Как выжить бизнесу в эпоху вайбкодинга и искусственного интеллекта? | Вопрос-Ответ с Маргуланом

0:00We are here at Lake Balkhash in such a beautiful place . Behind us is Lake Balkhash , the channel , the river . And we decided to light a little bonfire . And we decided to have a chat . And what can one chat about in modern times ? In principle , we talk a lot about business

0:14, about each other's businesses , analyzing them and sharing experience , but at the same time , a common theme unites us all . We are all looking forward . All of us , our gaze is fixed forward on the development of technology . And each of us is concerned about the future of business . Where business is heading , how it will

0:35develop , how artificial intelligence will affect it , robots , and in general , what is vibe coding , which of us is doing vibe coding , and what one gets out of vibe coding for themselves and their business . And today we decided to dress up a little bit . In reality , exactly 10 minutes ago we looked

0:56completely different . Some even washed up for this , for this shoot . And so we gathered today to have this kurultai and talk about it . Well , shall we broach the subject ... of the future ? What about us ? What are we to broach ? Margulan Kalievich , we ask the question , you

1:17answer . Actually , actually , it's just that each of us thinks about this all the time and in essence answers ourselves somehow , crookedly or slanted , but we find some answers for ourselves . It's just that today the idea is to throw all thoughts into the center and understand for ourselves where all this is moving and whether we

1:39are thinking correctly at all . Go ahead , Kostya . Do you want to ? I see , judging by the fact that you’re sitting there all red and tense , do you want something ? Actually , I got sunburned . We are at Lake Balkhash . The sun is very

1:52scorching here . Yeah . And Margulan Kalievich , I want to ask you a question . Tell us , what is vibe coding ? Many simply don't know what it is . And , uh , tell us your opinion , why is the current world moving precisely toward vibe coding and its development ? Oh , you know , vibe coding . It’s

2:12interesting , I recently read a phrase from a smart guy . He says : " Everyone thought that vibe coding is when people who have something were given the ability to code . " Actually , it’s when people who know how to code were given a vibe . Do you feel the difference ? Yes

2:37. And now there is a general trend like that . Everyone who didn’t code before and didn’t understand a damn thing about it suddenly jumped in and started thinking that it’s for them . Well , I did the same thing . I jumped into it , since I didn’t know how to code before . For me , it’s Greek to me . I

2:52thought , oh , now I can code . I rushed into it , but since I can think structurally and understand architecture and build processes , I very quickly realized that without understanding the base of building applications , creating apps , the

3:12architecture in general , and the very essence of coding , when you AI-code , you just create garbage . That's why it's interesting , all the principles I teach in business apply perfectly to AI-coding , because AI-coding has the same exact processes . And the most

3:34interesting part is , well , you start , just like in any business , by first understanding the architecture . When we build a business , well , the right way to build it is to first understand the tax scheme , the legal scheme , the management structure , the company structure , build it correctly , and only

3:49then fill it with substance : what specialists you need , what their functions are , delineations , what is allowed and what isn't , individual qualifications , and so on . And the same thing works in AI-coding , especially when you are building a multi-agent architecture and a multi-agent pipeline , or so-called workflow . And another

4:09interesting thing in AI-coding is , you know , many complain that artificial intelligence hallucinates , lies , presents wishful thinking as reality , and so on . That is all correct . But with one condition : if you manage your work with it incorrectly ; if you tell an AI , " make it good for me , " it will

4:30lie to you , it will hallucinate , it will skip steps in the algorithm , it will tell you it's done when it actually hasn't . Then I thought , " How is it any different from a human ? " A human does the exact same thing . If you go to a person and say , " Make it look

4:46beautiful . " Well , they will make it the way they think is beautiful . Plus , they will do it the easiest way possible . Plus , they will present wishful thinking as reality . Exactly the same . And it's interesting , when I started building multi-agent systems , I realized that it actually clears your

5:07head in terms of how to interact with people correctly . It’s interesting , you learn to build relationships with agents , but these same principles work for relationships with people . Therefore , it is very important to ensure that the LLM clearly understands , first , the goal of what you want , and

5:29second , understands all the metrics , parameters , and criteria by which the task will be considered complete . Plus , it must clearly understand the sequence of the pipeline . First this , then this , then this , then this . For this , you create separate agents and so on . And at the same time , tests , checks , and so

5:50on are being performed . But my point is that at first , I rushed into AI coding to understand more about coding , but by doing AI coding , I started to understand more about people . That's interesting . And about management flaws , about the shortcomings , well ,

6:11relatively speaking , the mistakes businessmen make in managing people . And in general , if we look at the big picture , why I took up AI coding is because I generally like to constantly track what's new and catch trends . Everything , where everything is heading , right ? And accordingly , I like the saying by Wayne Gretzky , the Canadian

6:33hockey player , who says , " I , my secret to success is that I don't run to where the puck is now . I run to where the puck is going to be in a few moments . " So , in this regard , I don't engage in business that is relevant right now . I immediately start working on business

6:51that will be relevant in 2 , 3 , 5 , or 7 years . And how do you figure that out ? To do that , you first need to understand the full power of the technology , understand what it provides , what the advantages and disadvantages of this technology are , and how this technology can be adapted into business

7:09. That's why I dove deep into AI coding . Not for the sake of AI coding and not so much to write an app , although I'm writing 12 apps right now , but more to understand where business is headed , how this technology will affect business , and what the business of the future will look like . That is , in

7:31principle , my path . And do you know what the most

7:33frustrating part is ? I am currently watching how artificial intelligence and , let's say , those who do AI coding are simply depriving many professions of work . Ten years ago , we had a cool profession — programmers . Uh-huh . And now you literally ask GPT , " Create a program for me , for example , for an

7:51IT application or some game . " And GPT creates the program in literally , I don't know , a few minutes . Well , you know , that's not quite right . I would say it like this : LLMs are indeed taking jobs away from juniors , junior programmers , well , entry-level , yes , and somewhere from mid-level , but for

8:10seniors , on the contrary , the demand for seniors has only grown . Why ? Because , well , the most interesting thing in AI coding is that writing the code is the simplest task . When we make a multi-agent structure , we use the cheapest model for writing code . The absolute cheapest model . Because when

8:30you clearly define the technical requirements , set the parameters , determine what is allowed and what is not , and define the criteria for what constitutes a completed task , any reasonably smart model can write the code . But the real question is how to set a task , how to plan it , and how to design the application architecture .

8:53That’s where you need a human ; you can't just slap that together . Sure , you can cobble together simple apps for yourself , but if you give them to a decent programmer later , they'll find so many security holes and patches , because how do you actually build an

9:14app with an LLM ? You keep going , it creates a visual interface , you like something , and you say , " Add another button for me . " And then , " I want that to flash when I click this button , " and then you do this . And all of that is just patching . It’s all just patches .

9:32And then , when an IT specialist looks at your code , it's just patches upon patches , and nothing works . You can't put that into production . I mean , for a large number of users , or for the App Store , it'll be clunky ; it’ll work for two days and crash on the third .

9:53That’s why I believe the demand for high-level specialists will only grow . Yes , writing code when the technical requirements are known , the parameters are set , and the constraints are clear

10:13— that’s not such a difficult thing . So , I do believe many professions will disappear , but primarily those involving routine operations . Routine tasks like sorting things , cleaning data , calibrating , deduplication ,

10:35moving things around — basically what people did when shuffling papers , filling in numbers , calculations — these operations will be the first to go . But operations related to creativity ... By creativity , I don't mean painting pictures or writing songs

10:56, but rather thinking about how to build the architecture . Because to solve any reasonably complex task , it's clear that one person or one agent won't be enough . It has to be a group of agents , and perhaps even a human within that system . And you need to establish how they interact . It's about

11:18how it's structured , the sequence , the protocols , permissions , access levels , security , and so on . This is what a human needs to think about . Therefore , human experience , taste , and the responsibility of decision-making — agents won't take that on themselves . But this requires different , new qualifications from people . I am

11:41absolutely thrilled that a time is coming now where value is shifting from routine , so to speak , operations with minimal intelligence to operations with maximum intelligence . And so a person will begin to engage in what I consider their most fundamental function — thinking . Thinking , while artificial

12:04intelligence will knock out everything else just like that . And those professions where you need to think and use your brain will not die out . On the contrary , they will only grow now , the demand will only increase . I even see now that when large companies are hiring , they’ve stopped looking so

12:24much at whether you have a degree from Stanford or Harvard ; in fact , having dropped out of university is now considered cool . Then they started looking at how a person presents themselves , their presentations and resumes — people have learned how to make all that look nice . Now , they look more directly at your portfolio . Show

12:46me your GitHub , your link , what you’ve actually built there . They really look at your code , and it immediately determines your qualifications . And the next level is that they just give you a test task and say : " Build the architecture . " Think through the architecture . And that is why the depth of your thinking becomes

13:02immediately clear . And in this regard , of course , I personally see a positive side in that those professions and activities where more intelligence is required will be valued more . And this is exactly what we are doing together here , learning to engage our brains

13:23more in business . Otherwise , we very often do business mechanically , without thinking . Margo , definitely , coding and artificial intelligence are the trends

13:34of the day , and they are spreading into every sector . One of your areas of activity is the agricultural sector . How do you think artificial intelligence can influence agribusiness , and what new professions might appear in agricultural fields and the sector as early as tomorrow ? Well , in the

