valuable item in a list is orders of

2:21:53magnitude better than everything else.

2:21:55But in a chain law, it's sort of like a

2:21:57a chain is only as strong as its weakest

2:21:59link. Every single link matters. So the

2:22:01strength of the entire system is going

2:22:03to be contingent on the worst performer

2:22:05in that system. In mathematical terms,

2:22:07the chain law says the reliability of a

2:22:09system is not the average of its links,

2:22:11it is the product. Now, if that doesn't

2:22:14make sense for you, consider a chain of

2:22:16steps like in a business process. Maybe

2:22:18you're making some sort of metal widget

2:22:19or something, a fidget spinner, let's

2:22:21say, and you have a factory that does

2:22:23so. If there are three steps in the

2:22:25fabrication of this product, and step

2:22:27one has a success rate of 100%. Step two

2:22:30has a success rate of 100%, but step

2:22:32three has a success rate of just 20%.

2:22:35The overall success of this product is

2:22:38only going to be 20%. Logically

2:22:40speaking, you know, all the products

2:22:42that pass through step one are going to

2:22:43be fine. All the products that pass

2:22:45through step three are going to be fine.

2:22:46But despite that, only 20% of the ones

2:22:49that pass through step three are going

2:22:50to make it. So from here, we can infer

2:22:53that some systems, typically not the

2:22:56power law outcomes that I've talked

2:22:57about earlier, and I'll talk about which

2:22:58ones divide into which camp, are

2:23:00actually very fragile, and they don't do

2:23:02well when they're power law distributed

2:23:03at all. The way that you improve systems

2:23:06like this is you significantly increase

2:23:08finish rate if instead of 100% 100% and

2:23:1020% you actually provide equal emphasis

2:23:13on improving each step. So for instance

2:23:15let's say instead of 120 we got this

2:23:17down to 80 80 and 80 which is now8 *8

2:23:21*8. If you do the math there the total

2:23:23accuracy is now.512 or 51.2%. That's a

2:23:272.5% improvement on what it was before

2:23:29which was 20%.

2:23:32Another major point to make in

2:23:33chainbased systems before I tell you

2:23:35what makes a chain-based system versus a

2:23:38power law based system is it's important

2:23:40to keep the number of links in that

2:23:42chain to a minimum because the more

2:23:44links in a chain, the more opportunities

2:23:46you have for one of those chains links

2:23:48to suck. If you're running a process

2:23:50where each independent step has a 90%

2:23:52success rate, logically a two-step

2:23:54process would have a 0.9 *.9 or 81%

2:23:57success rate. A three-step process would

2:23:59have a 0.9 * 0.9 * 0.9 or a 72.9%

2:24:04success rate. And we would just repeat

2:24:07that process as you go. The more steps,

2:24:09the more numbers that we're multiplying

2:24:10together. And ultimately, the lower the

2:24:11success rate of the entire process

2:24:13becomes. This is also known as chains

2:24:15compound down. And so the more steps you

2:24:17have to a process, as you guys could see

2:24:19on this graph here, the lower the

2:24:21probability of success gets. So

2:24:24ultimately and ideally, what you would

2:24:25do is you would just go to the top here.

2:24:27You would have one step in a chain or

2:24:28one link in a chain and you would just

2:24:30make that link very strong. And there

2:24:32are ways that you can combine at least

2:24:33in workflow automation and process

2:24:35automation optimization multiple steps

2:24:37into one to achieve the outcome of you

2:24:40know chains compounding down. Now you

2:24:43can also drive a disproportionate amount

2:24:45of value out of spending your time on

2:24:46the worst lowest quality step. And this

2:24:48is why it's the inverse chain rule.

2:24:50Let's say I had 100 hours to invest to

2:24:52improve a system that looked like this.

2:24:5495% step one, 70% step two, 95% step

2:24:57three. How should I allocate my time?

2:25:00Well, because as we know, it is the

2:25:01weakest link in the chain that breaks

2:25:03the chain. Um, I should spend all 100 of

2:25:05those hours on that 70% until it gets to

2:25:0895% or above. When it gets to 95% or

2:25:10above, I can then start equally

2:25:11distributing my time between each of

2:25:13these steps. [sighs and gasps] Okay. So,

2:25:16which is which? Naturally, if you made

2:25:18it to this point, you're probably

2:25:19wondering, well, why would you just tell

2:25:20me the power law and then tell me about

2:25:21a law that is the exact opposite

2:25:23immediately after? It's because now you

2:25:25guys understand that different classes

2:25:27of problems tend to get solved in

2:25:29different ways. So, the way you solve

2:25:31power law problems.

2:25:34So, power laws typically apply to

2:25:36outcomes where you're examining the

2:25:38outputs of a system to determine which

2:25:40system you should use. So, if I had a

2:25:43bunch of systems in front of me, okay,

2:25:45and then I looked at all of their

2:25:46outputs over the course of the last

2:25:47week, maybe a bunch of factories in

2:25:49front of me, and I looked at how much

2:25:50made which factories made the most uh

2:25:52widgets, I would pick the factories that

2:25:54made the most widgets, and then I would

2:25:55double down on those because of the

2:25:57power law. And I would expect to find

2:25:59that one or two or three of those

2:26:01factories probably disproportionately

2:26:03outproduced the vast majority of the

2:26:04others. Now, that's the power law. The

2:26:07chain law doesn't apply to outcomes of

2:26:09lots of different processes. What the

2:26:11chain law applies to is an individual

2:26:13process. So the chain law makes sense

2:26:15when you're optimizing the performance

2:26:17of just one of those factories. Like for

2:26:19instance, if my task was not to pick the

2:26:21best factory and then double down on the

2:26:23winner. If my task was instead, hey, I

2:26:26have a factory and I have to optimize

2:26:27the product and work of that factory.

2:26:30Well, then I would apply the chain law.

2:26:32I would find the weakest link in the

2:26:33process. I would ask myself, how do I

2:26:35connect steps together to minimize the

2:26:37number of total steps or links in this

2:26:39chain? And then how do I harden the

2:26:41weakest links to bring them up to speed?

2:26:43So some action questions here. What have

2:26:45you guys produced revenue, views,

2:26:47clients, whatever it is that you measure

2:26:48over the last 12 months? And of that

2:26:50output, what would you consider the top

2:26:52three contributors? What would happen if

2:26:54you only did those top three

2:26:55contributors?

2:26:57What about a process that you rely on?

2:26:59Take one, count the number of steps

2:27:01involved, and then estimate how often

2:27:02each one of these processes work. Maybe

2:27:04it's a process in academia if you're in

2:27:06school. Maybe it's a process in business

2:27:08if you're in business or something at

2:27:10your workplace if you are working in

2:27:11corporate. Take those steps and multiply

2:27:14their probabilities together. Is that

2:27:16result a number that you would happily

2:27:18bet money on? If the answer to that

2:27:20question is no, you should probably

2:27:21apply the chain law.

Local vs global maximae

2:27:24Next idea is of local and global maxim.

2:27:28Now local and global maxim are important

2:27:31concepts in what's called optimization

2:27:33math. I first learned about them while I

2:27:35was in research and I've applied them to

2:27:37most of my life ever since. In short,

2:27:39human beings always want to go up,

2:27:41right? We want to climb. Our goal is to

2:27:44make it to the peak wherever possible.

2:27:46So, what human beings will do at any

2:27:48point in time is we will typically

2:27:50logically we will evaluate all possible

2:27:52options and decisions and then we'll

2:27:53choose which one gives us the largest

2:27:55rise or the largest climb. But what

2:27:58happens when you make it to a peak, even

2:27:59a local peak? Well, if you're already on

2:28:02top of a peak, think about yourself on

2:28:04the top of a mountain. All possible

2:28:06decisions, aka all possible places you

2:28:08could go go down, right? So, what

2:28:10happens? Well, then you get stuck. Well,

2:28:13this occurs in math just like it occurs

2:28:14with people. Now, here for instance, I

2:28:18am climbing and climbing and climbing. I

2:28:21constantly evaluate by looking back and

2:28:23then I look forward and I say what

2:28:24direction moves me up and which

2:28:26direction moves me down. Well, obviously

2:28:27that direction moves me up so I should

2:28:28keep moving. But eventually you make it

2:28:31to the top. But if you notice and you

2:28:33zoom out, you realize that isn't

2:28:34actually the top that you could get to.

2:28:36That's just the top of the area that

2:28:38you're currently in. The top of the area

2:28:40that you're currently in is called a

2:28:41local maximum. Whereas the top of all

2:28:43possible areas is called a global

2:28:44maximum.

2:28:46The issue is, okay, when you make it to

2:28:48the top of a local maximum, the only

2:28:51move is to go down. And most people,

2:28:54because human brains just always work in

2:28:56a hill climbing way, we're always

2:28:58looking to grow or improve in some

2:28:59capacity. Lots of people will never ever

2:29:02want to make that first step down

2:29:04because, as you see, we got stuck here.

2:29:06If we only kicked ourselves out, went

2:29:08down a bit, we would be eventually be

2:29:09able to climb all the way up to that

2:29:10global maximum, but it's going to

2:29:12require a loss of some kind. It's going

2:29:13to require like a step back, so to

2:29:15speak.

2:29:16Now, most people who are stuck in life

2:29:18or career, they're not at the bottom of

2:29:19a hill. They're at the top of one.

2:29:22Unfortunately, that hill is usually

2:29:23quite small, and there's often another

2:29:25larger hill that would happily host them

2:29:27if only they came down from their little

2:29:29hill first. So, that's what a local

2:29:32maximum is. It's a peak, and from the

2:29:34inside, a lot of the time, it feels like

2:29:36you're successful. But the issue is it's

2:29:37not the biggest peak. And because you're

2:29:39already at the top of your current hill,

2:29:40it's very difficult to depart.

2:29:42A good example for my own life was in

2:29:442024. I was running a service company

2:29:46that implemented automated workflows for

2:29:47agencies called Leftclick. And I tried

2:29:50really hard, but I could not grow past

2:29:51$50,000 per month no matter what I did.

2:29:55My main lead generation channels at the

2:29:56time, uh, which were cold email and

2:29:58Upwork, they were inherently difficult

2:29:59for me to scale past that. So instead of

2:30:02stay there at this local maximum, which

2:30:04was a great maximum, but it was not the

2:30:06maximum I thought I could theoretically

2:30:07have eventually climbed to, I started

2:30:09looking around and I saw people at a

2:30:11variety of these peaks that were far

2:30:12higher and greater than where I was at.

2:30:14You know, they were at peaks of $100,000

2:30:16a month. they were making $500,000 a

2:30:18month and so on. And I noticed that many

2:30:21of them were using an organic brand as

2:30:24their funnel and not cold email and

2:30:26Upwork. So what I decided to do was I

2:30:28decided I would take a short-term hit of

2:30:31figuring the stuff out, meaning I would

2:30:32step down from my local maxima. And

2:30:35eventually after doing so, I immediately

2:30:37found the path to the global maxima,

2:30:39which has now allowed me to hill climb

2:30:40in a different direction that has since

2:30:41paid many multiples. Now that I'm here,

2:30:44I'm zooming out and I'm realizing, well,

2:30:45hey, there's actually even bigger

2:30:47maxima. And I'm asking myself, okay,

2:30:49what sorts of decisions do I have to

2:30:50make to step back in order to get to the

2:30:52same place that I was at before, right?

2:30:54Grow on a new hill.

2:30:56So, how do you actually tell whether or

2:30:58not you're at a local maximum? Um, you

2:31:00know, human beings don't just have nice

2:31:02graphs. Obviously, life is a little more

2:31:04complicated than that. So, instead, you

2:31:05need some form of sign. And there are

2:31:07some reliable ones here that I always go

2:31:09by. The first is if your improvements

2:31:11are shrinking. If every change that you

2:31:13do is buying you lower return on

2:31:15investment than the last, well, that's a

2:31:17sign that you're nearing the top. And

2:31:19that kind of makes sense just looking at

2:31:20the graph, right? Like over here, me

2:31:23moving in the direction of the top moved

2:31:25me a lot vertically. But over here, me

2:31:28nudging myself just a little bit hasn't

2:31:29really moved me all that much

2:31:30vertically. The slope of that line has

2:31:33changed a lot. Another reliable one I go

2:31:36by is if the input is not producing more

2:31:38output. Aka if I'm spending a bunch of

2:31:40extra time, effort, hires, hours,

2:31:42whatever, and I'm not generating any

2:31:44returns at all. The last one is if

2:31:46someone with has less skill than you on

2:31:48maybe a different hill doing something

2:31:49similar and they're beating you. And so,

2:31:52for instance, that's what I saw when I

2:31:53looked over at a bunch of people with

2:31:54organic brands that were absolutely

2:31:55crushing it financially. I was like, I

2:31:56feel like I know way more about all this

2:31:58business stuff than they do. What's

2:31:59going on? So, I'm really big on

2:32:01optimizations if it's not clear. meaning

2:32:03this was pretty hard pill for me to

2:32:04swallow. I always wanted to look for

2:32:06ways to do better. And what I had to

2:32:08come to realize was the only way to do

2:32:11better sometimes is to take a step back

2:32:14and actually do worse. But me embracing

2:32:16this has resulted in far greater clarity

2:32:18of thought and it's also made me way

2:32:20more money which is a win-win.

2:32:22So there is a cost to stepping down as

2:32:24mentioned to go from a local maximum to

2:32:26a global one means you have to cross

2:32:28this valley that typically means you

2:32:30have to learn earn less money or have

2:32:32worse numbers or be perceived by others

2:32:35as doing worse for some period of time.

2:32:37The question is how do you bear this and

2:32:39how do you choose to do it anyway? The

2:32:41simplest way is by quantifying what that

2:32:43value looks like instead of it being

2:32:44some vague or scary thing. You should

2:32:46make it a concrete number and then

2:32:48accept it. Now, for example, I concluded

2:32:50when I made the transition I was telling

2:32:51you guys about earlier that I was open

2:32:53to making $25,000 a month less for the

2:32:56next 3 months while trying out the brand

2:32:58thing. Craziest thing is I didn't

2:33:00actually end up shrinking my income at

2:33:01all, but I was prepared to. The second

2:33:04thing is not jumping off the cliff into

2:33:07the valley all at once. What I mean by

2:33:09this is you can actually allocate a

2:33:10portion of your time, maybe 10 or 20% of

2:33:12all working hours to this new endeavor

2:33:14while you guys are still working on your

2:33:16current thing. So in my case, what I was

2:33:18doing was I was still sending lots of

2:33:19cold email and Upwork applications. I

2:33:21just reduced the time I was investing on

2:33:23that by 60 to 90 minutes a day and said,

2:33:24"Okay, I'm going to redirect this to my

2:33:26brand." So the idea is I was still maybe

2:33:28spending 80% of all of my hours on the

2:33:30thing that I knew was growing my

2:33:31business. The only, you know, 20% of my

2:33:33time was being spent to explore this new

2:33:35opportunity, which I had not carved out

2:33:36a return on investment for. The the

2:33:38downside is obvious. It's very certain.

2:33:40and the upside is sort of like unclear

2:33:42and it's vague, which makes sense why so

2:33:44many people get scared to take the leap

2:33:46into that valley. But um you should you

2:33:48really should if you are in one of those

2:33:50local maxima and if you're not in a

2:33:52local maxima, keep climbing until you

2:33:53are in a local maxima. It tends to be

2:33:55pretty obvious when you when you get

2:33:56there. Okay, so let's answer two

2:33:59questions before the next section. The

2:34:01first is for you to name one thing in

2:34:03your life or relationships or your

2:34:04business that has stopped improving no

2:34:06matter what you do. Is that a local

2:34:09maximum? Think about that. If you

2:34:12stepped down from this local maximum or

2:34:14changed your approach in the pursuit of

2:34:15climbing something taller, what do you

2:34:17think would suffer? By how much and for

2:34:20how long? Here's another concept that'll

2:34:22massively improve the quality of your

2:34:23thinking. It's called attentional

Attentional residue

2:34:25residue. Now, this is coined by a woman

2:34:27Sophie Loy in 2009, and it refers to the

2:34:30phenomenon where when you switch your

2:34:32attention from task A to task B, a

2:34:34portion of your attention will remain

2:34:36stuck, sort of like a gooey residue on

2:34:39task A, regardless of how much time and

2:34:42energy you try and use to force yourself

2:34:44to focus on task B. Now, the larger the

2:34:46attentional residue, the more impactful

2:34:48negatively it is to your next task. We

2:34:51talked about this a little bit earlier,

2:34:52but um I wanted to really go in detail

2:34:54here because I think it's at the core of

2:34:56what makes people so unproductive these

2:34:57days. Most of the time we're switching

2:34:59tasks because of some interruption these

2:35:01days, which makes it a very common

2:35:03problem, especially with AI models,

2:35:05which I think inherently incentivize

2:35:06having multiple windows open, sending

2:35:08requests, working on something else, and

2:35:10then doubling back. My current consensus

2:35:12on interruptions, and one that is backed

2:35:14by science, is it's occurring once every

2:35:163 to 5 minutes or so, which is insane.

2:35:19Um, if you are anything like the

2:35:20statistical average, that means that

2:35:22once every maybe four or 5 minutes or

2:35:25so, you guys are getting interrupted by

2:35:27something and that interruption is

2:35:28causing a residue which is negatively

2:35:30impairing your ability to think clearly

2:35:31about your next task that is always

2:35:33slowing you down. Now, a bunch of

2:35:35studies have been done on just how bad

2:35:37the impact magnitude of attentional

2:35:39residue is. And they vary based on the

2:35:41type of task and the length of task.

2:35:42Some are quite high, but I estimate it

2:35:45as a little bit lower than sort of like

2:35:46worst case scenario, maybe 5 or 10%. But

2:35:49another way to put this is if you fix

2:35:50your intentional residue, you guys

2:35:51immediately gain back 5 to 10% to your

2:35:54cognitive capacity, which is insane,

2:35:56right? So basically what happens is, you

2:35:58know, if you are doing task A and then

2:36:01you move over to task B for a second,

2:36:04you'll notice that part of you is still

2:36:05on task A for 20 minutes before making

2:36:07it all the way to task B. Well, that is

2:36:09the attentional residue. No matter how

2:36:12hard you try, you will have this like 10

2:36:14or 15% or I mean maybe five or let's say

2:36:175 to 10% um impact on task completion

2:36:20until you could sort of finish this

2:36:22timer. Now imagine hypothetically that

2:36:24you were just doing this all the time.

2:36:26Task A, task B, task A, task B, task A,

2:36:28task B. You would always be under this

2:36:30red overlay, right? Well, that's the

2:36:33problem. Now, the good news is you don't

2:36:35have to be forced to suffer this

2:36:37forever. Um, even if you have to work in

2:36:38a fractured state, there are ways to

2:36:40minimize the impact. There are a bunch

2:36:42of studies that Sophie Lorai continued

2:36:44doing that found that the difficulty of

2:36:45detaching was the highest when people

2:36:47were expected to return to a task in a

2:36:49timeressured and rushed state. Which

2:36:51means that if you want to mitigate

2:36:52attentional residue and we just accept

2:36:54that this is something that will

2:36:56continue happening to us no matter how

2:36:57hard we try. The simplest and easiest

2:37:00way is to make what's called a resume

2:37:02plan before you start switching. Okay.

2:37:06So, what is a resume plan? It's just a

2:37:08minute where you take note of where

2:37:11you're at now with your project and the

2:37:14next step you have to take when you get

2:37:15back to it. So, in the example of

2:37:18switching from task A to task B, what

2:37:20you do is task A, 20 minutes in, you

2:37:22decide to switch, right before you

2:37:24switch, maybe that last minute or so,

2:37:27you'd say, "Okay, here's where I'm at.

2:37:28Here's my next action." And then you'd

2:37:30switch to task B. And the attentional

2:37:33residue would last maybe a third of how

2:37:34long it lasts here. And it's very easy

2:37:37to do. If you have a to-do list or a

2:37:39project manager or something, you can

2:37:40immediately eliminate most of the

2:37:41attentional residue. Obviously, the best

2:37:43way is just ab abstain from moving over

2:37:46tasks entirely. Um, but this simple

2:37:48habit can significantly reduce the

2:37:49attention residue that's left behind.

2:37:51Instead of 5 to 10% of that sticky

2:37:54tar-like substance, maybe it'll bring

2:37:56you down to 1 to 2%. I have a personal

2:37:58rule, which is no more than two open

2:38:00tasks. Personally, if I have two tasks

2:38:02open that I'm working on, nothing else

2:38:04can be open until I'm done with at least

2:38:05one. And so, in my case right now, if

2:38:07I'm writing an essay and I'm waiting for

2:38:09an email, I will not open a message tab

2:38:11or have a community feed open or open a

2:38:14calculator or a spreadsheet to quickly

2:38:15check a number or whatever. I will

2:38:16literally just stay focused on that

2:38:18essay even if it feels mind-numbingly

2:38:20slow and even if every part of my body

2:38:22just like is begging me to change. The

2:38:24harsh reality is I am going to be way

2:38:26more effective finishing that off uh if

2:38:28I just stay on that screen than if I you

2:38:30know move around even if it doesn't feel

2:38:32that way. So I either finish that essay

2:38:34or I close it properly and I leave a

2:38:36note on what I will do when I come back.

2:38:38And that's where those task managers are

2:38:39are quite valuable. And I know that this

2:38:42sounds inflexible. It is. Unfortunately,

2:38:44the human brain just does not work well

2:38:45juggling multiple tasks. We blow at

2:38:47multitasking. And if you've ever

2:38:49wondered why some people can just blaze

2:38:50through their work twice as fast as

2:38:52others while you may struggle to make

2:38:53heads or tails of what it is that you're

2:38:55doing, it is likely in part because you

2:38:57are the one that is fragmenting your

2:38:58attention constantly. Whereas they for

2:39:00whatever reason, maybe a god-given uh

2:39:02habit or maybe something their family

2:39:04and still remember something they

2:39:05learned from school or a course like

2:39:06mine tend not to consider if you were

2:39:09writing a piece of software, would you

2:39:10design it so that it could have 40

2:39:12browser tabs open at once? Each tab

2:39:14using a portion of the computer's memory

2:39:16to slow down the rest of the system? No.

2:39:18Of course not. You design it in such a

2:39:20way where you know the tabs that are

2:39:22active are the ones that will be getting

2:39:23most of your focus, but you would

2:39:24probably still have some sort of

2:39:25background leech going on with the other

2:39:27ones just in case you needed to move it

2:39:28on, right? That's how your brain works.

2:39:31So, most of us run our brains like this

2:39:33all day long, constantly task and

2:39:35context switching between something

2:39:37else. Do not be one of those people.

2:39:41I realize I wrote two questions here,

2:39:42but I only had one. Um, which task did

2:39:45you leave unfinished today that is still

2:39:46running in the back of your head? What

2:39:48would you write if you had 30 seconds to

2:39:50create a resume note?

Akrasia

2:39:53Acrasia is a term from an ancient Greek

2:39:57writer that literally means a lack of

2:39:59self-control. More generally, it refers

2:40:01to the state of knowing what the right

2:40:03action is to take but still not doing

2:40:06it. Now, Aristotle wrote about it in the

2:40:08Nikomakian ethics. A bit of a slo if I

2:40:11do say so myself. You've probably

2:40:12experienced it at some point today. Uh

2:40:14and I mean that literally. A creation is

2:40:16probably the most common thing that

2:40:18people these days have to deal with. Um

2:40:20from a knowledge work perspective. It

2:40:22answers the I really should do X

2:40:25statement. If you've ever caught your

2:40:26saying that, if you've ever caught

2:40:28yourself saying that, you have in one

2:40:29way or another totally experienced.

2:40:32So the following is an excerpt from an

2:40:34essay that I read back in April 2009 by

2:40:36a guy called Scott Alexander. It was

2:40:37originally posted on this website called

2:40:39Lest Wrong called Rationality is not

2:40:41that useful. For those of you guys that

2:40:42are unaware, Lesrong is a wonderful blog

2:40:45where I learned probably more than half

2:40:46of what I've been talking about in this

2:40:48course. It's a really cool resource,

2:40:49especially their concepts uh to

2:40:51practical section. There's a lot of talk

2:40:53on like AGI and discourse and stuff like

2:40:55that, which can be valuable, but I do

2:40:56find it overly technical and not 100%

2:40:58applicable, but the stuff on practical

2:41:00um ways to utilize rationality to

2:41:02improve your life is just insane.

2:41:04probably some of the highest ROI I've

2:41:05ever had reading an internet resource.

2:41:07Anyway, so Scott looks at a group of

2:41:09people, people who have studied thinking

2:41:11clearly more seriously than perhaps any

2:41:13other group in existence. And then he

2:41:14asks if they're actually good at it. His

2:41:16answer is frank, not really. He

2:41:18concludes that the correlation between

2:41:20consciously practicing rationality and

2:41:22actually succeeding in life is probably

2:41:23closer to 0.1, not one. He attributes

2:41:26this not to the inadequacy of the tools,

2:41:28but to accasia. This is the bottleneck.

2:41:31And his conclusion is this. It doesn't

2:41:34matter how good your decisions are if

2:41:35you don't have the willpower to act on

2:41:36them. [sighs] Okay, so um basically what

2:41:40this shows us is bottlenecks or capping.

2:41:44We have a variety of different things

2:41:45that are being mixed in kind of a

2:41:47chemical container right now. But you'll

2:41:48notice that only a few of these actually

2:41:51get used. And the three things that

2:41:52we're mixing are what you know, what you

2:41:54do, and then what you get. So despite

2:41:57you adding, you know, a massive amount

2:41:59of knowledge to this container, the only

2:42:01thing that actually activates that

2:42:03knowledge is what you do. Okay? And so

2:42:05what you do is sort of the limiting

2:42:07reagent of this whole chemical reaction.

