Agustin Lebron - Trading, Crypto, and Adverse Selection

1. 0:00 – 4:18

   Introduction

   1. ALAgustin Lebron0:00

      I tell my kids this all the time, like, life is not short, life is long. And what that means is, you should think of yourself as having many opportunities to learn things, and try things, and do things. Software development is fundamentally an exercise in sociology, like, in organizing teams and in creating processes and culture and conventions around the building of software.

   2. DPDwarkesh Patel0:22

      I think finance is 9% of GDP. Is that too high a price to be paying for liquidity and price discovery? Okay. Today, I have the pleasure of speaking with Augustin Lebrun, who is the author of The Laws of Trading: A Trader's Guide to Better Decision Making for Everyone. Um, this is one of those books, uh, you know Tyler Cowen calls these quake books that completely, um, shift the models you have of the world. Um, I- I- I really, really enjoyed reading this book. Um, so yeah, I- I'll let you describe your, uh, your background, Augustin. But before that, let me just, um, let me ask this question. So, um, Peter Thiel says that the Strawsonian reading of Zero to One is that you shouldn't start a startup. And I think that, uh, k- k- tell me what you think about this. I think the Strawstinian reading of The Laws of Trading is that you shouldn't trade, right? Because, um, you probably don't have edge, uh, because you're not better than a marginal trader. And if you think you have edge, it's probably 'cause you haven't factored in risks and other costs, um, so don't trade. Is- is that- is that what I should take away from this book?

   3. ALAgustin Lebron1:27

      I think you- you pretty much hit the nail on the head. I think a lot of the times that- that people, um, sort of start thinking about trading seriously, they start realizing more and more how- how- how hard a job it really is to do well. And, uh, and the answer is probably, look, if you're smart enough and- and good enough and hardworking enough to- to make a go at it and make a living at it in financial markets, there's probably an easier way to- to make money and, you know, have a satisfying life most of the time.

   4. DPDwarkesh Patel1:54

      Okay, yeah. So d- do you wanna, do you wanna talk about, um, your background, and then how, w-what you've been working on in the past and what you're working on now?

   5. ALAgustin Lebron2:01

      Yeah. So- so my background is engineering. That's kind of what I did in university. Uh, I did engineering for about, uh, six years professionally. I was a chip designer. Um, at the time, I was playing a lot of online poker, back when that was a profitable and arguably legal thing to do. Um, and so engineering was getting kind of boring and I wanted to do something else. And- and so I thought, well, what's- what's halfway between engineering and poker? And of course, that's quant trading. Um, so January 2008, walked into my boss's office and I said, "I want to quit." Uh, and- and he said, "Oh, where are you going?" And I said, "I'm gonna go into finance." And he's like, "Are you sure this is a good time to be doing that?" Um, and said, "Yep. No, I'm dead set on it." Um, and a few months later, uh, managed to get a job at Jane Street and- and rode out the implosion of Western civilization (laughs) -

   6. DPDwarkesh Patel2:50

      (laughs)

   7. ALAgustin Lebron2:50

      ... from- from the seat of a trading desk. Um, so I did that for a few years and then, um, left Jane Street a few years ago and started my own consulting company, um, basically just helping com- tech companies with growth things like management and hiring and that sort of thing. Um, and in the last few months, started a new company, uh, in the crypto space.

   8. DPDwarkesh Patel3:11

      How- how much are you willing to, uh, give up your edge by telling us what this is? Or if you're- if you're not willing to talk about it, that's okay as well.

   9. ALAgustin Lebron3:17

      Yeah, no, I mean, big picture, we're building a- a crypto protocol that is, uh, kind of new and has some pretty cool cryptographic guarantees, uh, against things that people don't like, uh, when they trade in crypto.

   10. DPDwarkesh Patel3:29

       Yeah, so let's get into some of the topics in the book. Um, so, uh, yeah, fir- first I want to talk about adverse selection because this was, you know, this was the most interesting, uh, part of the book for me. Um, so let- let me ask this question. Um, if we think of hiring workers, as, you know, placing bids on them, if you're like an employer, and then multiple employers can place bids on them, doesn't winner's curse imply that the average worker is probably overpaid because the true value of the employee- employees, not the highest bid, but the average bid that they would get paid on the market?

   11. ALAgustin Lebron3:56

       Yeah, you're right. Uh, from the employer side, it's definitely adverse selection all around. Like, first of all, if you're looking for, if you're just sort of posting a job ad, the applicants that apply are, you know, selected against in the sense that, uh, you're selected against that- that pool because, you know, people who are really, really good, probably their employers know they're really good and so they're really incentivized to keep them.

2. 4:18 – 9:22

   What happens in adverse selection?

   1. ALAgustin Lebron4:18

      And so the people who are kind of on the market are probably at the margin not as good. Um, not only that, but even just the mechanics of hiring, the person who has the final say in terms of whether this happens or not is the employee. And so you're going to get adversely- adversely selected there because, you know, the people who are really, really good are going to have lots of job offers and so they're going to pick from one of many offers. Uh, the people who aren't so good are going to pick from few offers. And so employers just systematically get adverse selected that way. Um, now whether that means that they're sort of systematically overpaid, I think that's a different question because in the end, companies have a pretty good idea, or at least should have a pretty good idea of what the marginal value of an additional employee is. Um, it's true, certainly, that people buy and large give up things in order for- in order to get the security of working at a company. So maybe that counteracts that- that sort of adverse selection in terms of pay. Um, it's not clear which way it washes out, I think, to me.

   2. DPDwarkesh Patel5:16

      Yeah. Byrnes Hobart, uh, recently wrote a blog post about your, um, th- this chapter in your book about adverse selection. And, um, so one of the things he said in a footnote, almost in passing, was that there should be more adverse selection in industries like finance, where, um, the motivation for people to work in them is money because in industry... Like, if a worker wants to work for SpaceX, there's a story you can tell about, like, why they're working for you and nobody else. In finance, you know, th- th- there's a lot of people, obviously, as you would- as you know, who are, like, might be bidding for really talented people. So if they're working for you, I- I- there- there's something suspicious about that. (laughs)

   3. ALAgustin Lebron5:48

      No, I- I think there's something to that. Um, certainly, you know, doing a lot of the hiring that I used to do, one of the biggest, uh, almost red flags is when somebody comes to you and says, "Oh, I've been wanting to be a trader my whole life."Because they're not, like, first of all, they don't know what trading is, right? They haven't known what trading is their whole life. They, they don't know what the job really involves. It's not tangible in the way that being a doctor is tangible. And so what they're really telling you is, "I've been wanting to make a lot of money my whole life," which is generally a pretty ... Well, let's say, like, in some jobs it's a good motivation, but it's not necessarily the motivation you're 100% looking for out of the gate in hiring someone.

   4. DPDwarkesh Patel6:23

      Oh, interesting, um, 'cause, uh, you, in your chapter on motivation, it seemed like you were implying that that is the motivation you should be looking for, 'cause if their motivation is emotional, then they're going to be losing to people whose motivation is to make money. So, um, I, uh, yeah, I'd love for you to talk more about, what, what is the motivation you are looking for?

   5. ALAgustin Lebron6:38

      Yeah. So, I mean, I think, so the, the motivation of, like, winning the game, of, like, making money, and, and that is sort of how we determine who wins the game, I think that, that part of the, the making money motivation makes an, makes a lot of sense for a trader. But the, like, all I wanna do is make the most money possible is correlated to things that, um, that aren't maybe so great. Like, because a lot of the job is, um, is sort of having an inherent curiosity about random things, for example. Um, and, um, it, like, if your, if your whole motivation is like, where can I sort of make the most money today, it's not necessarily optimal over the long haul. And so you kinda need to sort of balance that against these other things, like enjoying the game for its own sake, uh, enjoying the game for, for like, you know, sort of as an exploratory kinda thing. Um, so maybe that's, like, maybe a little bit inconsistent with something that I wrote in the book, but, um, but I think at the margin people need to hear the other thing more. (laughs)

   6. DPDwarkesh Patel7:38

      Uh, yeah. Okay. Interesting. So, and then how do you figure out if somebody enjoys the game for its own sake? I think you said in another interview that, um, uh, s- a company like Jane Street would hold it against you if you have, like, retail trading experience because, um, I guess th- uh, uh, you can talk more about why that is. But, yeah, so if, if that's not what you're, es- uh, that's not how you judge whether they would intrinsically enjoy the job, th- h- how- how is it that you would judge that?