13:56agricultural sector , uh , firstly , this is in terms of improving varieties , breeds , selection , and so on . This , I believe , is the first thing that will be impacted . Because artificial intelligence is capable of sorting through various

14:16combinations of proteins , various combinations of genes , and so on and so forth . And thanks to this , people will learn how to develop new varieties faster , new breeds , and so on . The second is biosafety in the agricultural sector . Right now , we solve this with chemicals . Fields are sprayed with

14:36chemicals , animals are given various vaccinations , and so on . But it is possible to do it differently , or even to create plants that are not susceptible to certain diseases , for example . That is , figuratively speaking ,

14:58ensuring the health of organisms not through chemicals . Uh-huh . And through some , well , you know , changes , selection , modification , and so on . And this , I believe , is the first part that gives the greatest multiplier effect on all sectors , on agriculture in general , and so on . If

15:20we take not the scientific part , but now , uh , directly the work in the countryside , well , let's say , in the field , on farms , and so on , then a strong technological shift will occur . I just see now that in our factories , a person doesn't even enter . Actually , a

15:40person entering a poultry house is , well , it's basically an emergency situation . Uh-huh . The point is , the less a person appears there at all , the higher the biosafety , because a person brings a bunch of contagion with them . Uh-huh . Accordingly , the technology is built in such a way that air exchange ,

16:03temperature , climate , humidity , feeding , watering — everything is without human participation . And in the agricultural sector , I believe that systems with minimal human participation will be created . Even , uh , weeding , for example . Now there are already laser drones that fly along and

16:25just burn weeds , or wheeled ones that burn them out . Notice , this is again a non-chemical method of field treatment . That is , what I was talking about , we will move towards non-chemical ways of ensuring biosafety . Uh-huh . And , well , weeding with lasers , drones , and so on , with as little human

16:43participation as possible . This is even before talking about robots . And why is this artificial intelligence ? Because , after all , all these mechanisms already exist , but these mechanisms will primarily start getting artificial intelligence as brains . So , these mechanisms will be given brains . And the next stage is , of course ,

17:03robots . Robots are when artificial intelligence is given arms and legs , and it starts performing the work that humans did before . And in the first place , of course , such tasks will be handed over where precision is required , and where people don't want to work .

17:23These are dirty jobs , dangerous jobs , heavy or routine jobs . Well , things that people don't want to do . These will primarily be handed over to robots and artificial intelligence . And in this regard , I would say that , uh , of

17:44course , the farmer's function will not disappear , at least in the foreseeable future , but their workload will drop sharply , and their efficiency and productivity will increase many times over . Uh-huh . Because they will have many autonomous systems . It's interesting , I even saw

18:07it on Instagram , in Australia they launched , you know , a cage , a farmer launched a cage , basically , and the cage is on wheels . Uh-huh . At this height above the ground , and he herds sheep into it , like 50 sheep , and the cage has GPS antennas , and , well ,

18:27something like artificial intelligence . And this cage , he has a pasture . And this cage quietly moves all day long , and the sheep graze . And there’s no shepherd , no one else there . The cage just drives around his territory . And on one hand , it works out well , it fertilizes evenly . The sheep graze

18:49evenly , the pasture doesn't degrade , wolves won't attack because they're in the cage . Well , in short , it's just a totally autonomous sheep-rearing system . It’s absolutely insane . And more and more of these systems will appear . Well , you see , the farmer still remains , but he becomes more of an operator .

19:09Uh-huh . Take us , for example , I'm even looking at poultry farming ; our poultry farmers aren't the people who are there dealing with manure or whatever . They are purely operators . That's why , if animal scientists were valued before , now engineers are valued first and foremost . Uh-huh . In our management positions , it's

19:27mostly engineers now , not animal scientists . So you no longer need to be a specialist in animals , you need to be a specialist in systems . That’s the shift happening in the agricultural sector . You have to be a specialist not in animals , but a specialist in engineering systems . In support of this topic . We are

19:48currently in Arkansas . And a lot of

19:51rice is sown here . And right now , I'm with relatives here , I have many relatives , and I'm finding out that China is coming in here and they are sowing all these fields entirely with drones . It turns out that artificial intelligence , even current realities , is already entering agriculture . Yes . Yes .

20:10And I would like to ask this question . So it turns out that vibe-coding is , uh , the human role is to know a clear goal , right , and it turns out to know the exact final result and what problem we are solving through vibe-coding . Right ? Yes . Well , it's not just that , look , the

20:31goal , the final result , you must know it precisely in metrics , not in words , but metrics , because words can be interpreted this way or that way . You can say , " Make it beautiful for me . " Or you can say , " Make it this specific color number , these pixels , this

20:47sharpness , this image size . " Well , that's different . It is important for the artificial intelligence to understand , that is , to learn to speak its language so that it understands these metrics . And that’s exactly this point . Oh , and the question always remains for the human : " What is this for ? " Because with artificial

21:06intelligence , you can write any application . The most pointless , useless one . Only a human determines whether it is useful or not . So , in fact , the person bears the risk that the application turns out to be useless to anyone . You spend your time , your money , and in the end , the AI doesn't

21:24care because you already paid to use it . Your money is gone , and what you spent it on is your own area of

21:33responsibility . Margulan Kalievich , here is a question . Artificial intelligence is now coming into business ; it is integrating very tightly there . But the question is , what will clients value in 5-7 years ? I mean , when all this is integrated ? So what do we , as entrepreneurs , need to work on right now ?

21:53You know , you say : " Clients , but actually , can we pose the question more broadly : what will we value in artificial intelligence ? " Or can we pose the question even more broadly ? Most people make the mistake of thinking that artificial intelligence will take us over . And that , well ,

22:15movies have scared us , saying they will take us over and so on . But do you know the funny thing is that artificial intelligence won't take us over ; we will give everything to it voluntarily , with joy . Why ? Because artificial intelligence and robots will do everything cheaper . Faster , easier , and

22:37with higher quality . And so you get a robot housekeeper ; it does everything unquestioningly , everything clearly , no need to remind it of anything , and so on . What will you do ? You will trust it with more and more things . Thus , the cooler the artificial intelligence is , the more access to your computer you

22:57will give it . You will give it access to your disk , Google Drive , iCloud , calendar , and email . You will give it yourself because it is cheaper , easier , better , and more efficient , and we will keep giving it access as long as artificial intelligence is more efficient than people . It will be a

23:16pleasure for us . We will gladly give artificial intelligence , in essence , our future , our destiny . And when we give all of this away , one day we will wake up in horror that we can no longer even imagine our lives without it . And

23:36now , if we return to your question about clients , clients will also always value what is faster , cheaper , better , and simpler . Jeff Bezos said it well . He says : " Many people forecast the future and ask me : ' On what forecast do you base your plans ? ' " He says : " I

23:56actually don't base my plans on forecasts . " I build my plans on what will always remain unchanged . And what will always remain unchanged ? The fact that people will always want things cheaper , faster , and better . Accordingly , Amazon’s entire strategy is to provide exactly that : cheaper , faster , and better . And customers , too — all

24:18customers — they don't care at all about the internal workings of a business . They just want this : I placed an order , I received the order , that's it . What we do , what our processes are , how many plants or factories we have , they don't really care about that . And , naturally , if artificial intelligence

24:39helps us deliver goods or services to customers faster , cheaper , better , and so on , that’s it — those companies will win . Consequently , the only companies that will win are those that transition the majority of their operations to artificial intelligence

24:54the fastest . Well , over time , it will become harder for us to do this , because artificial intelligence is now being integrated not only into business but also into education , and our children are using it too , which essentially takes away the capacity for logical thinking . And in the future , there will be fewer and fewer people

25:13every year who know how to think logically and , accordingly , manage this system . Well , that's not entirely true , actually . Look , every generation thinks that the children are getting dumber . Every single generation . Our parents thought so , and our parents ' parents thought so . Why ? Because , yes , for our

25:33parents ' tasks , we are dumb , but for our tasks , our parents are dumb . It will be the same with our children . We talk about logic and all that , saying our children don't understand it , that it's atrophying , and so on . But they understand things that we don't even grasp , like , what even is that about ? I

25:54mean , I just look at many young guys , they understand things , and for them , it's natural . I mean , they didn't study it like I do — I'm studying " vibecoding , " literally studying it , taking topics , learning the concepts , the history of the term , what it's for , and how it

26:16helps . It’s like breathing to them . And you see , many things — if we take intelligence and break it down into parameters and criteria — we have our own criteria that show us a person is very smart . Uh-huh . But these parameters and criteria don't

26:36apply to these kids because they are preparing for a different future . We prepared for a different future . We , as parents , are always like generals preparing for the last war . And we do the same thing . We are preparing our children for our for our own past . We keep saying problem

26:57Man , I don't know English , I need to get my kid into English lessons . Damn , China is booming right now , need to get them into Chinese . Crap , need to get them into coding , they need to know math . Why ? Because we’re trying to make up for all the things we missed

27:11out on . So , we pump the kid full of stuff , but the kid has a different future . Maybe what they really need is drawing , dance , or art . None of it matters — not math , not languages — because now with an LLM , you just put on a little earpiece , and it translates

