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. 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 Lebron, who is the author of the laws of trading, a trader's guide to better decision making for everyone. This is 1 of those books, you know, Tyler Cowen calls these quake books that completely shift the models you have of the world. I I I really, really enjoyed reading this book. So, yeah, I'll let you describe your background, Augustin. But before that, let me just let me ask this question. So Peter Thiel says that the Strawsian reading of 0 to 1 is that you shouldn't start a startup. And I think that tell me what you think about this. I think the Strawsian reading of the laws of trading is that you shouldn't trade. Right? Because you probably don't have edge because you're not better than a marginal trader. And if you think you have edge, it's probably because you unfactored in risks and other costs. So don't trade. Is is that is that what I should take away from this book? I think you you pretty much hit the nail on the head. Like, a lot of the times that that people 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 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. Okay. Yeah. So do you wanna do you wanna talk about your background and then what you've been working on in the past and what you're working on now? Yeah. So so my background is engineering. That's kinda what I did in university. I did engineering for about, 6 years professionally. I was a chip designer. At the time, I was playing a lot of online poker back when that was a profitable and arguably legal thing to do. And so engineering was getting kinda boring, 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. So January 2008, walked into my boss's office, and I said, I wanna quit. And and he said, oh, where are 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? He said, yep. No. I'm dead set on it. And a few months later, managed to get a job at Jane Street and and wrote out the implosion of western civilization from from the seat of a trading desk. So we did that for a few years and then, left Jane Street a few years ago and started my own consulting company. Basically, just helping come tech companies with growth things like management and hiring and that sort of thing. And in the last few months, started a new company, in the crypto space. How much are you willing to, 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. Yeah. No. I mean, big picture, we're building a a crypto protocol that is, kind of new and has some pretty cool cryptographic guarantees, against things that people don't like, when they trade in crypto. Yeah. So let's get into some of the topics in the book. So, yeah, 1st, I wanna talk about average selection because this was, you know, this was the most interesting part of the book for me. So let let me ask this question. 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 employee is not the highest bid, but the average bid that they would get paid on the market? Yeah. You're right. From the employer side, it's definitely adverse selection all around. Like, 1st 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, 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. And so the people who are kind of on the market are probably at the margin not as good. 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 adverse adversely selected there because, you know, the people who are really, really good are gonna have lots of job offers, and so they're gonna pick from 1 of many offers. The people who aren't so good are going to pick from few offers and so employers just systematically get adverse selected that way. 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. It's true certainly that people by 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. It's not clear which way it washes out, I think, to me. Yeah. Bern Hobart, I recently wrote a blog post about your, this chapter in your book about adverse selection. And so 1 of the things you said in a footnote almost in passing was that there should be more adverse selection in industries like finance where 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, 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, there's something suspicious about that. No. I I think there's something to that. Certainly, you know, doing a lot of the hiring that I used to do, 1 of the biggest, 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 1st 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. Oh, interesting. Because in your chapter on motivation, it seems like you were implying that that is the motivation you should be looking for. Because if their motivation is emotional, then they're going to be losing to people whose motivation is to make money. So I yeah. I I'd love for you to talk more about what what is the motivation you are looking for. 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, all I wanna do is make the most money possible is correlated to things that, that aren't maybe so great. Like because a lot of the job is, is sort of having an inherent curiosity about random things, for example. And 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, enjoying the game for for, like, you know, sort of as an exploratory kind of thing. So maybe that's, like, maybe a little bit inconsistent with something that I wrote in the book, but but I think at the margin, people need to hear the other thing more. 