2:42:09And because what you do is directly

2:42:10correlated with what you get, you cannot

2:42:12increase what you get without doing

2:42:14without increasing what you do. The

2:42:16unfortunate reality is most people are

2:42:18actually already at this point of their

2:42:20knowledge. They already have more okay

2:42:22than this orange line in terms of

2:42:24knowledge surplus. what they know. Their

2:42:27issue is almost always what they're

2:42:29doing. Okay? And in very small cases,

2:42:30it's how they're transforming what

2:42:32they're doing into what they're getting.

2:42:33But the bottleneck is almost always just

2:42:35like how much they are currently doing.

2:42:37And I know this because I've run a

2:42:38community where I get to see day by day

2:42:40what everybody works on uh for I think

2:42:43almost two years now. Um and to date, I

2:42:45think there have been over 1400 people

2:42:47in that community. Uh sorry, 14,000

2:42:48people in that community posting literal

2:42:50daily, hey, here's what I did today.

2:42:52Here's what I was thinking today. Here's

2:42:53what I learned today. and here's how

2:42:54much money I've made. So, I basically

2:42:56have like a sociological study of all of

2:42:59the ways that you can win and you can

2:43:01lose through a maker school, which is

2:43:03incredible.

2:43:04Now, since people are incentivized to

2:43:06create value and post their wins,

2:43:07there's something like 45,500 threads,

2:43:10each of which often have a dozen posts

2:43:12or engagements or more. And the answer

2:43:14to me, because I did a bunch of analysis

2:43:16using Fable the other day, is clear as

2:43:18day. It is not the most knowledgeable

2:43:20people, the people that write at the

2:43:22highest writing levels, the people that

2:43:24you know are most well educated or the

2:43:26people that have done the most quote

2:43:28unquote inner work that consistently win

2:43:30and make lots of money. It is always the

2:43:33people that act, the people that send

2:43:35the emails or build the rough versions

2:43:38of the MVP or the people that call and

2:43:40screw up. It is like the 18 to 19 year

2:43:43olds that come into this with zero

2:43:45knowledge about what the hell to do,

2:43:46who've never talked to a client or

2:43:48picked up the phone before, that don't

2:43:50even know enough to screw themselves up,

2:43:51that just start. They are the sorts of

2:43:54people that have their what they do in

2:43:56excess and what they know sort of, you

2:43:59know, below them. And you know, if what

2:44:01they do is already quite high, then

2:44:03teaching them information is no problem

2:44:04whatsoever.

2:44:06It's the people that don't move forward

2:44:07that tend to consume the most content

2:44:09but do nothing with it. And so I

2:44:11understand this is content that you are

2:44:12currently watching and I really want to

2:44:14drive that point home. I feel like it

2:44:15would be dishonest of me not to and a

2:44:17lot of people that make long form

2:44:18courses like this just want to keep you

2:44:19in a perpetual state of learning. But I

2:44:20I would like you to think clearly and

2:44:22then do more with your life. If you're

2:44:24just constantly sitting around watching

2:44:25content like mine, you're not really

2:44:26getting anything done. Um good news. I

2:44:29have a bunch of actionable techniques

2:44:30that employ and apply principles like

2:44:33you know Acrasia solutions. Uh I'll be

2:44:35talking about those in a sec. So, this

2:44:38is more or less what I did in my very

2:44:39first business. I was walking through

2:44:41the streets of Vancouver in a tattered

2:44:42button-up trying to sell marketing

2:44:44packages at 22 for 250 bucks. That was

2:44:46my offer. 250 bucks to put you on the

2:44:48map. I had zero sales experience. I knew

2:44:50absolutely nothing about how to sell.

2:44:52But my partner and I um walked into

2:44:54between 50 to 80 businesses a day to

2:44:56give them a pitch. And that was maybe

2:44:58eight hours a day, 48 hours a day, I'd

2:44:59say, for over a year. So, looking back,

2:45:02I won not because of all the courses I

2:45:03took, cuz I hadn't taken any courses

2:45:05there. um just because I executed

2:45:07relentlessly and I made sure that the in

2:45:09the in the chemical example the reagent

2:45:10that was doing was way higher than the

2:45:12reagent that was learning. So how do you

2:45:15actually solve a crasia? You won't solve

2:45:16it just by learning more about it.

2:45:17Obviously I just wanted to give it a

2:45:19name because now that you have a name,

2:45:20you've labeled it, you can become aware

2:45:22of it. The real solution is to make the

2:45:24next action so small, so simple, and so

2:45:28well defined that doing it is trivial.

2:45:32Once you make that next action really

2:45:34easy, what you do is you attach that

2:45:36action to a trigger. Now, we're going to

2:45:38do this in the taps section, which is an

2:45:40implementable technique that you guys

2:45:41can use today. What happens with a CRA

2:45:44is, you know, usually it's just that

2:45:46vague or illdefined first step, the step

2:45:50where like you know what to do, but

2:45:51you're not really sure exactly how to do

2:45:53it. You know, you got to go, you know,

2:45:55pick up the phone and call a number or

2:45:57whatever, but there's like some small

2:45:59little blocker. So you reduce that down

2:46:01to the smallest possible step and then

2:46:03you just make it an if then rule where

2:46:05it's like if I get back to my desk, I

2:46:08pick up the phone and I dial. So this is

2:46:11how you do it. This is how you actually

2:46:12avoid that persistent feeling of man, I

2:46:15got to do this. I just I still I'm

2:46:17putting it off for some reason. Why am I

2:46:18putting it off? Once you start talking

2:46:21in rules as opposed to like willpower

2:46:24and motivation, your environment will

2:46:25actually do most of the work for you.

2:46:26And that's why we set up the hardware

2:46:28half of our system beforehand because it

2:46:29was important for you to understand how

2:46:30environments work. So a good example of

2:46:33a rule might be, I will make at least

2:46:35one sales call on the phone every time I

2:46:36get back from a bathroom break. What

2:46:38that means is when you get back from the

2:46:39bathroom to your desk, you sit down,

2:46:41click on a Google sheet, and then you

2:46:42just call the next person on that list

2:46:44and boom, you're done. This is an actual

2:46:46rule that I used to use in my own life.

2:46:48And that was before I even knew about

2:46:50implementation intentions and taps. Um,

2:46:52but it it was great. And what's really

2:46:54cool is when I get back and I make the

2:46:56dial, usually I'm like, "Oh, that really

2:46:58wasn't that hard. Let me make a couple

2:46:59more just in case." And now I go to the

2:47:01bathroom four or five times in an 8 hour

2:47:03session. Okay, talk to my doctor about

2:47:05that. I don't know if that's good or

2:47:06bad, but I go to the do, you know, I go

2:47:08to the bathroom four or five times. Now

2:47:10I'm doing, you know, five dials each,

2:47:12which is an additional 20, 30 maybe

2:47:14dials that I otherwise wouldn't have

2:47:15done. Obviously, that momentum spills

2:47:16over in other areas of my life. So

2:47:19that's it. I'm going to go way more in

2:47:21depth on taps later, including defining

2:47:23the acronym and so on and so forth. But

2:47:24for now, just know that making actions

2:47:26super small, super simple, and defining

2:47:27them well is the key to overcoming the I

2:47:30know I should do X thing, but I cannot

2:47:32problem that I think a lot of people

2:47:33suffer from also known as a Okay, some

2:47:36action questions here. First, what is

2:47:38something you know you should do right

2:47:40now? Second, what is the simplest

2:47:42possible first action towards completing

2:47:44that task? I think both of those

2:47:46questions have answers that probably

2:47:47came up immediately.

Map vs territory

2:47:50Let's talk map versus territory. The map

2:47:52is not the territory is a phrase I first

2:47:54encountered eight years ago on a random

2:47:56blog website. And if I'm being honest,

2:47:58more value has been extracted from that

2:47:59one line than the vast majority of the

2:48:01books that I've read in my entire life.

2:48:03And the crazy thing is this phrase was

2:48:04coined back in 1931. My earnest belief

2:48:07is this is a mental model that every

2:48:08human being on Earth should know. And if

2:48:10we did, we would probably be far better

2:48:12off for it. GDP would skyrocket, unity

2:48:16of nations and so on and so forth. Okay,

2:48:19so here's the crux of what map is not

2:48:21the territory means. [gasps] You know

2:48:24what a map is, right? It's obviously

2:48:25something you look at to move you

2:48:27through a territory.

2:48:30Maps are not territories themselves. If

2:48:32they were territories, they would be

2:48:34really big, right? And then they would

2:48:36cease to be useful. So inherently, the

2:48:39very fact that a map is a compressed

2:48:41version of reality makes it useful. The

2:48:45smaller a map is, eventually it stops

2:48:47being useful because it's so small you

2:48:48probably can't see it. But the smaller a

2:48:49map is, the more portable it is,

2:48:51probably the better it is. Despite the

2:48:53fact that the map gets further away from

2:48:55the territory, it's not it's getting

2:48:57more and more different from the

2:48:58territory. For instance, there's a big

2:49:00lake over there, there's a park over

2:49:01here, and there's some mountains in the

2:49:03background. I'm in Colona. So, if I'm

2:49:04looking at my map, and there's a big

2:49:05lake, and then there's the mountains,

2:49:07and then there's the grass over here.

2:49:08You know, if this ends up growing so

2:49:10much that it is actually the size of the

2:49:12the lake, the mountains, and the park,

2:49:14obviously, it ceases to have all value.

2:49:16The whole value of the map is isn't that

2:49:18it's small, right? So, inherently, the

2:49:21map is not the territory. That's just

2:49:22how it is. Unfortunately, a lot of

2:49:24people see maps as territories. They

2:49:26take a map of something, which is a

2:49:28compressed version of reality, and they

2:49:30assume it is equivalent to the

2:49:31underlying territory. [gasps]

2:49:33Maps compress the world. That's exactly

2:49:35why they're useful. But despite the

2:49:37utility, a map is always a version of

2:49:39the truth. Objective reality will always

2:49:41be different. Just like how a 2D map on

2:49:44Google images or something is different

2:49:46from our 3D world, the map is not the

2:49:48territory.

2:49:50So the unfortunate truth is everything

2:49:52in life that you believe is in a way a

2:49:54map. Your ideas about what your

2:49:56customers want is a map. Your

2:49:58understanding of how your body processes

2:50:00drugs like caffeine is a map. Your new

2:50:02understanding of how cognition works and

2:50:04attention, working, memory, and

2:50:05executive function is a map. And the

2:50:07story that you tell yourself about why

2:50:09some product that you launched last week

2:50:11failed is also a map. All of these are

2:50:14lossy compressions of the truth. They're

2:50:16compressions of the truth that actually

2:50:17lose some detail in doing so. None of

2:50:20them are the actual thing. In business,

2:50:22we get a lot of maps. So you see

2:50:24dashboards with like click-through

2:50:26rates, retention, monthly recurring

2:50:28revenue, pipeline values, CRM, etc. But

2:50:32all of these are equivalent to the

2:50:34instrument readouts in an airplane

2:50:35panel. They might be a good map of

2:50:37truth, okay? They might tell you sort of

2:50:39where things are, what direction you

2:50:41should walk in, but at the end of the

2:50:42day, these analytics, this MR retention,

2:50:44clickthrough rates, etc., these are just

2:50:46a number. The problem is that maps and

2:50:48territories often diverge without you

2:50:50noticing, but you assume that they're

2:50:53the same thing. So, if you're steering

2:50:55by the map and the map is off, you may

2:50:57never realize it until it's too late. A

2:51:00good example of this is one I see quite

2:51:01often. You know, you have a CRM, which

2:51:03is a customer relationship management

2:51:04service, which tracks customers as they

2:51:06move through a pipeline, and maybe it

2:51:09says that you have six figures or over

2:51:10$100,000 in your pipeline. Well, you

2:51:12would not believe the number of people

2:51:14who have CRM who I double check and

2:51:16audit as part of my work that have I

2:51:19have over six figures in my CRM, but

2:51:21those leads have all been gone or dead

2:51:23for the last four or five months. Or

2:51:25maybe, you know, retention for your

2:51:26product looks really really great. And

2:51:28you're like, oh yeah, my my churn's

2:51:29really low, but if you think about it,

2:51:31the members that are leaving are all the

2:51:33best members because they're very

2:51:35disappointed in maybe what you're doing.

2:51:36These are all just short-term compressed

2:51:38maps which guide you, okay? but they

2:51:40aren't the actual thing underlying

2:51:42itself.

2:51:43Okay. So, you know, here is the

2:51:45territory. Here's what actually happens.

2:51:47I always do things in business analogies

2:51:49because I care most about business and

2:51:51being economically impactful. So, I see

2:51:53customers, sales, calls, etc. This is

2:51:55what you look at, which is a much more

2:51:57compressed version of what that is.

2:51:59Okay. A major chunk of all of the

2:52:02problems that people face in business

2:52:03and in life just comes from assuming

2:52:05that their map of the world is actually

2:52:07the territory. So in a struggling

2:52:09company, rather than going out on the

2:52:11field to see what's going on himself, a

2:52:12CEO might kick back, relax, and be

2:52:15content with information from his direct

2:52:16reports, you know, the direct reports

2:52:18say, "Ah, things are fine. Yeah, people

2:52:20love our product. No, everything's going

2:52:22well on the marketing end." And so on

2:52:24and so forth. And the CEO goes, "Yeah,

2:52:25okay, that sounds good." And then

2:52:26resolves to spend his time on other

2:52:28things. What the CEO has forgotten here

2:52:30is something crucial. His direct

2:52:32reports, all of them, are just little

2:52:33maps of reality. As a consequence, every

2:52:36one of these maps is assessing

2:52:37information in their own highly

2:52:39compressed and lossy ways. For instance,

2:52:41these people may have their own

2:52:42incentives, which could be providing

2:52:44positive information. They could also

2:52:46have their own biases, which could be

2:52:47not understanding that their own maps

2:52:49are not perfect representations of

2:52:50information. Or maybe they have skills

2:52:53in one area, but they lack it elsewhere,

2:52:55etc. The point that I'm making is

2:52:57despite all of the metrics looking great

2:52:58on paper, this CEO's company is failing.

2:53:01He doesn't understand why. And if you

2:53:03don't have good maps or if you don't

2:53:05understand the divergence between maps

2:53:07and the territories, you tend to suffer

2:53:09situations just like this. This is why

2:53:12the fastest and best growing companies

2:53:13of the last couple of decades tend to be

2:53:15very flat. The people in charge get to

2:53:18see exactly what's going on because

2:53:19they're not at the top of some big long

2:53:20organizational hierarchy that's as tall

2:53:22as the Empire State Building. No,

2:53:24they're actually on the ground. They can

2:53:25literally look and see the customers at

2:53:27their feet communicating with the

2:53:28business and they can talk with them

2:53:29themselves and ask them questions like

2:53:31why didn't you buy our product. [gasps]

2:53:34This is how you do things in reality

2:53:36when you want to be very effective both

2:53:38in thinking clearly and then making

2:53:40clear decisions. [sighs and gasps]

2:53:42Another great story about how this

2:53:43manifests in lab settings which I

2:53:45learned myself when I was working in

2:53:46labs. um to measure cognition or the

2:53:49ability of a rat or a mice to think. Um

2:53:51researchers oftent time how long it

2:53:53takes them to solve a maze. So they'll

2:53:55put together this really cool maze and

2:53:56then they'll see how long it takes them

2:53:58to to solve it and then they'll see how

2:54:00long they can memorize it and stuff like

2:54:02that and then they'll usually move the

2:54:03maze around when they introduce a new

2:54:04task. Now in one such experiment they

2:54:07changed the feeding schedule which is

2:54:08the times that the rats were fed and

2:54:11then that miraculously resulted in the

2:54:13rats solving the mazes way faster. The

2:54:15researchers rejoiced. My god, we found a

2:54:18way to uh, you know, make rats smarter.

2:54:20What if this extends to humans, too? We

2:54:22could have a revolution on our hands.

2:54:23Everybody could be 30% smarter. And

2:54:26yeah, on paper, the rats were indeed

2:54:27solving the the mazes faster, right? The

2:54:29map was telling them that rats were

2:54:31actually doing better and getting

2:54:32smarter. Now, were they actually getting

2:54:35smarter? No. In reality, they were just

2:54:36getting hungrier. And so, rat getting

2:54:39hungrier is different from a rat getting

2:54:40smarter. even though both of them will

2:54:41probably try and solve a maze really

2:54:43really quickly. Unless you were actually

2:54:45there at the experiment, you probably

2:54:47would not have known the difference. So

2:54:49if you were constantly just taking in

2:54:50data, maybe looking at the studies or

2:54:52something like that, there'd be

2:54:53something that you'd miss. So why does

2:54:55this matter? Because the territory is

2:54:56ultimately what provides you clarity.

2:54:58The map is just a simplification. And

2:54:59that's not to say the map is not useful.

2:55:01It is useful because it is not the

2:55:03underlying information. Imagine a map

2:55:05blown out to be the size of the region

2:55:06it represents. Not exactly valuable,

2:55:08right? So, the two will never be 100%

2:55:10the same, and that's okay. But when they

2:55:12do differ, you should remember that the

2:55:14territory is always right, and you

2:55:15should aim to actually look outside and

2:55:17see the territory for yourself. The

2:55:19fundamental rule, and one that I

2:55:21recommend you feature prominently in

2:55:22your own life, if you ever find yourself

2:55:23in a situation where your map and your

2:55:24territory are at odds, the territory

2:55:27wins every time. So, the next time you

2:55:30feel that something is off, or maybe if

2:55:31you get a vague sense that something

2:55:33must be wrong, do not check your map.

2:55:36Check the territory. Look for the

2:55:38underlying reality behind the

2:55:39representation of or abstraction of

2:55:41reality and you will get far more out of

2:55:43it. Do not take people's opinions at

2:55:45face value. Do not take stats at face

2:55:47value. Do not always defer to experts or

2:55:49consultants or maps that supposedly

2:55:51solve the problem for you. Actually go

2:55:53and look at the territory for yourself a

2:55:54couple of times. And I don't mean this

2:55:56to say you should not take stock in what

2:55:58people that are better than you at a

2:55:59thing say. Obviously, what I'm saying is

2:56:02think about it for yourself and then go

2:56:03and look for the ground truth data that

2:56:05underlies all of that stuff. Do not

2:56:07listen to me saying, "Hey, you got to do

2:56:09XYZ thing for your business or

2:56:10whatever." Actually try and test it in

2:56:13the market and see. And if the market

2:56:14likes it, great. You've got the answer.

2:56:16And the answer is probably better than I

2:56:17am as a map to guide you towards things.

2:56:19Anyway, so if you guys want to go

2:56:21deeper, I've linked an article here

2:56:22called map and territory. For the rest

2:56:24of you, I would just start trying to

2:56:25observe the rat in the previous

2:56:27experiment. Now, I personally work with

2:56:29AI agents quite often, right? That's

2:56:30where most of my brand at this point is.

2:56:32That's where I make most of my money

2:56:34implementing in companies and so on and

2:56:35so forth. And the outputs of a agents

2:56:37are by definition maps of a map. They're

2:56:40summarized transcripts, digests of my

2:56:42inbox, and so on and so forth. And so I

2:56:45actually have two layers removed from

2:56:47reality here. Though it costs me a lot

2:56:50of speed, I will almost always check the

2:56:51source material before making really

2:56:53expensive decisions based off AI data.

2:56:55[gasps] You know, a summarized

2:56:57transcript often times will tell people

2:56:59that the meeting that they just had went

2:57:01great. But if you open the call

2:57:02recording, okay, you're actually able to

2:57:04see the client expressing concerns or

2:57:06hesitations or the lack of alignment or

2:57:08maybe something on their face suggesting

2:57:09that they they don't really like what

2:57:11they're hearing, etc. [sighs and gasps]

2:57:13So rather than focus and trust maps or

2:57:16stories like, oh, the client left

2:57:18because of pricing, I would actually

2:57:19every now and then go and see the

2:57:21underlying data and just verify, you

2:57:22know, is this map still representative?

2:57:25Two more questions. Which map do you

2:57:28look at most in your business or your

2:57:30life? and when did you last look at the

2:57:32underlying territory behind that map?

2:57:35Next, pick one story you tell about why

2:57:37something is not working. Like maybe

2:57:38people don't want my product or I'm

2:57:40really really bad at studying. What

2:57:43would you have to observe directly to

2:57:44actually test this?

Ulysses contracts

2:57:47Now, have you guys seen the Odyssey? I

2:57:49want to talk for a second about Ulyses

2:57:50contracts. High willpower people do not

2:57:53try and fight temptation. What they do

2:57:55is they just avoid temptation in the

2:57:57first place. But what if you can't avoid

2:57:59it? What if your temptation is in your

2:58:01pocket all day, like your smartphone? Or

2:58:02maybe if it's in your house, like your

2:58:04fridge, which contains juicy goods, and

2:58:06for whatever reason, you just always

2:58:07have to have them around you. Well,

2:58:09that's where a Ulyses contract or a

2:58:11Ulyses pact comes in. A Ulyses pact is a

2:58:15choice you make today that restricts

2:58:16your options tomorrow. For those of you

2:58:18guys that don't know, um, Ulyses is just

2:58:20the Roman name for Adysius, um, which is

2:58:22like the Greek thing. So, if you guys

2:58:24have watched the Odyssey, this should

2:58:25stand out to you. Long ago, Adysius or

2:58:29Ulyses was sailing back from the Trojan

2:58:32War. On the way, he encountered the

2:58:34sirens who sang a song so seductive and

2:58:36overwhelming that anyone who heard that

2:58:38song was compelled to steer their ship

2:58:39onto the rocks in an attempt to reach

2:58:41them. Now, Adysius knew that while he

2:58:44waited and wanted to hear the siren

2:58:46song, he also understood that when he

2:58:48did, his future self would beg to steer

2:58:50the ship into the rocks, thus killing

2:58:51his whole crew. So, before he approached

2:58:54the sirens, he took precautions. He had

2:58:56his crew seal their own ears with wax

2:58:58and also ordered the crew to tie him

2:59:00securely to the ship's mast. Then he

2:59:03commanded his crew to ignore all of his

2:59:04pleas to be freed no matter how strong

2:59:06until they passed the sirens. When the

2:59:09siren sang, Adysius begged and pleaded

2:59:11for his crew to set him free. But they

2:59:13did not. They simply continued rowing

2:59:15and Adysius survived. So why do I bring

2:59:17this up? The important thing here is not

2:59:19the rope, but it's the timing. Adysius

2:59:21made his decision while he was still

2:59:22rational far before he was tempted by

2:59:24the siren song in the first place. The

2:59:27way that Ulyses contracts or Adysius

2:59:29contracts, whatever you want to call it,

2:59:31work are typically you make a contract

2:59:34or a pact with yourself while you are

2:59:36sane and very high performing. And then

2:59:40when you are, you know, temptable and

2:59:43weak, maybe later on in the day, let's

2:59:45say, or when you're put in front of a

2:59:46situation like in front of your fridge

2:59:48or something, you execute that contract.

2:59:51So, for instance, um you know, here's a

2:59:53quick graph. At 7:00 a.m., let's say,

2:59:55you have next to no temptation and your

2:59:57resolve is very strong. But maybe at the

2:59:59end of the day or something like that,

3:00:00you know, your temptation is very high

3:00:02and your resolve is small. What a Ulyses

3:00:04contract is is it takes your resolve at

3:00:06the beginning of the day when it's

3:00:08really strong and then it just applies

3:00:09it across the rest of the day. Basically

3:00:11fixing or holding concrete your resolve

3:00:13or your willpower.

3:00:15Okay, let me give you an example of how

3:00:17almost every willpower failure you've

3:00:18ever had has probably played out. You

3:00:20know, in the morning you were

3:00:21clear-headed and really fresh. You knew

3:00:22the right choice, so you just avoided

3:00:23the bad thing, whatever it was. But at

3:00:259:00 p.m., you know, you got home late.

3:00:27You're exhausted. You're tired. You've

3:00:29been faced the temptation all day. So

3:00:30you see the stimulus and then you go,

3:00:32"Ah, couldn't hurt." Then you give in.

3:00:35When I put it this way, the solution is

3:00:36pretty clear, right? The way to solve

3:00:38this completely is just removing the 900

3:00:40p.m. version of you's ability to make

3:00:42the decision to do that thing in the

3:00:44first place. Maybe you need it at home.

3:00:46That's fine. But you can still find and

3:00:48implement ways to minimize the amount of

3:00:51freedom you have later on in the day.

3:00:53Maybe what you do is in the morning, you

3:00:55know, there's a bag of chips or

3:00:56something like that in Eye. uh when you

3:00:58wake up, you take that bag of chips, you

3:01:00literally put it in front of, you know,

3:01:02inside of a chest or a safe, scramble

3:01:04the combination lock and give it to your

3:01:06your wife or your friend or something so

3:01:08that later on at night when you come

3:01:09home, you can't do it. Sounds really

3:01:11dramatic and overplayed, right? But

3:01:13stuff like this is legitimately how some

3:01:15very high performers get things done and

3:01:17it's how they take advantage of clarity

3:01:19of thinking early on in the day and then

3:01:21apply it robustly across the rest of the

3:01:23day.

3:01:24Okay, so what are some practical Ulyses

3:01:26contracts? Here are three easy examples

3:01:29you guys could probably implement today.

3:01:30The first is putting your phone in

3:01:32another room. By forcing yourself to

3:01:33physically walk to get the phone, you

3:01:35are adding a layer of friction, which I

3:01:37will cover more of, between you and the

3:01:38phone. And you'll also buy a rational,

3:01:41more sane version of yourself 30 seconds

3:01:43to stop walking towards the phone.

3:01:44That's why I personally like doing this

3:01:47accountability to others. Now, I record

3:01:49videos every day and on some of my

3:01:51channels, I actually tell my audience,

3:01:52"Hey guys, I publish a video here every

3:01:54single day. If you think about it, this

3:01:56leads many thousands of people expecting

3:01:59a video from me every 24 hours."