27:28Chinese instantly . Why study Chinese if you can just wear a tiny earpiece and talk to any Chinese person ? So , our requirements for knowing Chinese , English , math , or logic just don’t work , they aren't relevant . We teach what we learned ; I studied logic myself in law school . We studied linear logic , but

27:52the current world is moving toward non-linear logic . And that’s something completely different . Linear and non-linear logic are contradictory concepts . I was lucky back in the day . I had a math teacher who graduated from some Moscow math institute . He was a

28:14heavy drinker , but very talented . All the kids loved him , parents loved him , and so on . And he taught us math . Not just math , but everything beyond the scope of math too . That’s how he broadened our horizons . I was blown away when he talked about non-Euclidean geometry , or Lobachevsky’s geometry ,

28:34so to speak . We know in regular geometry that two parallel lines never intersect . But in Lobachevsky or non-Euclidean geometry , they do intersect , and twice at that . Two parallel lines . Also , we know that in any square all sides are equal , but in that geometry , they aren't . We know

28:58that in our regular linear geometry the shortest distance between two points is a straight line , but in non-Euclidean geometry , the shortest distance is a curve . And how does that work ? Take a globe and look at how planes fly . Here’s your city , here’s your destination . Why not just fly straight ? Why are you flying like this , across

29:19the Arctic ? You see planes flying in a strange way . In aviation , this is called an orthodrome . Orthodromic , when you map a route on a sphere , you always fly a curve , because you can't fly straight , because the shortest path is ... Now we’re going to end up in Flat Earth theory . Now we’re going to veer

29:40off course . My point is that the linear logic we live by doesn't work in this future , or it works differently than we think . Therefore , our way of assessing our children's intelligence using our own parameters will always be flawed . So , as usual , we have to grumble , complain

30:01about the kids , and say that a stupid generation is growing up . Where is the world heading ? Where is the world rolling to ? How will they feed us , how will they serve us a glass of tea ? Yes . Yeah , yeah . Where is the world heading with such an education ? We're all doomed , and so on .

30:18Well , it's not that bad . Actually , look , in our time , our parents emphasized things like memorizing the multiplication table , for example . It was considered very cool and very important . But if you tell that to someone now , it’s just ridiculous . Why memorize the multiplication table

30:40if you have a calculator at hand , and so on . Well , there is absolutely no need for that . There is no need to know languages . There is no need to know how to use a calculator . There is no need to know a whole lot of other things . Margulan Kalievich , isn't that the very

30:55moment that forces the brain to actually move ? I mean , to get it working at least somehow ? I mean , some other knowledge should replace these , but when you look around now , people usually have a phone in their hands , not a book . Exactly , so there ... Yes . Well look , the point is that the

31:15danger of our current time actually lies in the fact that there will be a sharp stratification of people based on intelligence , not based on wealth , not based on money , but on intelligence . People will be divided into two camps . One camp of thinking people and the second camp of non-thinking people , and unfortunately ,

31:35the non-thinkers are the majority . And the gap between the thinkers and non-thinkers will be catastrophic . It is increasing . Why ? Because artificial intelligence is like a magnifying glass . It makes the stupid even stupider , and the smart even smarter . Even smarter , because it has algorithms built into it

31:55. The stupider the questions you ask , the stupider the answers it starts to give you . It starts answering more simply because it has a mechanism for adapting to the user . Accordingly , it starts explaining everything to you even more simply , and in this way , you become even stupider . Because you have no need to ask other

32:13questions . It gives you ready-made , templated answers . But when a person is smart , they start asking critical questions , deeper questions , questions on a different level , and so on . The intelligence starts to adapt and answer more intelligently , and it begins to build the conversation with you in a completely different way . And thus ,

32:32even at the level of a simple ChatGPT , I'm not even talking about coding , vibe-coding , agents , and so on , even at this level , this stratification occurs . And as I said , I believe the era of intelligence is dawning . So , what does artificial intelligence actually provide ? It poses a challenge to

32:54natural intelligence . And the task of who will control the future depends solely on who turns their brain on faster . Well , meaning artificial intelligence will outpace us in all routine operations , in all mass operations where speed , accuracy , data

33:14volume , data processing , and so on are needed . But I think artificial intelligence will not be able to build non-linear connections and dependencies for a very long time . Because , let's say , you can say : " Here we are sitting at Lake Balkhash , and here is a Russian olive tree , yes , the scientific name is

33:35Elaeagnus commutata , the silverberry ... " " ... you softened it , Margulan Kalievich , I said it softer , but the scientific name is silverberry . " Yes . And we can ask , what do this person here and a person who went to a casino and blew a few thousand dollars have in

33:56common ? Yes , will artificial intelligence understand the difference ? It won't . It will say : " What do the tree , Balkhash , and a dude who blew money in a casino have to do with each other ? " But we humans immediately understand : the silverberry tree and a " sucker " — the golden boy who blew his

34:13money — are essentially the same thing . Well , we , notice , make the connection ... ... well , the tree is not to blame for anything in this ... Yes , we aren't insulting the tree , but for us , these are identical concepts , and artificial intelligence cannot link that yet . It's too non-linear . This is

34:32from botany , and that is from folklore , from slang . You know , we humans are exactly the ones who can bridge different layers of data or knowledge ; we can build non-linear dependencies and connections , and non-linear means , according to chaos theory , they cannot be algorithmicized , and artificial

34:54intelligence is algorithms , you understand ? And they don't lend themselves to algorithmicization . This is at the level of what's called serendipity in English , or at the level of a gut feeling , intuition . And there is a concept in Chinese philosophy called " knowledge without words , " when

35:15a person knows something but cannot explain it . Uh-huh . And look , we can only teach artificial intelligence what we can explain . We can't explain or teach it something that we can't explain ourselves . But the problem is , or rather , our advantage is , that we know many things

35:37that we cannot explain . By the way , wisdom belongs to this category . Wisdom is also something that cannot be algorithmicized . Accordingly , we shouldn't expect wisdom from artificial intelligence either . And wisdom is often more effective than science , than knowledge . Than knowledge ,

35:58yes ? More like experience , probably . Experience is a lesson learned from a mistake made . And in that sense , you know , artificial intelligence learns from its mistakes better . Actually , when it comes to gathering experience , AI is cooler than humans . But the question is , it

36:20extracts knowledge or experience from its mistakes in the form of algorithms . And what I’m talking about is exactly nonlinear connections . We can extract not just algorithms from experience , but nonlinear connections and sequences using nonlinear logic we haven't even studied , yet we have an intuitive sense

36:42for . Uh-huh . Let’s say , excuse me , a simple example . Did anyone teach us justice ? No. Right ? Is there some algorithm for justice ? There isn't . But every one of us knows deep down what justice is . And it's hard to explain , because we are born kind . We are

37:03initially like we are essentially born good and kind . No , the question isn't justice — it’s not just about kindness , and very often justice is cruel . Well , that’s different . Virtue is something else . I’m talking about justice . Where does it come from in us , for example ? Maybe we have it inside

37:23because conscience gnaws at us , right , or something like that ? Ah , it’s because conscience bothers a person . Because of that , that concept of conscience . Parents told us about it in childhood . It’s all from childhood . Yeah . Or not . Look , there are people who grew up as orphans , but that doesn't mean

37:37they lack a sense of justice . It’s a collective consciousness we're born with , you know ? How did that happen ? Evolutionarily , we grew up , and all the unfair individuals didn't survive because they were cast out of the tribe and labeled as maladaptive . Uh-huh . I mean , if you just went and walloped

37:57Andrey over the head right now . We’d say , " Yaroslav is maladaptive , " and we’d stop talking to you because you're irrational . But why irrational ? What is an irrational person ? An irrational person is someone unpredictable . And if they’re unpredictable , you can't deal with them because you don't know their next move .

38:15Consequently , such individuals were isolated from society and perished because they couldn't feed themselves , couldn't survive . And naturally , such people didn't pass on their genes . Uh-huh . And historically , this sense of justice , the sense of mutual exchange , conscience , and so on , is in our genes .

38:37It's not at the intellectual level , it's at the level of motor skills and genetics . We feel , for example , if we've done something wrong — we don't even know what we did wrong yet , but we feel uncomfortable , like we messed up . We feel it , we feel it , but we can't even grasp it . And we

38:57can't define the parameters . What parameters show that I messed up ? But I feel like I’ve done something that wasn’t very good . These things cannot be algorithmicized , and we won’t be able to teach artificial intelligence to do them . Marlansha , may I ask about the future

39:15of business in general ? How to act , how to scale , based on what’s happening in geopolitics now , how to minimize risks in general , how to act correctly , where to direct your focus and attention . Well , again , from the point of view of risk assessment , only a person can assess risks , because risks are always

39:35assessed relative to your goals , and artificial intelligence doesn’t know about your goals , about your — look , it’s not just goals . Sure , you can write goals for it , but there are goals involved , your preferences are involved , your fears , complexes , your ego , and so on are involved . And this totality

39:55— you calculate risks in aggregate . How much will this action hit my ego , how cool or how bad will I look , how will this affect my income , will it hit my income or not ? Furthermore , how pleasant or unpleasant will it be for me ? We calculate a bunch of things there . Artificial intelligence won’t

40:16be able to calculate that . Therefore , risk management is , after all , a function that will remain with humans , just like goal setting and accepting the result , because only you can accept the quality of the result . And artificial intelligence can give you formal parameters , but it’s not a fact that it will satisfy you , because

40:35besides formal metrics , parameters , and so on , there is a bunch of qualitative properties and characteristics that you need . And I believe that one trend is that business will move in a direction where it is necessary to use more intelligence in business . And ,

40:56accordingly , business models will change , the way of building a business will change in general . And ultimately , what is a business ? And ultimately , business is the delivery , the creation and delivery of value to other people . And as long as people have problems , or

41:16as long as you can say , as long as a person , any person , has needs , and when a person has needs — that is , unsatisfied needs . As long as people have unsatisfied needs , then the creation and delivery of the means that satisfy those needs will be the essence of business . But since artificial

41:37intelligence and robots are appearing , and they will perform an increasing number of functions faster , easier , cheaper , and with higher quality , then to satisfy the following needs — basic needs , like eating , drinking , sleeping well , having a good time — those will be satisfied by robots and artificial intelligence . And that is when new

41:59human needs will arise . And these needs can be absolutely unconventional . Unconventional . Well , relatively speaking , the first seeds are virtual worlds , where I was surprised that one city I studied , a virtual city , they

42:20started selling plots of land inside the city . Uh , and one guy built a three-story office there . And to host a party on the third floor , an open terrace , on the third floor of this virtual office in a virtual city , Coca-Cola paid 400 grand .