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, it's a company like Jane Street would hold it against you if you have, like, retail trading experience because, I guess, you can talk more about why that is. But yeah. So if that's not what you're if that's not how you judge whether they would intrinsically enjoy the job, how how is it that you would judge that? So I 1 of the things I've always said, maybe you've heard me say this before, is I would love to talk to the person who is the 3rd 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, a willing 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. But, yeah, just general Again, aside from sort of the mathematical and and and sort of risk taking parts, which are sort of maybe independent from this, certainly a strong desire to be in a competitive environment and to enjoy being in that environment. I think that's, you know, that that can take many forms, but I think that's a big part of it for sure. So then why is having domain expertise in trading not important? Is because usually in other industries, it's like if you the more experience you have in the industry, the better. And it seems like you guys are often hiring people who are just very analytically smart, but maybe you haven't been traders before. So, like, how how do you guys manage to do that? Why is that important? I guess the the thing I'm thinking of is that the concept of a domain is probably a lot narrower than people understand it to be. Like, if I'm there sitting there on my Robinhood account punting stocks back and forth, like, that is not the same domain as what a trader at a market maker or a top trading firm would do. 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 have you're 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. 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. 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. So you said in the book, it takes, like, 6 6 to 18 months before you can train a trader to be net positive. What is happening in that time? Like, what what what are the skills you're teaching them? 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. And so it's just a continuous stream of questions, answers, conversations, etcetera. Jane Street, to their credit, has improved on that. 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 think about that? Hey. Did you think about that? What would you do in this situation? Why? Why not? Etcetera. And that just that just takes time. I wonder so as you mentioned, you've done a lot of, you've helped in a lot of hiring for tech companies. I wonder if, how applicable this model is to the tech industry. So, I mean, could a company like Google just have a very effective boot camp where they get, like, people who study, like, physics or math at MIT? And maybe not necessarily computer science, but, you know, if if you don't know that much programming, you can still come in and then we'll make you, you know, 10 x in a very short amount of time. Or is that something special about finance and trading? 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. 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 0.1 percent 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, and putting them in these sort of boot campy situations, for, you know, 6 months or something where they learn, you know, useful skills. And at the end of it, there's, like, a 6 figure job with a western company. Like, there's no reason that that companies like Infosys or 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 1000000000000 dollar business potentially, or maybe it's a nonprofit, I don't know, in in closing this arbitrage gap. Your former colleague, Sam Beckman Fried, he, you know, obviously, the CEO of FTX, and he has, you know, started a big charity called the Future Fund. And 1 of their project ideas is exactly what you're talking about where you would 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're, like, scouting out this talent? Yeah. So I think 1 of the things that maybe isn't isn't terribly polite to talk about, but I think is critical is just g, intelligence. Like, it strongly predicts outcomes across jobs, across industries. And so you that is some element of it. That is certainly some element of it. But also, would say, 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 kinda 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 hardworkingness, stick to itiveness, whatever you wanna call it to use a principle Skinner term. And so, yeah, like, some combination of those 2 things, I think, are pretty are almost definitely predictive of of actual value. Have you have you heard of Pioneer? The thing started by Daniel Gross? Yes. I have heard of it. I don't know much much about it. 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 make building a startup like a video game. So Right. With, you know, the associated risk rewards and stuff. How do you deal with adverse selection in cases where, theoretically, adverse selection should work for you? But, you know, like, the counterparty prices in the possibility of getting a lemon. So, like, an example would be I'm 21 years old, and I'm a male. So it like, car insurance premiums for me are huge even if I'm if even if I'm a good driver because, you know, there's, like there 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 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. So how do you how do you deal with such scenarios when you're on the other side of the adverse selection? Yeah. Certainly, I think in the car insurance situation, I am fairly sure there are now car insurances that essentially put, like, a 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, I imagine that that you can sort of decrease your address selection by by taking advantage of those kinds of things. In the case of the the employment thing, that's a tougher 1. 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 wanna 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? 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. 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, you know, putting yourself in the right positions. And that I think that's that's maybe a a skill that's that that you learn over time, hopefully. Yeah. So I've 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 actual jobs. So, you know, questions that are almost brain teasers. Right. But there there's a kind of a Chester's and Spence argument you can make that it's like if all the tech companies are doing it, there must be some important reason why they are. So 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? 