   7. ALAgustin Lebron7:59

      So, uh, one of the things I've always said, maybe you've heard me say this before, is, um, I would love to talk to the person who is the third-best player in the world at some weird, obscure chess variant, because that is probably very correlated with things that I care about, such as, um, a willingness to guess, a willingness to really, like, grind and try to get really, really good at something, and to do so not because there's a huge pot of gold at the end of the rainbow, but because you just find inherent enjoyment in getting really, really good at something. So I think that's, that's pretty good. Um, but yeah, just general, um, again, aside from sort of the mathematical and, and, um, and sort of risk-taking parts, which are sort of maybe independent from this, uh, a s- certainly a strong desire to be in a competitive environment and to enjoy being in that environment. I think that's, you know, th- that can take many forms, but th- I think that's a big part of it, for sure.

   8. DPDwarkesh Patel8:51

      So then why is, um, having domain expertise in trading not important? Um, is it, uh, 'cause u- usually in other industries it's like if you, the more experience you have in the industry, the better.

   9. ALAgustin Lebron9:02

      Sure.

   10. DPDwarkesh Patel9:02

       And it seems like you guys are often hiring people who are just very analytically smart, but, um, maybe haven't been traders before. Um, so h- like, how, how do you guys manage to do that?

   11. ALAgustin Lebron9:10

       Right. I guess-

   12. DPDwarkesh Patel9:10

       And why is that important?

   13. ALAgustin Lebron9:11

       I guess th- the thing I'm thinking of is that the concept of a domain is probably a lot narrower than people understand it to be. Um, like, if I'm there sitting there on my Robinhood account

3. 9:22 – 15:09

   Why is having domain expertise in trading not important?

   1. ALAgustin Lebron9:22

      punting stocks back and forth, like, that is not the same domain as what a trader at a market maker, uh, or at a tr- top trading firm would do. Um, and in fact, to the extent that you think that that's the same domain, that is a thing that you have to unlearn when you come work at, at, you know, we'll say a real company. And, you know, that, that can happen, but it's just, it's kind of a problem. Like, it's just a thing you ha- you, you have in the back of your mind, right? Like, you'd rather take a blank slate, a really smart, motivated blank slate, and sort of teach them what they need to know than undo something and then teach them the thing they need to know. Um, you see this a lot of the time. The other thing is from a, again, at a meta level, probably in expectation, the person who's doing trading in their personal account isn't doing positive edge trades. Like, they're probably, on average, losing money. And so you would like the person to realize that maybe this is not a winning game for them, and so they shouldn't be playing it. And so again, there's sort of this adverse selection of, well, if they can't realize they're playing a losing game here, then that's probably not great.

   2. DPDwarkesh Patel10:20

      So, uh, you said in the book, uh, it takes, like, six, six to 18 months before you can train a trader to be net positive. Um, what is happening in that time? Like, what, what, what are the skills you're teaching them?

   3. ALAgustin Lebron10:32

      Yeah. So this varies from company to company and even has varied over the course of the history of Jane Street certainly. Like, when I started, it was very much the, the Socratic method, right? You sit next to a senior trader and their job is to teach you everything they know. Um, and so it's just a continuous stream of questions, answers, conversations, et cetera. Um, Jane Street, to their credit, has improved on that. Um, there's now sort of a boot camp that you go through where you basically just intensively learn the fundamentals of everything that, that you, that, you know, the firm needs, feels like you need to know as a trader. So that, again, accelerates the process. But it is very much sort of putting people in situations to sort of experience the decision-making process and iterating on that decision-making process. Like, what are you thinking about here? What do you think about that? Hey, did you think about that? What would you do in this situation? Why, why not? Et cetera. And that just, that just takes time.

   4. DPDwarkesh Patel11:22

      I wonder, so y- uh, as you mentioned, you've done a lot of, um, you've helped done a lot of hiring for tech companies. I wonder if, uh, how applicable this model is to the tech industry. So I mean, um, c- could a company like Google just have a very effective boot camp where they get, like, uh, people who study, like, physics or math at MIT, um, and maybe not necessarily computer science, but, you know, if, if you d- don't know that much programming, you can still come in, and then we'll make you a, you know, a 10X in a very short amount of time? Or is that something special about finance and trading?

   5. ALAgustin Lebron11:49

      I don't think so. In fact, I think that the most common failure mode I see in tech company hiring is hiring for skills instead of hiring for abilities and potential. Um, and it's just because skills are very legible. Like, it is fairly straightforward to spend an hour with somebody and understand whether they can write code in Python, right? And so it's like the drunk looking for the keys near the lamppost. Like, you just evaluate what's easy to evaluate. My, my dream, in some sense, and this is something that I can't really work on right now, but who knows, someday I could, is the idea of...... doing mass, mass screening for people around the world. Like, what I'd love to find is the smartest, um, 0.1% of high school, high school graduates around the world, India, Nigeria, all these countries that are being massively underserved by their educational system and their opportunities, um, and putting them in these sort of boot campy situations, um, for, you know, six months or something where they learn, you know, useful skills. And at the end of it, there's like a six-figure job with a Western company. Like, there's no reason that, that companies like Infosys shou- should, should be taking the lion's share of that arbitrage opportunity. Like, there's this incredible need in the world for people that are, you know, smart and motivated, and there's this incredible supply that we're just systematically under-tapping. So my answer to your question is yes. There is... I, I strongly believe there is a, there's a trillion-dollar business potentially, uh, or maybe it's a nonprofit, I don't know, in, in closing this arbitrage gap.

   6. DPDwarkesh Patel13:19

      Y- your former colleague, Sam Bankman-Fried, um, he, um, uh, you know, obviously the CEO of FTX, um, and he has, you know, started a big, um, charity called the Future Fund. And one of their project ideas is exactly what you're talking about, where you would... uh, there would be, like, large gains if you could enable talent from the developing world. So what is it that you would look for when you were, like, scouting out this talent?

   7. ALAgustin Lebron13:43

      Yeah, so I think one of the things that maybe isn't, uh, isn't terribly polite to talk about, but I think is critical, is just, um, G, intelligence. Like, it strongly predicts outcomes across, uh, jobs, across, um, industries. Um, and so you... that is some element of it. That is certainly some element of it. But also, I would say, um, I think in an ideal world, you would build this, this process, the selection process, kind of like a game, like maybe like a mobile game or something, where you're sort of... people are sort of incentivized to kind of keep trying at stuff, and maybe it's, it's a little bit of a grind. And, and again, you're sort of selecting for that hardworking-ness, um, sticktuitiveness, whatever you want to call it, to use a principal Skinner term. Um, and so, yeah, like, some combination of those two things I think are pretty... are almost definitely predictive of, of actual value.

   8. DPDwarkesh Patel14:38

      Have you, have you heard of Pioneer, uh, the thing started by Daniel Gross?

   9. ALAgustin Lebron14:42

      Uh, yes, I've heard of it. I don't know much, much about it.

   10. DPDwarkesh Patel14:46

       Uh, yeah, this sounds a lot like it. I, I don't know too much about it either, but yeah, this is... this sounds very similar. I think they're trying to, like, make, um, building a startup like a video game. So, um-

   11. ALAgustin Lebron14:53

       Right.

   12. DPDwarkesh Patel14:53

       ... with, you know, the associated risk, uh, rewards and stuff. Um, how do you deal with adverse selection in cases where theoretically adverse selection should work for you, um, um, but, you know, like, the counterparty prices in the possibility of getting a lemon? So, like,

4. 15:09 – 21:16

   How do you deal when you're on the other side of the adverse selection?

   1. DPDwarkesh Patel15:09

      an example would be I'm 21 years old and I'm a male, so, like, car insurance premiums for me are huge, even if I'm, um... if... even if I'm a good driver, because, you know, there's, like, um, there's the adverse selection the insurance company faces. And, like, back... going back to another example we were talking about, if there's, like, a great employee, um, who's... he might be getting underpaid because the company that's hiring him doesn't know how good of an employee he is before he is hired. Um, so how do you, how do you deal with such scenarios when you're on the other side of the adverse selection?