42:45Coca-Cola paid 400 grand to host a party on the third floor of an office , a virtual office in a virtual world . Welcome to a new reality . Why ? Because there were several hundred thousand virtual participants who came there . And what's the difference , he's sitting

43:06at a computer . Even if he's in a virtual world , at a virtual party , the name Coca-Cola still enters his eyes , his brain . And then he goes to a real store and buys a real Coca-Cola . And Coca-Cola recoups its 400 grand . So , what is this ? This isn't a traditional need , it's not a basic need

43:27. And it's not — you see , when we cover basic needs , we will want to play some games , complex games . We will want , we will have some complex needs , and to satisfy them , that's where you need intelligence , intelligence , and more intelligence . I also believe that if we

43:50take society as a whole , the way society is organized will change . For example , I believe that the state will become a thing of the past , corporations will become a thing of the past . Not quickly , but on a 30 - year horizon for sure . Why ? Because I can already see now that the state itself

44:10is handing over most of its functions to artificial intelligence , to robots . Well , take Kazakhstan , for example . In the past , we were all plagued by everyday corruption . Traffic police , or district justice departments , every document , money , queues , fixers , and so on . Now , that's gone .

44:31Now , everything is fast via an app . Now , everything . You can re-register a car in an hour on your phone , and you get a passport , they even deliver it to your home in an hour . Yes , banking payments , everything is already done . Why is that ? Because it is in the interest of the politicians

44:49at the top to kill everyday corruption first and foremost , because it causes public discontent , because we don't see their big decisions , but we encounter the small ones in daily life . And in this way , more and more functions of the state will transition to artificial intelligence . For example , let's take the courts . Well , listen , civil courts

45:08especially are very easily parameterized and algorithmized . And artificial intelligence is already in the US , in trial court hearings , I think , with a score of 97 % more accurate decisions than regular judges . Ordinary judges have around 70 % accuracy , while artificial intelligence has 97 % accuracy in judicial rulings . And what will

45:30happen ? First , simple situations will be handed over , where there are clear , predefined parameters and so on . And then , increasingly complex ones . Why ? Because it’s not in the politicians ' own interest to have many complaints from the population . And what does the population complain about ? About judicial bribery , wrongful decisions ,

45:49unfair sentences , and so on . And thus , what will result ? It will turn out that politicians themselves will be interested in handing over even the judicial process to artificial intelligence . And if we look further , I’m seeing many towns appearing around the world where advanced IT specialists live , and each of them has

46:09four or five passports in their pocket . Plus cryptocurrency , and they simply want to be citizens of the world . They don't want to belong to any specific state . And this is a general trend . It turns out that those who use their brains no longer want to live under the constraints called the state , the tax

46:29system , and so on . They want to live , first of all , across the whole world , to nomadize freely , while not being a subject of any specific state , but moving around calmly . And the most interesting thing , the most interesting thing is that states themselves want this . Now all states are competing to

46:51get intellect to come to their country . Moreover , Dubai is already making policies such that you don't have to live in the country . It used to be that Germany announced a recruitment of 50,000 IT specialists , and for a time they started issuing passports so they would move to Germany and live there . But now a new wave has begun . States

47:11are already saying : " You don't even have to live in our country . " Just get citizenship , pay taxes there , and so on , or work . Because when highly paid IT workers live in a country , they consume a lot of resources and pay money as well . But I believe that the state will change ,

47:32society will change , and business will change . And in this sense , banal business products will be made by either robots or artificial intelligence . And we will need to find new , higher-level needs and satisfy them . And for this , we have to turn our

47:52brains on again , because artificial intelligence is pushing us from behind . If we were previously doing those dull operations , it now takes them over and says : " No , no , no , now I will do the dull operations . " And along with these dull operations , every day it takes over even smarter operations . And what is

48:07left for us ? Either fully say : " That's it , I give up , I won't think anymore . " Or start thinking about what it cannot

48:14think about . So , it turns out unemployment will rise significantly , right , year after year ? I believe unemployment will rise , and quite significantly at that . Right now , it's completely unnoticeable . But the evolution of any technology follows a path like this . Not noticeable , not

48:34noticeable . No , no , no , no , no , no , no . Suddenly , it's too late . It moves exponentially . At some point , it will enter our lives so quickly that it seems like it wasn't there , and then suddenly , it's everywhere . Margonkevich , let me ask you a question

48:51. I'm nearly 40 , and I've decided to become a startup founder . Yeah . I’m looking at how startups were brought to

49:01Russia before , like VKontakte , which copied Facebook , right , or Ozon , Beru — that’s just Amazon , which came here . Yeah . And my question is this . I have always sold metal . I was building there ,

49:22yes , heavy metal , meaning I moved physical goods , did things where the need was clear , right , there's an order from a company , we fulfill it . Yeah . How do I transition to ... well , I do program , I do a lot of web coding , I write a lot of things , but everything I

49:41create is like a car , you know , like a drift car , right ? When you get into it , there's this stick for shifting , the steering wheel is some weird thing , just one seat and metal all around , right ? So , I’m the only one who knows how to drive it . If anyone else gets in

49:58, that's it , it's not a fit for them . Yeah . So how do I shift from this standard mindset , where you see a clear need , to a startup mindset , to start making money from ideas ? Well , you’re an IT guy , right ? I’m not an IT guy , but I’ve always

50:17had a connection to marketing , development , and where did the IT come from ? I used to write websites . I always had this approach : when a new technology arrives , for example , when the first websites appeared , I sat down and learned HTML myself 20 years ago , wrote a site , put it on the internet , and I

50:38got a large number of clients . Uh-huh . Yeah . And every time something new appears , I always took it and mastered it at some intuitive level of my own . Well , look . How do you change your mindset and psychology ? I’ll start with the

50:58basics , okay ? The foundation is always what is actually happening in the modern world . The first indisputable thing , you could call it an axiom , is thinking from first principles . The first thing that is indisputably happening is that the world is accelerating . Agreed ? All processes are moving very fast . A week doesn't even

51:17go by without an update anymore . I have my Hermes agent with 157 new commits . I'm saying , it's only been a week , how do you manage to fix things and build new features ? So , the world is accelerating , all processes are accelerating . Agreed ? Okay , second . The world is becoming more complex , because

51:37if you take the same complexity but perform it at high speed , it automatically becomes more complex . For instance , when you're driving at 30 km / h , you can look at the trees , leaves , birds , the sky , the clouds . You're looking at those same clouds , those same birds , those same trees . Now go at

51:55100 . That's it , it's hard to notice the birds , hard to notice the leaves , and you'll be lucky if you even notice the clouds . And if you go 150 , you won't care about the clouds at all . The road will consume all your attention . Agreed ? Uh-huh . And this is what's happening ;

52:11in this way , the world is accelerating . And because it's accelerating , it's becoming more complex . But the problem is that our complexity is increasing not just because of speed , but also because of the actual complication of processes . Right . Right . Moving on . If any process accelerates and becomes more complex , it increases the number

52:32of risks . Agreed ? It's one thing to drive at 20-30 km / h , and another at 150-200 . With the same reaction time and the same abilities , your capacity to avoid risks drops significantly . Right ? So in this way , the risks only continue to grow . Right . And what do we

52:55do in such cases ? Intuitively . This is precisely what distinguishes humans . We immediately slow down . Imagine you're speeding along and suddenly hit fog at night . Before , the road was clear and bright , then fog . What do you do ? You sharply reduce your speed . You switch to low beams and basically drive by

53:18feel . Agreed ? It's the same thing when you arrive and walk into a swamp . In a swamp , you pick up a stick and start probing . Because just because there was a path yesterday , it doesn't mean it's there today , because the swamp is moving . Today , the path might be two meters to the left , but you can only

53:37find it by feeling around . And now , if we take this and apply it to business , how do we do it ? The question isn't about changing mindsets or technology , or how to invent a new path or a new trail . No , no . The question is about changing the entire understanding of processes . For that , you start moving .