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. However, you can kinda 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. 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 legitimate justification that as long as you could show that it is important for job performance, then you can kinda 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. 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. 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, 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 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. Yeah. And maybe it makes sense to select for the latter type of person as well. Right? Or I don't know. We we we just prefer able to hire. But Well, so so I think this is the thing about about companies. Again, there's a lot of schizophrenia in tech hiring. 1 of the things that's clear is everybody says they wanna hire a players, but only a small fraction kind of by definition can hire those those sort of high percentage or a 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. 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. And so you try to select for, like, an 80th percentile person, but you end up selecting, like, a, like, a set of 50th percentile person people who'd 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 1 or 2, like, 90th percentile people and I should evaluate for and in particular pay for that. And then the rest, I should try to hire a 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 the company, but nobody wants to hear that. And nobody wants to build a company like that. That's a great example of, like, a barbell strategy. So I'm wondering, do do you have any ideas of what good arbitrage opportunities in tech hiring might be? I know I think SpaceX, some of their early engineers were from the gaming industry because they're very used to doing optimization problems there. But it's it's not that's traditionally a high status career. So there there's, like, arbitrage 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 at Google or something? Yeah. So I think 1 of the things I always tell companies is go more junior. Like, if you look at 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 I'm talking about somebody who just came out of, like, a reasonable CS program. Right? And you look at their salary 3 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 be like, there's definitely a kink at the 2 to 3 year point because every startup there I mean, every tech company seems to wanna have 2 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 1st 2 years. And if they do, they tell themselves, well, they're just gonna leave after 2 years to go for a higher paying job somewhere else. 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 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 kinda getting the the the inertia working in your favor anyway. So, like, let's work on these things. Sounds very similar to the sheepskin effect of the last semester of college. So the the it it Brian Kaplan has a good really good argument about this in case of an education, which is that the last semester of college, like, boost your earnings many times more than the percentage of college you spend in that last semester. And it can't be because you're, like, learning that much more in the last semester, which I guess sets up an arbitrage opportunity for hiring people in, like, right before they're about to finish their last year or something. But you see, like, 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 2 to 3 years 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 2 years, and, like, you're not seeing the really, really good ones. Intuit's keeping those. Right? So 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 is what the reason so is this just, I guess, you you just have to do the you had to trade whatever market that you have to at the moment? Or because I would think you say in the chapter on edge that 1 of the ways you can actually get is to specialize. So is it a mistake of firms to let their traders over their career trade in multiple different categories, or is that necessary in order in order to build your general aptitude as a trader? Yeah. So I think it's a balance. 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 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. And I think it would be a pretty big mistake to put me in that situation. But within, we'll say that the the well defined realm of, like, quantitative trading, I think a lot of the same skill sets apply in different markets. Like, you're you're kinda 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, it 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. So, yeah, I think it's a balance. So I I I think finance is 9% of GDP. So I understand the argument that, you know, finance helps allocate scarce resources to where they're needed most. But if we're giving up, like, a 10th 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 a liquidity and price discovery? So is finance too high a fraction of GDP? I go back and forth on this question. I really do. Because kind of when you see it from the inside, a lot of it is 0 sum competition. And and it feels like, come on, there's gotta be a more efficient way to do this. But at the same time, of outside view, we haven't come up with a more efficient way to do this. And it's hard to argue with GDP growth. And so I kinda go back and forth on it. Certainly, I think the other thing about it is, there's 2 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. 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 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 that we should be doing, are biased towards thinking like, yeah. You know what? This is probably a good thing to be doing or 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. And then would that that would that fraction shrink without without harming efficiency if like, are there inefficiencies created by government regulation or by restrictions on capital flow? 