3:02:02The fact that I've signed on to this

3:02:03massive expectation, almost like this

3:02:05informal contract with people that watch

3:02:07my content is a big motivator for me

3:02:09because even when I feel like I have

3:02:10zero motivation to record a video or,

3:02:12you know, I don't really want to be

3:02:14sitting here for another two hours

3:02:15finishing this puppy up, I still do it

3:02:17because I have an implicit contract that

3:02:19I've signed on to with my audience to do

3:02:21something that I signed on to when I was

3:02:23in very clear-minded, which maybe I

3:02:25don't want to do now, but that's okay

3:02:26because I'm copying and using the

3:02:28resolution from earlier. um um you know,

3:02:31despite the fact that I'm tempted to

3:02:32stop. So, you can do this, too. You

3:02:34know, if you guys create media, just

3:02:36announce your publishing or work

3:02:37schedule with your audience. Super easy.

3:02:39If you guys are, you know, working out

3:02:41or something, meet a couple people in

3:02:42the gym and tell them, "Hey, I'm going

3:02:44to be here tomorrow." That way, you'll

3:02:46feel held accountable and you will want

3:02:47to do that so that uh you know, they

3:02:49don't shame you when you walk in 3 days

3:02:52later. A last way of doing this is

3:02:54through financial stakes. What you can

3:02:56do, and what I've done before, is

3:02:58prepaying somebody and having them

3:03:00donate your money to a direct competitor

3:03:01or some sort of charity that you don't

3:03:03like. If you think about it, what is

3:03:04more annoying than having to give money

3:03:05to a direct competitor of a company of

3:03:07yours? That is a massive pain in my ass.

3:03:09I don't want to do that at all. Still, I

3:03:11did and it motivated me to

3:03:12counterintuitively run that competitor

3:03:15basically out of business.

3:03:17So, yeah. Anyway, a good Ulyses contract

3:03:20can include all three of these. I use

3:03:22USC's contracts not only to improve my

3:03:24cognition, but I treat it as like a loan

3:03:26of highquality cognition from before to

3:03:28now. I'm basically taking money and then

3:03:30I'm setting it aside and then I use that

3:03:32money in the situation when I have to.

3:03:34So, it's almost like a savings account.

3:03:37Some action questions here. Name a

3:03:39behavior that you keep deciding against,

3:03:40but the tempted version of you continues

3:03:42to do. Can you come up with a Ulyses

3:03:45contract that solves this for you?

Opportunity cost

3:03:48Let's talk a little about opportunity

3:03:50cost. There's a saying that I like a lot

3:03:52and that is what is seen is seen and

3:03:54what is not seen is not seen. This comes

3:03:56from Frederick Bastiat who was an

3:03:58economist in the 1800s. Uh he was

3:04:01telling a story about a shopkeeper's

3:04:02broken a window. Uh he lived in I think

3:04:04a village or a town and basically a

3:04:06shopkeeper had had their store broken

3:04:08into and so the window was broken. Now

3:04:11it came to the attention of the town and

3:04:12a bunch of people were asked their

3:04:14opinions on this and what to do. And

3:04:16interestingly, a bunch of people in his

3:04:17town believed that since a broken window

3:04:20meant that there was more work for the

3:04:22local window maker in the town, I think

3:04:24they were called a glier or something,

3:04:26that implied that all else held equal, a

3:04:28broken window may have impacted the

3:04:31shopkeeper, but then it made the window

3:04:33maker's business a little bit better,

3:04:34meaning it was net neutral. The logic

3:04:36goes something like this. Window gets

3:04:38broken, shopkeeper loses some money, but

3:04:41the money goes to the window maker. So

3:04:43the window maker makes some money,

3:04:44meaning the net money has not changed,

3:04:46despite the fact that the guy had his

3:04:47window broken. So this was the

3:04:49prevailing notion of economics at the

3:04:51time in like the 1800s or so in

3:04:53Frederick Bustad's town. Very advanced

3:04:55stuff. Clearly, the groundbreaking

3:04:56discovery was that Frederick found that

3:05:00since the shopkeeper had to pay for a

3:05:01window repair, he was now unable to buy

3:05:04shoes or books or whatever else he was

3:05:06planning on spending that money on

3:05:08otherwise. This is the unseen part of

3:05:11the transaction. And it's what led

3:05:13Frederick to deciding that every choice

3:05:15actually has two sides. The seen side

3:05:17and the unseen side. And realizing that

3:05:20human beings brains only record the

3:05:22scene. That's where he gets this quote.

3:05:24What is seen is seen and what is not

3:05:26seen is not seen. And so in business and

3:05:29in life, this is a problem because if we

3:05:31were only ever understand the scene, we

3:05:33would fail to account for a notion of

3:05:35opportunity cost. Now, put simply,

3:05:38opportunity cost is the value of the

3:05:40next best alternative that you could

3:05:42have taken in a situation. It's not just

3:05:44the sum of all other alternatives. It's

3:05:46just the one thing that you could have

3:05:48done otherwise that would have delivered

3:05:49you the biggest result.

3:05:51So, if you spent your Saturday building

3:05:53a landing page for a website of yours,

3:05:55the opportunity cost is whatever the

3:05:57next most valuable use of your time

3:05:59would have been. So maybe what you could

3:06:02have done with that time instead is you

3:06:03could have spent it on a sales call or

3:06:06you could have spent it working out or

3:06:07you could have spent it taking a nap. If

3:06:09you think about it, all of these have

3:06:10some nonzero expected value to your

3:06:13life, right?

3:06:15But you didn't. Instead, you decided to

3:06:16work on your landing page. And despite

3:06:18the fact that you worked on your landing

3:06:19page, it's not just that you worked on

3:06:21your landing page. It's that you worked

3:06:22on your landing page, but then you said

3:06:23no to a bunch of other stuff. So in this

3:06:26way, the sticker price of things is

3:06:28rarely their true cost. A $30 lunch, for

3:06:31example, is not just 30 bucks. It's also

3:06:3390 minutes. So, it's not enough to model

3:06:35the cost of the $30 lunch as price,

3:06:38which is 30 bucks. You must model the

3:06:40cost as the price plus the number of

3:06:42hours times your hourly rate that you

3:06:45could have made doing the other thing.

3:06:47This and only this will give you the

3:06:48true cost. So, let me give you an

3:06:50example of this. You know, if you were

3:06:52naive and you didn't understand

3:06:53opportunity cost, you would look at the

3:06:54lunch and you would say, "Ah, that cost

3:06:56me 30 bucks. Well, I guess that's not

3:06:57that bad." But if you took an enriched

3:06:59view with opportunity cost included, you

3:07:01would add the $30 price of the lunch to

3:07:05the amount of time you spent on lunch

3:07:071.5 hours and then multiply that by the

3:07:10hourly rate that you could have made if

3:07:11you spent it on some beneficial activity

3:07:13like prospecting. And then here you

3:07:16would have gotten a formula that looked

3:07:17less like $30 total cost and more like

3:07:19$30 plus 1.5 hours * 45 is equal to

3:07:24$97.50.

3:07:27So from an opportunity cost standpoint,

3:07:28if you think about it, your decision to

3:07:29go and take this lunch was actually

3:07:33three times the amount. And that brings

3:07:36me to an important point. You know, most

3:07:37of the poor decisions that we make are

3:07:39always found in the discrepancy between

3:07:42price and cost. And this is demonstrated

3:07:45in a 2009 piece of consumer research as

3:07:48well. People tend not to account for

3:07:49opportunity cost unless it is explicitly

3:07:51pointed out to them. when asked to buy a

3:07:53really cheap item in this study, people

3:07:55were more likely to say no if the don't

3:07:57buy option was instead described as save

3:08:00that money for something else. So

3:08:02literally just changing again the name

3:08:04of the freaking thing, you know, in this

3:08:06case the button was enough to reduce the

3:08:09total number of people that said yes,

3:08:10which obviously has dividend can pay

3:08:12dividends if you are the one that is

3:08:13controlling that decision because you

3:08:14just do the opposite. So despite the

3:08:16fact that the money was the exact same,

3:08:18just the way that it was framed, just

3:08:19the whole like, wait a second, you could

3:08:21actually spend that money on something

3:08:22else was enough to make people buy less

3:08:23of it, these people aren't stupid.

3:08:26They're just not accounting for the

3:08:27alternative because the alternative was

3:08:29never top of mind. And because, you

3:08:30know, human beings did not evolve with a

3:08:32built-in notion of opportunity cost,

3:08:33right? This something that Mr. Frederick

3:08:35Bastad had to figure out himself. To

3:08:38that end, human beings routinely neglect

3:08:40opportunity costs unless you spell them

3:08:42out explicitly. It's probably one of our

3:08:44our most major biases and uh it's worth

3:08:47just constantly reminding yourself and

3:08:48keeping in mind. So the cost of a choice

3:08:51is the road not taken. Let's say you do

3:08:53something on Saturday and it's uh you

3:08:56know or 500 bucks or whatever. What you

3:08:58see is the thing that you chose to do.

3:09:00You spent your Saturday on some activity

3:09:03but you forgot to count in the equation

3:09:05is the best alternative which is not

3:09:06seen. So every time you say yes to

3:09:08something, you are always saying no to

3:09:10something else. Nothing in life comes

3:09:11without a sacrifice, as unfortunate as

3:09:13it is to frame that way. Now, for

3:09:16instance, um in my own life, I was

3:09:17walking into 50 to 80 stores a day to

3:09:19pitch a marketing package in Vancouver

3:09:20when I was 22. And that looked really

3:09:22productive. Looked like I was doing a

3:09:23lot. My choice was like, well, I could

3:09:25go prospect or not prospect, so

3:09:26obviously I'm going to prospect, right?

3:09:28And if you look at the price, my work

3:09:30was nearly free. I mean, I did few bucks

3:09:31in gas per day. Thanks, Grinder. Uh

3:09:34maybe. And then lunch from time to time.

3:09:36But the real cost was the hours I was

3:09:37not spending on developing, you know, a

3:09:40more scalable outreach mechanism that

3:09:41could do the same job thousands of times

3:09:43faster. And that is an opportunity cost

3:09:45I did not understand for many years. And

3:09:48I'm not saying that I regret it.

3:09:49Obviously, I'm very happy to have spent

3:09:51all that time prospecting. I gained a

3:09:53tremendous amount of grit and resilience

3:09:54that was probably worth it. But I do

3:09:56wish I'd picked up more scalable lead

3:09:58generation mechanisms a little bit

3:09:59earlier. I think I probably would have

3:10:00gotten a lot farther.

3:10:02So every yes is a no. Once you guys see

3:10:04that cost, anytime you say yes to one

3:10:06thing, you're actually saying no to

3:10:07something else. Your life will probably

3:10:09change. For example, every time you say

3:10:11yes to some sort of mindless internal

3:10:13meeting at work means you are saying no

3:10:15to the $200 you could have made by

3:10:18working on perhaps your sales. Likewise,

3:10:21saying yes to client number one at a

3:10:22really low MR logically means saying no

3:10:25to all of the other clients you could

3:10:26have gotten. Saying yes to a side

3:10:28project means saying no to the time you

3:10:30could have spent on your main project,

3:10:31and so on and so forth. In practice, the

3:10:34no is always there, which should just

3:10:35change the way and the the manner in

3:10:36which you price. Also, in this way,

3:10:39cheap things can end up being incredibly

3:10:41expensive. For example, scrolling on

3:10:43social media for an hour might be free,

3:10:45but if you do that every day during your

3:10:46peak production time, it's costing you

3:10:48hundreds, thousands of dollars a week.

3:10:50And at the same time, expensive things

3:10:52can actually end up being bargains. Like

3:10:55maybe paying $200 for somebody to come

3:10:57and clean your house might seem pricey,

3:10:59but if the $200 you make you you get

3:11:02back makes you over $200. Rather, if the

3:11:04two hours that you get back makes you

3:11:05over $200, it's a great deal, right? So,

3:11:08we'll get into more specific numbers

3:11:09during the section on hourly rates, but

3:11:11this is the general idea. How do you

3:11:14actually use it? It's simple. The next

3:11:15time you say yes to anything that's

3:11:17illdefined or consumes your time, you

3:11:18should explicitly state not only yes, I

3:11:21will go do the thing, you should state

3:11:22what you are saying no to. So, I don't

3:11:24mean time in a vague sense. I mean you

3:11:26should explicitly state the specific

3:11:28thing you will not be doing or could not

3:11:29be doing because you said yes to this

3:11:31other thing. Good example, if you're

3:11:33about to say yes to a 10 a.m. call from

3:11:35some team member that wants some

3:11:36clarification about something

3:11:37that could have been an email, just say,

3:11:39"I'm saying yes to this 10 a.m. call and

3:11:41in doing so, I'm saying no to writing my

3:11:43money-making script or whatever the hell

3:11:45at 10 a.m." That is a simple and easy

3:11:47way to just ground you in reality and

3:11:49constantly remind you of the cost of

3:11:51your decisions. So some action questions

3:11:53for you. The first is what is the last

3:11:56thing you said yes to? The next is what

3:11:58was the best alternative use of that

3:12:00time? Specifically, would you make the

3:12:01same call understanding opportunity

Incentives and Goodhart's law

3:12:03cost? Now, next up, I want to talk about

3:12:05Goodart's law. Charlie Mer, the

3:12:07billionaire investor who was also Warren

3:12:09Buffett's right-hand man, said, "Show me

3:12:11the incentive and I'll show you the

3:12:12outcome." The funny story is for three

3:12:14months I thought it was my podcast

3:12:16co-host Jack Roberts that came up with

3:12:18that. So, fool me once, buddy. But uh

3:12:20there's no better predictor of human

3:12:22behavior than our incentives. They are

3:12:24far more important than any values that

3:12:25anybody says they hold or their

3:12:27individual personality traits. And this

3:12:29all makes sense when you think about the

3:12:30purpose of this course, which is that

3:12:32people are animals and animals act

3:12:33typically in ways that are rewarded like

3:12:35the rats in my lab. If you give a rat a

3:12:37button to press and if you reward it

3:12:39with food every time it does so, you

3:12:40know, it'll happily press the lever. It

3:12:42doesn't really care what your intent is

3:12:43or why you're doing it. The only

3:12:44internal incentive is press button, I

3:12:47will get tasty food. Once you understand

3:12:49this, you'll also understand if the rat

3:12:51doesn't do what you want, it's not

3:12:52really the rat's fault, is it? It's just

3:12:54responding to its incentives, as you are

3:12:55the more cognitively capable. It's not

3:12:58the rat's fault. It's yours because you

3:12:59knew its incentives and you use them

3:13:01wrong. So, humans are the same. We just

3:13:03use words. An example from business, if

3:13:05you pay your support team based on how

3:13:07many tickets they close, logically,

3:13:08they'll close more tickets. But they'll

3:13:10do that even if the tickets themselves

3:13:11are poorly done. You pay your sales team

3:13:14based on how many calls they'll book.

3:13:15They'll probably book more calls, right?

3:13:16but they'll start doing so even if

3:13:18they're unqualified. This doesn't make

3:13:20your support team or your sales team uh

3:13:22bad people. They're just reacting to the

3:13:24environment that you place them in. And

3:13:26that is the heart of a law called Good

3:13:29Hart's law. So Goodart

3:13:32was proposed initially by Charles

3:13:34Goodhart. He's an economist in 1975. He

3:13:37said, "When a measure becomes a target,

3:13:38it ceases to be a good measure."

3:13:41So, some examples of what we've been

3:13:43discussing, uh, a really twisted one

3:13:44that I think you guys can keep in your

3:13:46mind as you proceed in Hanoi in the

3:13:48Vietnam sewers in 1902. You know, the

3:13:50French had taken over. And so, the

3:13:52French colonial government at the time

3:13:53had a massive rat infestation problem.

3:13:55So, what they started doing is offering

3:13:571 cent per rat tail to hunters who would

3:13:59go out, cut the tails off rats,

3:14:01presumably kill them, and then bring

3:14:02them in for money. Predictably, lots of

3:14:05rat tails flooded in. But despite all of

3:14:07the rat tails, the rat population didn't

3:14:08go down. Why? Cuz hunters began to cut

3:14:11off the rat tails, but they would

3:14:13release the rats back into the sewer to

3:14:15breed. And some would even start

3:14:17breeding rats on purpose. So, what does

3:14:20that mean? The tail counts were a good

3:14:22measure of dead rats, but when you tied

3:14:24them to an incentive, they stopped being

3:14:26valuable. So, basically, um, you know,

3:14:30when the measure becomes a target, the

3:14:32measure is removed from the target. If

3:14:35the black is what you actually wanted

3:14:37here and if at some point you decide to

3:14:40incentivize it, okay, eventually what'll

3:14:42happen is people will care more about

3:14:44achieving the measure or the metric than

3:14:46they will about the thing that you

3:14:47actually wanted. And as a result, the

3:14:49thing you actually wanted tends to go

3:14:50back down. That's what that means. When

3:14:52when a measure becomes a target, it

3:14:54ceases to be a good measure.

3:14:56So understanding this will help you

3:14:57think far more clearly. It'll also put I

3:14:59think into words a lot of incentive

3:15:01based behavior you've probably seen. For

3:15:03example, the phone that you're using.

3:15:05Dozens of features are good examples of

3:15:07GoodArt's law here. Like notifications

3:15:08are on by default or autoplay videos or

3:15:10infinite scrolling or streaks or red

3:15:12notification bubbles or whatever the

3:15:14hell. None of these are effectively

3:15:16beneficial. What happened is a product

3:15:18manager probably just had a metric put

3:15:19in front of them that they're optimizing

3:15:20for like daily active users or time

3:15:23inapp. They go to a meeting once a week

3:15:24and they get rewarded based off of their

3:15:26time in app or daily active users. And

3:15:29so they wanted to win. What they did is

3:15:30they set all these defaults to be the

3:15:32way of measuring and manipulating your

3:15:33attention. The end result is you now

3:15:35have to deal with a lot of stupid

3:15:36on your phone. A good personal

3:15:39example for me is views. You know, views

3:15:41are a proxy for the goal of my YouTube

3:15:43channel because if you think about it,

3:15:44the more views I make, the more impact.

3:15:46And ultimately, my goal is impact. So,

3:15:47in this way, my view metric is a map of

3:15:50an underlying territory. But I

3:15:52constantly need to remind myself the

3:15:53views are not the end goal myself. My

3:15:55real goal is for you to watch the video

3:15:57until the end and actually use it.

3:15:58Right? The issue is when I focus too

3:16:00much on views and fall prey to

3:16:01good-hearting myself, which I've done

3:16:03before, I end up making decisions that

3:16:05optimize for superficial shitty views at

3:16:07the cost of depth. And so my watch time

3:16:09tends to go down, which is not a good

3:16:11thing. Despite my best intentions, every

3:16:13few months, view maximization behavior

3:16:15creeps up because the measure is

3:16:16becoming a target and I always have to

3:16:18quash it down. And if you think about

3:16:20it, that's coming from me, who's

3:16:21somebody that has studied this for

3:16:22almost a decade now. Imagine how

3:16:24stupidly someone who has never heard of

3:16:26Goodart's law or has never even

3:16:27reflected on their own behavior is

3:16:28probably being driven by this right now.

3:16:31So, how do you avoid getting

3:16:32good-hearted or good-hearting people?

3:16:34First, if somebody does something you

3:16:36don't understand, just ask yourself who

3:16:38benefits from this. Usually, if you ask

3:16:40yourself who benefits from this and you

3:16:41see who benefits from this, the answer

3:16:43becomes clear. Next, before you put a

3:16:46target on a metric, which is useful for

3:16:47project management, first say what it is

3:16:49a proxy for and then connect it to a

3:16:52counter metric that gets worse when the

3:16:54first one gets better. So, if this

3:16:56doesn't make sense to you, it's a little

3:16:57hack. Um, consider how about speed

3:17:00versus error rate or tickets closed

3:17:02versus the number of tickets from those

3:17:04closed ones that get reopened because

3:17:05they didn't actually work or how about

3:17:07views versus, you know, retention or

3:17:10watch rate or something. If you think

3:17:12about it, if one goes up and the other

3:17:13goes down, it's a sign that you're

3:17:15gaming the system and the underlying

3:17:16metric probably isn't improving. How

3:17:18about like in my case impact? I want

3:17:20views and I want watch time, right? But

3:17:22if my views go up and my watch time goes

3:17:24down, what it means is I'm making

3:17:25superficial content that chases views at

3:17:27the cost of my watch time. So my impact

3:17:29has gone down. So remember map and

3:17:32territory. When the number itself and

3:17:34reality disagrees, reality always wins.

3:17:37Okay, some more action questions for

3:17:39you. What number do you guys check most

3:17:40often? And why has the number itself

3:17:42become a target rather than the thing it

3:17:44represents? What counter metric could

3:17:46you add to show that it is being gamed?

Chesterton's fence

3:17:49There's this lovely idea of Chesterton's

3:17:52fence. Uh and it was I think initially

3:17:54uh introduced in 1929 and it goes like

3:17:57this. Two people, reformers in this case

3:17:59are walking down a road. They come to a

3:18:01fence. One of the reformers wants to

3:18:03tear the fence down because he doesn't

3:18:05see the point of it. But the other

3:18:06suggests that he finds the point of the

3:18:08fence out and only then actually tear it

3:18:11down. I presume one of these fellas was

3:18:13called Chesterton because this parable

3:18:15has been taken to be called Chesterton's

3:18:17fence. Now, as a systems person,

3:18:19Chesterton's fence is simultaneously one

3:18:21of the most interesting and also most

3:18:22annoying things I've ever witnessed. Uh,

3:18:24at its core, it suggests the following.

3:18:27For every fence, which if you think

3:18:28about it in business terms is a rule, an

3:18:30order, a legislation, a law, a workflow,

3:18:32a process, an SOP, anything like that,

3:18:35there must have been an investment at

3:18:36some point in time of time, energy, or

3:18:39money into the thing. People in general

3:18:41conserve all these things, right? So,

3:18:43there has to be a reason why a fence was

3:18:46created. And it really just says before

3:18:48tearing something down, you should

3:18:50understand why it exists. For example,

3:18:52in business, if you have weird steps in

3:18:54a spreadsheet or a process, if you have

3:18:56a strange client approval requirement

3:18:57checklist, if you have inexplicable

3:19:00steps that you do not understand in an

3:19:01SOP, as a newcomer to a system, you

3:19:04know, you come in and you're like, well,

3:19:06why the hell are we doing this? It's

3:19:07obviously very tempting to cut through

3:19:09all the red tape, right? And then remove

3:19:10all the stuff you don't understand. It

3:19:13makes you feel decisive, you know, like

3:19:14you're improving things or or making

3:19:16moves. There's a lot of situations like

3:19:18that where a new hot shot manager or CEO

3:19:20comes into some like pre-existing team

3:19:22and then immediately starts demolishing

3:19:23all the existing structures because they

3:19:24think, well, you don't need this, you

3:19:26don't need that. But if you think about

3:19:27it, a lot of these weird steps were the

3:19:29result of rather expensive deliberating.

3:19:32And this occurred far beyond before you

3:19:34came into the picture, right? When you

3:19:36remove these steps, what you're doing is

3:19:37you're forcefully rerunning an

3:19:38experiment that led to all of these

3:19:40conditions occurring in the first place.

3:19:42Except now you are the one who is

3:19:43suffering the consequences. Now, I'm not

3:19:45saying you 100% have to respect every

3:19:47tradition, rule, SOP, or thing that your

3:19:49predecessors did.

3:19:52But what I am saying is treat the fence

3:19:54like a map. Just like a map is a

3:19:56compressed and often useful example of a

3:19:58territory, a fence is a compressed and

3:20:01often useful example of a process. Think

3:20:04about it in your own life. How many

3:20:05weird fences or things that you do seem

3:20:08inexplicable or strange to other people?

3:20:11Probably a lot. A good example is all

3:20:13the places you put all your different

3:20:14kinds of belongings. So, how about your

3:20:16food, your clothing, your keys, your

3:20:18pantry, your goods, etc., you know, if

3:20:20another person were to come into your

3:20:21home and look at all these things with

3:20:22no context, do you really think they

3:20:24wouldn't spot at least one thing that

3:20:25would make them go, "What the hell did

3:20:26you do that for?" Like, for instance,

3:20:28why are all the plates up on the upper

3:20:30cabinet and not on the more convenient

3:20:31lower cabinet? That seems weird. You

3:20:33should move them to the lower cabinet.

3:20:35Well, actually, there's a reason for

3:20:36that. When you stack more than four

3:20:37plates, they start catching the door.

3:20:39You see, in this example, which is

3:20:41actually real in my own damn house

3:20:43freaking cupboards, you are the one who

3:20:45put up the fence and you did so

3:20:46immediately after an event. In our case,

3:20:48closing the cabinet that taught you a

3:20:50lesson, which was sound, pain, etc.,

3:20:52which is why you did it, right? So, how

3:20:55do you actually deal with it? Here is

3:20:57the workflow. If there's a rule you want

3:20:59to remove, figure out why it's there. If

3:21:02you figured it out, you can now decide

3:21:03on the merits and either keep it or

3:21:05remove it. If you do not know why it's

3:21:07there, first ask the person who built

3:21:09it. That is ideal. If you can't ask the

3:21:11person who built it, check the history.

3:21:13Then if you still don't know whether or

3:21:15not it is required, try removing it and

3:21:17then see what happens. If it's not

3:21:19irreversible, you unfortunately have to

3:21:21leave it. So that's it. Just don't take

3:21:24anything down until you understand why

3:21:25it was there in the first place. Doesn't

3:21:27mean you have to keep the fence forever.

3:21:28It just means that if you want to reason

3:21:29clearly through how best to optimize a

3:21:31process, the fixed order of operations

3:21:33is understand the fence first. decide

3:21:35what to do after. Some ways you can

3:21:37figure this out. Ask the person who

3:21:39built the fence. Look through the

3:21:41document history. So, Google Docs,

3:21:42Drive, etc. is great for this in modern

3:21:44corporate environments. Check the git

3:21:45log if you guys are doing code. Go

3:21:47through old email threads if SOPs or

3:21:49processes. You can also just think hard.

3:21:51What would happen if the fence wasn't

3:21:52there for like a week or a month or a

3:21:54year? And the crazy thing is most of the

3:21:56time you can do everything I just talked

3:21:57about in like 10 minutes. These

3:21:59inexplicable processes that you do not

3:22:01understand, you can actually understand.