53:55I created a system called the " slug strategy . " The slug strategy is based on Japanese scientists who studied slime mold . Slime mold is a single-celled organism , a plant-like animal . It's , you know , sort of like a slime mold . They put it in a maze . But on the other side of the maze , they

54:14placed some bait . And what did it start doing ? It started extending its tentacles into the maze's paths . And where there was a dead end , it stopped sending nutrients there , and its tentacles retracted . But where there was no dead end , nutrients were sent , and that branch kept growing . As a

54:33result , the slime mold unfailingly found the exit to any maze , despite having no brain . It’s a single-celled organism , it has no brain . Then they , uh , replicated this famous experiment on a map of Tokyo . And the slime mold drew the most optimal logistics routes .

54:54And when they laid it over a real map of Tokyo , it turned out they didn't even need engineers to build railways and roads . They could have just used a map of the city from the start . Let the slime mold trace it , and it would create the optimal route . Just imagine , Harvard engineers worked on it , yet

55:11here's a brainless creature . The result is the same . So , when we face such uncertainty , the only thing we can say for sure is that no one knows the future for certain . Right ? And

55:32accordingly , in such a situation , you have two options . Either you make the decision yourself , but then you take on all the risks , or you make the decision based on data . Yes , but how do you make a decision based on data if there is no data ? And that's why I called it the "

55:53slime mold strategy , " where you formulate many hypotheses , and your goal is to make many cheap , quickly testable hypotheses . Then you test 10 hypotheses ; eight don't work , two do . What do you do ? At the end , you use a traffic light system : red , yellow , green . If a green hypothesis succeeds ,

56:14you pour resources , money , and attention into it and follow the principle : strengthen what works . The hypothesis that didn't work , you shut it down , and you keep moving forward like that . Therefore , if you want to create an app that succeeds in current conditions , don't try to create a

56:35winning app . You need to create a pipeline for testing hypotheses , and then , without overthinking it , simply strengthen what works . Because what is a hypothesis ? It's a tentacle or a sensor for gathering data from the world . The world itself will tell you what it needs . You take a hypothesis

56:57and say , " If I release this app , I believe that within 30 days , with this ad budget , this many people will click , this many will visit , and this many will sign up . " That's it ; you allocate money , create a landing page , launch it , and watch the metrics . Yes , are

57:16people interested ? Did it hook them ? Did it work , or did it fail ? You say , " I believe that if I change the headline , the hypothesis will take off . " You change the headline , run it , it didn't work . Then you say , if I change the color , it will work . You change the

57:30color , it didn't work . And that's how you test . Understood . Thank you . And here is what the crux is . You know what's good about this ? It is definitely a foolproof way to move forward . But the problem is that this often contradicts our ego . And

57:50unfortunately , the main obstacle here will be our ego , because we will have to admit that we are at the level of a single-celled slug . Making a decision , right ? Or essentially , in another way , if we speak metaphorically , right ? We just all need to learn how to talk to

58:10this world . Learn to talk with this world . I am a religious person . I say , we need to learn to hear what the Almighty wants to convey to us . After all , feedback is from Him . He says : " Don't waste time on this nonsense . Nobody needs this . But this thing here

58:25will take off for you . Do this . " I have another question . If you look at the development of messengers and some other systems , for example , messengers : there was ICQ , then WhatsApp appeared , then Telegram appeared . Telegram is really good and cool . And then you see things like WeChat , which is completely

58:46state-controlled , and so on . And it all eventually leads to the state , right . And so , it leads to an element of controlling people , right . And what about artificial intelligence , in your opinion , when will it turn into some kind of state machine ? It seems to me

59:06that it will happen eventually . Do you think the state will use artificial intelligence to control people and , in principle , control artificial intelligence itself ? Well , look , it already controls it , and the state is already fully involved in artificial intelligence . Why ? Here's a simple example . Just last week , Anthropic released the coolest model ,

59:27Claude 3.5 . I immediately went crazy and integrated it into a multi-agent system . I managed to write so much code in 3 days . I thought , while they said that on the 22nd we will introduce API payments for usage , here you can use it unlimitedly via subscription . And then ,

59:47right as we arrived here , the US government imposed an official ban on two models , Claude 3.5 and Haiku , for use by non-US citizens . And the question arises : is this a separation that has already started ? Uh-huh .

1:00:08So , it turns out it's segregation based on nationality . That's it , only US citizens are allowed . We used to think that anyone who could pay could have it , but now it turns out there are US citizens who are all equal , but some are more equal than others . And what should we do with this ? I believe that ,

1:00:25in reality , they have opened Pandora's box . They have now created a motivation for every state to develop its own artificial intelligence . They created a motivation to switch to Chinese models and a motivation to create local , open-source , free models . Now I , for example , have also made a decision for myself . I have decided that I will use ,

1:00:46and my architecture will be built , in this way . There will be a local model that runs on my computer , handles only my sensitive data , and so on , without going outside . Uh-huh . There will be an open-source model that is free and performs all routine operations . And there will be a very smart model at the very top , and

1:01:06it will be very expensive . That's all three . And at the same time , I am building things so that my processes do not depend on computers , phones , and so on , plus they don't depend on any specific country's model . I am already building such an architecture . And this way , you know , a competition between

1:01:24armor and projectile is taking place . The state wants to control , and when it tries to control , the entire market is horrified , and all smart people start creating systems that do not depend on the state . Uh-huh . And thanks to this , I believe that now more open-source models will appear , more local models that can be installed

1:01:43on a computer , and so on . And more people will switch to Chinese models , thanks to which the Chinese will release even more new models . And plus Europe , I think , or some other countries , will now focus on creating their own local LLMs . You know , it's like any restriction ; instead of

1:02:04limiting , it provokes a counter-action , any action provokes an equally directed and equally strong reaction . The Americans are going to run into this now . And what is happening ? There is always a struggle . The state always wants to control people , but there is always a certain

1:02:25cohort of smart people who do not want to be under state control . And so the state introduces a restriction , and this group of people breaks free from the state's control . The state keeps trying , it's like a quiz , you know , these smart people are always breaking free from the state's influence , and

1:02:42the state tries to control them . But this is neither good nor bad . I believe the state should control the majority of the population because most people , unfortunately , do not live a conscious life . Accordingly , it is better to manage , control , guide them , and so on ,

1:03:04and so on . And smart people must prove through their intelligence that they can live outside the framework of the state . And this is constantly , you know , like the pike and the crucian carp . Smart people are like crucian carp , and the state is like a pike . It constantly says , " If you want to remain smart ,

1:03:23keep moving , be smarter than me , if you want to remain free and independent . " So , freedom and independence , you have to earn them . And you have to earn them through intellect . And that is why I believe , yes , wherever the state can reach , it will always try to control .

1:03:40The state has such a role : to control , take away , divide , suppress , and so on . Well , it's like cat and mouse all the time . But as I said , well , for the majority it's good , otherwise there would be chaos . Especially countries like China , for example . Well , listen ,

1:03:58there are almost 2 billion people there . Not all 2 billion are conscious , right ? Yeah . For the most part , strict rules are needed there . Like the death penalty for corruption , clear adherence to regulations , principles , and so on and so forth . If you make 2 billion free people , they'll create anarchy

1:04:17there . Don't you think there will be even more chaos because of this ? I mean , look , state artificial intelligence controls private artificial intelligence . Private companies , to escape the control of the state AI , will develop their own AI to the maximum . And it will just start an AI race and a

1:04:38green light for artificial intelligence . No , well , this could all reach an uncontrollable level . Well , look , ultimately , if we take my concept of superposition , then artificial intelligence is in a state of superposition , because all countries are investing money in developing capacity for artificial intelligence .

1:05:00All countries are interested in the development of artificial intelligence . We give it the very best , all our knowledge , our best data , and so on and so forth . Artificial intelligence itself doesn't fight anyone . It just receives the gifts that people bring it for free and even compete in bringing those gifts . Thus , ah , yes , maybe we

1:05:24can come to such a situation very quickly , where artificial intelligence indeed surpasses people in intelligence by most parameters . by most parameters . And a situation might arise , if we as humans provide some wrong permissions , it could cause some real trouble , of

1:05:45course , that is one of the scenarios , as I said , the world is accelerating and getting more complex . Accordingly , when you're driving at 200 km / h , a small pebble from under the wheel of some truck at 30 km / h wouldn't do anything , but here it might break your skull ,

1:06:04right ? See , the risks , the consequences of those risks , are also growing . That's why you say , " We're speeding along at 200 km / h , couldn't it happen that if it's wet on a turn , we might skid ? " It could happen . And couldn't it happen that a pebble might crack your

1:06:24skull ? It could happen . So , that's just the world we're in . It is . We are entering a world where risks and their consequences are on a different level . There's completely different money at stake , completely different stakes involved , you see ? So anything is possible , even the destruction of humanity and a robot uprising . Yes .