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? That's also a tough 1. And and it's and it's not that I haven't thought a lot about these. It's just I feel like I don't have 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? There are some things that I would regulate more, and this is probably gonna be a very unpopular opinion among my my financial friends. But, like, I think leveraged ETFs should be banned from from retail trading. Like, I think this they're just kind of a bad instrument, in particular, like, all the volatility products. So I feel like that should probably be regulated some more. 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 status and let people invest in whatever they want? Or should we make it even more restrictive? I'm not sure about that 1. And certainly, the other thing about it is, like, 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 3 and that's gonna be, like, an extra thousand employees for every large bank in the world. That's probably kind of a deadweight loss, but but doing things more simply doesn't seem like it's gonna 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. What is the longer and future of trading firms look like? So if 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 okay. I mean, economic growth speeds up, if markets get more efficient over time, then, again, you would expect the profits that any 1 trading firm can get to decrease. So is there a future for highly profitable trade firms like Jane Street, like, the far future? 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 gonna be profitable. Now, are they going to gain, like, we'll call them excess returns? 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, but sometimes it's really good, like, when when there's lots of market volatility and that sort of thing. 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, 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. It seems unlikely to to to to stop, just because you sort of gain the the benefits of the the economies of scale just kinda keep going up. 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, there's gonna be, like, a big consolidation over the next 10 years. I think that's the natural arc of things. Oh, interesting. So yeah. Yeah. Can you describe what these economies of scale look like in finance? And 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 smaller investments where you can't take as big a state without moving the market? Yeah. So the thing about finance or, like, market making trading in general is 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 gonna be are there 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 companies or a large successful companies trader 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 j street traders who are now at home and kind of doing it on their own for fun. So I think those will always kind of be there. Is there a potential that markets can get, like, way, way more efficient if we have we don't have much stronger AI? And and at at what point will the work that even traders do that's, like, much more I don't know. Much more model generation and, like, thinking abstractly. At what point can that even get automated away and not just, the road calculations? Yeah. I would say it's already getting and gotten, 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 kinda the limit. Right? When I was doing it, like, we could handle, a 100 stocks. Right? Market making in a 100 stocks. Again, technology just made technology just made everything more efficient or more efficient in human time. 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've all I have all these overfitting predictions. 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, think it's, 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, 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 kinda 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 as slowly but surely, 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, disappeared away. 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 because they had 1 steam plant and they had to, like, all these belts and stuff to, like, use the the power from that 1 steam plant. Right? And then, like, electric motors happen and it's, 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. That seems inevitable to me. I'm curious why you're skeptical that, like, a scaled up GPT 3 or other language large language model. I'm curious. So why does it not have applicability in financial markets? Like, I I know there's, 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 so why why is that unlikely to happen? So there's a couple of things that I might say. 1 is is the concept of sample efficiency. Like, these things are incredibly sample inefficient in a way that the way the 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 is the things that our brains have, which are structures for, 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 the the models, like, they're incredibly impressive. But it's still a Clever Hans thing. And so there surely must be a better architecture out there much like our brains have these sort of architectures that 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 that I don't think GPT 3 certainly has has evidenced. 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 Buchanan Fried. He's you know, he he he went into Jane Street with the explicit goal of earning to give. Yep. Tyler Cowen announced that $20,000,000 have been donated to his Immersion Ventures grant program from Jane Street traders. And, you know, even reading your book, like, reference so many thinkers that are prominent in, like, rationality spheres. And you there's just to be a big overlap with this community and with at least a part of the shredding world that I'm familiar with. Now that could just be selection selection effects. But what what is going on here? Yeah. It's a great question. I think maybe at 2 levels. 