   2. ALAgustin Lebron15:38

      Yeah, certainly I think in the car insurance situation, I am fairly sure there are now car insurances that essentially put, like, uh, like, a accelerometer and a GPS on your car, and they essentially monitor how safely you drive or whatever, how jerkily you drive probably. And, uh, I imagine that, that you can sort of decrease your adverse selection by, by taking advantage of those kinds of things. Um, in the case of the, the employment thing, um, that's a tougher one. Um, at some level, the most important thing you can do is select your coworkers as, as a potential employee. And so getting really, really good at evaluating your interviewers, I think is... I think it's an undervalued skill, not so much because you want to tell, like, are they good or not, but it's more like, are they a good fit for me? Is this company a good fit for me? And, and the best signal of whether the company is a good fit for you is who the people are that are interviewing you and what do they ask you to do. Um, if a company is at all sensible, what they ask you to do in the interview is highly correlated to what you do in the job. And so that's kind of maybe like a baseline. Don't, don't adverse select yourself by, by just kind of being like, "Meh, yeah, I think this will probably work out," or, or perhaps more importantly, "This is a high-status company. I am told that it is a high-status company," and that... letting that override your personal understanding of what the experience was. I think that happens very, very frequently. Um, so once you get past that, then you're probably in good shape already. And at that point, I think it just comes down to (laughs) , you know, putting yourself in the right positions. And that... I think that's, um, that's maybe a, a skill that's... that, that you learn over time, hopefully.

   3. DPDwarkesh Patel17:13

      Yeah, so I, I, um... there's a common thing that my friends complain about who are programmers, which is that when they're interviewing, they get asked questions that are very unlike their, um, actual job. So, you know, questions that are almost brain teasers.

   4. ALAgustin Lebron17:26

      Right.

   5. DPDwarkesh Patel17:26

      But there's a... kind of a Chesterton's Fence, uh, argument that you can make that it's like, if ev- all the tech companies are doing it, there must be some important reason why they are.

   6. ALAgustin Lebron17:33

      (laughs)

   7. DPDwarkesh Patel17:33

      So, um, have, have you figured out the reason why such brain teasers are so common? Is it just like G is so important that this is the best way to measure it?

   8. ALAgustin Lebron17:40

      Yeah, exactly. So, so this is the thing, right? The, the, the dirty secret of, of all of this stuff is that explicitly testing for IQ is illegal in the United States as a, as a, as an employment practice. Um, however, you can kind of drive a truck through it because companies do. Like, for example, Wonderlic is a company per- maybe people have heard of Wonderlic because it's the test they give quarterbacks in the NFL. Um, Wonderlic is, is a company that is dedicated, for example, to, to building employment testing that is essentially IQ testing, but has the, the... you know, whether it's a fig leaf or actually li- legitimate justification that as long as you can show that it is, uh, important for job performance, then you can kind of do the testing, right?And so, essentially, I feel like a lot of these brain teaser type questions are, as you say, you know, IQ tests disguised. Um, I think oftentimes they are badly misapplied by the interviewers. Like, I think it takes actually a lot of really, really hard training and, and experience to ask these sorts of questions in a way that gets you the signal you want. Um, but I think that's a, that's a big part of it. Like, the, the extent to which you view your job as vocational, um, is, is the extent to which you're going to hate those brain teasers, right? Like, so if I'm a programmer and I want my job to be I'm just gonna write code all day and sit down and just write code, then you're not gonna like those brain teasers because you don't think of them as part of your job. Whereas if you think of your job as a programmer as somewhat more expansive in the sense of like, well, I'm here to really think about hard problems and ha- I happen to implement them in code, then maybe you're gonna think of the brain teasers as more correlated to the thing you want to be doing. So again, select for what you like. (laughs)

   9. DPDwarkesh Patel19:20

      Yeah, and maybe it makes sense to select for the latter type of person as well, right? If, if, or a- or, I don't know which is preferable to hire, but, um-

   10. ALAgustin Lebron19:26

       Well, so, so I think this is the thing about, about companies. Again, there's a lot of schizophrenia in tech hiring. Um, one of the things that's clear is everybody says they wanna hire A players, um, but only s- a small fraction kind of by definition can hire those, those sort of high percentage or high percentile kinds of people. And so what ends up happening is a lot of startups have the failure mode where they try to build these incredibly selective processes, um, but the people who, who they really, really want are never gonna accept their offers. They're gonna go somewhere sort of more high status or more high paying in particular, um, and so you try to select for, like, an 80th percentile person, but you end up selecting, like, a f- like, a set of 50th percentile person, people who look like 80th percentile people, which is really, really bad. And so what you should actually do as a startup is be very clear-eyed and say, "Look, if I have a team of 10, I probably need one or two, like, 90th percentile people, and I should evaluate for, and in particular, pay for that. Uh, and then the rest I should try to hire kind of 40th percentile people and, you know, put them in situations where they can be effective." That's a much, much more cost-effective way and more stable way to build a company, but nobody wants to hear that, and nobody wants to build a company like that.

   11. DPDwarkesh Patel20:45

       Th- that's a great example of, like, a barbell strategy. (laughs)

   12. ALAgustin Lebron20:48

       (laughs)

   13. DPDwarkesh Patel20:48

       Um, um, so I'm wondering, d- do, uh, do you have any ideas of what good arbitrage opportunities in tech hiring might be? I know, um, I think SpaceX w- some of their early engineers were from the gaming industry-

   14. ALAgustin Lebron20:58

       Mm-hmm.

   15. DPDwarkesh Patel20:58

       ... because they're very used to, um, doing optimization problems there, but, um, it's, it's not, that's traditionally a high-status, uh, c- career. So, uh, there, there's, like, arbitrages there. I, are you, do you have any ideas now of, like, what is a good place you would be looking for really talented potential future programmers if you were, if you couldn't compete with pay,

5. 21:16 – 25:37

   Why you should invest in training your people?

   1. DPDwarkesh Patel21:16

      uh, at Google or something?

   2. ALAgustin Lebron21:17

      Yeah, so I think one of the things I always tell companies is, um, go more junior. Like, if you look at s- if you look at the salary of somebody who just comes out of school, and I'm not talking about somebody who just came out of Stanford. I'm talking about somebody who just came out of, like, a reasonable CS program, right? And you look at their salary three years later, like, it could be almost double sometimes, right? It's just a crazy, crazy jump, and that is kind of unjustified. I mean, you can sort of see the argument for it, but it's just bec- like, there's definitely a kink at the two to three-year point because every startup or ev- I mean, every tech company seems to want to hi- have two years of experience. And a lot of it is because companies just don't want to or can't see themselves investing in the training of those first two years, and if they do, they tell themselves, "Well, they're just gonna leave after two years to go for a higher-paying job somewhere else." Um, but I think those are terrible answers, by and large, to the problem. Like, you should be investing in training your people. You also get the benefit of training them exactly the way you want, and if you put in that work, uh, and you think carefully about what it is that people are coming to work to do for you day-to-day, probably they're not gonna leave, right? Like, if, if you give them a reason to not leave, they're probably not gonna leave. Switching jobs is incredibly costly and risky. People don't go out of their way to do so, so, like, you're kind of, you're kind of getting the, uh, the, um, the inertia d- working in your favor anyway, so, like, let's work on these things.

   3. DPDwarkesh Patel22:44

      Sounds very similar to the sheepskin effect of the last semester of college. Um, so the, uh, it, uh, Bryan Caplan has a g- g- really good argument about this in The Case for Good Education, which is that-

   4. ALAgustin Lebron22:55

      Yeah.

   5. DPDwarkesh Patel22:55

      ... the last semester of college, like, boosts your earnings many times more than the percentage of college you spend in that last semester, and it can't-

   6. ALAgustin Lebron23:02

      Sure.

   7. DPDwarkesh Patel23:02

      ... be because you're, like, learning that much more in the last semester, um, which, I guess, sets up an arbitrage opportunity for hiring people in, like, r- right before they're about to finish their last year or something.

