Full transcript
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.