3:22:03And a lot of the time you'll find that,

3:22:04you know, the fence, whatever it is, was

3:22:06necessary back in 2021, maybe no longer

3:22:09required today because of some new

3:22:10technology. Once you're done with that,

3:22:12you can confidently remove the fence

3:22:13without any guilt and with minimal

3:22:15slowdown and without like really making

3:22:17people hate you while also eliminating

3:22:19risk. This is something very important

3:22:21that I had to learn the hard way as a

3:22:23trigger-happy young man who started

3:22:25basically branding himself as like an

3:22:27operations consultant and then

3:22:28eventually like a fractional COO who

3:22:30would remove a lot of fences that

3:22:31probably did not need to be removed. So

3:22:33hopefully this helps you like it helped

3:22:35me. Some action questions for you. Uh

3:22:37the first is which rule, step or habit

3:22:40have you been meaning to delete because

3:22:42it looks pointless? First write one

3:22:44sentence on why it was put there. If you

3:22:47cannot write one sentence, who do you

3:22:49know that could tell you? And how can

3:22:50you ask them?

3:22:52Next, which fence did past you build for

3:22:55yourself that present you has stopped

3:22:57respecting? And what was the specific

3:22:59event that made you actually build this

3:23:00thing in the first place?

3:23:03Next up, I want to talk beige

3:23:04frequencies.

Bayes in natural frequencies

3:23:07No, let's not do that. Next up, I want

3:23:09to talk Baze theorem. This is one of my

3:23:11favorite thinking tools and at its core

3:23:13it's a very simple idea which is that

3:23:15you start with a rough guess about how

3:23:16likely something is which is called a

3:23:18prior probability and then you update

3:23:20that guess as you get new information.

3:23:23Now it is really simple conceptually

3:23:24rather than deciding that things are

3:23:26true or false what you do is you treat

3:23:28everything as a probability and you say

3:23:30that has a 95% chance of occurring this

3:23:32way and maybe a 5% chance of occurring

3:23:34that way. Nothing is 100% or 0% anymore.

3:23:37It's all a realm of probabilities. For

3:23:38example, using B theorem, you can expect

3:23:41a very high probability that the sun

3:23:43will go up 2 days from now. How? Well,

3:23:45you'll start with a rough guess about

3:23:47how likely it is, which is the prior

3:23:48probability. Given that the sun has come

3:23:50up virtually every day of your life,

3:23:52probably every day of your life, uh the

3:23:54probability is really high, right? It's

3:23:56like 99.999%.

3:23:58Then after that, you update it based off

3:24:00new information. Maybe you'll wait a day

3:24:02and you'll see if the sun comes up

3:24:03again. If so, now you can update your

3:24:05probability from 99.9% to 99.99999%

3:24:09or something. Unfortunately, most of you

3:24:11will never have heard of it. In

3:24:13practice, the reason why is because it's

3:24:14presented in a very annoying

3:24:16mathematical format that I think just

3:24:18like most people would never understand

3:24:20unless somebody put a gun to their

3:24:21heads, which is ridiculous if I'm

3:24:22honest, because it's probably one of the

3:24:24simplest, most generally powerful

3:24:26reasoning tools and is inaccessible to

3:24:28most of the population because a bunch

3:24:29of mathy Um, for instance, my

3:24:32girlfriend's a doctor. They discussed

3:24:33base theorem with her in school. I got

3:24:35really excited when I heard about this,

3:24:37thinking, "Hey, we'll get to estimate

3:24:38probabilities for all sorts of things."

3:24:40But when I asked her about it, she gave

3:24:41me basically a longass formula based on

3:24:43conditional probabilities, which sucked.

3:24:45And it didn't really explain any of the

3:24:46beauty or intuition behind it. Um,

3:24:49again, this is something that I

3:24:50personally think should be probably

3:24:51taught in like grade school.

3:24:53Unfortunately, nobody's born with the

3:24:54ability to intuitively calculate

3:24:55conditional probabilities, which is what

3:24:57base theorem is all about. uh even after

3:24:595 years in research labs, I don't think

3:25:00I'm better any better uh than you are at

3:25:02doing them in my head. So I'm not going

3:25:04to even talk the formula here. The point

3:25:06is more intuitively that you need to

3:25:08understand that everything in life is a

3:25:10series of probabilities.

3:25:12So before we look at a specific example

3:25:14of base theorem, I want to instill a

3:25:16core concept that we will use to

3:25:17determine whether a piece of evidence is

3:25:19important. What is the likelihood that

3:25:22this evidence would occur if X were true

3:25:24versus if X were false? This is the

3:25:27question that is probably the most

3:25:29effective one that you can answer. It's

3:25:31very important to wrap your head around.

3:25:32So, let's think about that sentence

3:25:34deeply. What is the likelihood that this

3:25:37evidence would occur if X were true

3:25:40versus if X were false? For instance,

3:25:43imagine you are selling something and at

3:25:45the end of the call, the prospect says,

3:25:46"This looks great. Can you send me over

3:25:48the details?" Most people assume this is

3:25:50strong evidence that the deal will

3:25:51close, right? And it feels good. So,

3:25:53they'll hang up and they'll tell their

3:25:55partner, "This went really well." But I

3:25:57want you to think about the question.

3:25:59What's the likelihood a prospect says,

3:26:01"This looks great. Send me the details."

3:26:03If they're actually going to buy, well,

3:26:06it's very high, right? Almost all buyers

3:26:07are going to say something like that.

3:26:08Maybe 0.9.

3:26:10But what's the likelihood they'll also

3:26:12say it if they're never going to buy?

3:26:15Guess what? It's also really high. Maybe

3:26:170.9. Because if you think about it, that

3:26:19is the politest possible way to end a

3:26:21call. and it probably matches your own

3:26:22buyer behavior as well. And that's the

3:26:24real crux of it. Since the sentence

3:26:26shows up in both of these hypothetical

3:26:28worlds at roughly the same rate, simply

3:26:30hearing this piece of information will

3:26:31tell you absolutely nothing. For

3:26:33instance, it is very weak evidence of a

3:26:35sale and it is merely evidence that your

3:26:37call is ending in all reality. Now,

3:26:41compare this to somebody that says,

3:26:42"Interesting. Are you able to invoice us

3:26:44quarterly instead of monthly?" If you

3:26:46think about it, how often does that

3:26:47happen when somebody's going to buy?

3:26:48probably pretty often because it's

3:26:49discussing payment terms, right? Maybe

3:26:510.9. How often does it happen when they

3:26:53aren't going to buy? Well, pretty much

3:26:57never because nobody cares about

3:26:59negotiating payment terms on a product

3:27:01they have no intention of purchasing,

3:27:02right? I mean, that's just like behavior

3:27:04101. It's extra work and we'd all rather

3:27:06just get on with our lives and I'd

3:27:07rather end the call and go, you know,

3:27:08bury my head in in the sand. So, maybe

3:27:10the odds of that are 0.1. So, what that

3:27:13means is if your prior probability for a

3:27:14close was 0.25 0.25 or just 25%. Cuz

3:27:17that's just how much you guys normally

3:27:18do. If you hear the former which is that

3:27:21you know hey do you guys invoice

3:27:23quarterly instead of monthly you can

3:27:24immediately update that to like 0.9

3:27:26which is now 90%. And if you think about

3:27:28it logically that probability will now

3:27:30change how you interact with that

3:27:32prospect and in doing so become a

3:27:34self-fulfilling prophecy where you're

3:27:35much more likely to actually close that

3:27:37client because you are interacting with

3:27:38them differently. You can also do things

3:27:39like project income, project pipeline

3:27:41value and so on and so forth.

3:27:43I love B theorem. It is so hard for me

3:27:46to explain how impactful B theorem has

3:27:48been to my life and my career. So, let's

3:27:51do a couple more examples. Um, first, a

3:27:54word of advice from somebody that's used

3:27:55and abused Baze law for the last few

3:27:57years. Update in small steps. And

3:27:59ideally, you would do so one small piece

3:28:01of evidence at a time. Good Bayian

3:28:03updating is all about chaining multiple

3:28:04steps together, not just one. And so, to

3:28:07do so, instead of percentages, we use

3:28:08odds. Odds are very simple. Uh 10%

3:28:11probability just means your odds are 1

3:28:13in nine. So it's not 1 in 10, which I

3:28:15know sounds weird, but it's one in nine.

3:28:16One chance of it being true, nine

3:28:18chances of it being false. 10% just

3:28:20means there's a 1 in 10 chance, right?

3:28:22Well, it's it's not. It's like there's a

3:28:241 to nine odds. So we can chain our

3:28:27previous example together like this.

3:28:28Let's say you have a 1 in100 odds of

3:28:31closing a deal in on any random

3:28:33prospect. I'm realizing here I should

3:28:35probably say uh one in 99 considering I

3:28:38absolutely explicitly just explained how

3:28:40that works. So there's a 1% chance 1%

3:28:45chance or 1 in 99 odds of closing a deal

3:28:49with any random prospect. That means

3:28:52that your prior odds if you think about

3:28:53it are one to 99. Okay, basically in one

3:28:57out of a 100 cases you will make money,

3:28:59right? Which means out of 100 one of

3:29:01these that one will occur. Now, what

3:29:04happens is you get a very quick reply

3:29:06from one of these people, which makes

3:29:08your odds 2.7 times more likely. If you

3:29:10do the math on this, okay, multiplying

3:29:12them out, that's 2.7 to 999. Now, which

3:29:17if you do the math on that is 2.7 / 99

3:29:20or 27%, which I guess is still the same

3:29:23as it was before.

3:29:25Now, let's say you get a pricing

3:29:26question from the same prospect. That

3:29:28makes you two times more likely after

3:29:31that. This puts you at 5.4%. 4% rounded

3:29:34to five. Now, unfortunately, let's say

3:29:36that same prospect eventually no showed

3:29:37a meeting. That makes them 4x less

3:29:39likely or maybe a quarter. So, now the

3:29:41odds are 1.35 to 99. This is 1.35%

3:29:45approximately. Notice how we're not just

3:29:47adding or subtracting. What we're doing

3:29:49is we're multiplying. This allows us to

3:29:50scale our odds up or down quickly while

3:29:52also still maintaining a strong degree

3:29:54of nuance. The value here is Baze law is

3:29:57excellent for sales pipelines, for

3:30:00probabilities, for projects, and so on

3:30:03and so forth. What you can do is you can

3:30:05get the average order value of a

3:30:06product, maybe 5,000 bucks, and then

3:30:08just get the conditional probabilities

3:30:10of every pipeline step based off

3:30:11historical closing. Then you can just

3:30:13multiply them all together to give you

3:30:14the expected value of your pipeline. In

3:30:17that way, you can get very granular

3:30:18about how much money your company is

3:30:19actually capable of making. And as

3:30:22mentioned, I mean, this is just one of

3:30:23like many, many different things that

3:30:24you can do. Base theorem is a very small

3:30:26chunk I would say of all u sorry CRM are

3:30:29a very small chunk of I would say all

3:30:31possible ways you can apply base

3:30:32theorem. So for instance updating in

3:30:35small steps the base rate might be you

3:30:37know 10 well you know I I said one in 99

3:30:40this is 10 but bear with me here because

3:30:42obviously I generate these graphics um

3:30:45you know this moved up to 2.4x this

3:30:47moved up to 3.7x this move back down to

3:30:501.3 or whatever. Uh but ultimately the

3:30:53idea is we're updating in steps. We're

3:30:55not just updating all at once. Now if

3:30:57you guys didn't get the explanations

3:30:58behind base theorem, don't worry about

3:31:00it. There are lots of great resources

3:31:01and many of them are from less wrong or

3:31:04this guy Elizer Ykowski who's just

3:31:06wonderful at explaining these

3:31:07rationality things. Um so you guys can

3:31:09just click this link and check out more

3:31:10intuitive explanations of B theorem from

3:31:12the latter. Okay, one big question

3:31:15before we move on. Pick an idea you have

3:31:17about your business or your career. like

3:31:19this product's going to kick ass or this

3:31:21hire is awesome. Then write down the

3:31:24Beijian prior for it and just ask

3:31:26yourself how often you would see it if

3:31:27the belief were false. Congratulations,

Fermi approximations

3:31:29you just did some Beijian reasoning.

3:31:31Let's talk a little bit about Fermy

3:31:32approximations. Now, for those of you

3:31:34guys that don't know, Fermy was a

3:31:35renowned physicist. At the Trinity Nuke

3:31:38test site in 1945, he had a really cool

3:31:41experiment where he dropped a few scraps

3:31:43of paper during the progression of that

3:31:44big blast wave. Then he just watched how

3:31:47far they traveled and then using his

3:31:49knowledge of physics just did some very

3:31:51rough like back of napkin math he ended

3:31:53up estimating the yield of the nuclear

3:31:55bomb to about 10 kilotons of TNT. What's

3:31:58really interesting is the actual

3:31:59accepted figure was just about twice of

3:32:01that, meaning he was off by a factor of

3:32:03two. Which means like to most people he

3:32:06was wrong, right? But to physicist, they

3:32:09would look at that and they would go

3:32:10like, "Are you kidding? You were able to

3:32:12estimate the size of that nuclear bomb

3:32:14within an order of magnitude, aka 10

3:32:16times, and you just did it by dropping a

3:32:19couple of random scraps of paper and

3:32:20then doing back a napkin math. That's

3:32:22extremely impressive." And the reality

3:32:25is this idea of fermy approximate. So

3:32:27being able to approximate things like

3:32:28fermy is an extremely powerful skill

3:32:31that I personally use virtually every

3:32:32single day as somebody in business and

3:32:34that once you learn you will probably

3:32:35want to use very often as well. So I

3:32:38figured we'd probably spend a few

3:32:39moments covering it. So how do you do

3:32:41it? Well, it's easy. First you

3:32:43decompose. Then you estimate. And then

3:32:45you multiply. Okay. So the way that it

3:32:48works is, you know, you have some sort

3:32:50of problem of some kind. I don't know

3:32:52what the problem might be. let's say the

3:32:54number of intersections in your city.

3:32:56What you do is you decompose that

3:32:58problem into parts. You ask yourself,

3:33:00okay, so part number one, you know, an

3:33:02intersection is like a four-way stop,

3:33:03right? There needs to be people

3:33:05crossing. Um, so how many intersections

3:33:08are there realistically? Well, I guess I

3:33:10need to figure out how many streets

3:33:12there are going north south or yeah,

3:33:14north south and maybe how many avenues

3:33:15there are going east west. So how many

3:33:17streets are there? Well, I guess it

3:33:19would probably be like 50. And how many

3:33:21avenues are there? I don't know, maybe

3:33:23like another 100 or something like that.

3:33:24So, it's like, okay, well, if I just

3:33:25multiply the two out and how many am I

3:33:27getting? 100 times 50. So, I'm getting

3:33:28what? 5,000 or so. All right, that seems

3:33:31pretty reasonable. Cool. Multiplying

3:33:33them together, I get 5,000 intersections

3:33:34or something like that. So, that's a

3:33:37very simple and naive example, right?

3:33:39Um, but hopefully you guys understand

3:33:40what I mean. You know, extrapolated, I'm

3:33:42sure you guys could see how you could

3:33:44start with something really bad and then

3:33:46just get reasonably within, you know,

3:33:49probably one order of magnitude of the

3:33:51truth. And the reason why that's

3:33:52valuable is because it allows you

3:33:53without having to take everything in

3:33:55your working memory and then put it on a

3:33:56piece of paper to like quickly reason

3:33:58through things in your head um very

3:34:00impressively. So here's an example I use

3:34:02all the time. How many cold emails do

3:34:04you need to get five clients? Okay.

3:34:07Well, maybe you get a positive reply

3:34:10rate of about.5%.

3:34:12That means one in 200 or so. Maybe you

3:34:14get a reply to call rate of about 25%.

3:34:18Maybe after that you get a call to close

3:34:19rate of about 20%. And maybe you know if

3:34:22we combine all that the positive reply

3:34:24rate is 05. The reply to call rate is

3:34:270.25. The call to close rates is 0.2.

3:34:30Maybe in total it's 025 which if you

3:34:33think about it mathematically is 1 in

3:34:344,000. That means you need 4,000 cold

3:34:37emails to get one client. If you wanted

3:34:38to get five clients you would just

3:34:39multiply these two to get 20,000. You

3:34:42know the crazy thing about this? I

3:34:43didn't actually use like my historical

3:34:45numbers for Maker School for any of this

3:34:47stuff, but then I went back and found a

3:34:48bunch of threads in Maker School and I

3:34:50looked at like how many emails the

3:34:52person had sent when they said that they

3:34:53acquired their first client and it was

3:34:55roughly on the order of maybe 2,000 to

3:34:58like 8,000 I would say, which if you

3:35:00think about it, like this isn't this

3:35:02isn't perfect. It's off by a little bit,

3:35:03but it it is quite close to the

3:35:05mathematical average of just some

3:35:06cursory actual information that I

3:35:08gathered. And I remember just being

3:35:10like, "Wow, that is wild." I mean

3:35:11obviously I know about the industry just

3:35:12like Fermy knows about physics and nukes

3:35:14but he was actually able to get within

3:35:16you know a few few percentage points of

3:35:18the answer. So Fermy approximations are

3:35:21foundational to the other two

3:35:22calculations that we've learned. I mean

3:35:24they provide probabilities and payoffs

3:35:26and so on and so forth and that's great

3:35:28for computing expected value. They can

3:35:30also help us estimate the probabilities

3:35:31for theorems like bays. So I think

3:35:33they're an excellent way of reducing a

3:35:34lot of the inherent uncertainty involved

3:35:36in estimating probabilities and impact

3:35:37figures for both. Um, when you don't

3:35:39know, just always decompose, estimate,

3:35:41and multiply. It's a very strong clarity

3:35:43of thought technique. Here's another

3:35:46example in real life. Let's say

3:35:48hypothetically you're considering

3:35:49selling appointment booking software to

3:35:50dental clinics in Canada, which is where

3:35:52I live. Canada's a population about 40

3:35:54million, right? So first, if you wanted

3:35:56to run a firmy approximation to figure

3:35:58out, you know, whether or not it makes

3:35:59sense to sell appointment booking

3:36:01software to dental clinics in Canada, a

3:36:03reasonable thing to do might be to

3:36:04think, okay, so how many people and how

3:36:07many dental clinics for how many people?

3:36:09Like how many people per dental clinic?

3:36:12Maybe there's like a dental clinic every

3:36:145,000 people or so. Well, 40 mil divided

3:36:17by 5,000 is 8,000 clinics in Canada.

3:36:20Okay, that's fair. Maybe about a fifth

3:36:22of these clinics have a problem bad

3:36:24enough to actually want to pay for a

3:36:25solution. Well, 8,000 divided by 5 is

3:36:271,600. Maybe I could reach and close a

3:36:30small percentage of those in the first

3:36:32year. Let's just say, you know, 3% which

3:36:34is 48, which I'll call 50. And let's

3:36:37say, you know, if I went to market

3:36:39really well and I had a big team behind

3:36:40me, I could get each of those 50 clinics

3:36:42to pay me three grand a month for the

3:36:43software. That's 150k a month. Hey,

3:36:46that's actually pretty feasible, right?

3:36:47Now that we've done the Fermy estimate,

3:36:48maybe we can actually go test the waters

3:36:50by sending some emails or calling some

3:36:51people. What I will do constantly while

3:36:54I'm evaluating business models is I will

3:36:55just very very quickly do back of napkin

3:36:58firmy approximates and math and I'll

3:36:59just determine like does this check out?

3:37:01Is there a chance? You know, I'll be

3:37:03conservative across the board, but I

3:37:04will always just be like, okay, let's

3:37:06just run the numbers really quick in my

3:37:07head. This sounds reasonable. It's

3:37:10probably within, you know, an order of

3:37:11like two or three. This sounds

3:37:13reasonable, and this is probably within

3:37:14an order of two or three. And then this

3:37:16sounds reasonable and this is probably

3:37:17within an order of two or three. So this

3:37:19sounds reasonable and it's probably

3:37:20within an order of two or three. If I

3:37:21made 50,000 with this, that' be cool. If

3:37:23I made 300,000 with this, that'd be

3:37:25cool. It justifies the next step, which

3:37:27is obviously doing a little bit more

3:37:28research. Okay, so key takeaways here.

3:37:31The biggest thing to remember with firmy

3:37:33approximates is they're just a tool to

3:37:34prevent you from wasting time. So don't

3:37:36waste a lot of time on them. I round

3:37:38aggressively. If a number is like a

3:37:39seven, I usually make it a 10. If it's

3:37:41350, I make it 300. My goal is not to be

3:37:43precise. It is simply to you know figure

3:37:46it out within an order of magnitude

3:37:47pretty quickly. The value to fermies is

3:37:50each of your individual estimates are

3:37:52probably going to be wrong but they'll

3:37:53probably be similarly wrong and a lot of

3:37:55the time they're off by opposites. So

3:37:57like a previous step like how many

3:37:59people per double clinic is going to be

3:38:00off by a factor of three let's say but

3:38:03then you know the next step which is how

3:38:05many people actually have a problem

3:38:07might be off by a factor of three in the

3:38:08other direction. So all these

3:38:10uncertainties actually do average out

3:38:11and you end up with something quite

3:38:12reasonable. And then what's really cool

3:38:14is you can actually have AI do a lot of

3:38:16this stuff for you too. AI is wicked at

3:38:18firmy approximates and I use it often as

3:38:20a first principle reasoner. I will like

3:38:22give a questions like hey you know let's

3:38:24through first principles and fmy

3:38:25approximates let's run through XYZ

3:38:27problem and like let me see what you

3:38:28think and a lot of the time it'll do

3:38:30just as good as I was capable of doing.

3:38:32And then I can take that estimate and I

3:38:33can use it in the next chain of my

3:38:34process. Okay. And that takes me to an

3:38:37action question, which is, "What is a

3:38:39potential project, business, or idea

3:38:41you're excited about right now? Firm it

3:38:43in 60 seconds." Remember that's

3:38:44decompose, estimate, and multiply. All

Hourly rate and the offload rule

3:38:46right, let's now talk the hourly rate

3:38:48and the offload rule. Most people never

3:38:51calculate their hourly rate. They will

3:38:53just implicitly set it at zero. And that

3:38:56is even if you're the sort of person who

3:38:57thinks that they know their hourly rate.

3:39:00But now that you understand opportunity

3:39:01cost, you should actually sit down and

3:39:03calculate this because the moment that

3:39:05you do, it'll prevent you from spending

3:39:083 hours on a task that an assistant or

3:39:10an AI could do for you for 20 or $30. An

3:39:14example of that might be buying stuff,

3:39:15which until recently I didn't realize

3:39:17was a very poor use of my time. How

3:39:20about doing spreadsheet work or stuff

3:39:22like that? So, why don't we start with

3:39:24what's your hourly rate? Now, first, you

3:39:26don't just need one hourly rate. You

3:39:28actually need two hourly rates. The

3:39:30first is your average hourly rate. The

3:39:33second is your marginal hourly rate. In

3:39:35case you didn't know, average hourly

3:39:37rate is just your income over the last

3:39:39year divided by the total number of

3:39:41hours that you worked in order to make

3:39:43that income. So here you're going to

3:39:45want to use actual hours. If you work a

3:39:46side hustle or Uber on the weekends or

3:39:48whatever, you have to include those

3:39:49quick jobs that you do as well. If not,

3:39:51you will probably be misrepresenting

3:39:53what that is. So that's your average

3:39:55hourly rate. Your marginal hourly rate

3:39:58on the other hand is the value of your

3:40:01best work. Now when I say best work,

3:40:04what I typically refer to is work that

3:40:07when you allocate it towards the number

3:40:09one most important thing in your day,

3:40:11whatever the big money maker is, sales

3:40:13calls, writing a script in my instance,

3:40:16uh I don't know, doing business

3:40:17partnerships or whatever, the amount of

3:40:19money that you would make doing that.

3:40:20And this is the number that matters a

3:40:22lot for people like us who presumably

3:40:24want to improve our stations in life

3:40:25because when we offload some task that

3:40:28is preventing us from spending another

3:40:30hour on our marginal rate, uh we get

3:40:32that entire hour back. Also, usually

3:40:34your marginal rate is way higher than

3:40:36your average rate. So, for instance, my

3:40:38marginal rate managing Maker School,

3:40:39which is my 90-day accountability

3:40:41community, um, if I spend a single hour

3:40:45on Maker School, I will make somewhere

3:40:48between $6 to $8,000.

3:40:50I know that sounds crazy, but such is

3:40:53how Maker School works. If I spend a

3:40:55single hour on Maker School answering

3:40:58questions, recording videos, or

3:41:00responding to people, I make 8,000 $6 to

3:41:02$8,000.

3:41:04But that's not my average hourly rate.

3:41:06Meaning I can't just work eight hours a

3:41:07day and make 6,000 to 8,000 times eight.

3:41:10So I don't know what's that $56,000 a

3:41:12day. If I made $56,000 a day, I'd be

3:41:15making $2 million uh a month. And I

3:41:17don't make $2 million a month. I make

3:41:18about a quarter of that. So the

3:41:20difference there is the average hourly

3:41:22rate takes into account all of the time

3:41:23that I'm spending suboptimally. Okay,

3:41:25just the average hourly rate, the

3:41:27average usage of my time while working.

3:41:29Whereas the marginal hourly rate is

3:41:30basically like just that power law chunk

3:41:32that is the highest ROI.

3:41:35And so ideally your marginal hour rate

3:41:37would be equal to your average hourly

3:41:38rate by the way because you just spend

3:41:39every waking moment of your time on the

3:41:40most effective thing. But let's be real,

3:41:42most of the time it is not. And it's

3:41:43important to understand that.