1 is the idea of being very rational and not fooling yourself and 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, think, in the 2 circles or at least probably it should be. 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 1 thing that Jane Street has going for it differentially from those other firms maybe is, the 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. And so I think that's there's a lot of overlap there. 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 gonna be a very natural fit for you. And I think maybe that's some of it too. When I had Bern Hobart on the podcast, we talked about whether debugging or finance was a better application of, like, rationality principles because in each case, gotta, like, update your beliefs and so on. And 1 interesting point he brought up was in finance, you have you not only have to model, like, a static system as as you would had in debugging, but you also have to model other agents and their incentives and their motivations, which makes it a much more, like, dynamic system to get a hold of in your brain, which I guess may it could even mean that, like, the tools or, like, the current rationality movement are not good enough to, you know, be able to think about those things as well as probably you guys that have natively developed in the industry. Yeah. And look. I the the cross pollination goes both ways. But, yeah, the the idea of of you being an agent in the world you're trying to study is fundamental in trading, and it makes it, like, so much more interesting. I think that's 1 of the getting back to the AI thing just because it occurs to me is 1 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 dataset, and I'm gonna get a trading strategy. And okay. That's great. Like, let's say you you've 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 gonna do a small fraction of the good trades, you're gonna do all the bad trades you want. 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? And so yeah. That's definitely a huge component of it. So you have a very interesting chapter on software and technology in the book. And 1 of the things you argue for is that we should take the concept of technical debt seriously in a financial sense. So is 1 implication of this interpretation that you should be willing to accept technical debt more if you're 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. But maybe maybe if you don't have to take 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 you're just gonna

Be hampered the entire way along. So yeah. So more generally, the question is what kinds of firms should be more willing to take on technical debt? Yeah. Certainly, startups is is the classic example, and it and it's and it's nonrecourse debt. Right? Like, if it goes belly up, like, you don't have to pay it back. Right? You're done. 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, productive way to do software startups Because, yeah, like, the the the implied interest rate that you're willing to pay is incredibly high. Larger companies, it's interesting. Like, if you ask yourself, this is a kind of a conversation I had with with with 1 of my good friends 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, like a like a like a sort of an archaeology of software that occurs where where, you know, if you build if you've been building a software a 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? So I think that's that's kind of, like, an accumulated debt that the large companies certainly have. The the the yeah. That's so interesting. They're just, like, servicing the debt they accumulated in, like, the eighties and nineties when they were growing rapidly. And you you can even think of, like, them moving to a new platform or, like, rewriting their code as, like, refinancing their debt or something. Right. Exactly. In fact, like, I would say, probably the best probably the best book I have ever read about software development is actually, science fiction. Wernher Binge, A Deepness in the Sky, I feel like is, very crucially about like, it sort of takes this idea, like, what if we've been building on the same software stack for 6000 years? What does that look like? Like, what does that world look like? And I think it teaches us a lot about how to think about large software projects, large long term software projects. Yeah. So I'm super interested in how you guys think about software in the financial industry. I know Jane Street uses OCaml. So 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 there's more safety in a functional functional programming language. Yeah. So how do you think about, like obviously, there's a much more reason to want to have, like, safe code because you're dealing with an adversary there in some sense. So, yeah, I'm curious, like, how do you guys make the engineering decisions, and what are the, like, the trade offs involved when you're doing when you're working in finance? Yeah. So as you said, like, James Street uses OCaml. I think 1 of the 1 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, in the like, you can use the type system to make, impossible states unrepresentable. This is like a really good software engineering thing you should do, and it makes it sort of very easy and and, 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. But, yeah, like, you know, Jane Street and companies like it obviously optimize for avoiding hot loops and code that incinerate money really, really fast. And that is not what your average, whatever SaaS startup optimizes for, or it shouldn't be anyway. 