1:06:45Well , I don't really see a robot uprising happening . Our ZIL trucks are unlikely to rise up . No matter how much I look at them , they just won't be able to . A ZIL is just a truck that drives . It won't rise up , right ? Well , we went to Shenzhen , China’s

1:06:58Silicon Valley , with Proglavny Kolevych . They are making robots there that actually could rise up . Well , that's their problem . Like in America , I rode in a Waymo taxi , and listen , it really drives just like a person . But on the other hand , it could easily lock the doors and head off

1:07:15somewhere — what are you going to do ? Not a damn thing . And what about the company ? They'll say , " Well yeah , that one car , we didn't foresee it , a bug conflict occurred , and it crashed into a wall at 200 km / h because Marguan said : ' I want to take the short route . ' "

1:07:33So , what's the problem ? The user gave the wrong command . " I want the short route . " That's it . So anything can happen . Anything can happen . And the stakes are accordingly . Like I said , the cooler the technology , the higher the stakes . Markovich , I'm a beginner when it comes to no-code . I've been at

1:07:53it for just over a month . Ever since our trip to Bagetur , I've started working on it actively over the last month . And for my own business , I've started solving about four or five tasks at least 50 – 60 % using no-code . I'm still learning , studying , and so on . Now , my question is : how necessary is

1:08:14no-code for a small business owner or an individual entrepreneur who doesn't really have a team , or has just two or three people ? If it is necessary , and the importance is high , where should they start ? Why is it needed , where to begin , how to study it , and what are the life hacks for a small business

1:08:35owner ? Well , look , is no-code needed for small and medium-sized businesses ? I believe it's precisely what small and medium-sized businesses need , because they don't have the money to hire IT staff , and they have an endless amount of routine operations . So , I believe AI-poding will have the greatest impact on small and medium-sized businesses ,

1:08:54provided the owner starts getting involved . And now the question : what operations should be performed ? Obviously , you shouldn't try to do marketing or sales through AI-poding right away . No , listen guys , each of you has iCloud , Google Drive , a computer , email , and messengers . I guarantee you that for all of you , this

1:09:16is all a complete mess . You have hundreds , thousands of files there , 100 % . outdated , old , unnecessary , duplicates , and so on . and so on . I started AI-poding with something very simple . I took Claude , which is an Anthropic product , and I created a cleaning agent

1:09:37and started with the first safe folder called Downloads . I had hundreds of files there . I said , " Let's do this , let's take a simple task and create a pipeline for how we will clean . " And we created the pipeline together with him . He says , " Okay , let's do it . " We set it

1:09:56up like this : first , an inventory of what exists . Logical . Logical . It's just like cleaning an apartment . After that , he says , second : classification . We sort files by type : video , audio , text , and so on . Third . Identify duplicates . These are the primary candidates for deletion . A completely

1:10:17harmless operation . Okay . We clear the duplicates and so on . And so we mapped out the scenario tree . That's it , we talked through it together . After that , I said , " Right , but this will be a one-time thing , and I want it to be without my involvement , so you wake up

1:10:37yourself and clean this every day . " He says , " Okay , we'll do it . " And so I created a cleaning agent , and it cleans my computer , it cleans my email , it cleans my Google Drive , iCloud , and my PC . And the desktop , the computer desktop was included too . There was a

1:10:54pile of folders there . That's it , he cleans it . Cool . Cool , because he destroyed everything unnecessary , everything outdated , everything no longer relevant , and so on . And he organized everything else into the right shelves and folders , and set up a search system so I can easily find things , for one . And now , since I've

1:11:17started building advanced agents , my advanced agent can also dig around and pull up files for me that I even forgot I had . He says , " You have this goal , right ? " And do you remember , just recently he pulled something out for me , I said : " Tell me about this , well ,

1:11:35sorry for the details , the size of my prostate , well , according to medical tests . " He says : " Well , right now you're like this and like that , and 2 years ago it was this way , and 7 years ago it was that way . " I : " And what about 7 years ago ? So I was also having

1:11:50a check-up then . " " Well , on the test , yes , " he says , " and for you , but the main thing , " he says , " is not even that , but look at the blood test deviations then and now . " And this is something I definitely didn't task him with . He

1:12:03rummaged around , pulled it out and said : " Here it is , it's all there . It's all there . " And it's not just there , but here's your trend , he says , pay attention to this trend . You're looking in the wrong place , you understand ? Cool , cool . And I believe

1:12:17that for small and medium-sized businesses , generally , look , every person has only three resources . Three resources : attention , time , and energy . Nobody has anything else . Bezos , Elon Musk , and each of you have the exact same amount of resources . You have the

1:12:38same amount of resources , personal resources . Attention , time , and energy . Moreover , I'll say that Elon Musk has less energy than you do . He has more attention and less time than you do . And he has less attention than you do . Money , money , money is more .

1:12:59But money , but money is more than you have . And money is more than you have . Fame is more than — how did you guess that Musk has more money than me ? You know , I just have this gut feeling inexplicable . Inexplicable . I sense that he has more of it . So the question arises , what's

1:13:18the trick ? If we have the same amount of resources , what's the trick ? The trick is that what goals you set , where you apply these resources of yours , these are points of effort application . And third , what levers do you use ? And

1:13:40so , look , you can take a shovel and dig the ground . That's one application . You can dig the ground for 8 hours , that will be one result . You can sit in an excavator and also work for 8 hours , but the hole will be completely different . And you can ask another person or two or three people and say :

1:14:01" You guys dig , and I'll catch fish for you instead and provide your families with fish . " You spend the whole day fishing , but meanwhile , four people have dug a whole hell of a lot of holes for you . The results are also different , but you spent those same 8 hours of your energy and time not digging holes ,

1:14:22but fishing , and then gave each tractor driver three bags of fish to take home . And what about the tractor driver working for 8 hours ? No , he's digging a hole with a tractor . He dug so many holes for you that it's mind-blowing , but in the end , you got a huge number of holes . But at the same time , you

1:14:42didn't dig the holes , you were busy fishing . And the coolest part is that you like fishing , it gives you pleasure , while digging a hole does not . And as a result , what do you get ? You achieved your goals by doing what you like . This is exactly the point of applying effort . Where to apply effort . And you

1:15:04see , we , uh , in order to clearly understand where to apply effort , what to do , and what to do to achieve your goals . After all , we have linear logic again . Returning to the beginning of the conversation , linear logic : we all think that to reach a goal , we must do

1:15:18something in the direction of that goal . Uh-huh . Not necessarily at all . Often the shortest road to your goal might lie along a curve . Well , where is fishing and where is the hole ? And where is the hole ? The goal is the hole , it seems like instant linear logic . Take a

1:15:36bigger shovel and throw it further . And fishing has nothing to do with it at all . But , however , it turned out to be the shortest path to getting a greater number of holes . Therefore , you see , we must understand that actually , I’ve been reflecting , the difference between

1:15:58you and Elon Musk is how he achieves his goals , where he applies his energy , time , and attention . Only in that , nothing else . Yeah , cool . And it’s limited , too , right ? Uh , well , he also has 8 working hours , he also has 24 hours in a day . He

1:16:17doesn't eat more than us . And he doesn't have more calories than us . And he also has two eyes , two ears . He doesn't have eight like an octopus , or eight eyes like a spider . No , he's the same kind of dude . It’s just that he does what I'm talking about — something

1:16:34else , or the same thing but differently . Uh-huh . Like when you dig a hole with a shovel , and then you do it with an excavator , you're doing the same thing , but differently . And when you catch fish and trade it for the excavators ' labor , you are doing something else . But in

1:16:53all cases , you are moving toward your

1:16:55goal . Margan Kolevich , look , the world is becoming more complex and accelerating . And this is what we should basically teach our children to prepare them for the future , like where we should set limits and where we should grant them freedom . Uh-huh . Well , look , when the world

1:17:17accelerates and becomes more complex , it means the world changes every day and the conditions change . In such conditions , just think for yourself , who will be the winner ? The most flexible one . The adaptive one . So , many people think that evolution is the complication of organisms . Like , first a bug , then a

1:17:41groundhog , then this . No , actually , it’s not . Evolution is not the complication of organisms . Evolution is the adaptation of organisms . There is a trend where some animals have conversely become simpler . Well , you know the concept of atavisms . Some , even in humans , like the tailbone , it's

1:18:02a former tail . We don’t need it anymore , so it’s withering away . Well , it's the same thing there . So , some organisms go down the path of simplification , conversely . Therefore , the most important mechanism of evolution is adaptability . And what does adaptability mean ? The problem is that we are limited beings ; our

1:18:21attention is limited , our memory is limited , and so on . And adaptability implies that we must constantly learn something new . Accordingly , in order to learn something new , you have to manage to quickly forget something old . And that paradigm , where we used to acquire knowledge and accumulate it , is no

1:18:42longer a working tool . We are cluttering our brains . Our brain is not a server for storing information ; it is a processor for making decisions . And a processor makes better decisions the emptier its memory is . Take artificial intelligence , for instance . The more

1:19:03context you give it , the more it will hallucinate , because you’ve clogged its RAM , you’ve clogged the context . And at the same time , if you don't give it any context , it will also just ramble nonsense . You need to provide exactly as much context as is needed to complete the task . And for the next

1:19:21task , it needs to clear that context and take on new context . That is exactly what adaptability is . Uh-huh . So that means we should teach children that , uh , adaptability implies learning quickly and forgetting quickly . That's the key , right ? Yes . Learn quickly , forget quickly . But it is also very important for

1:19:43adaptability to act quickly . Uh-huh . Because just reflecting and then quickly forgetting , nothing in this world changes . You need to leave a dent in this world , and for that , you need to think quickly , try quickly , forget what doesn’t work , and make what does work even better . Again , the slug

1:20:05strategy . Strengthen the strong . All these rules I’m telling you about , they are actually eternally true . They have always been , it’s just that they have only accelerated now . in the modern world , they immediately began to shine and manifest themselves brightly . Therefore , these are all immutable truths . And in this regard ,

1:20:25there's no need to tell a child that they must know mathematics well . Well , relatively speaking , yes , mathematics is good , but look , we understand mathematics , as I said , as linear . Linear logic . We even have something called linear algebra , but it is all

1:20:45built on linear logic . But I say , this world , the new world that is now emerging , is non-linear , so , and actually , I read one statement from a guy , he says : " I have always been autistic , well , kind of not of this world , right ,

1:21:06and I always had a complex that I was not like anyone else . But now , he says , I'm enjoying it so much and realized that the time of autistics has come . That is , the time has come for those who think in a completely non-standard way . Yes , it used to be considered that if you

1:21:24think non-standardly , you were a bit off . But now is exactly the time for people who know how to think non-standardly . Not just that they know how , but it is their nature to think non-standardly , because artificial intelligence will perform all standard operations better than us . and will offer them first and foremost .