   8. ALAgustin Lebron23:11

      But you see, like, f- like, give me, like, I'll give you a perfect example here in San Diego where, where startups in San Diego tech, tech companies in San Diego love to hire Intuit employees that have two to three years ex- experience because Intuit hires a bunch of people, and they train them, and they train them pretty well, and, and then, like, they get poached. But of course, like, nobody really actually thinks about the idea that, like, Intuit knows who the good and the bad are after two years and, like, you're not seeing the really, really good ones. Intuit's keeping those, right? So... (laughs)

   9. DPDwarkesh Patel23:40

      Uh, so you say in the book that you've traded over your long career in trading, you've traded all kinds of different financial instruments. I wonder, um, what, what is the reason, wh- so is this just, um, I guess, you, you just have to do the, wh- you had to trade whatever in, um, market that you have to at the moment? Or 'cause I, I, I would think, you say in the chapter on edge that one of the ways you can actually get edge is to specialize.

   10. ALAgustin Lebron24:03

       Mm-hmm.

   11. DPDwarkesh Patel24:04

       Um, so is it a mistake of firms to let their traders over their career trade in multiple different categories, or is that necessary in or- is that in order to build your general aptitude as a trader?

   12. ALAgustin Lebron24:14

       Yeah, so I think it's a balance. Um, certainly, I don't think that... again, it depends on how big the reference class is. Certainly, I have never done any trading that looks like, s-Look at a balance sheet and an income statement and listen to an earnings call and make a bet on that. Like that's sort of fundamental trading. I have never done any of that, um, and I think it would be a pretty big mistake to put me in that situation. Um, but within, we'll say, the- the well-defined realm of like quantitative trading, um, I think a lot of the same skill sets apply in different markets, like you're- you're kind of build- bringing the same skill set to different markets, and having that experience of going around and looking at different kinds of markets and how they work informs, like sort of informs how you think about things and- and gives you that- that wider vision that I- I think makes you a better trader. Um, so yeah, I think it's a balance.

   13. DPDwarkesh Patel25:07

       So I- I think finance is 9% of GDP, so I understand the argument that, you know, finance helps allocate scarce, uh, resources, um, to where they're needed most. But, um, if we're giving up like a tenth of our resources to make the allocation of the rest of the resources more efficient, is that too high a price to be paying for liquidity and price discovery? Um, so is finance too high a fraction of GDP?

   14. ALAgustin Lebron25:31

       Um, I go back and forth on this question. Um, I really do. Um,

6. 25:37 – 31:06

   Is finance too big at 9% of GDP?

   1. ALAgustin Lebron25:37

      because kind of when you see it from the inside, a lot of it is zero sum competition, um, and- and it feels like, come on, there's got to be a more efficient way to do this. Um, but at the same time, kind of outside view, we haven't come up with a more efficient way to do this, um, and it's hard to argue with GDP growth. And so I kind of go back and forth on it. Certainly, I think the other thing about it is, um, there's two countervailing forces. You can- you can sort of be inside something and be really, really familiar with it, and just your act- the act of being very, very familiar with something just gives it legitimacy kind of automatically. Um, but at the same time, like if you look at something from afar, you're like, oh, that's ridiculous, right? Like that's- that's not- that's not a thing that should exist, right? And so it's just sort of this perverse thing where the people most, like the most well-informed people, the people who really could or should be making these decisions about like is this a legitimate thing we should be doing, are biased towards thinking like, um, yeah, you know what? This is probably a good thing to be doing or there- there's value to this. And so it's- it's hard to sort of disentangle the- the like the experience and- and the biases that that experience sort of gives you.

   2. DPDwarkesh Patel26:53

      And then would that- would that fraction shrink without- without harming efficiency if, um, like are there inefficiencies created by government regulation or by restrictions on capital flow? Um, or is that like basically what you should expect it to be even in a free market or in an- in an optimally regulated market, let's say?

   3. ALAgustin Lebron27:14

      That's also a tough one. Um, and- and it's- and it's not that I haven't, uh, thought a lot about these, it's just I feel like I don't have, um, I don't have a great answer. Like at the margin, what would I... Like if you- if you sort of made me like regular- regulator of the world, like at the margin, what would I do? Um, there are some things that I would regulate more, um, and this is probably going to be a very unpopular opinion among my- my financial friends, but like I think leveraged ETFs should be banned for- from retail trading. Like I think that's just- they're kind of a bad instrument, uh, in particular like all the volatility products. Um, so I feel like that should probably be regulated some more. Um, but at the same time, the sort of qualified investor status thing that people are driving a truck through, like that seems weird. Like should- should there be, should we just eliminate the qualified investor, uh, status and let people invest in whatever they want? Or should we make it even more restrictive? Um, I'm not sure about that one. Um, and certainly the other thing about it is like, um, a lot of the regulations, especially around capital requirements for banks, are incredibly baroque and they feel like job Ponzis a lot of the time. Like we need to figure out a way to employ all these people and like, okay, we're just gonna create like Basel III and that's gonna be like an extra thousand employees for every large bank in the world. Um, that's probably kind of a deadweight loss, but- but doing things more simply doesn't seem like it's going to get you the thing, like the sort of the stability outcomes you want. And so yeah, it's just... I feel like it's just kind of poor trade-offs all around. (laughs)

   4. DPDwarkesh Patel28:47

      What does the long run future of trading firms look like? So if, um, if economic growth continues to stay low, then you would expect like other financial instruments to stop growing at high rates as well. But even if economic rates, uh, e- economic growth speeds up, um, if markets get more efficient over time, then again you would expect the profits that any one trading firm can get, um, to decrease. So is there a future for highly profitable, uh, trade firms like Jane Street, like in the far future?

   5. ALAgustin Lebron29:17

      So I think to the extent that Jane Street and companies like it provide a service to the world, and I really do think they provide a service to the world, then they're going to be around and they're going to be profitable. Now, are they going to gain, um, like we'll call them excess returns? Um, e- even that's not so obvious because the thing about trading firms is, especially market makers and that sort of thing, like most of the time the business is pretty good if you're really good at it. Um, but sometimes it's really good, like when- when there's lots of market volatility and that sort of thing. Um, but that's precisely because you are the person, you are the entity that is willing to take the risks that nobody else is willing to take. And to the extent that we're going to still continue to have volatility in terms of either like market volatility or, you know, economic downturns or whatever, there's always going to be, um, a service that these- that these companies are gonna provide. Now over the long run, I feel like probably there's going to be more consolidation. That seems unlikely to- to- to- to stop. Um-Just because you sort of gain the- the benefits of ... The- the economies of scale just kind of keep going up. Um, but then again, you have sort of new things that come up, like crypto and that sort of thing, where, like, it's the Wild West right now, and there's gonna be, like, a big consolidation over the next 10 years. I think that's the natural arc of things.

   6. DPDwarkesh Patel30:36

      Oh, interesting. So, um, yeah, can you describe what these economies of scale look like in finance? And, um, um, and then what is the trade-off where if you're, like, too big, then it's not even worth your time to, like, look at smaller, uh, smaller investments where you can't take as big a stake without moving the market?

   7. ALAgustin Lebron30:52

      Yeah. So the thing about finance or, like, market making trading in general is, um, it's very labor-intensive, right? So you should think of it almost like the value of a seat or the value of a person's time. And so are there going to be s- are there

7. 31:06 – 36:16

   Trading is very labor intensive

   1. ALAgustin Lebron31:06

      going to be inefficiencies in the market, like pockets in the, you know, pink sheets or something where it's just not worth a large company's or a large successful company's trade or time to look at? Yes. Like, those will always exist, and they'll get slowly competed away by- by the- by the mom and pop trading operations, or- or even just the, like, the former Jane Street traders who are now at home and kind of doing it on their own for fun. Um, so I think those will always kind of be there.

   2. DPDwarkesh Patel31:31

      Uh, is there a potential that markets can get, like, way, way more efficient if, uh, we have, we develop much stronger AI? And, um, and then at- at- at what point will, um, the work that even traders do that's, like, mu- much more, um, I- I don't know, much more m- model generation and, like, thinking abstractly, at what point can that even get automated away? Um, and not just, like, the rote calculations?