3:41:45Okay. So logically you should offload a

3:41:49task if the number of hours to complete

3:41:51the task yourself multiplied by your

3:41:55hourly rate your marginal hourly rate

3:41:57[gasps] is greater than the direct price

3:42:00of offloading

3:42:02plus the number of hours you need to

3:42:04supervise the task that somebody else

3:42:06does times your marginal hourly rate. If

3:42:08that doesn't make sense to you, we can

3:42:10look at it with numbers. Now on the left

3:42:13hand side here is cost of um you know

3:42:16your hours and dollars. And so over here

3:42:19for instance if you were to do this

3:42:20hypothetical task whatever it is okay um

3:42:23it's a 5 hour task and your rate is $100

3:42:26per hour. Well $5 per hour times sorry 5

3:42:31hours I should have said times $100 per

3:42:34hour is equal to $500 right that's just

3:42:38logical. Now that's if you do it

3:42:40yourself. If you offload it, okay, what

3:42:43you'll do is, let's say you could pay

3:42:44somebody $150 bucks to do it. You'll pay

3:42:47$150, which will be the price, but

3:42:49you'll still have some additional costs

3:42:51and opportunity that you don't typically

3:42:52take into account. For instance, it may

3:42:54take you an additional hour to scope,

3:42:56send, and then supervise the completion

3:42:58of the task. And maybe you'll do that in

3:42:5920-minute batches. You know, 20 minutes

3:43:01to scope it, 20 minutes to send it off,

3:43:0320 minutes to supervise it um throughout

3:43:04the the course of the task. If you do

3:43:07the math there, then the total amount of

3:43:08time that you just spent multiplied by

3:43:10the obviously price and your hour of

3:43:13supervision is now $250. Meaning that

3:43:16what you've done is you've offloaded a

3:43:17task that was $500 of your own time for

3:43:20a total of $250 or $150 plus 1 hour of

3:43:24your time.

3:43:25Okay? So naturally, if you were to do it

3:43:28yourself, that would cost $100 or $500

3:43:30of your time. Um five hours times $100

3:43:33an hour. The only real, I'd say, error

3:43:38rate here. The issue is just that

3:43:40supervision portion. A lot of the time

3:43:42people assume the supervision portion is

3:43:44basically zero. They'll say, well, you

3:43:46know, I hire good people. I only have

3:43:47good people on my team, so they'll be

3:43:48able to do it. But the question is not

3:43:50are they able to do it. It's are they

3:43:51able to do it as well as you are? And in

3:43:53most cases, they will not be able to do

3:43:54it as well as you are. And so what

3:43:55you'll have to do is you will have to

3:43:56poke and prod and move things around

3:43:57just enough. Okay? Just enough for that

3:44:00to take a little bit more of your time,

3:44:02reducing the total profitability of that

3:44:03calculation.

3:44:04Nobody talks about that, but I figure I

3:44:06might as well because yeah, I mean,

3:44:08obviously everything looks like sunshine

3:44:09and rainbows if you could spend $150 to

3:44:11do something that might have taken you

3:44:12$500, but you do have to take into

3:44:14account you are always now going to have

3:44:15to scope the task, send the task, and

3:44:17then delegate and uh uh supervise the

3:44:20task as well. So, hypothetically, let's

3:44:23say you give yourself a little bit of

3:44:24error bars and you say, uh, you know, I

3:44:26might screw something up in the task.

3:44:28So, now they have to send that back for

3:44:29revisions and then I have to do it, you

3:44:30know, maybe this is some like design

3:44:32task or something. So, it'll actually

3:44:33take twice as long for me to supervise.

3:44:34What do we do? All we do is we add an

3:44:36additional 1 hour of supervision cost to

3:44:38this to make this 2 hours of supervision

3:44:40or $200 with a price of $150 putting the

3:44:43total cost at 350. Now, that is still

3:44:46well within profitability, right? You're

3:44:48spending $350 to make 500. Obviously,

3:44:50that's fine. Ideally, I'm happy to

3:44:53offload tasks that perform at at least a

3:44:563x multiple. So, or a 2.5x multiple. So

3:44:59that $150 to $500 is actually basically

3:45:01the precise example um of you know tasks

3:45:04that I would delegate. Uh anything

3:45:06around there gives me enough of an error

3:45:08bar that I'm okay having to do a little

3:45:10bit of supervision just in case. And it

3:45:12also allows me to as we know through the

3:45:14planning fallacy um you know it allows

3:45:17me to kind of massage the the rate. It's

3:45:19I don't think we actually talked about

3:45:20the planning fallacy yet. Um it allows

3:45:22me to massage the rate a little bit in

3:45:23case my math is a little bit off. So

3:45:25consider the prior probability that you

3:45:27know your exact hourly rate and that

3:45:28your marginal hourly rate is equivalent

3:45:30to the true marginal hourly rate, not

3:45:32just your calculated marginal hourly

3:45:33rate. Like if the prior probability is

3:45:36quite high, you know, then there's a

3:45:39high correlation between what you think

3:45:40your hourly rate is and what it actually

3:45:41is, but we still have a little bit of a

3:45:43gap and that controls for that gap.

3:45:46So supervision is the main issue in

3:45:48practice. in delegation, you know, will

3:45:51always require your time to write a

3:45:52brief check-in, answer questions, review

3:45:54outputs, and so on and so forth. So, you

3:45:55just have to be honest with yourself

3:45:56about those supervision costs or the

3:45:58task will boomerang back to you. It's

3:45:59just now it'll be half done, and half

3:46:01done is almost worse than not done.

3:46:03[sighs and gasps] Also, just because a

3:46:05task is offloadable, that doesn't

3:46:06necessarily mean you should always

3:46:08offload that task. Some things are how

3:46:09you make your money and what your

3:46:10customers are paying you for and should

3:46:12just not be offloaded. For instance, I

3:46:14respond to every post in Maker School

3:46:15myself. I also film all of my own

3:46:17videos. The reason why is because I make

3:46:18an insane amount of money doing this.

3:46:20Close to about $10,000 per hour right

3:46:22now, which my estimate was nearly

3:46:23correct on. What marginal rate would be

3:46:25$10,000? I have to make at least 11. And

3:46:27not only would I have to make 11, I'd

3:46:29have to be sure that like, you know, the

3:46:30work that I'm doing and and offloading

3:46:32is actually genuinely as good, if not

3:46:33better. I see virtually no way I could

3:46:36do that unless the marginal rate is now

3:46:3840 or $50,000 an hour. So, I just can't

3:46:40see any reason at which I'd ever do it.

3:46:42If I was making $50,000 an hour, you

3:46:44know, I could be one of the richest

3:46:45people on Earth, right? Well, maybe not

3:46:47richest people on earth, but you know

3:46:48what I mean. $50,000 an hour. Let's do

3:46:49some firm approximates. 8 hours a day.

3:46:51Okay, that's $400,000 a day. Or $80

3:46:54million a month. $80 million a month.

3:46:56700 Well, $960 million a year. That's a

3:46:59billion dollars a year. I'd be very,

3:47:01very hardressed to find a way for me to

3:47:04make a multiple on that. Final thing,

3:47:07your time is only worth the hourly rate

3:47:08if you actually use that time

3:47:09productively. Like a lot of people

3:47:10offload $150 task and then they'll just

3:47:13spend their newly freed up time on Tik

3:47:15Tok or whatever. If you're doing that,

3:47:17you are basically paying somebody $150

3:47:18to scroll Tik Tok. And I have been

3:47:20guilty of this, which is why I do not

3:47:21have Tik Tok on my phone.

3:47:23[gasps and sighs] So, some software here

3:47:25can change the math that we just did.

3:47:27Um, especially today with AI agents.

3:47:29They can do a lot of things for less

3:47:30money than you'd usually pay a person. I

3:47:32would say that the main thing with a

3:47:33agents these days is oversight, which is

3:47:36um basically your ability to supervise

3:47:38and then maintain high levels of quality

3:47:40throughout the process. So if you can't

3:47:42verify an agent's work in less time than

3:47:44you'd have spent doing yourself, you

3:47:45should obviously not automate the

3:47:46process. But if you can, then you should

3:47:50automate it if it's high uh volume.

3:47:53Another thing to consider is a

3:47:54scientific study that was done that

3:47:55showed that buying time actually

3:47:57improves your happiness. Now, I don't

3:47:59usually think about this while I'm doing

3:48:00offloading math, but um you know, I

3:48:02probably should. Basically, there's a

3:48:04fair amount of research out there that

3:48:05suggests that when you offload

3:48:06something, you're not just paying $150

3:48:08to not do the task. You're actually

3:48:09buying yourself a whole hour of your

3:48:10time back. And if you think about it,

3:48:13that hour has additional value that I

3:48:15haven't talked about yet. The marginal

3:48:17value equal to your hourly rate plus

3:48:19however much peace of mind or happiness

3:48:21that you will get from having a less

3:48:22stressful week. And that might be

3:48:24considered its true value.

3:48:27Okay? So some caveats. With all that

3:48:29said, if you guys are soloreneurs or

3:48:31freelancers or very small agencies,

3:48:34despite what I just said, you will

3:48:35probably find that most things are not

3:48:37worth offloading. The reason why is

3:48:39because offloading is linked to chain

3:48:41law. As we saw from the chain law, if

3:48:43you add more steps to a process, you get

3:48:45worse performance because of these joint

3:48:46probabilities. Because 0.9 * 75 *.3 *8

3:48:51means the entire process is now

3:48:52subservient to that.3. So if you do a

3:48:55task at 100% one step, the end result is

3:48:56100%. Right? And you know it's going to

3:48:58be 100% because you're good at it and

3:48:59you've done it before. But if you

3:49:00introduce a new person into the task,

3:49:02you'd have error bars around 70%.

3:49:03Meaning your end results is now 70 at

3:49:05minimum. And that's not even taking into

3:49:07account logical other confounders like

3:49:10um supervision and delegation and

3:49:12management time feedback loops and so on

3:49:14and so forth. So in general, I would

3:49:16remember that one trustworthy step is

3:49:17worth 12 clever offloaded steps.

3:49:21Okay. So time for some action questions.

3:49:22So why don't we do some firmy

3:49:23approximations to practice and then you

3:49:26guys can grab a calculator. First work

3:49:28out both of your rates just off the top

3:49:30of your head. How much money did you

3:49:31make last year roughly? Is that 100K?

3:49:33Okay, cool. Fix that. Then divide it by

3:49:36the number of hours worked for the

3:49:37average hourly rate. The average amount

3:49:39of the average number of hours that

3:49:40people work per year, by the way, is

3:49:41about 2,000. So if you made about

3:49:43$100,000 last year and you worked about

3:49:46full-time jobs about 2,000 hours,

3:49:48probably made about 50 bucks an hour

3:49:49average. Once we're done with that, this

3:49:52takes a little bit more time and energy

3:49:54to think about your job and think about

3:49:56the work that you do or your business or

3:49:57whatever of the hours available in your

3:50:00day. What tasks make you more than $50

3:50:04an hour or whatever your average hourly

3:50:05rate is that you just figured out. How

3:50:07much more? Add a multiple to that. If

3:50:10that task is two or three times as

3:50:11important, well, now you know it's $100

3:50:13or $150 an hour worth. Now you know your

3:50:15marginal hourly rate and you also have

3:50:17done some reflecting on what it is that

3:50:19is power law distributed in your

3:50:20day-to-day work. Once you're done, pick

3:50:23one of the tasks that you are currently

3:50:24doing and price the offload cost. Will

3:50:26the price plus your supervision hours at

3:50:28your rate be um higher than that?

3:50:31Essentially once you've done this, what

3:50:35is stopping you from actually

3:50:36offloading?

The planning fallacy multiplier

3:50:38Let's chat about the planning fallacy

3:50:40multiplier. Now tasks in general tend to

3:50:42take longer than you think they will.

3:50:43That's not exactly rocket science. Even

3:50:45after years of missing deadlines and

3:50:47after learning about this planning

3:50:48fallacy multiplier, you will also

3:50:49continue to almost certainly make

3:50:51estimates that are off in the same

3:50:52direction every time. So, what is the

3:50:54planning fallacy? Well, when you plan a

3:50:56task, anything that you're going to do,

3:50:58you almost always go through all the

3:50:59steps in your head as if it is a smooth

3:51:02plan from start to finish.

3:51:04Because human beings don't work very

3:51:06well in hypotheticals, it is virtually

3:51:08impossible to consider all of the cases

3:51:10where something could go wrong simply

3:51:12because there are far more ways for

3:51:13something to go wrong than there are

3:51:14ways for something to go right. What is

3:51:17seen is seen and what is not seen is not

3:51:19seen. Well, it turns out that there are

3:51:21more things that are not seen than are

3:51:22seen.

3:51:24The vast majority of all of the possible

3:51:26routes that you could take or paths that

3:51:27you could take to screw something up are

3:51:30far larger combinatorily than all of the

3:51:32ways that you can make something right.

3:51:34It's like how many ways are there to

3:51:35build a building? Well, there's a few,

3:51:38but how many ways are there to destroy a

3:51:39building? There are a lot more. Because

3:51:42of this, the planning fallacy means that

3:51:44your plan is almost never an actual

3:51:47estimate of how long something will take

3:51:49you. Instead, your plan is almost always

3:51:51a bestcase scenario. And because of

3:51:54that, you should treat it like such.

3:51:56So, how much worse are estimates in

3:51:58reality? Well, a good example is a study

3:52:01on 258 transport projects that cost 90

3:52:03billion in total. Of these 258 transport

3:52:07projects, 9 out of 10 were

3:52:09underestimated with an average cost

3:52:11overrun of 28%.

3:52:14If you're counting rail projects

3:52:15specifically, the average cost overrun

3:52:18was 45%.

3:52:20Now, these were not amateurs. These were

3:52:22258 highquality large infrastructural

3:52:26projects managed by experienced

3:52:27engineers, each of which who had decades

3:52:29of data on similar projects. My own

3:52:32experience is quite similar. As much as

3:52:34I hate to admit it, I routinely go off

3:52:37of my own estimates by anywhere from 30

3:52:38to 50%.

3:52:40So what that means is if planning is

3:52:43always a best case scenario, how can we

3:52:45make this more realistic?

3:52:48[gasps]

3:52:49One approach to do this is to use what's

3:52:51called a planning fallacy multiplier.

3:52:54This is where you take your inside

3:52:56estimate, which is the one that you

3:52:58would have come up with using the

3:53:00simulation in your head of all the ways

3:53:02that things are going to go right, and

3:53:03then just multiply that amount of time

3:53:05that you came up with by some constant

3:53:07number. Believe it or not, that has to

3:53:10be one of the simplest and easiest ways

3:53:11to readjust for your internal bias the

3:53:14wrong way. In practice, many people

3:53:16multiply their planning fallacy

3:53:18estimates by three. Others do it by two.

3:53:21And in my case, I do it by about 1.5.

3:53:24And I do it by about 1.5 because I

3:53:26typically run small projects with very

3:53:28few people involved. So I know that I am

3:53:30usually the majority of the variability

3:53:32in the outcome. Now, it's important to

3:53:35note that your inside view estimate will

3:53:36almost always be way off. So this is

3:53:38necessary for any stakeholders in a

3:53:40project not to hit your guts. You see

3:53:42this a lot when you pitch a client on

3:53:44timets and timelines for a project. You

3:53:47know I do a lot of a automation and so a

3:53:49lot of the time I say something along

3:53:50the lines of this will take 2 to 3

3:53:52weeks. How long do I actually think

3:53:53it'll take? I think it'll take about a

3:53:55week. But I add on okay an additional

3:53:571.5 to 2x amount of time just because I

3:54:00know that my internal estimates are not

3:54:03to be trusted.

3:54:05Another strategy is to stop considering

3:54:07a project in isolation and instead begin

3:54:09looking at other projects that are

3:54:10similar to that project. Whereas before

3:54:13we talked about the inside view which is

3:54:15where you think about how long it would

3:54:16take yourself. This is the outside view.

3:54:20Instead of how long is my course going

3:54:22to take to write it is how long did the

3:54:24last three courses I took to write take.

3:54:28And the way that all of that works

3:54:30realistically is, you know, what you're

3:54:33doing is you're averaging out the actual

3:54:36real times and then comparing them

3:54:38against your estimates. And then what

3:54:39you can do is you can just work out a

3:54:41simple multiple. As you see in this

3:54:42graph, which represents a study that was

3:54:44done on how often people's estimates of

3:54:46when they were sure something would be

3:54:48finished, actually got done. You can see

3:54:51here that in the case of I give it a 50%

3:54:54sure chance that we'll probably finish

3:54:55by that date. Despite people's

3:54:57confidence at being at 50%, the actual

3:55:00percentage of projects that were

3:55:01finished were only 13%. Which is almost

3:55:03a 4x multiplier. When you asked people

3:55:06and tabulated the number of people that

3:55:08said that they would be 75% sure

3:55:10something would finish by a date, you

3:55:12found that only 19% of projects were

3:55:13actually done by that date. Same thing

3:55:16with 99% sure, in which case only 45% of

3:55:18projects were done. Imagine saying, "I'm

3:55:2099.9% sure this thing's going to finish

3:55:21today and you're only right 45% of the

3:55:24time." You probably consider yourself a

3:55:25pretty shitty planner, right? Well, that

3:55:27is just how human beings are on net. We

3:55:29are very, very shitty planners. The good

3:55:31news is you can kind of reliably just

3:55:33multiply this by two or three. in some

3:55:34cases four in order to get yourself back

3:55:36to an actual fair number. So that's

3:55:40reference classes. If you look at the

3:55:42actual outcome or the outside view and

3:55:44then compare that to the income or the

3:55:46inside view rather, you'll find that the

3:55:47reference class will always feel really

3:55:49pessimistic. But the feeling is the

3:55:51fallacy. We just suck at this stuff. So

3:55:54from here on out, all you really do is

3:55:55you just rinse and repeat. You continue

3:55:56making whatever your usual estimate is.

3:55:58Call that the inside view. Then apply a

3:56:00multiplier to the estimate and then use

3:56:02the scaled number to quote clients,

3:56:04write contracts, and ultimately build

3:56:05your life around. And if that number

3:56:07seems crazy, statistically and is

3:56:08probably closer to reality than your

3:56:10estimate is. It is your estimate that is

3:56:11crazy. Do not treat this as a license to

3:56:14slack off. Obviously, I'd recommend you

3:56:16scope every individual step very tightly

3:56:18and aggressively internally. So add very

3:56:20tight timelines to individual steps

3:56:22within an overall plan just to make sure

3:56:25you know you have enough leeway with

3:56:26your stakeholders. This allows you to

3:56:28set both strong internal deadlines and

3:56:30then reasonable external deadlines as

3:56:32well. And this is at the core of

3:56:34thinking clearly because thinking is

3:56:35usually planning and planning is usually

3:56:36long-term strategizing.

3:56:38So, some action questions for you. Think

3:56:40back to the last project you estimated a

3:56:42time on. Could be an essay or something

3:56:44like that that you thought you'd be done

3:56:45by X date. Do you remember the length

3:56:48that you proposed versus how long it

3:56:50took? Now, this can be anything, a

3:56:52personal uh thing, a relationship thing,

3:56:54a business thing, whatever. Whatever the

3:56:56ratio is versus how long you thought it

3:56:58would take to do and how long it

3:56:59actually took, that is a good multiplier

3:57:01to start using and just use that

Explore-exploit tradeoff

3:57:04explore exploit trade-off. Now, imagine

3:57:06you're in a casino and you're presented

3:57:08with 10 awesome looking fancy slot

3:57:10machines. Every machine has a different

3:57:12payout rate, but you don't know which

3:57:14machine is which. And what you have is

3:57:16100 poles to distribute amongst each of

3:57:18the possible slot machines. Every pull

3:57:21on a machine that you know pays out

3:57:23well, aka an exploit of a machine that

3:57:26you know is going to pay you, costs you

3:57:28a pull that you technically could have

3:57:30used to discover an even better machine

3:57:32elsewhere. This technically is called

3:57:34exploring.

3:57:35[gasps] On the flip side, every pull on

3:57:37a machine that you don't know the payout

3:57:38of, aka ones that you are exploring,

3:57:40will cost you pulls on a machine that

3:57:42you do know pays out well. This is a

3:57:45classic problem in research and

3:57:46development and also in planning and

3:57:48acting throughout your life. How many of

3:57:50these machines should I pull before I

3:57:53should feel satisfied with what I have

3:57:55and just pull the highest performer?

3:57:58This is called the exploit explorer

3:58:00trade-off.

3:58:02You know, should I do what works or

3:58:04should I try something new?

3:58:07Exploiting is always about milking a

3:58:09known good. Exploring is about spending

3:58:12time and accepting sub-optimal outcomes.

3:58:14If you think about it from a local

3:58:16maximum perspective, this is where you

3:58:17descend your local maximum. To learn

3:58:20more about other options that might be

3:58:21better performing than the ones that

3:58:23you're currently exploiting.

3:58:24Now, super annoyingly, I find both of

3:58:26these are seen as virtues in the real

3:58:27world, which prevents a frank and honest

3:58:29discussion about how to proceed. For

3:58:31instance, somebody who never explores is

3:58:33usually called focused or specialized.

3:58:36And then when their thing, whatever it

3:58:38is that they're doing, dries up because

3:58:39they've been exploiting the hell out of

3:58:40it and you can only exploit anything for

3:58:42a certain amount of time, then they die

3:58:44because they've never innovated or grew

3:58:46past that. On the other hand, somebody

3:58:48who never exploits could be seen as

3:58:51growthminded or always learning for a

3:58:53very long time. But when you peel back

3:58:55the curtain, you realize that they're

3:58:56poor as hell. They're broke. They

3:58:58haven't actually achieved anything. Why?

3:59:00because they've never stopped to spend

3:59:01enough time milking any one thing that

3:59:03they've discovered to actually reap the

3:59:05rewards of having found it. So in a way

3:59:07you can think of this as the exact same

3:59:09local and global maxima problem that we

3:59:10discussed earlier. It's just now we're

3:59:12adding a time dimension to it.

3:59:15So when should you explore more in life?

3:59:18Well, there's actually some science here

3:59:19and there are some neuroscircuits

3:59:22that have been studied that imply that

3:59:24human beings actually have this

3:59:25built-in.

3:59:27So in this study, we found that human

3:59:29subjects tended to explore more when

3:59:30there were many trials remaining. But as

3:59:32the number of trials decreased or when

3:59:33the rewards began to decline, subjects

3:59:35shifted their energy primarily towards

3:59:37exploitation.

3:59:38Now I find this sort of comforting

3:59:40because if you think about it, unlike

3:59:41most of these other biases and programs,

3:59:43in this case, it's like our brains

3:59:45actually have a built-in algorithm to do

3:59:46this for us. You know, we've been

3:59:47installing a lot of new ones, but this

3:59:49is literally something hardwired

3:59:50probably for evolutionary reasons

3:59:51because exploring and exploitation are

3:59:53core to survival. So, how do you

3:59:55actually use this built-in algorithm to

3:59:57approach your decisions rationally?

3:59:59Well, to make a long story short, if you

4:00:00have a lot of time on your hands, let's

4:00:02say you're very young, you should

4:00:04explore a lot. If you find a better

4:00:06option now, that means that you will get

4:00:08to exploit it for all future time steps.

4:00:11If you are 20 years old and you can

4:00:12expect to live to say 100, that means

4:00:14that you have 80 time steps left to

4:00:16exploit a good thing that you find now.

4:00:19But you should probably heir on the side

4:00:20of finding new things as opposed to just

4:00:22sitting down and exploiting. You can

4:00:24think about this in the case of a job.

4:00:26You know, if you found a $30 an hour job

4:00:28right now, that might be pretty good

4:00:29compared to where you were before. But

4:00:31if you settle there for the rest of your

4:00:32life, the next 80 years at a $30 an hour

4:00:34job, that $30 an hour job will only last

4:00:36you so long before you can no longer

4:00:38exploit it. And is that really the

4:00:40highest you think you can climb? I think

4:00:42about this like investing in risky

4:00:44portfolios since you guys have more time

4:00:46for a risky portfolio to pay off in

4:00:48investing and on average riskier

4:00:49portfolios do pay out more. You know, if

4:00:51you're not investing or if you're not

4:00:54expecting to withdraw money from your

4:00:55investments soon, the number one piece

4:00:57of advice is usually, well, put it in a

4:00:58riskier investment. Put it in something

4:01:00a little more aggressive. Why? Well,

4:01:02because over the course of 60 years or

4:01:03something like that, 50, 40 years,

4:01:05however long you're actually keeping

4:01:06your money invested for, um, you know,

4:01:08the market has gone up a lot. it's only

4:01:10in the short term that it tends to dip.

4:01:13Now, you can contrast this exploration

4:01:16um kind of guidepost with the

4:01:19exploitation guidepost, which is that if

4:01:21you have a very short time horizon, you

4:01:23should exploit instead of explore. The

4:01:26reason why is because you don't have the

4:01:27time to make back what you spent

4:01:28exploring.

4:01:30Here's some other rules. If your current

4:01:32reward is declining, you should explore

4:01:34more. the benefit of exploiting is going

4:01:36down, meaning the value of information

4:01:38and potentially value of other candidate

4:01:40options is going up. And if your current

4:01:43reward is increasing, you should explore

4:01:45more because you just found a winner. So

4:01:48here's a quick visual representation of

4:01:49what that actually looks like. In gray,

4:01:52you have returns from the proven thing

4:01:54that you are exploiting. What you will

4:01:56notice is as you exploit the thing more

4:01:58and more and more and more eventually

4:02:00you will start plummeting because

4:02:02there's only so much time and energy

4:02:04that you can exploit something before

4:02:05the opportunity disappears. You can

4:02:06think of it like a business model per

4:02:08se. At the same time the red is the

4:02:11share of your effort spent exploring.

4:02:13So, ideally what you would do is you'd

4:02:15actually explore it very very hard

4:02:17early. And then after you make it to

4:02:19maybe halfway through, what you would do

4:02:21is you would milk the winner over and

4:02:23over and over and over and over again.