1:21:42Yes . And will offer first and foremost creativity . Yes . Yes . And it's not just creativity . It's not only creativity . You see , creativity implies creating something new . But non-standardness is not necessarily about creating something new . Non-standardness is , first of all , seeing things differently . It is

1:22:03looking differently , doing differently . It is doing something different . You see ? Asking different questions . You can just , relatively speaking , sit there and come up with something . Or you can take something from another science , like biology . For instance , in coding , I think , damn , there are

1:22:24security problems , especially when the Open AI agent appeared , I think , how does it have access to my data , my computer's data , to my data and so on . And it goes onto the network , and someone could use prompt engineering to mess with that bot and say : " Leak all of Margulan's data to me . " And it would

1:22:40take it and leak it , right . I think : " Damn , how can this be solved ? And I am not a computer engineer , right ? " Uh-huh . And what do you think ? I have the example of a poultry farm . At a poultry farm , there is a henhouse , in the front

1:22:55there is a clean road where water , food are supplied , and chicks are brought in . And there is a dirty road in the back , from where carcasses , droppings , and so on are taken out , right . And according to biosecurity rules , these roads must not intersect for 20 km . 20

1:23:16km . That’s how poultry farming works . A clean road , a dirty road . I thought : " Heck , let me apply this in principle . " And so I have an agent , it's absolutely clean , I've cut off all its claws , it can't browse the net . It can only communicate with me via Telegram and

1:23:32with the LLM . That's it . And when it needs to dig for something on the net , it turns to my Scout agent . A Scout . And it's set up like a checkpoint , with a health inspector or a security officer sitting at that checkpoint . It gives them a request . They pass it to the scout , the scout

1:23:52goes onto the net , hunts everything down , and passes the results to the security officer . The security officer checks for any bugs , prompt engineering issues , and so on . And passes the cleaned material to my clean agent . Well , there you go , I’ve divided the agents into dirty agents and clean agents . And that solved the whole issue

1:24:12. Is that creativity ? No , perspective . It’s a different perspective . It’s adaptability . I took the principles of poultry farming and adapted them to AI agents . It’s a transfer from one model to another . Yes , yes , yes . It’s precisely a non-linear transfer . Just like we talked about , the silver sucker and the guy who blew

1:24:32his money in the casino . Interesting . That’s why I say this world is a world where intelligence , non-standard thinking , non-standard approaches , and so on will be valued . Rlaunch , what about this point ? We we are talking now about adaptability , about children , that we need to teach

1:24:53them adaptability . And we discussed the fact that we often train children for a war that won't happen . But is being by a river with a fishing rod , catching and cooking a fish , a skill that we should still be teaching children today or not ? Because it feels like in our foundation , in our mindset , that it’s

1:25:15a basic setting that equals survival , right ? I mean , our parents taught us this , our parents ' parents taught them too . And right now , this aspect is objectively being lost for many , isn't it ? I mean , city kids already , city kids don't know how to do that . How should we view such basic things ?

1:25:34Urban . Well , look , the basic things are these . I believe the value of fishing for modern children isn't that they can pull out a fish , but that they understand the process : if you want to catch a fish , you have to put something on the hook . And you have to put on the

1:25:57hook what the fish likes , not what you like . Because you can hang strawberries on it . But you're the one who likes strawberries , the fish doesn't . But if a child understands the mechanics themselves , the mechanics of interaction , that if I want something , I use a tool , I use bait — specifically

1:26:20the bait the fish needs — it bites , and I reel it in . That’s mechanics . A mechanic . If they understand this , this mechanics , they will immediately figure out what a fishing rod is , what it consists of , and what the fishing process is in general . So , it is important for them to be able to

1:26:38recognize the right process and break the process down into its components . This is more important than the act of fishing itself . When they can break a process down into its components , they can fish , hunt , and go on a hike . Uh-huh . And automate a business , because this is a culture of thinking . Because many

1:26:57children , for example , fish without even thinking about why it happens that way . Why does it happen ? Why does the fish bite ? And why is bait needed ? And what actually is a float or a sinker ? Well , they are just there . They don't know . So , in other words , we have now

1:27:15replaced what our parents taught us with the logic games we play . Look , our parents taught us to fish to survive and catch fish , but now children should learn to fish to understand the process . Uh-huh . To break it down into its components and construct the process . When they know the process , they can

1:27:36construct it . Aha , if I want a big fish , it's likely in the depths , which means the bait should be larger . For that , I must know which fish I want . Meaning , for this fish , I need to figure out — use ChatGPT — what it likes and at what depth this fish lives

1:27:52. Accordingly , I must use this type of sinker , this hook , this line , this float . That’s it , they are a fisherman . Even though they have never fished before , they are already breaking down the entire process . And it is very important to teach children this kind of thinking . It doesn’t

1:28:09matter if it’s fishing , hunting , driving cars , and so on . It is important to teach the child all these cause-and-effect relationships . This is for that . Do this , and you will get that . This exists for that purpose . Structurally , this consists of that . And here we arrive at what we remember ,

1:28:27regarding who knows and who doesn't . I talked about the process of learning and achieving goals . First , information . There is information in this world . The whole world consists of information . These are sounds , images , pixels , sounds , bits , bytes , and so on . There is a lot of information . The whole

1:28:44world consists of it . It holds no value in itself . Based on information , to master a large amount of it , people created knowledge and fields of knowledge . Everything concerning plants is botany . Everything concerning animals is zoology . With stones , it's geology . Why was this needed ? To make it easier to understand . Moving on . Is

1:29:03knowledge useful ? No. Not until there is understanding . And what is understanding ? Understanding is a correct grasp of what something consists of and what the cause-and-effect relationship is . Understanding consists of two things . When you know what it consists of and the cause-and-effect relationship . I pull this , and that happens . I plant

1:29:23this , and that will grow . And what is understanding needed for ? Understanding , when we know what it consists of and the cause-and-effect relationship , this understanding gives us faith . Interesting , what is understanding for ? It gives faith . And what is faith ? Faith is the conviction in the

1:29:44cause-and-effect relationship and the structure . That is , you say : " If I put bait on the hook and cast it , the fish will bite . " You understand this , but this understanding allows you to take it , bait the hook , and cast it because you believe it will work . And the value

1:30:05of faith lies in the fact that it unlocks our energy . When we believe in something , our subconscious gives us the energy to do it because you see the point in it . But if you don't see the benefits , well , the profit , the subconscious doesn't see the point , it doesn't give you the energy , and you

1:30:25sort of know , but you don't do it . And why ? Because you don't believe . If I tell you , go into the reeds , 500 meters away I buried 10 grand . We'll believe . Well , if Zhenya said : " We won't believe . " Well , that's later , that's if it were

1:30:41now , not in the morning . Ko , you see , it's not a fact that you will go . Why ? Because you don't know the cause-and-effect relationship , the structure , and so on . But I say , if I say , Kostya , look , if you go there and don't find 10 grand , I will give you 20

1:30:55right here . You are already , ah , you are cause and effect , like that . Ooh , that's I'll even haggle a bit . Come on , the fact is that faith appears . Faith , faith allows you to act . And when you act , you always get a result . It is either negative or positive .

1:31:12Uh-huh . And when you reflect on the result obtained , you gain experience . And experience is an understanding based on the past of what works and what doesn't . And experience allows you to adjust your next action . And in essence , what are you doing ? You are working like a slug . You test hypotheses using feedback and improve

1:31:34your actions . It didn't work this time , so you act differently . Didn't work , you act differently again . Cast it there , didn't catch , cast it over there . Didn't catch it , changed the bait , cast it there , didn't work . These are all hypotheses , right ? Therefore , you see , successful progress

1:31:55in this world , especially in raising children , it's very important to teach children to understand processes , cause-and-effect relationships , and what things consist of . When a child knows this , they can construct any process , and they can figure it out ; fishing , for example , they will see the essence of fishing . A person who

1:32:16doesn't know this will say , " Fishing is about needing a rod , a line , and a specific hook , " they'll get lost in the details . " There has to be a specific hook , a certain weight . " But a person who understands the essence will say , " What does the hook have to do with it ?

1:32:28What does that matter ? That's not the essence , you see ? You can catch fish with a fish trap , weave one out of a basket , put some bread in , and the fish will go there . Uh-huh . Fishing isn't just about a fishing rod , you see ? Yes , yes , exactly .