   3. ALAgustin Lebron31:51

      Yeah. I would say it's already getting and gotten comp- uh, like, more efficient. Like, when- when my former boss started, the idea of an options market maker having 10 stocks that they were market makers in was like, that was kind of the li- the limit, right? When I was doing it, like, we could handle like 100 stocks, right? Market making in 100 stocks? Again, technology just make- technology just made everything more efficient or more efficient in human time. Um, that will continue. Like, you can- you can sort of set up things where I'm looking at some data and I can, like, run a bunch of different models and just select the good ones and make sure that I'm not overfitting because I have all th- I have all these overfitting productions. This is all stuff that you can do now that maybe you couldn't do 20 years ago. That will definitely happen. I think when people talk about AI and trading, I think it's, um, it's very hard to, it ... Like, we have to define terms. I think that's the hard part is defining terms when we talk about AI, because if we talk about ... If, like, if you ask, um, a reasonably aware person what AI means, not ... Probably today in 2022, 90% of people are gonna say, "Oh, we're talking about large language models." Of course, that's what AI is, right? And so is the question like, is GPT, is GPTN going to be a significant force in- in markets? Like, I'm honestly kind of skeptical about that. I don't know that- that the "let's just keep making larger transformers" is the way that we're gonna get to AI, but that's my personal parochial opinion. But if we think of AI more broadly as, um, as slowly but surely, uh, increasing the range of things that, things that machines can do that humans can do, like the- the more we sort of creep into the things that humans can do that machines can do as well, then- then yeah, then- then, like, the- the human part is going to slowly start to get, uh, disappeared away. Um, I think the- the- the natural analogy is what happened in the 20th century with manufacturing where, like, it used to be kind of all human power and a little bit of machine power where you had kind of this, like, big central ... Like, why did factories in the 19th century and early 20th century, why were they kind of tall and thin? Well, it's 'cause they had one steam plant and they had to, like ... All these belts and stuff to, like, use the- the power from that one steam plant, right? And then, like, electric motors happen and it's like, okay, now factories are horizontal, right? But over time the- the trend is for it to be sort of less human power and more machine power. And I think the- the analogy is perfect. I think AI over time is going to take more and more of that sort of cognitive load from the human. Um, th- that seems inevitable to me.

   4. DPDwarkesh Patel34:19

      I'm curious why you're skeptical, um, uh, that, uh, like a scaled up, uh, GPT-3 or other language, uh, large language model. Um, uh, I'm curious. Uh, so why- why does it not have applicability, um, in financial markets? Uh, like I- I know there's like a toy version where you have like GPT-10 and you ask it to complete the sentence. The best trade I can make today is and then ... (laughs) Um, so wh- why- why is that unlikely to happen?

   5. ALAgustin Lebron34:44

      So there's a couple things that I might say. One is- is the concept of sample efficiency. Like, these things are incredibly sample inefficient in a way that the way that humans learn are not. And so there's something fundamental there that- that we're not getting, right? And the thing that I think we're not getting is, um, is the things that our brains have, which are structures for, uh, semantic understanding. Like, to the extent that- that these large language models have semantic understanding, it's kind of by accident, right? It's just like, it's the clever Hans thing, right? It's just, like, a super clever Hans and it's super impressive. And I'm not criticizing (laughs) the- the models, like they're incredibly impressive, but it's still a clever Hans thing. Um, and so there surely must be a better architecture out there, much like our brains have these sort of architectures that, um, that sort of specialize in certain things that- that give these- these machines like semantic understanding, or at least give them the potential to have semantic understanding. Um, that I don't think GPT-3 certainly has- has evidenced.

   6. DPDwarkesh Patel35:46

      Uh, so Jane Street seems like a mysterious place, but what's interesting to me is there seems to be a large overlap with the rationality and EA community. So obviously you have Sam Bankman-Fried. He's, um, you know, he- he went into Jane Street with the explicit goal of earning to give.

   7. ALAgustin Lebron36:01

      Yep.

   8. DPDwarkesh Patel36:01

      Tyler Cowen announced that $20 million have been donated to, um, his Emergent Ventures grant program from Jane Street Traders. And, you know, even reading your book, like you reference so many thinkers that are prominent in, um, like

8. 36:16 – 48:00

   Overlap of rationality community and trading

   1. DPDwarkesh Patel36:16

      rationality spheres and you ... Um, so there seems to be a big overlap with this community and with at least a part of the shorting world that I'm familiar with.

   2. ALAgustin Lebron36:26

      Mm-hmm.

   3. DPDwarkesh Patel36:26

      Now that could just be selection, selection effects. But what- what is going on here?

   4. ALAgustin Lebron36:30

      Yeah, it's a great question. I think, uh, maybe at two levels. One is the idea of being very rational and not fooling yourself and, um, and to use a Yudkowsky term, just shut up and multiply. Like, I think that that is a, that is a thing that is very common, I think, in the two circles, or at least probably it should be. Um, like try to really understand the real world and it matters to do so, and doing so using kind of rational, mathematical, logical approaches. I think that there's a lot of overlap just inherently there, but I think you could say that about any number of finance, Wall Street, whatever, trading firms. I think the one thing that Jane Street has going for it differentially from those other firms maybe is a, a culture of collegiality. I think that's kind of an important thing that, that Jane Street has developed over the years and continues, I think, to have. Um, and so I think that's, there's a lot of overlap there, but like it's the kind of place that if you are an EA person, thinks about things rationally and just enjoys the, enjoys the process of kind of this collegiality and, and, and working with people and thinking interesting thoughts together, Jane Street's going to be a very natural fit for you. Um, and I think maybe that's some of it too.

   5. DPDwarkesh Patel37:40

      When I had Byrne Hobart on the podcast, um, we talked about whether debugging or finance was a better application of like rationality principles, because in each case you had to like update your beliefs and so on. And one interesting point he brought up was, um, uh, i- in finance you have, you not only have to model like a static system, um, as, as you would have in debugging, but you also have to model other agents and their incentives and their motivations, which makes it a much more like, uh, d- dynamic system to get a hold of in your brain. Uh, which, I guess, may... It could even mean that like the tools or like the current rationality movement are not good enough to, uh, you know, b- be able to think about those things as well as probably you guys have natively developed in the industry.

   6. ALAgustin Lebron38:21

      Yeah. A- and look, I, the, the cross-pollination goes both ways. Um, but yeah, the, the idea of, of you being an agent in the world you're trying to study is fundamental in trading, um, and it makes it like so much more interesting. I think that's one of the, getting back to the AI thing, just because it occurs to me as one of the, the big failure modes, is to think, to think that, "Okay. Well, yeah, I'm just gonna like throw some AI and, or machine learning or something at this data set, and I'm going to get a trading strategy, and..." Okay, that's great. Like let's say you, you figured out something that predicts the price movement 55% of the time, like that thing can still actually lose a lot of money in production because of the again, so there's the adverse selection effect of you're only going to do a small fraction of the good trades, and you're going to do all the bad trades you want. Um, but also if you are actually making money at it, this is like a big shining signal to the rest of the world, like, "Hey, there's money over here, like why don't you compete it away?" Um, and so yeah, that's definitely a huge component of it.

   7. DPDwarkesh Patel39:23

      So you have a very interesting ch- chapter on, um, software and technology in the book, and one of the things you argue for is that we should take the concept of technical debt seriously in a financial sense. Um, so is one implication of this interpretation that you should be willing to accept, uh, technical debt more if you're a rapidly growing company? Because, you know, if like you're a startup that's growing fast, it makes sense to maybe take out a lot of loans because you can pay back the interest plus way more. Um, but maybe, maybe if you don't end up l- taking it financially, maybe that's... You would think that if you're like scaling rapidly, that's the worst time to take on all the technical debt because you're just going to be hampered the entire way along. So yeah, so more generally the question is, what kinds of firms, um, should be more willing to take on technical debt?