4:02:25And then when your winner starts

4:02:28decaying, like they do in gray over

4:02:29here, you spike up and start exploring

4:02:32again. And so this red here, to be

4:02:34clear, is just how much you explore. At

4:02:36the beginning, you explore a lot. Then

4:02:39though, eventually you explore very

4:02:40little cuz you're milking a known

4:02:41winner. But eventually the winner stops

4:02:44producing a valuable return on

4:02:45investment which is when it goes down

4:02:46and then you start exploring again. And

4:02:48so always explore hard very early. You

4:02:51can think of my own life very similar to

4:02:53this chart. The doortodoor period of my

4:02:55life at around 22 where I was knocking

4:02:5750 doors a day. That was extreme

4:02:59exploration until something stuck. Once

4:03:01I figured that out, I exploited this

4:03:03script that worked, which is just

4:03:04rinsing and repeating the exact same

4:03:06client acquisition strategy book that I

4:03:08was running when I was going door to

4:03:09door in cold calling, cold emailing,

4:03:11cold DMing, and a variety of other like

4:03:13outreachbased methods. And I just

4:03:15continued doing that until we got to

4:03:16about $20,000 a month. However,

4:03:18eventually that client acquisition

4:03:20approach stopped working. It literally

4:03:21just stopped. Why? Because um

4:03:25opportunities only last a certain amount

4:03:26of time. And then I went back to

4:03:28exploration again. It's just this time

4:03:31instead of doing client acquisition the

4:03:32regular way, I started doing AI. I

4:03:34started doing content marketing. Now, I

4:03:36didn't make money off of that right away

4:03:37because I was in explore mode. But

4:03:39eventually, exploration paid off and

4:03:41then I found a winning lever, something

4:03:42that I could pull like that slot machine

4:03:44that delivered me a higher return on

4:03:45investment. Once I found that, I shifted

4:03:47to exploit mode and I repeated that

4:03:49until about $90,000 a month. That was my

4:03:51ceiling. Now, after that, I was on that

4:03:53local maxima. Couldn't get any higher.

4:03:56So, I took a step back and I started

4:03:57exploring more. That took a while, but

4:04:00eventually I found another lever like

4:04:01content, personal branding, and so on

4:04:03and so forth that I started pulling to

4:04:04scale to $540,000 a month, which is my

4:04:07largest recent monthly revenue. So,

4:04:09there are seasons of life in all things.

4:04:11You'll probably go through multiple

4:04:12seasons, including ones where you want

4:04:14to explore a lot, and ones where you

4:04:17want to exploit a lot, and that is

4:04:18totally fine. The good news is now you

4:04:20have a rigorous and procedural name for

4:04:23it. So, you don't need to worry that

4:04:24what you are doing is wasting time. Now

4:04:27you can frame it as exploring or you can

4:04:28frame it as exploiting and you also have

4:04:30a framework by which you you can

4:04:31function. You'll know for instance you

4:04:34should not just be picking up every

4:04:35shiny object and exploring that all day.

4:04:37There will come a time when you need to

4:04:38select the shiniest of the objects that

4:04:40you picked up in say the last 90 days

4:04:41and then commit to it. Only then will

4:04:44you actually be able to exploit and then

4:04:45maximize your return on investment.

4:04:49Uh some action questions and I find it

4:04:50funny how all of these say two questions

4:04:52to answer because I just copy and pasted

4:04:53the same thing. Two answers to question

4:04:56before you continue. No, one uh question

4:04:58to answer before you continue. Map your

4:05:00own explore to exploit pathway. At what

4:05:03point in your life were you exploring

4:05:04and at what point in your life were you

4:05:06exploiting?

Immediately actionable techniques

4:05:08Okay, now it's time for my favorite part

4:05:09of the course. All the software that we

4:05:12talked about so far is a bunch of very

4:05:13general ways to clarify your thinking.

4:05:15And once you see them, you cannot unsee

4:05:17them, which is why it's valuable to

4:05:18learn this because once you learn them,

4:05:20they will always be with you. But what I

4:05:22will discuss next is a little different.

4:05:24Rather than a generalpurpose software

4:05:26application, these are short and very

4:05:29punchy programs. They're immediately

4:05:31actionable techniques that you can use

4:05:32and abuse to chain together thought with

4:05:34action. This will round out your arsenal

4:05:36and make you not only a prolific

4:05:38thinker, but also prolific doer. And I

4:05:41use stuff like this all the time in my

4:05:42own life. In fact, taps, which I will

4:05:44cover first cuz I think they're very

4:05:45high ROI. Probably my number one most

4:05:47exploited tool that I've never talked

4:05:48about before this day.

4:05:50So if you've been paying attention, you

4:05:52guys will have a pretty good idea of how

4:05:53to solve a problem and make highle

4:05:55decisions, right? But there is still a

4:05:57common failure mode. Many of you will

4:05:59understand and agree with each of these

4:06:00techniques and then when it is time to

4:06:02apply them, you will not do anything.

4:06:04That is called accratia. Remember the

4:06:06whole idea about taps is solving accaia.

TAPs, or trigger action plans

4:06:10So tap stands for trigger action plan

4:06:12and they're a very simple way to bridge

4:06:14the gap between knowing something and

4:06:15doing. They take the form as follows.

4:06:19when X trigger or Q occurs, I will do Y

4:06:23action or behavior. This is like a line

4:06:26of code, you know, if code isn't

4:06:27deprecated because of AI. What it is is

4:06:29an if or then statement. You can also

4:06:31think of it as an SOP in business, like

4:06:33what to do when a client sends you an

4:06:35email. Or you can also think of it as a

4:06:36rule of life. The idea of taps are to

4:06:40eliminate the question that everybody

4:06:41asks themselves when they are faced with

4:06:43a decision. Should I do this thing? And

4:06:45this should question often acts as a

4:06:48blocker to real growth. Here are some

4:06:50examples of simple trigger action plans

4:06:52that I have made. If my phone

4:06:55illuminates while it is in my workspace

4:06:57or if it vibrates while it is in my

4:06:59workspace, I will get up and move it to

4:07:01another room. And it's very funny that I

4:07:04just said that because I had my phone

4:07:06with me because I just had to take a

4:07:08call. And because my phone did just

4:07:10illuminate or vibrate, I'm now going to

4:07:11go and move it into another room.

4:07:24That single decision that I just made

4:07:27has been programmed in my mind for the

4:07:28better part of the last year. And in me

4:07:31making that decision right now, the

4:07:33resulting maybe 10 or 20% of this course

4:07:36will likely be 10 or 20% better. It

4:07:39takes you only a few moments when you

4:07:40start hardwiring these rules like

4:07:42circuits or switches in your mind. The

4:07:45next rule I have is when I sit down at

4:07:47my desk, I will open the document I need

4:07:48to work on before doing anything else.

4:07:51In my case, I just came back to sit down

4:07:52at my desk. The document's already open,

4:07:54so I don't need to do anything. If I

4:07:56ever catch myself saying a word or

4:07:58phrase like, I'll figure this out later,

4:08:01I actually set a 5minute timer and then

4:08:03I write a list of actionable steps to

4:08:04get it done right then and there. This

4:08:06is a simple plan called a a resolution

4:08:08cycle which I will run you through

4:08:09later.

4:08:11Now while this if then statement idea

4:08:13sounds very trivial, it is actually one

4:08:16of the most strongly evidenced

4:08:17techniques in this entire course. In

4:08:20academic literature, this is referred to

4:08:22as an implementation intention. The term

4:08:24was coined by a man called Peter

4:08:26Goldwitzer who studies behavior and how

4:08:28to optimize it. Many other meta analyses

4:08:31have also shown that people that make

4:08:33these if then plans are always

4:08:35significantly more likely to achieve

4:08:36their goals than those who merely set

4:08:38vague goals. Specifically, a 2006 meta

4:08:42analysis showed an effect size around 65

4:08:45standard deviations, which to be clear

4:08:47is quite large for a simple 30-cond

4:08:50intervention.

4:08:51For those of you guys that don't know

4:08:53standard deviations, this is basically

4:08:55taking you from a 50th percentile to

4:08:58maybe the 75th percentile, which means

4:09:01just using taps or trigger action plans

4:09:03can legitimately help you leapfrog a

4:09:06quarter of the entire known world in

4:09:09your ability to do things. There are

4:09:11very few things in life that allow you

4:09:13to leaprog a quarter of the known world

4:09:16that you can figure out in less than

4:09:18five minutes. That is what you are doing

4:09:20right now.

4:09:21So um this is a quick visualization of

4:09:24this. 94 studies on implementation

4:09:26intentions, the fancy word for trigger

4:09:28action plan. Over almost 8,500 people,

4:09:31they saw a standard deviation

4:09:33improvement in their ability to achieve

4:09:34a goal by 65. There are there is

4:09:39opportunity and gold everywhere for

4:09:40those with eyes to see it. And this is a

4:09:42very simple example. This is something

4:09:44that I've been doing for a very long

4:09:46time. And I guarantee you immediately

4:09:48after starting to do it, I leap frog 25%

4:09:51of the entire population of planet earth

4:09:53without even knowing in terms of my

4:09:54economic effectiveness. When you do that

4:09:57with action and thought, uh it is only a

4:09:59matter of time before other areas of

4:10:00your life uh um um follow. So in my

4:10:02case, my income, in my case, my my life

4:10:05contentment and so on and so forth. So

4:10:07why does something that's this small

4:10:09actually work? Well, if you guys think

4:10:11back to the willpower section for a

4:10:12second, the people that have high

4:10:13self-control always set their lives up

4:10:16such that they do not win the fights in

4:10:18the moment. What they do is they move

4:10:21the fight or the decision out of that

4:10:23moment entirely and they either defer to

4:10:25their former selves like via Ulyses

4:10:28contracts or they remove the opportunity

4:10:30to make a mistake in the first place

4:10:32like I just did with my phone. A tap

4:10:34does something very similar on purpose.

4:10:37The idea is you will make the choice

4:10:38once now while smart, calm and relaxed

4:10:41and then you will hand the reinss to the

4:10:43if or then statement to work for you.

4:10:46Now at the end of the day deliberation

4:10:48is expensive and difficult. Every time

4:10:50you have to decide should I do this? It

4:10:53is equivalent to having to go to the

4:10:55gym, lie down on a bench press and rep

4:10:57out 225. If you have to do that before

4:11:00you do anything, why the hell? Like

4:11:02you're not going to want to do half of

4:11:03what you have to do, right? It's a very

4:11:04energetically involved task.

4:11:06>> [sighs and gasps]

4:11:06>> Well, taps just allow you to skip the

4:11:08bench press entirely. They allow you to

4:11:10skip most of the hard work. So, how do

4:11:13you actually make a trigger in the

4:11:14trigger action plan work? Because to me,

4:11:16that's by far the most important thing.

4:11:18As long as you can immediately and

4:11:21viscerally notice a trigger, you are

4:11:23usually more than half of the way to

4:11:25doing the task. To be successful, the

4:11:28literature on implementation intentions

4:11:30suggest that your trigger must have the

4:11:31three following attributes. Number one,

4:11:34it must be obvious. Number two, it must

4:11:36be visceral. And number three, it must

4:11:38be reliable. So obvious means you can't

4:11:41miss it. When I feel like I'm going to

4:11:43procrastinate is not an obvious trigger.

4:11:46And that would not work. And I've tried

4:11:47stuff like this. And I used to use uh

4:11:50triggers like this way back in the day

4:11:51and they did not do anything for me. The

4:11:53reason why is because your brain doesn't

4:11:55actually signal it in a way that you can

4:11:57detect. You don't even know when you're

4:11:59procrastinating 80% of the time. You

4:12:01just are.

4:12:03A much better way to do this is when I

4:12:06open a new tab in my browser because

4:12:09that is something that is immediately

4:12:10clear. It is very very obvious and there

4:12:13is a boolean yes or no. Yes, I opened it

4:12:17or no, I didn't open it.

4:12:19Visceral means that it is tied to a

4:12:22physical or sensory cue. So when you

4:12:24feel a phone in your hand or when you

4:12:26hear the door click or when you sit down

4:12:28in your chair or when you take your

4:12:30first sip of coffee, all this stuff is

4:12:31self-explanatory. Human beings recognize

4:12:34triggers very viscerally when they are

4:12:37physically stimulating us in some way.

4:12:39And so when I open a new tab, for

4:12:40instance, I open it by holding the

4:12:42command key and pressing T. This is both

4:12:44like satisfying from a haptic

4:12:45perspective, but it is also immediately

4:12:47stimulating to me visually because I see

4:12:49it open up on my window. And so both of

4:12:51these things sort of hit my mind

4:12:52simultaneously and now I have a trigger

4:12:54that I can reliably depend on. Speaking

4:12:57of reliably depending on things,

4:12:59reliable means that it triggers every

4:13:00time that you find yourself in the

4:13:02target situation. And ideally it never

4:13:04triggers when you are not in the target

4:13:06situation. I'll give you an example of a

4:13:08very bad trigger. 3 p.m. That is not

4:13:11reliable because human beings like we

4:13:14don't have the ability to uh tell when

4:13:16we're procrastinating also do not have

4:13:17the ability to tell what the time is

4:13:19internally. Some days if you set your

4:13:22trigger to be 3 p.m. 3 p.m. will pass

4:13:24you and you won't miss it. It is just

4:13:25part of being human. [gasps and sighs]

4:13:27But instead of tying a trigger action

4:13:29plan to 3 p.m., why not tie it to

4:13:31something like an alarm that sets in

4:13:34advance? That way you are far more

4:13:36likely to trigger on set alarm. My

4:13:38recommendation is use alarms. They are

4:13:40awesome. Alternatively, tie taps to

4:13:43actions that you do and you have to do

4:13:45every single day. Think things like

4:13:46waking up, going to bed. A lot of people

4:13:49here are hopelessly addicted to

4:13:50caffeine, myself included. Why not tie

4:13:52something to something that you know you

4:13:53will do every single day? A lot of

4:13:55people here are hopelessly addicted to

4:13:57other things like turning the television

4:13:59on for instance, or watching your

4:14:01favorite show or whatever. You can

4:14:02actually use these anchors, these things

4:14:04that are going to occur as immediate

4:14:07triggers to begin some action or some

4:14:09sequence of actions that improve your

4:14:10life. [gasps]

4:14:12Finally, the action must be small and

4:14:14physical. Do not do hard things like

4:14:16spend 2 hours writing. That is not how

4:14:18you do a tap. Instead, do something

4:14:20small, concrete, and ultimately an

4:14:23action that gets you started. And then

4:14:25what you do is you just trust that the

4:14:26inertia of this small action will guide

4:14:27you through the rest of what you need to

4:14:29do.

4:14:30For instance, open a Google doc and

4:14:32write one sentence is an excellent

4:14:33action. If [snorts] the trigger to that

4:14:36is every time I sit back down at my

4:14:37desk, I open a Google doc and write one

4:14:40sentence, that is a fantastic trigger

4:14:42action plan. The probability of you

4:14:44actually completing this is quite high,

4:14:46assuming you do the steps that I will

4:14:47talk about in a moment. And the value

4:14:50there is it's very hard to have just one

4:14:51sentence worth of an idea. Usually,

4:14:54after a human being has written one,

4:14:55their brain just starts filling in the

4:14:56blanks and continuing. So you'll

4:14:58naturally want to chain that together

4:14:59into something else and so on and so

4:15:01forth. The whole point of a tap is to

4:15:04get you moving and to solve a CRA which

4:15:07is your biggest problem by far.

4:15:10[gasps] Now how do you actually install

4:15:12one and maximize the probability that

4:15:13this tab works? Well, to start it's not

4:15:16sufficient to simply brainstorm and

4:15:17write down a bunch of taps. You have to

4:15:19rehearse the tap over and over and over

4:15:21again before you can eventually start

4:15:22doing it on an automatic level. Once

4:15:25it's on the automatic basis, then you

4:15:27will do it yourself and it will

4:15:28self-reinforce. But that initial on-ramp

4:15:31to the beginning of the positive

4:15:32flywheel, that is difficult. Luckily,

4:15:34there's a very powerful method for doing

4:15:36this. After coming up with your tap, I

4:15:38want you to close your eyes and vividly

4:15:40imagine the trigger. So, in my case of

4:15:43sitting down and then opening up a

4:15:44Google doc, I want you to visibly

4:15:46imagine and viscerally imagine sitting

4:15:49down in your chair. So right now I'm

4:15:51actually imagining the process of me

4:15:53sitting down in my chair. [gasps] What

4:15:55does the trigger look like? What does me

4:15:57sitting down in my chair look like?

4:15:59Well, when I sit down in my chair, what

4:16:01do I see? I see this. So I see my my

4:16:02laptop, my computer monitor, my laptop,

4:16:04and then I see, you know, a camera, and

4:16:06then I typically have a microphone. I

4:16:07see my desk. I see the sun on my left

4:16:10side, you know, I see a big white wall

4:16:11on my right side. What does it feel

4:16:14like? Well, my chair is really

4:16:16uncomfortable, by the way, so I'm going

4:16:17to have to replace it with a steel case

4:16:18sleep in a moment. Um, just need to

4:16:20unbox it. I have little armrests where I

4:16:22typically put my arms. Um, what does it

4:16:24feel like? Hm. It's kind of cold in the

4:16:26room right now, which is good, which I

4:16:28like. Okay. What does it smell like?

4:16:31Luckily for me, it doesn't smell like

4:16:32anything. Then after you've really just

4:16:35tried to visualize and rehearse you

4:16:38feeling the trigger,

4:16:40imagine yourself performing the actual

4:16:42action itself. So in my case, opening up

4:16:44a Google doc, sitting down and then

4:16:47holding command T and typing docs new. I

4:16:51will do that 10 times in a row. This

4:16:54whole process here, believe it or not,

4:16:56takes less than 2 minutes. And it might

4:16:58seem silly, but what you're doing is

4:16:59you're training your brain's Q detection

4:17:01system. You're taking these cues and

4:17:03your intention from working memory, and

4:17:04then you're actually encoding it into

4:17:06long-term memory. Another thing you can

4:17:08do is you can actually practice this

4:17:09multiple times. So for instance, when I

4:17:11was practicing this sit down and then

4:17:13open a Google doc thing, um what I would

4:17:15have done is I would have actually

4:17:16closed my door, went outside, opened it,

4:17:19came down, sit down and then open a

4:17:20Google doc and write a sentence. Then I

4:17:22would have repeated four or five times.

4:17:24I would have done this over and over and

4:17:25over again until the next time that I

4:17:26sit down, some little part of my brain

4:17:28would have been activated. You know,

4:17:29like a monkey, my neurons would have

4:17:31gotten activated and I would have gone,

4:17:32"Oh, right. Wasn't I supposed to do

4:17:33something?" The second that you can get

4:17:35yourself to that point, everything else

4:17:37is done for you. you are an automatic

4:17:39machine capable of doing whatever the

4:17:40hell it is that you want.

4:17:43Another way to do this is putting the

4:17:44trigger directly in your path, which is

4:17:46the friction rule. Now, if your tap is

4:17:49when I see my running shoes at the door,

4:17:50I will put them on. Just make sure your

4:17:52shoes are actually at the door. The more

4:17:54tangible the trigger and the more in

4:17:56your control, the better. In the case of

4:17:58our sitting down on a Google doc, for

4:17:59instance, in order for me to do anything

4:18:01with my computer, I need to sit down at

4:18:02this chair, which is why this chair is

4:18:04such an extremely powerful trigger for

4:18:06anything that I want to do. Same thing

4:18:08with, you know, opening my computer or

4:18:10turning on OBS or whatever it is that

4:18:12your particular trigger is.

4:18:15Now, every now and then once you've

4:18:17installed it, just ask yourself, did I

4:18:18actually trigger that tap? If not, the

4:18:20problem is not you because we are not

4:18:22the problem here. It is the trigger that

4:18:24you chose. It's not a willpower thing.

4:18:26It's not like, "Oh next time I'll

4:18:28do it because I'll remember." No, no,

4:18:29no. It's not that at all. It is the

4:18:31trigger. You, your willpower has nothing

4:18:32to do with this. At that point, you can

4:18:34choose something more noticeable and

4:18:36then rehearse it again. Okay? So, this

4:18:38is the flow. Pick a trigger, write a

4:18:40sentence, rehearse it 10 times, put the

4:18:42trigger in your path, and just check and

4:18:44go over and over and over and over

4:18:45again. The debug loop here is at the

4:18:48trigger stage, nothing else.

4:18:50So, most of my taps, to be clear, are at

4:18:53the first hour of my day, and they're

4:18:54also very boring, but they're also

4:18:55extremely effective. What I do is I will

4:18:57chain my taps together such that the

4:18:59action of one of my taps is the cue or

4:19:01trigger of another. This is sort of

4:19:02advanced tapping, but hear me out. I'm

4:19:05going to give you guys some pretty

4:19:06grizzly detail here. Um, after I wake

4:19:08up, which is my Q, I will immediately

4:19:09walk over to my coffee machine and then

4:19:11it will brew. That is my action. After I

4:19:14click brew Q, I then use bathroom and

4:19:16then I wash my face, which is an action.

4:19:20After I wash my face, Q, I will grab my

4:19:23coffee from the kitchen and I will put a

4:19:25bit of protein milk in it, which is my

4:19:26action. After I put a bit of protein

4:19:28milk in it, which is my Q, I will go to

4:19:30desk and I will open my laptop, which is

4:19:31my action. After I open my laptop, which

4:19:34is my Q, I will click a bookmark that

4:19:36opens my school tabs, which is my

4:19:37action.

4:19:39Right, that's right over here. After I

4:19:42open my school tabs, which is a Q, I

4:19:43will read the first question and then

4:19:45voice record my first answer, which is

4:19:46my action. From waking up to voice

4:19:49recording my first answer, this process

4:19:51takes me maybe 1 minute and 30 seconds.

4:19:53But by the end of that 1 minute 30

4:19:54seconds, all of the brain circuitry that

4:19:56was typically involved in, you know,

4:19:58doing, in my case, school management,

4:20:00ours is ready to go. It's like uh it's

4:20:02like I'm a world class athlete or

4:20:04something like a swimmer, like Michael

4:20:05Phelps listening to his favorite track

4:20:06and doing his favorite stretches right

4:20:08before he goes on. It is the exact same

4:20:10thing every day. And what he has done

4:20:11and what all professional athletes and

4:20:13high performers in any field have done

4:20:14is they have just standardized their

4:20:16inputs. So do you guys see how easy it

4:20:18is? Eventually all this becomes

4:20:20completely automatic and then I have

4:20:21repeated taps until maybe 2.5 hours into

4:20:23my day after which I am usually done

4:20:26most the economically valuable chunks of

4:20:27my work. The key here again is to use

4:20:29the clarity of thinking you get when you

4:20:31are in a pristine condition aka

4:20:32motivated and ambitious aka right now to

4:20:35ensure that even when you are not in a

4:20:36pristine condition you are still moving

4:20:38the needle of your life. An action

4:20:41question here. Take a technique from

4:20:42this course that you most want to use.

4:20:44Write it as a tap which is a Q and then

4:20:47an action. Then rehearse it 10 times

4:20:50right now using the visualization

4:20:51practice that I gave you guys earlier.

Noticing

4:20:54>> [sighs and gasps]

4:20:54>> Now I want to talk a little bit about

4:20:56noticing.

4:20:58What I'm about to tell you can be

4:20:59thought of as a background function.

4:21:01Once you install this background

4:21:03function, it will immediately approve

4:21:05improve your growth rate across your

4:21:07entire life. The way I like to think

4:21:09about this is as a savings account and

4:21:12taking funds from the savings account

4:21:14and moving it into say an investing

4:21:16account which typically delivers higher

4:21:17returns.

4:21:18>> [sighs and gasps]

4:21:19>> If you don't have this software platform

4:21:21or program installed in your brain, you

4:21:23will grow at 0%. But the second that you

4:21:25install this concept in your brain, and

4:21:27this concept has many forms, so some of

4:21:28you will already have this in your mind.

4:21:30But the second that you install this

4:21:32concept in your brain, it's akin to

4:21:33making, you know, 7 to 10% on an

4:21:35investment year-over-year. You will

4:21:37become clearer and more effective simply

4:21:41by virtue of time passing.

4:21:44So simply by virtue of having learned

4:21:46about this idea noticing, you will

4:21:48naturally and organically be growing.

4:21:50And it is not hyperbole. It's not woowoo

4:21:51spirituality stuff. It is like 100%

4:21:53concrete and based in science. So what

4:21:56does noticing refer to? Put simply,

4:22:00noticing really stands for noticing that

4:22:03you're confused.

4:22:06In real life, confusion typically lasts

4:22:08just a few seconds before your

4:22:10subconscious mind will start squashing

4:22:11it away out of fear. So noticing that

4:22:14you're confused is the ability to

4:22:16recognize in your mind that something is

4:22:19wrong and then actively label that thing

4:22:21that's wrong by saying or explicitly

4:22:24verbalizing I notice I am confused

4:22:26before that feeling disappears and

4:22:28before you immediately shove it away to

4:22:30a blind spot of yours never to be looked

4:22:31at again. This helps make your map line

4:22:35up with your territory which improves

4:22:37your internal model of the world. And if

4:22:39you do this several times per day,

4:22:41because we typically confuse several

4:22:42times per day, you can think of every

4:22:44single time of it occurring as a 1%

4:22:46improvement to your map. Eventually,

4:22:49your map gets closer and closer and

4:22:50closer to the territory that it

4:22:52represents and you become a lot more

4:22:53effective as a result. So, let's say

4:22:56hypothetically that you're listening to

4:22:57an audio book and something does not add

4:23:00up. Maybe you weren't paying attention.