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, processes and culture and conventions, 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? And so all that sociological stuff ends up being some of the most important stuff to think about. Now that you're working in finance, but you have a start up, so you have to think very carefully about this trade off. How like, how are you managing this given that you have to, like, I guess move fast, but you also need to be safe? Hire really, really good people, honestly. Like, don't skimp on those 1st few employees is is, I think, a really important thing. Like, where where the bar is kind of, like, the bar is kind of weird. Like, it's not it's not like there's sort of 1 total ordering over quality of engineer. Right? There's like they're incredibly multivariate. But, certainly, 1 really, really good thoughtful engineer who can build correct code is worth for not so thoughtful people in a spot like that. And so that's kind of the thing we're optimizing for right now. And such engineers, do you expect or give them a lot of knowledge about finance, or can they just function knowing about engineering just 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? So need is probably a hair strong, but certainly the culture that I wanna build is 1 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 another way? Probably, but but that's not the company I wanna And so in your career, you've done so many different things, engineering, trading, consulting. Yeah. So how much carryover and lessons do you feel like you had between these different domains, or do you feel like they're they they they have, like, self contained pools of knowledge? So I think if there's 1 constant for me, it's I am surprised by how much my previous careers inform my next careers. Like, when I when I wanted to to move from engineering to trading, it did continually surprise me how useful, like, the the engineering training as opposed to just kind of, like, may hopefully being just generally smart and being able to figure things out. Like, the actual engineering training was was useful. And then coming back to the consulting with companies, again, really surprising how like, I expected that, you know, when we're doing kind of the the management and hiring consulting that it would be about the nuts and bolts of, okay. Well, what is a good hiring process look like? What kind of interview questions do you wanna build? How do we evaluate them? Etcetera etcetera. 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, surprised me how how non obvious a lot of that stuff was to the people I was talking to. And so now, yeah, like, hopefully bringing all of that those experiences, to the table in in this new start up that I'm doing, you know, I'm I'm optimistic that that'll occur again. You would think that people like you who have so much experience in so many different industries, they would be the most common archetype of of a startup founder because, like, they they have so many general skills. At least in popular culture, and maybe this isn't 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 is the is the person who, like, starts a start up out of college. Why are there not more founders who have a broader skill set and lots of experience? I I think there actually are. Like, if I if I remember correctly, and maybe this is something I read maybe a year ago, the average startup founder is actually significantly older than 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. But I think there's a lot of people kind of just doing it possibly with similar backgrounds to mine. I think it works. There was 1 question I forgot to ask about adverse selection, which is if if you let let's take a company like Jane Street. If the counterparty knows that they're trading against Jane Street and they know that Jane Street has a great reputation of making profitable trades, why does anybody even make that trade? And, mean, as a follow-up, does that mean that Jane Street has to pay, like, a higher cost to make the same trade because it has, like, this reputation of making really profitable trades, which means that there's almost a negative feedback loop of if you become too successful, like, the market makes it really hard for you to continue being successful? No. 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 because 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'm a, you know, a large 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, 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 they're an expert in. Right? They 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. 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 0 sum in that sense. And what is the role of market makers in crypto if you have automated market makers like Uniswap or something? So then what what what is the what what is, like, the comparative advantage of, I guess, a smart market makers? Well, so I think the thing I would argue is and perhaps you've seen this paper from, like, last fall, but that that shows that at least half of liquidity providers on Uniswap v 2 lose money. They just lose money. And that's on priors what you would expect. Right? Like, let's say that there was no fee on Uniswap. Right? Like, let's say 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 5 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 outsized 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. Does that mean that you're also pessimistic about passive investing in the long term of somebody just, putting a source of, you know, putting a certain amount with their money in the S and P? 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. Whereas when you're when you're trading either FX or something that doesn't, like, earn yield from from, like, actually providing value to the world, then no. You probably shouldn't expect to make money by passively investing in that. What what made you interested in getting into crypto at this time, transitioning to that industry? Yeah. So I think the thing about crypto that I like is to the extent that you 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. The extent to which crypto is a shelling point around which everybody has decided, look, all of the crazy weird stuff that we wanna 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 the crypto goes to 0 and all that's happened is we've had a large wealth transfer from the rich olds to the young, like, people who wanna build cool stuff. Like, that's still good for the world. You know? 