   8. ALAgustin Lebron40:08

      Yeah. Certainly startups is, is the classic example and it, and it's, and it's non-recourse debt, right? Like if it goes belly up, like you don't have to pay it back, right? You're done. Um, so, so yeah, like startups should definitely do this. And, and you see it all the time, right? This concept of, of an MVP where, you know, let's just get something out there, let's get some feedback from the users with the understanding that... Hopefully with the understanding that you're going to have to essentially rewrite it from scratch if it's successful. I think it's a very useful and very, very, um, uh, productive way to do software startups, um, because yeah, like the, the, the implied interest rate that you're willing to pay is incredibly high. Um, larger companies, it's interesting, like if you ask yourself... This is a kind of a conversation I had with, with, uh, with one of my good friends, um, who I actually did consulting with. He worked at Qualcomm for a lot of years and, and I asked him because he worked very closely with Microsoft, like, "Microsoft employs tens of thousands of software engineers. Like, what do they do all day?" And, and he said to me, like, "Look, I don't actually know for a fact, but I'm pretty sure the vast majority of them are like, well, this library is deprecated. We need to upgrade this thing. Let's change like all this like code and all these different little places." Right? So like there's just sort of a, uh, like a h- like a, like a sort of an archeology of software that occurs where, where, you know, if you build, if you've b- been building a software, piece of software for like 20 some odd years, like there's just all this cruft in there that you're just continually trying to maintain so that it's functional as you go from, you know, this OS to this other OS to the cloud to whatever, right? Um, so I think that's, that's kind of, uh, like an accumulated debt that, that large companies certainly have.

   9. DPDwarkesh Patel41:51

      Th- th- yeah, that's so interesting. They're just like servicing the debt they accumulated in like the '80s and '90s when they were growing rapidly.

   10. ALAgustin Lebron41:56

       That's right.

   11. DPDwarkesh Patel41:56

       And you can even think of like them moving to a new platform or like rewriting their code is like refinancing their debt or something.

   12. ALAgustin Lebron42:01

       Right, exactly. In fact, like I would say, um, probably the best ma- uh, probably the best book I have ever read about software development is actually, uh, science fiction, um, Vernor Vinge, uh, A Deepness In The Sky, I feel like is, uh, very crucially about... Like it sort of takes this idea like what if we've been building on the same software stack for 6,000 years? What does that look like? Like what does that world look like? Um, and I think it teaches us a lot about how to think about large software projects, large long term software projects.

   13. DPDwarkesh Patel42:33

       Yeah. So I'm super interested in how you guys think about software in the financial industry. Um, I know Jane Street uses, uh, OCaml, um, so th- and because I mean there's like safety... You can tell me more why this is, but from what I understand, it's like there's more safety in a functional, uh, functional programming language. Um, yeah, so how do you think about like...

   14. ALAgustin Lebron42:53

       Mm.

   15. DPDwarkesh Patel42:54

       Obviously, there's, m- much more reason to want to b- have, like, safe code because you're dealing with an adversary there in some sense. So, uh, yeah, I'm curious, like, how do you guys make the, uh, engineering decisions and what are the, like, the trade-offs involved when you're doing... when you're working in finance?

   16. ALAgustin Lebron43:07

       Yeah. So, uh, as you said, like, w- Jane Street uses OCaml. I think one of the, one of the biggest advantages of using that language is it, it is strongly and statically typed. And so you can put a lot of things, um, in the... Like, you can use the type system to make, uh, impossible states unrepresentable. This is, like, a really good software engineering thing you should do, and it makes it sort of very easy a- and, um, and rich environment to do that in. And so this, like, "Oh, I didn't know I had to handle this explode problem" is kind of minimized. Um, but yeah, like, you know, Jane Street and companies like it obviously optimize for avoiding hot loops in code that incinerate money really, really fast, and that is not what your average, whatever, SaaS startup optimizes for, uh, or it shouldn't be anyway. Um, but I, but the thing I keep coming back to in talking to, you know, technology leaders and that sort of thing is software development is fundamentally an exercise in sociology. Like, in organizing teams and in creating, uh, processes and culture and conventions, uh, around the building of software. Like, you know, software development is fundamentally the management of complexity, like, the science of managing complexity because it is incredibly complex, right? Um, and so all that sociological stuff ends up being some of the most important stuff to think about.

   17. DPDwarkesh Patel44:29

       Now that y- y- you're working in finance, but you have a startup, so you (laughs) have to think very carefully about this, um, trade-off, um, how... L- like, how are you managing this given that you have to, like, I guess, move fast, but you also need to be safe?

   18. ALAgustin Lebron44:41

       Uh, hire really, really good people, honestly. Like, don't skimp on those first few employees is, is, uh, I think a really important thing. Like, where, where the bar is kind of, uh... Like, the bar is kind of weird. Like, it's not, it's not like there's sort of one total ordering over a quality of engineer, right? There's like... They're incredibly multivariate. Um, but certainly, um, one really, really good thoughtful engineer who can build correct code is worth four not so thoughtful (laughs) people in a spot like that. And so that's kind of the thing we're optimizing for right now.

   19. DPDwarkesh Patel45:18

       And, um, such engineers, do you expect or give them a lot of, um, knowledge about, uh, finance, or can they just function knowing about engineering, uh, j- just about engineering, and then you can just, like, tell them, "We need a program that does this," or do they need to have an understanding of how trading and finance works?

   20. ALAgustin Lebron45:37

       So need is probably a hair strong, but certainly the culture that I want to build is one where it's almost need. Like, it's almost like want, right? Like, I, I would want to hire somebody... I want to hire somebody for whom understanding the problem domain deeply is a critical part of the job they feel they're doing. And so is it possible to build something like this, um, another way? Uh, probably, but, but that's not the company I want to build.

   21. DPDwarkesh Patel46:03

       Um, and so in your career, you've done so many different things, engineering, um, trading, uh, consulting. W- yeah, so, uh, h- how much carryover and lessons do you feel like you've had between these different domains, or do you feel like they're, um... Uh, th- they, they have, like, self-contained pools of knowledge?

   22. ALAgustin Lebron46:20

       So I think if there's one, uh, constant for me, it's I'm surprised by how much my previous careers inform my next careers. Like, when I, when I wanted to, to move from engineering to trading, um, it did continually surprise me how useful, like, the, the engineering training as opposed to just kind of, like, me hopefully being just generally smart and being able to figure things out. But, like, the actual engineering training was, was useful. Um, and then coming back to the consulting with companies, um, again, really surprising how... Like, I expected that, you know, when we were doing kind of the, the management and hiring consulting that it would be about the nuts and bolts of, okay, well, what does a good hiring process look like? What kind of interview questions do you want to build? How do we evaluate them? Et cetera, et cetera. And there's a component of that, but all of the other trading stuff, like how to think about the market for candidates and that sort of thing, like, it surprised me how, how non-obvious a lot of that stuff was to the people I was talking to. Um, and so now, yeah, like, hopefully bringing all of that... Those experiences, uh, to the table in, in this new startup that I'm doing, um, you know, I- I'm, I'm optimistic that that'll occur again.

   23. DPDwarkesh Patel47:30

       You would think that people like you who have so much experience, um, in so many different industries, they would be the most common archetype, um, of, of a startup founder, uh, because th- the... Like, they have so many general skills. Um, at least in popular culture, and maybe this isn't, uh, represented in, like, what is... Who, who are empirically the most successful founders, at least in popular culture, it seems like the trope is, you know, somebody who, like, has no particular skills (laughs) is the, is the person who, like, starts a startup out of college. And w- why are there not more founders who have, um,

9. 48:00 – 50:43

   The age of startup founders

   1. DPDwarkesh Patel48:00

      a broader skill set and lots of experience?

   2. ALAgustin Lebron48:02

      I, I think there actually are. Like, if I, if I remember correctly, maybe it's something I read maybe a year ago, the average startup founder is actually significantly older than, um, than sort of the popular conception. It's just that the young, flashy startup founder gets all the press, right? And, and perhaps rightly so. Like, I'm, I'm not besmirching, you know, the young founder's press. Um, but I think there's a lot of people kind of just doing it possibly with similar backgrounds to mine, um-I think it works.

   3. DPDwarkesh Patel48:31

      Th- there was one question I forgot to ask about adverse selection, um, which is if, if you're l- l- let's look at a company like Jane Street. If the counterparty knows that they're trading against J- Jane Street, um, and they know that Jane Street has a great reputation of making profitable trades, why does anybody even make that trade? And, um, I mean, as a follow-up, does that mean that Jane Street has to pay like a higher cost-

   4. ALAgustin Lebron48:53

      Mm-hmm.