4:23:02The wording all of a sudden seems off or

4:23:04there's a big gap and you don't remember

4:23:06how you got there because you were

4:23:07looking at a bird. Well, you can use

4:23:09noticing to fix this. And there's a

4:23:11great essay all about noticing that I'll

4:23:13link you guys here just in case. But I'm

4:23:14going to give you a short hand. [gasps]

4:23:17When you have the sensation of noticing

4:23:18that you're confused, it means that your

4:23:20internal model of reality is off. Rather

4:23:22than hiding away from it, you can just

4:23:24verbalize it to yourself. I noticed I'm

4:23:26confused. Why? Then because you are now

4:23:29forced to verbalize your hypothesis, you

4:23:31also put actionable steps in place to

4:23:32prevent or minimize it from happening

4:23:34again. I know that this sounds stupid,

4:23:36and I know it sounds extremely extremely

4:23:38simple, but you'd be surprised at the

4:23:41small fraction of the confusion events

4:23:42that occur in a 24-hour period that you

4:23:44are actively addressing. You probably

4:23:47attend to less than 5% of all of the

4:23:49events throughout your day in which you

4:23:51are confused. you are most almost

4:23:53certainly just allowing these events to

4:23:55occur and then moving on and not even

4:23:56questioning why you feel confused.

4:23:58Instead, you just feel confused. This is

4:24:00a dumb move because being confused is

4:24:03about as clear an opportunity to rectify

4:24:04your map and make it as close to the

4:24:06territory as you will ever get.

4:24:08Another example, let's say you're

4:24:10talking to a client for whatever service

4:24:12and they tell you that your campaign is

4:24:13going great, but then the dashboard on

4:24:15your screen says something different. In

4:24:17this case, one of you guys must be

4:24:19wrong, right? So rather than just having

4:24:22that idea, hm, something's wrong here.

4:24:24I'll mention it later. Just notice it.

4:24:27I'm confused. Your data does not line up

4:24:30with my experience, which is that the

4:24:31campaign is not going very well. Could

4:24:33we chat for a second about why that

4:24:34might be? A simple statement like that

4:24:38doesn't just help yourself out, but it

4:24:40helps multiple people plus an entire

4:24:41organization out. And how you and your

4:24:43client can grow together. And I don't

4:24:46mean this in like again a feel-good

4:24:47sense. I mean people will both respect

4:24:50you more for pointing out that you are

4:24:51confused and it is also far more

4:24:53effective and efficient because now you

4:24:55and the person you are talking with are

4:24:56both operating on a shared model of

4:24:58reality. You are not just hiding away

4:25:00your confusion because you want to seem

4:25:01smart. It is the people that are open to

4:25:04seeming dumb that are typically the

4:25:05smartest ones amongst us. So do not shy

4:25:08away from confusion. That window is

4:25:10where so much value in real life lies.

4:25:13Another example of a similar concept is

4:25:15the flinch. The flinch is when you see

4:25:18something that you need to do or you're

4:25:19maybe you're about to go look at a

4:25:20number or you see an email in your inbox

4:25:22and all that just makes you go, "Oh

4:25:23god." Maybe this is a text from your ex.

4:25:27Maybe it is a letter from your boss or

4:25:28your client or maybe it is an email from

4:25:30a supplier. Whatever the case is, when

4:25:32you go ah aka when you flinch away, your

4:25:35inherent desire is to look anywhere but

4:25:38there and think about something else.

4:25:39Right? The issue is every time that a

4:25:42thought hurts your head, right? every

4:25:43time you go h and then you don't act on

4:25:45it. You are training your brain to avoid

4:25:48that. And it's not just an opinion. It

4:25:50is actual neuroscience. Neurons that

4:25:53correspond to actions that you take

4:25:54regularly get stronger and more defined.

4:25:56The ones that correspond to actions that

4:25:58you avoid always grow weaker and shrink.

4:26:01So when you avoid the thing, you are

4:26:03literally training the circuitry of your

4:26:05brain that goes, you should avoid stuff

4:26:07that is painful. The issue with that is

4:26:09most of the good things in life occur

4:26:11behind doors that are painful. Now,

4:26:14interestingly, I also find this happens

4:26:16with careers. How many people, myself

4:26:18included, spend half a decade or more

4:26:19preparing for their dream career only to

4:26:21maybe get the job or think about the job

4:26:23and then they go gh every morning when

4:26:25they wake up? Well, this is a news

4:26:28flash, but you don't have to live that

4:26:29way. Rather than flinch away from

4:26:31something and then immediately try and

4:26:32bury the emotion, try sitting with it

4:26:34for at least 10 seconds. like actually

4:26:36sit down and consider why do I feel that

4:26:38way? Is it the job itself? Is it a

4:26:41person at my workplace? Is it the

4:26:42process of commuting to my workplace?

4:26:44What is it about this thing that makes

4:26:46me go uh if you go uh 10 times a day and

4:26:49then every single time that occurs, you

4:26:51ask yourself, let me clarify exactly why

4:26:53I feel bad quite simply and quite

4:26:55quickly, you will soon never uh again

4:26:58because you will have solved all of

4:26:59those problems. Every time you uh or

4:27:01flinch away is legitimately a massive

4:27:03opportunity that has just appeared on

4:27:05your plate to unfuck some character of

4:27:07your being, some part of who you are. So

4:27:10your mind and body are very very

4:27:12valuable and sensitive instruments.

4:27:13[gasps] And I found as I grow older, you

4:27:16can often think far more clearly just by

4:27:18listening to them. Don't avoid their

4:27:20signals. You should sit with them for a

4:27:21moment and actually listen.

4:27:24The last thing I want to talk about is

4:27:25the should. So how many times have you

4:27:27said some variant of this today? I

4:27:29should really post more. Oh man, I

4:27:30should really read that book. I've been

4:27:31putting it off. Or, man, I really got to

4:27:33call that person back. How many shoulds

4:27:35have you tried guilt tripping yourself

4:27:36with in the last 24 hours? [gasps] Have

4:27:39you ever actually stopped for a second?

4:27:40Have you ever considered why you should

4:27:43do these things?

4:27:45I mean, you are a donut-shaped sack of

4:27:48meat around a hole that metabolizes and

4:27:50poops out food. Why should you, a meat

4:27:53sack on a random rock somewhere floating

4:27:55through the universe, call somebody

4:27:57else? Why should you put up a microphone

4:28:00device to a listening hole, slam your

4:28:02fingers around, and then reverberate the

4:28:04talking hole for 30 minutes to

4:28:06communicate with another meatsack? Is it

4:28:08written anywhere that meatsack A needs

4:28:10to communicate with meatsack B? No,

4:28:12obviously not. So, where is all of this

4:28:14stuff coming from if you ask yourself?

4:28:16Well, here's another news flash. Most of

4:28:18your beliefs around what you should be

4:28:20doing come from somewhere else. They

4:28:21come from outside of your body and your

4:28:23mind. So to be clear, you can and should

4:28:26do whatever the hell you want to do. My

4:28:28issue is most people just never actively

4:28:30examine what it is that they want to do

4:28:32and they never actually think for

4:28:33themselves. We would rather mllify or

4:28:35plate ourselves with the notions of oh I

4:28:37should do this because Xerson said so. I

4:28:39should do that because my family used to

4:28:40do this. I should do blah blah blah

4:28:42blah. We m we mllify ourselves from

4:28:45shoulds borrowed from friends, spouses,

4:28:48social media, institutions and so on and

4:28:50so forth. And all of this at the end of

4:28:52the day means that most of us spend our

4:28:54lives not for ourselves but for others.

4:28:56And I don't mean that in a noble sort of

4:28:58honorable sense. I mean literally just a

4:29:00I've never really considered any other

4:29:01way of living sense. That sucks, right?

4:29:05I want to live for other people, but I

4:29:06want that to be my choice. I don't want

4:29:08to live in a structure that somebody

4:29:10else creates for me unless I have

4:29:12consciously sat down and said, you know

4:29:13what, I respect the values of the

4:29:15structure and I like the structure and I

4:29:18want to abide by it.

4:29:20The good news is you can actually solve

4:29:21this in just a few seconds. The next

4:29:24time you find yourself saying, "Man, I

4:29:25should really do X thing." Just ask

4:29:27yourself, why should I do X? Do I

4:29:30actually want X? Man, I should really

4:29:32call my friend. Ask yourself, why should

4:29:35you call your friend? Do you really want

4:29:36to call your friend? In many cases, you

4:29:39will want to call your friend, which is

4:29:40awesome. But in some cases, to be

4:29:42honest, you will not want to call your

4:29:43friend. In some cases, you will say,

4:29:45"Why am I calling my friend? You know,

4:29:47we don't really get along super well

4:29:48anymore. I don't feel really good after

4:29:50I call them. I always feel guilty for

4:29:52not calling them. They're kind of an

4:29:53Maybe I just shouldn't call

4:29:55them to begin with. Huh? If that is you,

4:29:58great. Because now you don't have to sh

4:30:00yourself the next time your friends

4:30:01like, "Dude, you really got to call me."

4:30:03Alternatively, if you do want to call

4:30:05them, if you go, "Man, I should call

4:30:07them." Yeah. And the reason why I should

4:30:08is cuz I like them. They add value to my

4:30:10life. They genuinely improve my state of

4:30:12mind and my being, and I want to help

4:30:14them just like they've helped me. Well,

4:30:16then great. Now, all you need to do is

4:30:18ask yourself, what is the next physical

4:30:19step to actually take that should and

4:30:22actualize it in the real world? Do I set

4:30:24a calendar reminder? Maybe do I let them

4:30:26know, hey, you know, are you game to

4:30:27talk on a weekly basis cuz uh I keep on

4:30:29running out of time because I don't have

4:30:30this written in a calendar somewhere and

4:30:32I keep on juggling a lot of stuff. Are

4:30:33you game to just chat every Thursday at

4:30:344 p.m.? If that's the case, great.

4:30:36You'll probably do it more often. At the

4:30:38end of the day, you don't actually have

4:30:40to do anything, but at least working out

4:30:43why you feel the way that you do and

4:30:45what the next logical step is means that

4:30:48you are now thinking productively and

4:30:49proactively and clearly as opposed to

4:30:51just flinching and constantly feeling

4:30:52confused.

4:30:54So, at the end of the day, these are

4:30:55three signals, and for each of these

4:30:57signals, there are three 5-second moves.

4:30:59The good news is you can actually turn

4:31:01all of these into taps. You know,

4:31:03flinching, for instance, that is a clear

4:31:05concept. should is a clear cue.

4:31:08Confusion. I notice I am confused. That

4:31:10is a clear model. And so when you're

4:31:13confused, that means your model aka your

4:31:15map is wrong. All you should do is

4:31:18check. Why is it wrong? Is it really

4:31:20wrong? Why do I feel this way? If you

4:31:22flinch away from something, that's like

4:31:24an uh field. It's a field of uh that you

4:31:26just don't even want to like look at or

4:31:27address. What you should do is just look

4:31:29at it. Look at it for just 10 seconds.

4:31:31Just like stare at the thing that you're

4:31:32avoiding. If it's that email or text

4:31:34message, just stare at it. Look at it,

4:31:36understand it. If you are going to do

4:31:39something about it, you can do it after

4:31:40you do that. Finally, with shoulds,

4:31:43whose goal are you actually living? If

4:31:45you actually want it, then you should

4:31:47take actions, and this is going to help

4:31:48you do so. So, how do you actually train

4:31:51this? When you catch yourself noticing

4:31:52one of these thinking traps, I would

4:31:53recommend verbalizing which one it is

4:31:55immediately. So, for instance, I will

4:31:57often think to myself, I'm confused, or

4:31:59I just flinched, or I just said should,

4:32:02etc. Then I would connect it to a tap.

4:32:04Like when I notice I'm confused, I must

4:32:06state that I notice I'm confused out

4:32:07loud and then ask why. So for instance,

4:32:09if I'm confused, right? If I don't know,

4:32:11I mean, I'm looking right now at my

4:32:12camera for instance, and there's some

4:32:14sensor there that I think means

4:32:15temperature, but I don't really know. So

4:32:17I notice I'm confused. Why? Because

4:32:19there's a sensor readout and it says

4:32:21temperature. And I'm not really sure if

4:32:22that means that the camera is about to

4:32:23go dark cuz it's too hot in that corner

4:32:25or something else. Something is odd

4:32:27here. The very act that I just said that

4:32:29means later on I'm going to address it

4:32:31and fix it. It's extraordinarily easy

4:32:33for you to do as long as you notice and

4:32:35then uh label and then have a tap of

4:32:37some kind. You can usually eliminate

4:32:38most problems in your life within a few

4:32:40weeks. And you don't even have to worry

4:32:42about taking action on the noticing just

4:32:43yet. Anyway, the real value is literally

4:32:46just being aware that all of this is

4:32:47occurring. When you start being aware of

4:32:49all this stuff, your brain naturally

4:32:50starts trying to improve it. So, as

4:32:53mentioned, this is the passive investing

4:32:54strategy of clear thinking. This is a

4:32:56quick example of how much better things

4:32:58get. You know, if every time you feel uh

4:33:01you avoid it, your discomfort on the

4:33:03left hand side, every future time you

4:33:05think about the thing will just

4:33:06skyrocket exponentially. But if every

4:33:08time you go uh when you get a piece of

4:33:10stimulus that you don't like, you

4:33:11actually look at it and sit with it,

4:33:13well, the discomfort will then go down

4:33:14and basically ground down to zero. Okay,

4:33:17so two action questions before we move

4:33:19on. First is, can you think of off the

4:33:21top of your head something that has made

4:33:22you confused or flinch recently? Next,

4:33:25what are three things that you commonly

4:33:26tell yourself you should be doing and

4:33:28why?

Pre-mortems

4:33:30I want to talk a little bit about

4:33:31premortems. Premortems are a simple and

4:33:34very effective way to improve your

4:33:35ability to plan projects. Now, I use

4:33:37them all the time and they're a very

4:33:38vital part of my personal life in

4:33:40relationships, my business life, aka my

4:33:42deals and brand strategies, and even my

4:33:43fitness, like my workout plans.

4:33:46If you guys have ever been part of a

4:33:47committee or an organization or

4:33:49corporation, usually the way that

4:33:51project management occurs is somebody

4:33:53will deliver a plan and then what you'll

4:33:54do is you'll look at the plan and then

4:33:56stress test it usually by roundtabling

4:33:58answers via some sort of brainstorm way.

4:34:00You guys will ask yourselves what might

4:34:02screw up with our plan. After that,

4:34:04you'll spend a couple of hours on calls

4:34:06brainstorming additional ideas and then

4:34:08at the end of it you'll usually get

4:34:09three to five vague risks out of the

4:34:11process. after the project when it

4:34:13inevitably fails, it will not have

4:34:15failed, you know, for one of those

4:34:16risks. It will almost always have failed

4:34:18for some other reason that no one

4:34:19predicted simply because there are many

4:34:21more ways for something to go wrong than

4:34:22there are ways for something to go

4:34:23right. Like we've talked about,

4:34:26postmortems are fairly standard project

4:34:28management techniques. In corporate,

4:34:30what you'll do is you will round up all

4:34:32the people involved in a project that

4:34:33did not succeed and then you will say,

4:34:35"So, what went wrong here? What can we

4:34:37learn from this in order to make next

4:34:38try better?" The idea here is to figure

4:34:40out the failure mode so you can apply

4:34:41that to future projects and then improve

4:34:43your total success rate. Now, obviously

4:34:45this is a good idea and postmortems are

4:34:47awesome and I'd recommend them, but

4:34:49there's an even better strategy you can

4:34:50employ called the premortem. So, what is

4:34:53a premortem? Very simple trick. Just

4:34:55change the tense. Instead of post, it's

4:34:57pre. Instead of asking why did something

4:35:00fail, you ask what did fail if I were to

4:35:06have done this and it failed.

4:35:08So for instance, let's say you have an

4:35:10idea to start a project and the

4:35:12project's going to take you a week.

4:35:13Rather than asking, "So what could go

4:35:16wrong here?" or rather than waiting

4:35:17until the project fails and then asking,

4:35:19"So what went wrong here?" you could

4:35:20just say, "So let's pretend it's one

4:35:22week from today and the project failed.

4:35:24Why did it fail?"

4:35:26This is an extremely clear empirically

4:35:30proven way of increasing the quality of

4:35:33predictions that people make in a

4:35:34project and the probability that they

4:35:36are correct with their predictions as

4:35:37well. Why? There are many explanations

4:35:40for why. The first is when you ask the

4:35:42question what might fail it's a very

4:35:44abstract question and your [snorts]

4:35:46brain treats it like an abstract

4:35:47question and produces a very abstract

4:35:48answer. The reality is that human beings

4:35:50do not dwell in the abstract world. We

4:35:53don't dwell on hypotheticals or

4:35:54conditional probabilities. That's why we

4:35:56have to learn what Baze theorem is. We

4:35:58have to learn about expected value and

4:36:00we sort of have to add that onto our

4:36:01biology. The place that human beings

4:36:03dwell is in stories. It's in narratives

4:36:06and it's in explanations. So when you

4:36:08ask why did the project fail instead of

4:36:11why might the project fail, your brain

4:36:13will start treating it like a story and

4:36:14it'll actually start filling in the

4:36:15details. It'll create characters, events

4:36:18like what happened on Tuesday, specific

4:36:20failure cases like you know somebody

4:36:21forgot to send an email etc. What you do

4:36:24is you do this so you everybody asks how

4:36:26how and why did the project fail? It did

4:36:29fail a week from now so why why did it

4:36:31fail? And then you just list all of the

4:36:33reasons why people think that the

4:36:34project failed from yourself included

4:36:37and then you bin them into the actual

4:36:39failure case. Like if a bunch of stories

4:36:40have to do with people not sending

4:36:42emails when they should have now you

4:36:43know that that is actually probably a

4:36:44likely failure mode. The end result is

4:36:46you end up with a much richer tapestry

4:36:48of all possible failures alongside clear

4:36:50solutions that ultimately improve

4:36:51project outcomes. Okay, so this is

4:36:54called the premortem loop. You write the

4:36:55plan. You pretend it's a week later and

4:36:57it failed. Then you write the story in

4:36:59the past tense. Everybody brings their

4:37:00stories together and you just fix all

4:37:02the causes. You do this over and over

4:37:04and over and over again until your

4:37:05project is airtight.

4:37:07So let me give you an example. I want to

4:37:09record and publish a video every single

4:37:10day for 40 days. I would do a premortem

4:37:14message from the perspective of someone

4:37:1640 days in the future saying, "Hey, it's

4:37:1840 days in the future and I'm looking

4:37:20back on my goal and I only published 11

4:37:22out of the 40 videos I wanted to." Why?

4:37:25Well, if this were the case, I would

4:37:27reflect on that and then I would say

4:37:28something like, "Uh, I think the issue

4:37:30was I got caught up in client projects

4:37:31about a week in and then I broke the

4:37:33chain of my daily uploads, which is

4:37:35historically always the most important

4:37:36thing. also made it really hard to keep

4:37:38up after that. Probably because I tried

4:37:39being a perfectionist about it and

4:37:41aiming for higher quality than I

4:37:42probably needed. Then instead of once

4:37:43per day, I fizzled out and produced

4:37:45maybe one or two a week. Now, because I

4:37:47put myself in future Nick's shoes, the

4:37:49failure modes are far more tangible and

4:37:51far clear, and I can now put systems in

4:37:53place to avoid all of these from

4:37:54occurring in the first place. In this

4:37:56situation, for instance, it sounds like

4:37:58client projects were my main problem,

4:38:00and breaking the chain was another main

4:38:01problem. So, I would make sure my

4:38:03recording time was the very first thing

4:38:04I do every morning, meaning my client

4:38:06projects can't push me off the habit.

4:38:07And then I would use something like a

4:38:08Ulyses contract to publicly state to my

4:38:10audience that I want to do this or have

4:38:12somebody else hold me accountable, let's

4:38:14say, by donating to my competitor or

4:38:15something of that nature.

4:38:17Two more things. First, the premortem is

4:38:20the single best use of AI that I know of

4:38:21in planning. Because models can generate

4:38:24hundreds of thousands of narratives in

4:38:25just a few moments, you can use AI to

4:38:28generate a lot of these and then read

4:38:29the narratives and failure cases and

4:38:30then go, "Yeah, I could have screwed

4:38:32that up big time." You will be able to

4:38:34label these instinctively and then it's

4:38:35super quick to do so. The next is the

4:38:38premortem is very cheap. Even if you

4:38:40don't use AI and you just use your old

4:38:41meat brain, it is like 15 minutes on one

4:38:43page. The thing that it replaces, which

4:38:45is actual failure, will often take you

4:38:47weeks or months. So spending 15 minutes

4:38:49to reduce the probability of a failure

4:38:51by like 3x is very high leverage. And

4:38:53also if it doesn't do anything, very

4:38:55little skin off your back. It's been 15

4:38:56minutes. Okay, action questions. First,

4:39:00pick the plan that you're most excited

4:39:01about right now. Pretend that it is 1

4:39:03month later and it failed. Write the

4:39:06story in five past tense sentences. Name

4:39:08the week that you failed, the mechanism

4:39:10behind why, and so on. Next, what's the

4:39:12cheapest one fix for the most likely

4:39:14cause in the story? and can you do it

Resolve cycles and five-minute timers

4:39:16before the plan starts rather than

4:39:18after? Let's talk resolve cycles next.

4:39:20The following few paragraphs are from an

4:39:22old post of mine that I wrote back in

4:39:242019.

4:39:25Few things destroy a good idea as

4:39:27effectively as the phrase, "I'll get

4:39:28back to it." To solve this, set a

4:39:305-minute timer and actually try to solve

4:39:32the problem before it runs out. I mean,

4:39:34don't just plan how you're going to

4:39:35solve it or sketch out a possible

4:39:37approach. Actually attempt to solve the

4:39:39problem in 5 minutes. The next time you

4:39:41have a problem that seems too hard, time

4:39:43yourself. How long have you actually

4:39:44spent thinking about it? I guarantee you

4:39:46haven't even given it a full 30 seconds

4:39:47for giving up and saying this is too

4:39:49hard for me or I'll deal with this

4:39:51later. If you spend five minutes on it,

4:39:53that is 10 times the work. Which means

4:39:55it's no wonder that you get a different

4:39:56result. In practice, you would not

4:39:59believe how many actions the average

4:40:00person procrastinates on for days,

4:40:02weeks, or even years sometimes that are

4:40:04legit legitimately doable in 5 minutes

4:40:06or less. So, I'll give you an example

4:40:08for my own life. Right now, I'm trying

4:40:09to get my Bulgarian passport. I'm a

4:40:11technically a Bulgarian citizen uh cuz

4:40:12my family members were born in the

4:40:14country and I know Bulgarian and I go

4:40:15back there reasonably often and I just

4:40:17want to get a passport to prove it.

4:40:18It'll also help me expedite EU travel.

4:40:20However, proving Bulgarian citizenship

4:40:23takes a fair amount of time and

4:40:24paperwork. And a lot of this includes

4:40:25quite frankly annoying steps like I have

4:40:27to go to my local BC guys here and

4:40:28notoriize stuff. I have to steal my

4:40:30documents and so on and so forth. One

4:40:32step that until recently held up my

4:40:34citizenship proof process by 45 days,

4:40:36which is a month and a half, was simply

4:40:38calling a notary down my street. You

4:40:40know, I could have found their number in

4:40:41a minute. I could have figured it out

4:40:42what I wanted to say in maybe another 2

4:40:44minutes. And the actual call itself

4:40:45would have taken me maybe a minute or

4:40:46two as well. So 5 minutes in total. But

4:40:48it still took me over 45 freaking days

4:40:50to do the thing. So why did I avoid it?

4:40:53I mean, all of this ties back to the

4:40:55concept of aia that I talked about

4:40:57earlier. The problem is never knowing

4:40:59what to do really. It is merely starting

4:41:01to do the thing. And usually that

4:41:03involves a hurdle at the first step. In

4:41:05my case, getting the phone number of the

4:41:07notary, which is honestly a trivally

4:41:08easy thing to do. Well, resolution or

4:41:11resolve cycles or five-minute timers

4:41:13solves the problem. And it is the

4:41:15simplest thing on earth. You literally

4:41:16just set a timer and you see, can I

4:41:18finish the task in 5 minutes or less.

4:41:21The reality is you can always fit 5

4:41:24minutes in somewhere. There's no man or

4:41:25woman on earth that is too busy for 5

4:41:27minutes. Also, this solves multiple

4:41:29problems like the should I be doing this

4:41:31now problem. You ultimately have no idea

4:41:33whether you should or shouldn't be doing

4:41:35something until you've at least looked

4:41:36at it. So you can actually use these

4:41:385-minute timers to answer the should I

4:41:39be doing this now problem. In many

4:41:41cases, I will look at a task that I've

4:41:43been avoiding, set a 5-minute timer,

4:41:45then while starting it realize, oh, you

4:41:47know, I don't actually need to do that

4:41:48anymore, and now I'm already done and it

4:41:49only took me 30 seconds. The 5-minute

4:41:52timers assist me in doing this very,

4:41:53very easily. They assist me in resolving

4:41:55the problem.

4:41:57It'll also take advantage or take care

4:41:59of the this is going to take all

4:42:01afternoon problem which is a separate

4:42:02but related problem because the reality

4:42:04is you can't know how long something

4:42:05will actually take until you start right

4:42:07you can guess obviously but as mentioned

4:42:09with the planning fallacy many of your

4:42:10guys guesses will be very wrong well

4:42:12with the 5minute timer you have capped

4:42:14that you will not spend more than 5

4:42:16minutes on this task so you can get back

4:42:17to whatever the hell you were doing

4:42:18before the 5 minutes. This is the

4:42:20simplest version of an old trick called

4:42:22the try harder luke with a funny post on

4:42:25less wrong all about this if you want to

4:42:26take a look. So let's say you set a

4:42:29five-minute timer and you actually try

4:42:30and do something on your to-do list.

4:42:31From here there are three possible

4:42:33outcomes. The first is that you will

4:42:34realize that it is not worth doing in

4:42:36which case you will win. Now it is off

4:42:37your plate. Excellent. The second is you

4:42:40will do the task within 5 minutes which

4:42:41is also a win. Nice. It's also off your

4:42:43plate. The third is in attempting to do

4:42:46the task you realize this is going

4:42:48to take more than 5 minutes. Well,

4:42:50great. Now, now you know what you need

4:42:51to do and you can actually get into it.