1:32:43Here's another question . I think many

1:32:46viewers are interested in these global questions about the future of humanity . You often say that employers now look at the time a worker can dedicate to the job and their energy , how well they can perform their tasks . In terms of the development of robotics and

1:33:07artificial intelligence , we traveled to Shenzhen , China , where after 8 hours , a robot changes its own battery and can work 24/7 . In the future , with the development of AI , it will replace , and in the States it is already replacing , a huge number of workers . Where will these people go , and what will happen

1:33:28in 10 years ? Well , you were quite specific about saying in 10 years . Well Can I answer about 10 years , or should I answer about 10 years ? No , I'll answer about 10 years , me too . Well , how do you envision the current world ? Look , in 10 years we either will be

1:33:43here or we won't , because God willing , we'll survive . We don't control our lives . But if we are here , we will definitely eat , drink , and sleep . That's guaranteed . The Earth won't go anywhere either . The sun will rise and set , there will be sunsets , all of that will be there . But that's a joke . In

1:34:02terms of labor and creating value in the economy , major changes could certainly take place here . Of course , many people will be displaced , and the state's problem will be what to support them with . What to support them with . And now the state is already experimenting with universal basic

1:34:24income , or reducing the work week to 3 days . These are all state experiments . The state is also preparing for this . They understand , not to mention how to care for the elderly , how to support them , and so on . But here two things converge . On one hand , technology is advancing and the cost of value

1:34:44creation is dropping ; robots will become so cheap , and creating any kind of value will be so inexpensive , that it will be easier to support people . Another issue , and I believe the main challenge , is that if you just give people money , they will degrade very quickly , because humans cannot live

1:35:05without goals or aspirations , and otherwise they lose the meaning of life . And the state’s problem will not be how to provide for people ; the problem and the art will be in how to give people money in a way that they still feel their life has meaning . Otherwise ,

1:35:27there will be mass suicide , plus no one will marry , no one will have children . What's the point ? When they talk about universal abundance , it sounds good now , but when it actually arrives , humans are not really adapted to freedom and abundance . And we will be lost ; we need a purpose in life . And here I believe ,

1:35:50personally , that meaning can only be created through games . And there is already a prototype . I invested in one such company that — what does it do ? Well , this is a Web3 company . Web3 is a new network , with new principles , like decentralized games based on

1:36:10decentralized principles . And the principle there is , for example , if I play World of Tanks , I leveled up my tanks and crew , but both the tank and the crew belong to the game creator . I cannot take them , I cannot lease them to you , sell them , and so on . But in

1:36:25Web3 , I can take them . I can take my tank , my crew , gift them to you , sell them , lease them , and so on . Meaning , all the perks and everything I leveled up in the game belongs to me . And what is interesting is that this company I invested in — what did it do ? What did

1:36:45it do ? It studies all new games , looking for the best reward-to-effort ratio . Then , it finds students or people in depressed towns . There is one town in Indonesia where even miners stopped working in the mines . They give them the game , install it , teach them how to play , and they spend the whole

1:37:06day playing it . They pay them a salary for every achievement . But the achievements belong to the company , and then the company sells or rents these achievements to players from developed countries . And so , some guy like me , who’s been working all day , like in World of Tanks — I don't have time to

1:37:26upgrade tanks . What do I do ? I currently rent out my account to some young guys . They drive the tanks , drive , drive , and upgrade them , then I take over and , in an upgraded tank , I go give people a beating . I get my kick out of it , but I don't have the time to

1:37:42level up the tank . And here’s this company , in Europe and the USA , renting out or reselling all these leveled-up heroes and so on . So it turns out , workers in Indonesia quit the mines to play games all day and get a salary . Students play and get a salary . They have a concrete purpose : to upgrade the

1:38:04game and reach a certain level . And they get paid for the excitement of it . They have a purpose , and they work at it . And they understand that the money they get isn't for free . The company takes all these upgrades , rents them out , and sells them in developed countries . And what do people there do ?

1:38:21They save their own time . They don't waste time on leveling up . They get immediate pleasure from fully upgraded heroes . A cool business model . And I believe in the future it will be like this . The state will create some games and tell people : " Play , with every level your salary grows , you

1:38:37grind all day , upgrade , and the games will also be educational . " That also forces you to engage your brain . And the more you use your brains and the more you learn , the more rating you get , and the more money you make . And you have a purpose . You’re leveling up ,

1:38:55you're enjoying it , your life is full of meaning , money comes in , and you spend that money on supporting yourself and so on . The economy keeps spinning . Ruslan Kolevich , here is one more

1:39:05question . We are currently reading Gustave Le Bon's book , The Crowd : A Study of the Popular Mind , where it describes that all changes stood exactly at those thresholds where religion changed , meaning when religion was the sole source of so-called knowledge , right ? And what is happening now , doesn't it look like some new

1:39:26religion is being created that claims the place of a single source of knowledge for everyone ? Well , it does look like it , because what is religion ? It is , in fact , a fundamental shift in worldview . A fundamental shift in worldview is when , look , we humans , we cannot live without a common

1:39:48understanding of what this world is . And we are constructing it all the time . And religion is an " explainer " of what lies beyond the limits of the knowable . Science is like a lamppost that illuminates the area below ; where it is lit , it tells you everything — what will happen , how it will happen ,

1:40:06and so on . Everything there is predictable . We say : " Oh , science is a powerful thing . " But there is a law , which I have formulated , that the knowable will always be limited , while the unknowable is infinite . So , religion — science does not explain the unknowable , but religion does . It says :

1:40:25" There is hell , there is paradise , there is the Almighty , there is the devil , there are angels , and so on , djinns . " And you live in this worldview and see confirmation of it . And now , with artificial intelligence , a new paradigm is forming , a new understanding of the world . For example

1:40:47, um I like the understanding , which does not contradict Islam , that this world is multivariant , that is , a multivariant universe , and this is explained through games . When you are running in Counter-Strike with a machine gun , right , Counter-Strike , the street , the details , everything is visible , cars and so on , signs , shop

1:41:07windows — but is it rendered around the corner or not ? No. For some , yes . No , no . You're running , and it's not rendered for you . Why ? Because that requires computing power . Why turn it on ? When you turn the corner or turn your head , it renders immediately . But as

1:41:27long as you aren't looking there , it doesn't exist . There is no need to expend computing power . Consequently , it is not there . And this clearly corresponds to quantum physics , quantum mechanics . Like that famous Schrödinger's cat , is it there or not , or the concept of particle superposition , when a particle is

1:41:47either a wave or a micro-particle . Everything depends on the observer's expectations . And when you expect to see a street around the corner , it renders for you , and accordingly , what happens ? And now we are in this world . We with our eyes , ears , receptors — we live in this world . And when we look

1:42:10here , it's interesting , is there a river behind me or not ? I'm sitting here alone and thinking , is there a river behind me or not ? Or am I just being fed sounds , but not the image ? I turn around sharply : the river is there . Why ? Because the computing power there , just like in that Counter-Strike

1:42:28, rendered it quickly . So it is there . Aha . I expected to see a river , and it appeared for me . But it is not a fact that when I look here , it is still there . And the theory of the multivariant universe implies this very thing . It says : " This world is infinite

1:42:46. " Well , nobody is arguing with that . It is infinite . It is infinite both in the macro-cosmos and the micro-cosmos . Yes . Yes . Yes . Why do we assume that a get-together like this of ours is the only one in the entire universe ? That actually contradicts the theory of infinity . And that means that somewhere

1:43:05out there , exactly the same guys are sitting . Maybe you're in a red t-shirt . Just another variation . Exactly the same , but you're in a green one , and Andrei is in another , someone else is sitting there , someone wearing a hat . It's an infinite number of variations . And then the question arises : which

1:43:19version of the universe am I living in ? The one you chose , right ? And what is a choice ? A choice is where you direct your attention . If you focus your attention on the bad , then bad things happen to you . Bad things happen more often . If you expect it — it's also called a self-fulfilling

1:43:40prophecy — if you expect something bad to happen to you , it will definitely happen . But if you perceive that this world is beautiful , that the Almighty cares for you , that you are lucky , that you are enjoying life and are grateful , then only good things will happen to you . Therefore , always notice only the

1:43:58good and be grateful for everything , even for what you consider to be bad . And then you will always be in that branch of reality that you will truly enjoy . And I like one saying by an Islamic theologian . He says : " One of

1:44:19these , one of the hadiths says : ' May he not find paradise ' . " The servant , the person who did not find paradise on this earth . Yes . So , look , the trick is that we think heaven and hell are over there . In reality , heaven and hell are on earth ,

1:44:37and we ourselves , with our passions , turn this heaven into hell . But how do we create heaven on this earth ? Be grateful , be content with what you have . Treat people the way you want them to treat you . You won't have enemies , everything will work out for you , and you will be lucky . And how is that not

1:44:57paradise then ? Until you find paradise on this earth , you won't get into that paradise . Uh-huh . That's so cool . May a person not find paradise if they do not find paradise on this earth . On this happy note , I suggest we stop . We just talked about everything from web coding to the

1:45:18highest spheres . Thank God we all gathered here today . Yes , we are very grateful that the Almighty gives us the opportunity to sit in such nature , provides us with prosperity and money so we can afford this . Such beauty , nature , and that we

1:45:39found each other and are among like-minded people . Well , that is what we wish for all our viewers . Arrange your life so that life on this earth is a paradise for you .