   5. DPDwarkesh Patel48:53

      ... to make the same trade because it has, like, this reputation of making really profitable trades, which means that there's almost, um, a negative feedback loop of if you become too successful, like, the market makes it really hard for you to continue being successful?

   6. ALAgustin Lebron49:04

      No, I, I, the answer is no, and I'm pretty sure the answer is no, and the reason is because, again, getting back to this idea that Jane Street provides a service to the world, right? Like, so who are they ... Jane Street doesn't wanna trade against other market makers, and other market makers don't wanna trade against Jane Street 'cause they're in the same business and they know that like, that's not who they're gonna make their money from. Who they're gonna make their money from is people who need the service that Jane Street provides. So for example, like if I am a pension fund or if I am a, um, you know, a large, um, hedge fund or something and I wanna put on a bet in some random country, maybe I should just buy that country's ETF, right? It's certainly a lot easier, more straightforward, convenient, um, to just buy the ETF than to go to that country's stock market and buy all the individual stocks, right? And so that's not a thing that they're ex- they're an expert in, right? They're not an expert in trading Vietnam stocks, right? They're just an expert in making these macro bets, let's just say, right? And so Jane Street provides them the service of being able to sell them that ETF, um, and then Jane Street takes care of all the, all the little details, right? That's the thing that Jane Street is really good at. And so there's gains from trade there. It's not, it's not zero sum in that sense.

   7. DPDwarkesh Patel50:14

      Um, and what is the role of, um, market makers in crypto if you have automated market makers, um, like Uniswap or something? So then wha- wha- what is the, what is like the comparative advantage of, I guess, smart, uh, market makers?

   8. ALAgustin Lebron50:28

      Well, so I think the thing I would argue is, and it, perhaps you've seen this paper from like last fall, but that, that shows that at least half of liquidity providers on Uniswap V2 lose money. They just lose money. And that's on prior is what you would expect,

10. 50:43 – 57:31

    The role of market makers in crypto

    1. ALAgustin Lebron50:43

       right? Like, let's say that there was no fee on Uniswap, right? Like let's do liquidity providers just toss their money in, then like liquidity providers are systematically getting adverse selected against by every trade that happens, right? And so the fee that you collect as a liquidity provider is a compensation for the adverse selection that you are undertaking by being a liquidity provider, but, of course, that fee is sort of set by fiat, right? Like it's either the five-bit pool or the 30-bit pool or whatever. Like it is not adaptive to like market conditions, right? And so I, I am personally long-term skeptical about CFMMs as a market mechanism that is going to work. I just, I don't see how, I don't see how it makes sense for somebody to just like throw some money in a pool and expect to get sort of outsize returns by just doing nothing, right? Like outsized returns come from you knowing how to do something or being able to do something nobody else does, right? And so it just, it doesn't strike me as a, as an exciting thing very long term.

    2. DPDwarkesh Patel51:43

       Does that mean that you're also pessimistic about passive investing in the long term of somebody just like putting a source of, you know, putting a certain amount with their money the S&P?

    3. ALAgustin Lebron51:50

       So the difference there ... I think the difference there is passive investing is at least, again, over a long haul, you are providing risk capital to companies that are hopefully sources of discounted future profits, right? And so there's like, there's a reason that you might expect that to make money for you. Um, whereas when you're, when you're trading either FX or something that doesn't like earn yields from, from like actually providing value to the world, then n- no, you probably shouldn't expect to make money (laughs) by passively investing in that.

    4. DPDwarkesh Patel52:21

       What made you interested in getting into crypto at this time, uh, transitioning to that industry?

    5. ALAgustin Lebron52:26

       Yeah, so I think the thing about crypto that I like is to the extent that you b- believe in this somewhat stagnationist theory that, look, whether it's through regulation or just cultural changes or whatever, that we're not doing bold, new, exciting, weird things, uh, the extent to which crypto is a shelling point around which everybody has decided, "Look, all of the crazy weird stuff that we want to try, we're gonna do it here." I like that. I think that that is a very good thing to, for the world. And if, and I'm not saying this is going to be the case, but if all of crypto goes to zero and all that's happened is we've had a large wealth transfer from the rich olds to the young, like people who want to build cool stuff, like that's still good for the world, you know? (laughs) Like, I think it's gonna be more than that. I think there's a lot of interesting, exciting things that are gonna, that are gonna come out of the crypto world. Um, but you know, at, we get at least that, right? Like a, a coordination around trying new things.

    6. DPDwarkesh Patel53:22

       If, if that doesn't work, um, and in like taking your negative example as, um, let, let's say that's a hypothetical. Wh- I, I actually do wonder, but what is the actual wealth transfer that's happened here? Is it actually been from ... 'Cause like if, um, if institutional investors have not gotten that much into crypto as compared to like, you know, some grandma, maybe not grandma, but like, I don't know, some middle-aged guy. Um, so then has the act- has the actual wealth transfer been from wealthier to poorer, or I wonder if it's been the other way around?

    7. ALAgustin Lebron53:48

       I think it ha- I think it has to have been. Like, loo- look at all these, you know, look at all these VCs raising all these funds, like the LPs in those VCs funds are olds, right? (laughs)

    8. DPDwarkesh Patel53:59

       Yeah. There, there's a good story to be told about adverse selection in venture capital as well. Um, so, um, but yeah, so that, that's, it's basically a transfer of wealth from like VCs to (laughs) VCs to like 21-year-olds.

    9. ALAgustin Lebron54:10

       Yeah, the other thing about, like the other thing about crypto, like people always, especially people from Jane Street, like whenever I meet them again and you know, say, "Hey, how's it going?" Like almost the first question they ask me when they find out what I'm doing is like, "So what, like are you all laser eyes now? Like what's your deal?" And I think by crypto standards, I think I'm very non-laser eyes, um, in the sense that this is probably gonna be an unpopular opinion within the crypto world, but I think success for crypto definitely looks like integration into the financial system.Like, it just, it's not like it's going to replace it. It's not gonna be like, "Oh, Goldman and Chase are gonna go to zero and, and, uh, Coinbase is gonna crush it." Like, n- that's not what it looks like. Success for crypto looks like traditional finance integrates, takes the best ideas, and crypto companies are incredibly successful in that process, but we end up with something that's kind of a hybrid of the best of both. Like, I think that's success.

    10. DPDwarkesh Patel55:01

        Yeah. And I'm curious, so like what does, um, what, what does the future look like in a world where crypto is very successful? Like, for example, what, what would, uh, w- uh, what would, uh, something like the stock market look like if, um... Uh, w- would it be, like, far more efficient if it's over crypto, or would it be less efficient because of gas fees, um, or b- but, you know, maybe it's, like, payments internationally?

    11. ALAgustin Lebron55:20

        Right.

    12. DPDwarkesh Patel55:20

        But yeah, I'm curious what you think, like, 20 years down the line, the success case for crypto looks like.

    13. ALAgustin Lebron55:24

        Um, so I'm gonna leave the financial markets to last. Like, I think Western Union is outta business is probably a good outcome. Like, it's probably good. All those stupid, um, like, all those stupid, uh, Thomas Cook money exchange in the airport things are outta business. Like, that's probably good. So like, if a- if only that happens, I think we're already in good shape. Um, certainly, the, the idea of NFTs as transferrable, uh, signals of, um, uh, facts about you or facts about whatever persona or avatar you wanna have, um, I think is pretty exciting. Like, the idea that I have to, like, call my university and get a transcript from them and stuff, like, that seems insane to me. Um, and the, in the, like, how, how some of these, uh, kind of credentialing systems can work with NFTs strikes me as, as a fairly natural thing. Um, I think to the extent that, um, that crypto is breaking the oligopoly of a few, uh, large financial participants in the market today, I mean, I, I don't know if you, you followed the saga of the CFTC, uh, review of FTX's proposal to, to, to do sort of a different kind of, um, futures margining process on, like, on actual real futures. I think this is a good thing. Like, there's a lot of vested interests and entrenched interests that are kinda getting their bell rung, and, and that's a good thing. So that's, that's kinda the direction that I would, that I would take it, sort of the, uh, the financial infrastructure or the plumbing of, of finance is probably gonna be sort of crypto-ified. That doesn't mean it's all going on chain. I think, you know, all a blockchain is is a very slow, weird database, but it is a very slow, weird database that has some useful properties in some situations.