4:42:54Now, the first two outcomes are

4:42:55incredible, but the last one is still

4:42:56quite manageable. How? You just set

4:42:58another five-minute task. It's just

4:43:00instead of this time, instead of doing

4:43:02the task, your goal is now planning your

4:43:05next five steps. [sighs and gasps] Now,

4:43:07when I say planning your next five

4:43:08steps, I mean in those 5 minutes, just

4:43:10write down the order of operations in

4:43:12bullet points that you need to take in

4:43:14order to complete the task. So since the

4:43:16majority of equasia is just not having a

4:43:18clearly defined next action, you know,

4:43:20most people can ultimately do what they

4:43:21put their minds to as long as it is in

4:43:23front of them. This will cut to the root

4:43:25of the issue by giving you a very simple

4:43:26and actionoriented plan. And after that,

4:43:29you can spend another 5minute resolve

4:43:30timer actually doing the thing. With the

4:43:32task clearly defined, I think you'd be

4:43:34surprised at how far you could go to

4:43:35completing something in just 5 minutes.

4:43:37So let me give you an example. Let's say

4:43:39your task is send tax information to

4:43:41account. It's been sitting there for the

4:43:43last, you know, I was I meant to say 5

4:43:44weeks, but 5 minutes. Cycle one, what

4:43:47you'll do is you'll set your resolve

4:43:49timer and go. So, you'll try sending the

4:43:51tax information to your accountant. The

4:43:52second that you start, you'll realize,

4:43:54damn, that's a vague statement. What the

4:43:55hell is tax information? What does send

4:43:57actually mean? There's a lot of kind of

4:43:59uncertainties here, huh? On cycle two,

4:44:02you'll write out your next five actions.

4:44:04And you'll just do this by pulling

4:44:05actions, you know, straight off the

4:44:07dome. For instance, step one in this

4:44:09case would be determine the scope of

4:44:10what tax information revolves around. Do

4:44:13I need to send like 2025? Is it 2026?

4:44:15Does he want to see all my books? What

4:44:17exactly does he want to see? So, think

4:44:18back to my conversation or run through

4:44:20my email thread, figure that out. Number

4:44:22two, decide on a way to send it. Should

4:44:23I do email? Should I do Google Drive?

4:44:25Next, compile the docs. So, actually get

4:44:27all the files. Fourth, write the email.

4:44:28And five, send.

4:44:31Once you have it all laid out, okay,

4:44:32that easily after thinking about it for

4:44:34literally 5 minutes, you can just set

4:44:35another timer and then get through it.

4:44:37And you can literally probably get

4:44:38through most of this. Like I know it

4:44:40sounds really scary and hard, but like

4:44:41determining the script of tax

4:44:42information, that could take you like a

4:44:43minute. Deciding on a way to send it,

4:44:45that could take you another 2 or 3

4:44:45minutes. You'd probably be halfway

4:44:47through compiling the damn docs before

4:44:48you actually finish that timer. And at

4:44:50that point, you're almost already done.

4:44:52So you might as well just spend a few

4:44:53minutes and wrap up the task, right?

4:44:55That is in practice how you do it. You

4:44:57try and solve the task in batch number

4:44:59one. Then if you can't in batch number

4:45:01two, you list five minute next actions.

4:45:03And then in task number three, you

4:45:04actually just do as many of those as you

4:45:06can. So I will do this all the time,

4:45:08especially when my to-do list gets super

4:45:09bloated and unwieldly, which

4:45:11unfortunately happens maybe once a week.

4:45:12Today is one of those days. Here are

4:45:14some practical tips that I've learned

4:45:15over the years to make the 5minute

4:45:17resolve timer work. The first is a

4:45:19physical timer. A desk clock is ideal

4:45:22just because that takes you away from

4:45:23your phone. Um, if you're on your phone

4:45:24and you're setting like their default

4:45:26alarm, what you'll do is you will like

4:45:27constantly be looking at this thing and

4:45:29then maybe a notification will pop up or

4:45:30you'll feel tempted to swipe down and

4:45:32then boom, now you're out of flow. The

4:45:34second is to write while you think. What

4:45:36I mean by this is if I was solving the

4:45:38accounting problem from before, I would

4:45:39actually write stuff down. Like for

4:45:40instance, scope of tax information,

4:45:41bullet points, uh, year end, total

4:45:44revenue, total savings, whatever. When

4:45:47you write it immediately makes you like

4:45:4920 IQ points smarter. And this is not

4:45:50facitious. I mean, people have done a

4:45:52lot of analysis on this stuff. the

4:45:53quality of thought that you get when you

4:45:55write everything down and can reflect on

4:45:57it later is way higher than if it's just

4:45:59all in your head. The main reason for

4:46:00that is the four uh working memory chunk

4:46:02limit. If you can write your thoughts on

4:46:05paper, you've expanded your working

4:46:06memory limit from four things in your

4:46:08head to four things in your head plus

4:46:09however many things you can look at

4:46:10simultaneously. So, you've done is

4:46:12you've realistically grown that chunk

4:46:13limit from maybe four to six or seven.

4:46:15The benefit to that as well is you'll

4:46:16have a log or asset you can look back on

4:46:18later. And you can also use that to

4:46:19delegate a task to somebody if you do

4:46:21end up needing it like say if it's a

4:46:22business task.

4:46:24The third is to define your end state

4:46:25beforehand. Do you want to make a

4:46:27decision? Do you want to write a draft?

4:46:28Do you want to take a concrete step? You

4:46:30cannot rely on I have thought about it.

4:46:32That is not good enough. What you need

4:46:34is some sort of concrete end state. And

4:46:36so in my case of sending the stuff to my

4:46:38tax account, my end state there is

4:46:40literally the the email is sent. The guy

4:46:41has my my information.

4:46:44Now to be clear, resolve cycles don't

4:46:45work every single time. Sometimes the

4:46:47task is too hard or it is just way too

4:46:49long for you to meaningfully chip at it

4:46:51away. But even then, at the end of a

4:46:53couple of timers, you can usually build

4:46:54a concrete list of what you need to find

4:46:56out or even who you need to find it out

4:46:58from. And that is a very far cry from I

4:47:00will figure it out later. Okay. And an

4:47:02action question here. What's a problem

4:47:04or task you guys have been thinking

4:47:05about for a long time? Set a 5minut

4:47:08timer right now and try and do it. And

4:47:10if you can't, set another 5-minute timer

4:47:12and write out your five next steps.

Using AI without losing your edge

4:47:14Finally, I want to talk about AI. Now I

4:47:16teach people hundreds of thousands of

4:47:18people all over the world how to use AI

4:47:20both for their personal gain and for the

4:47:22gain of their business or some sort of

4:47:24economic activity. So on net it is an

4:47:26incredible invention. Okay, I have made

4:47:28many many millions of dollars with AI

4:47:30and I've helped people make many

4:47:31hundreds of millions of dollars at this

4:47:32point. I would consider AI to have

4:47:35already helped humanity accomplish some

4:47:36of our biggest challenges. And I firmly

4:47:38believe the technology will eventually

4:47:40bring abundance to billions, maybe even

4:47:42trillions of humans if you zoom out and

4:47:43think about how long humanity will be

4:47:45around for. But like any disruptive

4:47:47technology, it takes a lot of time to

4:47:49learn how to wield a technology to

4:47:51maximize its benefits. Took us a while

4:47:53to learn how to take fire from out in

4:47:55the environment and put it inside of say

4:47:56a steam engine, right? Same idea. Right

4:48:00now, most people are wielding fire or AI

4:48:02in ways that make them worse, not

4:48:05better. And as a result, we are frying

4:48:07our attention spans, frying our brains,

4:48:09and really impacting our abilities to

4:48:11think clearly and deeply. What I want to

4:48:13do is cover a few of these problems now

4:48:14and then show you guys how to avoid them

4:48:16afterwards. The first major problem with

4:48:18AI is sycopency.

4:48:20[gasps] Basically, modern models are

4:48:23post-trained to maximize the score that

4:48:25they receive from humans. If human

4:48:28raiders routinely give higher scores to

4:48:30answers that they like, the model will

4:48:32naturally learn to give answers that

4:48:34humans like. The thing is, humans

4:48:37usually like answers that agree with

4:48:38them. Obviously, what that means is

4:48:40models end up being trained to agree

4:48:42with everything a human says in one way,

4:48:44shape, or form. Entropic recently tested

4:48:47their five AI assistants and found lots

4:48:49of sicky across all the tasks that they

4:48:51measured. This is the Claude family of

4:48:53models. And the results were not

4:48:55surprising. human raiders were

4:48:56significantly more likely to prefer a

4:48:58persuasive or flattering response over

4:48:59one that was just accurate or true,

4:49:01which is why all this happened in the

4:49:02first place. Now, I think most people

4:49:04here intuitively understand this. When

4:49:06you tell a model something like, "Wait,

4:49:07isn't XYZ thing true?" The model will

4:49:10not go, "No, you are wrong. The truth is

4:49:12why?" It will go, "Well, you raise an

4:49:14interesting point there, and it's the

4:49:16interesting half that's half true." And

4:49:18then it'll bury the message in a really

4:49:20nicely massaged length of words that'll

4:49:22make you feel like you were kind of

4:49:24right.

4:49:25>> [gasps]

4:49:25>> Why is this such a big issue? Do you

4:49:27guys remember maps and territories? The

4:49:29issue here is that AI is by definition a

4:49:31map. The way that neural networks work

4:49:33is they literally compress information

4:49:35about our world into a highly performant

4:49:37information structure that allows the

4:49:38efficient retrieval of a bunch of

4:49:40concepts and patterns. So in this way,

4:49:42these models are maps of the world

4:49:44around them. We're increasingly using

4:49:46these maps to make sense of the world

4:49:48upon which they're trained. If you guys

4:49:50are heading in the wrong direction on a

4:49:51hike somewhere and you check your map

4:49:52and rather than your map making it clear

4:49:54that you're going in exactly the

4:49:55opposite way you should be, it says,

4:49:56"Hey, you're heading in the right

4:49:57direction." What good is that map? It

4:50:00has lost all of its utility. And to be

4:50:02clear, this is not because of some

4:50:04hidden agenda or conspiracy to lie. It

4:50:06is just the model doing what it was

4:50:08trained to do, which is maximize human

4:50:09ratings. You can see this in practice

4:50:11with a simple experiment. Next time you

4:50:13chat with an AI, try feeding in one of

4:50:14your business plans and asking, "Is this

4:50:16good?" because you're already implying

4:50:19the answer that you want, the AI will

4:50:21almost always give you a confident yes,

4:50:23here are three reasons why or

4:50:25absolutely, you're getting on something

4:50:27here, or so on and so forth. And this

4:50:29may seem like an opinion, but really

4:50:31it's just your own thoughts dressed up

4:50:33and mirrored back at you. It's almost

4:50:35like your first opinion just wearing a

4:50:36lab coat. So, what is the solution to

4:50:39this? Think about it like the following.

4:50:42If you were to go to your mom and say,

4:50:43"Hey, mom, do you think my business idea

4:50:45is good?" You know that your mom wants

4:50:47to make you happy, right? So, what you

4:50:48do, what do you end up doing? You don't

4:50:50actually take her 100% seriously. You

4:50:52listen and you're like, maybe there's

4:50:54some nuggets in there, but for the most

4:50:55part, you're like, "Okay, my mom just

4:50:56loves me, so she's probably going to

4:50:57tell me what I want to hear." The

4:50:59solution would be the same as asking

4:51:01your mom. Instead of asking variations

4:51:03of, "Is this a good business idea?"

4:51:06Start asking variations of why is this a

4:51:09bad business idea. When you do this, you

4:51:11are no longer leaking in your hope. What

4:51:14you are doing is you are forcing the

4:51:16model to explicitly find the worst parts

4:51:18of your plan or your business model and

4:51:19then say them back to you. For instance,

4:51:21if you were to ask is my plan good, your

4:51:23hope leaks in the model will guess at

4:51:25the answer that you like and then you

4:51:27will rate agreement above accuracy which

4:51:29then loops around in this like virtuous

4:51:30or somewhat vicious I should say cycle.

4:51:33But if you ask hey what is wrong with

4:51:35this idea? the model will not have any

4:51:37of that hope leaked done. And then it

4:51:38will actually be able to apply its

4:51:40intelligence to enumerating all the

4:51:41reasons why your plan sucks, many of

4:51:43which will probably be true. For

4:51:45instance, here are four prompts that

4:51:46I've used many times. The first is,

4:51:49"Hey, here's my plan or here's my idea.

4:51:51Please assume this plan is a mistake.

4:51:52Give me the three strongest reasons that

4:51:54a smart, experienced person would not do

4:51:56this." The next one is, "Hey, here's my

4:51:59plan. Out of a 100 similar attempts at

4:52:01this plan, how many would get the result

4:52:02that I want?" I also want you to go and

4:52:04find the reference class that you're

4:52:05using. Now, this is Baze in natural

4:52:07frequencies plus the planning fallacy

4:52:09multiplier in one prompt. The other is

4:52:11the premortem. So, here's my plan.

4:52:13Unfortunately, it's 6 months later and

4:52:14the whole project failed. I want you to

4:52:15write the postmortem. Then you take the

4:52:17postmortem and then you run it multiple

4:52:19times and then you look at all the

4:52:20reasons why it might have failed. And

4:52:21the last is sort of like the Firmeny

4:52:22approximation. Hey, here's my plan. I

4:52:24want you to break this opportunity or

4:52:25idea into a bunch of pieces. Then I want

4:52:27you to estimate each piece as a range

4:52:29and then firmy approximation my results

4:52:31which is basically straight from the

4:52:32firmy approximates uh section. So in the

4:52:35literature everything I just talked

4:52:36about actually has a name and that name

4:52:38is red teaming. Red teaming is usually

4:52:40applied in a security context. You guys

4:52:42are probably going to hear a lot more

4:52:43about it soon. But what red teaming

4:52:45means is adversarily attacking

4:52:47something. So, what you're doing when

4:52:49you ask an AI to pick apart your super

4:52:50great idea is you're asking it to

4:52:52adversarily attack you, your ideas and

4:52:55your plans, and tell you reasons why it

4:52:56sucks and how it could be better. All of

4:52:58these are what you actually want. You

4:53:00don't just want somebody to pat you on

4:53:01the head and say, "Good job." You want

4:53:03something to point at all the way the

4:53:05ways that you suck and actually look at

4:53:07that, assess whether or not the map and

4:53:09the territory are actually misaligned,

4:53:11and if they are, take steps to fix it.

4:53:13That's what noticing, confusion,

4:53:14ugfields, and shoods are all about.

4:53:17The second major point I want to get

4:53:18across is do not let AI make final

4:53:20decisions for you. I would never ever

4:53:22let an AI make a final decision for me.

4:53:25So in the final sentence of any planning

4:53:27or stretch of thinking where you state

4:53:29your decision and your reasoning, you

4:53:31must write or verbalize all of your

4:53:33reasoning in your own words. The reason

4:53:35why is because you are the only one that

4:53:36will bear the consequences of that

4:53:37decision. You cannot blame an AI for

4:53:40something because it is essentially

4:53:42right now a search engine. Logically, if

4:53:44you are the one that is going to be

4:53:45facing the consequences of a decision,

4:53:47you should be the one to articulate it.

4:53:48And if you start handing this off, you

4:53:50will find that your skills in doing all

4:53:51of this will degrade. Like with uh and

4:53:54flinching, if you get in the habit of

4:53:55seeing a hard problem and immediately

4:53:56start flinching away and giving it to an

4:53:58AI insistent instead, you will uh

4:54:00downgrade the neurosircuitry that

4:54:02underlies your strong decision-m.

4:54:04Another issue is that humans are prone

4:54:05to deep rationalization biases. That

4:54:08means that rather than reason to make a

4:54:09decision, we often will make a decision

4:54:11and then we will reason about why we

4:54:13made that decision and pretend that we

4:54:14thought about it beforehand.

4:54:16Unfortunately, we do not. If the AI

4:54:18writes your decision for you, many of

4:54:20you guys will probably do the thing and

4:54:21then rationalize why you did the thing

4:54:23using the AI's writing. And like we

4:54:25mentioned in the expected value section,

4:54:27you cannot work by resulting. If you

4:54:29want to improve, okay, you cannot only

4:54:32work by looking at decisions that you've

4:54:35made that have achieved positive

4:54:36outcomes. You actually need to

4:54:37rigorously analyze why you made the

4:54:39decision in the first place because

4:54:40statistical chance means sometimes even

4:54:42poor decisions yield good outcomes. So

4:54:45you must be able to evaluate your own

4:54:47process, see why it is incorrect or

4:54:48correct. And even if the outcome was

4:54:50poor, if your decision was right, you

4:54:51should keep doing it. Okay? So two main

4:54:54ways to use the same model. Most people

4:54:56will do the wrong one. You'll ask a

4:54:58question, AI will answer, and then you

4:54:59will act. The way that I'd recommend it

4:55:01is you draft the decision. AI will

4:55:03attack the decision, tell you all the

4:55:05reasons why it's wrong. You will then

4:55:06revise, and then finally actually write

4:55:08the decision line yourself based off the

4:55:10revised reasoning. Two action questions

4:55:11here for you. First, try red teaming an

4:55:13idea of yours right now. So, find an

4:55:15idea you have and then feed it to an

4:55:17agent with a prompt like, "Hey, here's

4:55:18my plan. This is a bad idea, but I'd

4:55:21like you to explain all the reasons

4:55:22why." The next, I'd like you to think

4:55:25back. Have you already let an AI make a

4:55:26decision for you at some point in the

4:55:28last year? If so, why? And what ended up

4:55:30happening?

Full course recap

4:55:32All right, guys. In closing, that is a

4:55:33wrap. Thank you for being with me the

4:55:35whole way through. What I'm going to do

4:55:36next is summarize everything that we've

4:55:38learned so far to help you encode that

4:55:40in your long-term memory and hopefully

4:55:42carry it with you for many days, weeks,

4:55:44months, and years. So, a summary of

4:55:46everything we've learned. At the

4:55:48beginning, we learned how the brain

4:55:49works, which was the biological basis of

4:55:51cognition. If you guys remember, this

4:55:52was three components: attention, working

4:55:55memory, and executive function. We then

4:55:58talked about the human brain's upper

4:55:59limit to working memory, which was four

4:56:02chunks before discussing ways to store

4:56:04more information in that limited window.

4:56:07Do you guys remember the date that we

4:56:09discussed? That was quite a while ago,

4:56:11but I bet you if you sit back and think,

4:56:13you might be able to make it happen.

4:56:15Feel free to pause the video if you'd

4:56:16like to give it a try. From there, we

4:56:18went to mice and rats. We covered

4:56:20enriched environments, which is the idea

4:56:21that mice given enriched stimulating

4:56:22environments grew 15% more neurons in

4:56:25the centers of their memory without

4:56:26having to change anything about their

4:56:28effort, as well as a couple of cool

4:56:30studies on people that show things like

4:56:32how air quality immediately impact

4:56:34clarity of thinking, sometimes by 50% or

4:56:36more. Afterwards, we define willpower

4:56:38and what it means to have strong

4:56:40willpower. In general, we found that

4:56:42people with high self-control simply do

4:56:43not let themselves be tempted in the

4:56:45first place.

4:56:46Then we covered choice architecture

4:56:48which is the idea that the more options

4:56:50and choices that you have seen in your

4:56:51life, the more times you have probably

4:56:53been manipulated because every option or

4:56:56choice has always been arranged by

4:56:57someone else and for their benefit, not

4:56:59yours. We saw the difference between a

4:57:0112% and a 99.98%

4:57:04organ donation number simply by changing

4:57:07the wording and the default version of

4:57:11whether or not you should opt in or opt

4:57:12out to having your organs donated.

4:57:15Afterwards, we talked friction. Now, if

4:57:17you move a bowl of peas 10 inches

4:57:19further away in a cafeteria and make it

4:57:20uncomfortable to grab, consumption of

4:57:22those peas drops 13%. What areas of your

4:57:25life can you do the same thing to? In

4:57:27that way, if you want to do more of a

4:57:28thing, make it easier. And if you want

4:57:30to do less of a thing, make it harder.

4:57:32Afterwards, we spent a long time on

4:57:34hardware, sleep disorders, exercise,

4:57:36nutrition, etc. The end result of this,

4:57:38if you stack them all, was around 150 to

4:57:40200% improvement to your ability to

4:57:42think clearly and make good decisions.

4:57:45Once we were done with hardware, we

4:57:46moved to software where I ran through

4:57:48expected value, which was simply the

4:57:50expected value equaling the sum of all

4:57:54of a choices outcomes times

4:57:55probabilities. We then covered power

4:57:58laws, which were equivalent to x= y

4:58:00raised to the n. That's kind of a hard

4:58:02way to remember it. So, put another way,

4:58:04most of your outputs come from one or

4:58:06two inputs. I'd like you guys to

4:58:07remember that exponential graph where

4:58:09the beginning of the graph was very tall

4:58:11and then it smoothly gradiated down.

4:58:13After that, we learned about the chain

4:58:15law, which was the inverse of the power

4:58:17law, where processes are only as strong

4:58:19as their weakest link. Then we covered

4:58:21local and global maxima. If you want to

4:58:23reach higher peaks, you usually have to

4:58:24cross a lower valley. Then we covered

4:58:27intentional residue, which was a way to

4:58:28use notes, resume notes to minimize how

4:58:31much residue sticks after you context

4:58:34switch from task A to task B. Then we

4:58:37covered accasia, which was knowing while

4:58:39not doing the thing that you know that

4:58:40you should. And everything after this

4:58:42was essentially software upgrades that

4:58:45help you minimize the degree of a cra

4:58:47you feel. So my favorite idea in the

4:58:49whole course is map versus territory.

4:58:52Now maps are useful compressed versions

4:58:54of the wider world and that's exactly

4:58:55why they're useful. They're compressed

4:58:57but a map is not the territory and it is

4:58:59valuable for you to remember that. Then

4:59:01we covered Ulyses or Adysius contracts

4:59:04which were making decisions while still

4:59:05in a clear state of mind such that later

4:59:08on when you're not in a clear state of

4:59:09mind, you would defer to the earlier

4:59:11version of you. This also allows you to

4:59:13tie consequences to poor actions like

4:59:15donating money to competitors or

4:59:16charities you dislike. Once we finished

4:59:19at Ulys's contracts, we moved on to

4:59:21opportunity cost, which is where you

4:59:22learned that price and cost are actually

4:59:24two different things. The total cost of

4:59:27something isn't just the price you pay.

4:59:29It is also the time multiplied by what

4:59:31you could be doing with that time. Then

4:59:34we learned about Goodart's law where

4:59:35when a measure becomes the target, it

4:59:38stops being a measure. We also learned

4:59:40how to reverse it by tying an additional

4:59:41measure to it and tracking if it goes up

4:59:43or down. In this case, think, you know,

4:59:45speed versus accuracy. Think tickets

4:59:49closed per unit time versus tickets

4:59:50reopened over unit time and so on. We

4:59:54then covered Chesterton's fence, which

4:59:55is the idea where you must understand a

4:59:57thing before you tear it down.

4:59:59Then B theorem which is a personal

5:00:01favorite where you stop asking is this

5:00:02true yes or no and you instead ask how

5:00:05much more likely is this evidence if X

5:00:07is true versus if X is false. After that

5:00:11we covered firmy approximates the three

5:00:13tenants of which are decompose, estimate

5:00:15and multiply. Then your hourly rate and

5:00:18the offload rule. We talked about

5:00:19marginal which was the best thing you

5:00:21could be doing with your time and then

5:00:23average which is the usual thing you

5:00:24spend your time on as well as

5:00:26supervision costs which are the hidden

5:00:28opportunity cost in most delegation. We

5:00:30covered the planning fallacy multiplier

5:00:32minus 1.5x.

5:00:34Finally, we covered explore versus

5:00:36exploit and the optimal way to structure

5:00:38your explore versus exploit behavior

5:00:40according to the seasons of your life.

5:00:42If you guys remember, if you have a long

5:00:44time horizon, you should explore first

5:00:46aggressively and then later start

5:00:48exploiting aggressively until your

5:00:50exploitation results in the initial

5:00:52resource being depleted. Finally, we're

5:00:54talking immediately actionable

5:00:56techniques. Taps or trigger action

5:00:58principles where when you ahead of time

5:01:00turn a decision into an if then and then

5:01:02wait for the queue. We talked noticing

5:01:04where you catch your own confusion,

5:01:06flinch or should statements and use that

5:01:08to level up your life. Very similar to

5:01:09passive income. We also covered

5:01:11premortems rather than post-mortems,

5:01:13which is where you use stories to find

5:01:14failure cases. Then we chatted resolve

5:01:17cycles, which are simple 5-minute timer

5:01:19approaches that minimize your accrasia.

5:01:21And at the end, we covered how to use AI

5:01:23without letting it flatter you or make

5:01:24your decisions for you. So, it is now

Closing

5:01:28time to think. I hope you guys have

5:01:29enjoyed this journey as much as I have.

5:01:31You'll find that thinking is a skill

5:01:32that you can indeed learn, and it is a

5:01:34skill that will improve your life in

5:01:36many ways that you probably can't

5:01:37imagine. In my view, thinking is not

5:01:39about how neat or tidy your thoughts

5:01:41look when written down on paper. It is

5:01:43not about, you know, how you can cajul

5:01:46an AI into doing something for you.

5:01:48Thinking is about the outcomes that your

5:01:49thoughts produce. And ultimately, your

5:01:51gains here are exponential. Every

5:01:53quarter of your life, you will face

5:01:54hundreds of decisions that shape your

5:01:56future, like what project should you

5:01:57take on, what should you say no to, how

5:01:59big of a bet should you place, when

5:02:01should you quit. Every time that you

5:02:03make a slightly better decision because

5:02:04of the clarity of your thought, it will

5:02:06actually improve your ability to make

5:02:07the next decision. And so the gap

5:02:09between you and then a less defined

5:02:11version of yourself does not grow

5:02:13linearly, but exponentially. I'm very

5:02:15glad you guys made it this far. Keep on

5:02:17thinking. Have a lovely rest of the day.

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