    14. DPDwarkesh Patel57:03

        Uh, what, what are three books you would recommend?

    15. ALAgustin Lebron57:04

        Uh, Deepness In The Sky. Deepness In The Sky by Vernor Vinge. If you're a software engineer and you like science fiction, you know, read it with the eye towards thinking of it as a softer book is a thing I would say. Um, if you wanna think about kind of risk-taking in general, uh, Aaron Brown's Red-Blooded Risk is... I'm, I'm trying to think of books that probably people haven't heard of. Um, Red-Blooded Risk by Aaron Brown is really, really, really good. In fact, all of his books are really good. Like, um,

11. 57:31 – 58:47

    Three books that you recommend

    1. ALAgustin Lebron57:31

       the thing that got me interested in finance was reading his book, uh, The Poker Face of Wall Street 'cause I was playing poker at the time, and it's kind of like, "Hey, maybe Wall Street, maybe that's a thing." So The Poker Face of Wall Street by Aaron Brown or, uh, the Red-Blooded Risk. Um, and one that's, uh, kind of off the wall a little bit is, um, it's called Kolyma Stories by Varlam Shalamov, and it is a collection of stories about people who s- who sort of lived in the gulag in Siberia during sort of Stalinist times. Um, I think it is possibly the most revealing book about human nature that I've ever read. Um, it's depressing. Like, don't... Like, read it in a sunny place, you know?

    2. DPDwarkesh Patel58:08

       (laughs)

    3. ALAgustin Lebron58:09

       But, but it's, uh, it's revealing.

    4. DPDwarkesh Patel58:12

       Is this a covert way of telling us about the working conditions at Jane Street?

    5. ALAgustin Lebron58:15

       No, not at all. (laughs)

    6. DPDwarkesh Patel58:17

       (laughs) Um, yeah, so fi- final question is, um, y- you know, you've been, um, successful in so many different, uh, industries and you've, you know, you know the lessons of, uh, you know, working in so many of them. So i- is there advice you would give to, like, somebody who's in their early 20s? Um, I guess most of my audience is probably going to, to the extent that they're working in those industries, are probably gonna be programmers, but n- I don't know. Maybe after interviewing you, I'll, I'll have, like, a few traders or wanna-be traders who are listening as well. So yeah, if, if you have, like, some advice you w- w- w- think would be useful for somebody who's very young.

12. 58:47 – 1:03:01

    Life is long, not short

    1. DPDwarkesh Patel58:47

    2. ALAgustin Lebron58:47

       Yeah. I would say, like, number one thing I was, I tell my kids this all the time, like, life is long. Like, life is not short. Life is long. And what that means is you should think of yourself as having many opportunities to learn things and try things and do things. And so again, this is just my own experience, but, um, I feel like I'm sort of sequentially obsessive. Like, I will sort of block off six years of my life, it turns out. Like, empirically, this is what has happened to, like, get really, really good at a thing. And then, like, okay, next six to seven-year period, I'm gonna try to get really, really, really good at another thing that is kind of different. Um, and that's worked out for me because, um, it's easy to undervalue the importance of deep, deep, deep expertise in a thing and the process that it, that is required to get really, really good at something. Um, and so this idea of kind of sequential excellence I think is a thing that I, that I like to think about a lot, um, 'cause you have the time, right? Like, spend five years being a, you know, a front-end developer and get just incredibly good at that. And then, you know, go do something else. Maybe it's not programming. Maybe it's something else, right? Um, and maybe come back to it, right? And you'll have this other perspective. Um, yeah. That's kinda my thought.

    3. DPDwarkesh Patel1:00:07

       Yeah, that, that's super interesting. I'm curious if you think, um, like, uh, l- let's say you had... Uh, I guess it wouldn't be possible with crypto, but, like, let's say you had been a trader, like, you had, instead of doing electrical engineering and computer science, you had just, like, done trading, uh, from the very get-go. Would you have been... By the end of your trading career, would you have been more succes- uh, suc- successful in the counterfactual where you've been a trader the whole time or one where you had the experience from engineering? And then, you know, same with, uh, consulting. I mean, um, yeah, so I, I, I guess, is the career path with a lot of, um, deep specialties but changing what that specialty is over time, is that, does that lead to a higher peak in the end or the one where you just focus on one career?

    4. ALAgustin Lebron1:00:46

       Yeah, it's a good question. I think it probably varies by person. Like if you are, um, if you are destined or have the capacity to be a world-changing physicist, then probably you don't do any of the sequential weirdness. You just kind of go down that road. Um, but well, maybe- maybe I'm gonna... I'm- I might edit that, because one thing that I do believe about- about discoveries, whether it's in trading or in science or anything like that, is there's sort of two types. There's the evolutionary type, which is take a body of work or a field and just sort of push the boundaries out on it a little bit, and then there's the revolutionary type. There's the, like Albert Einstein, there's the Claude Shannon, um, these sorts of people where it's like, "I'm just gonna invent a whole new field," right? And so actually Claude Shannon's kind of an informative case, because he famously just basically played games all day and just thought about random things and- and kind of tried to have as broad, uh, an exposure to things as he could. I mean, rode unicycles and that sort of thing. So, you know, maybe- maybe like you- you need to be a little bit self-aware about kind of which of the two you might- you might be.

    5. DPDwarkesh Patel1:01:55

       Yeah. Okay, so the book is The Laws of Trading, available on Amazon. Um, and yeah, do- do you wanna give your Twitter handle plus may- any other place where viewers can find you?

    6. ALAgustin Lebron1:02:06

       Sure. So yeah, it's AugustineLeBron3. I don't know why three, but that's what it is. Um, I mostly talk about trading, sometimes talk about software, um, sometimes talk about random things in the world. Um, yeah, that's- that's... I- I am not much of a social media guy. In fact, if it hadn't been for the book, I pro- I would still be a social media non-existent person, but I- I've kind of gravitated towards Twitter. It's where- where I end up having interesting conversations.

    7. DPDwarkesh Patel1:02:34

       Yeah, yeah, I've enjoyed being a follower. Um, is there anything, uh, is there anything we didn't touch on in the conversation that you think might be, uh, might be interesting to close on or, um...

    8. ALAgustin Lebron1:02:42

       Well, I mean, um, selfishly, I wanna ask you Dwarkesh, like tell me about what you're doing. Like, what- what is this that- that you're building here?

    9. DPDwarkesh Patel1:02:50

       That's a good question. Um, yeah, so this was, um... To give you the backstory on this, this was, I- I think my sophomore year of college or maybe junior year, um, COVID

13. 1:03:01 – 1:04:40

    Short history of Lunar Society

    1. DPDwarkesh Patel1:03:01

       hit and I was really bored because classes went online, and so I just, you know, started the podcast. I just cold emailed my first guest. Um, yeah, actually by the time I was releasing, I didn't even have a name for the podcast because I just had like a recorded episode, but so anyways, just kept it up, um, and then I graduated like four months ago. Actually, technically graduated like two weeks ago, but I was done with my classes four months ago, and then I thought, all right, I have a little bit of money saved up from an internship and then another grant, and so I thought, all right, let me just do this like full time for a few months and see what happens, and got some traction. So, um, I don't know where this leads, but actually the comment you made about, um, um, the, you know, going deep on one particular thing and then maybe have... Using the skills you learned there to transition to another, that, uh, that makes me feel a lot better because I don't think my long-term trajectory is, um, being a podcast host or writing a newsletter, uh, but I do... So, you know, I'm, I would like, love to go back to tech and startups, um, um, you know, like in the future. I have a computer science degree. But, um, yeah, so hoping to learn as much as possible through the podcast and writing and then hopefully use the skills I learned there to do some cool things in other fields.

    2. ALAgustin Lebron1:04:18

       Love it. Sounds like a great plan.

    3. DPDwarkesh Patel1:04:21

       Yeah, yeah, yeah. Thanks. Um, awesome. Yeah, thanks for coming on, Augustine. This was one of my favorite podcasts I've done. It was so many insights.

    4. ALAgustin Lebron1:04:27

       Awesome. Thanks Dwarkesh. Really enjoyed it.

Episode duration: 1:04:40