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. But, you know, we get at least that. Right? Like, a a coordination around trying new things. If if that doesn't work, and then, like, taking your negative example as let let let's say that's a hypothetical. I actually do wonder, what is the actual wealth transfer that's happened here? Is it actually been from because, like, if 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. So then has the has the actual wealth transfer been from wealthier to poor, or I wonder if it's been the other way around? I think it I think it has to have been. Like, look look at all these, you know, look at all these VCs raising all these funds. Like, the LPs in those VCs funds are old. Right? Yeah. There's there's a good story to be told about adverse selection and venture capital as well. So but yeah. That so that that's it's basically a transfer of wealth from, like, VCs to VCs to, like, 21 year olds. The other thing about, like, the other thing about crypto, like, people always especially people from Jane Street, like, whenever I meet them again or, you know, say, hey. How's it going? Like, almost the 1st 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 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 0 and and, Coinbase is gonna crush it. Like, 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. Yeah. And I'm here. So, like, what is, what what does the future look like in a world where crypto is very successful? Like, for example, what what would what would, something like the stock market look like if, would it be, like, far more efficient if it's over crypto, or would it be less efficient because of gas fees? Or, you know, maybe it's, payments internationally. But, yeah, I'm curious what you think, like, 20 years down the line success case where your crypto looks like. So I'm gonna leave the financial markets to last. Like, think I Western Union is out of business. It's probably a good outcome. Like, it's probably good. All those stupid, like, all those stupid Thomas Cook money exchange in the airport things are out of business. Like, that's probably good. So, like, if if only that happens, I think we're already in good shape. Certainly, the the idea of NFTs as transferable signals of of facts about you or facts about whatever persona or avatar you wanna have, 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, seems insane to me. And the and the like, how how some of these kind of credentialing systems can work with NFTs strikes me as as a fairly natural thing. I think to the extent that that crypto is breaking the oligopoly of a few large financial participants in the market today I mean, I I don't know if you you followed the saga of the CFTC review of FTX's proposal to to to do sort of a different kind of, futures margining process on, like, on actual real futures. I think this is a good thing. Like, there's a lot of vested interest and entrenched interest that are kinda getting their bell wrong, and and that's a good thing. So that's that's kind of the direction that I would that I would take it. Sort of the, 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 the blockchain is is a very slow, weird database, but it is a very slow, weird database that has some useful properties in some situations. What what are 3 books you would recommend? A Deepness in the Sky. A Deepness in the Sky by Werner 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. If you wanna think about kind of risk taking in general, Aaron Brown's Red Blooded Risk is I'm I'm trying to think of books that probably people haven't heard of. Red Blooded Risk by Aaron Brown is really, really, really good. In fact, all of his books are really good. Like, the thing that got me interested in finance was reading his book, The Poker Face of Wall Street, because I was playing poker at the time, and I was kind of like, hey. Maybe Wall Street. Maybe that's a thing. So poker face of Wall Street by Iron Brown or, the red blooded risk. And 1 that's, kind of off the wall a little bit is, it's called Kalima Stories by Varlam Shalimov, and it is a collection of stories about people who who sort of lived in the gulag in Siberia during sort of Stalinist times. I think it is possibly the most revealing book about human nature that I've ever read. It's depressing. I don't I read it in a sunny place, You know? But but it's it's revealing. Is this a covert way of telling us about the working conditions at Jane Street? No. Not at all. Yeah. So final question is, know, you've been successful in so many different industries, and you've you know, you know the lessons of, you know, working in so many of them. So is there advice you would give to, like, somebody who's in their early twenties? I guess most of my audience is probably going to to the extent that they're working in these industries are probably gonna be programmers, but don't know. Maybe after interviewing you, I'll I'll have, like, a few traders or 1 of you traders who are listening as well. So, yeah, if if you have, like, some advice you think would be useful for somebody who's very young. Yeah. I would say, like, number 1 thing I always 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 I feel like I'm sort of sequentially obsessive. Like, I will sort of block off 6 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 6 to 7 year period, I'm gonna try to get really, really, really good at another thing that is kind of different. And that's worked out for me because, 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. And so this idea of kind of sequential excellence, I think, is a thing that I that I like to think about a lot, because you have the time. Right? Like, spend 5 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 some

Else. Right? And maybe come back to it. Right? And you'll have this other perspective. Yeah. That's kind of my thought. Yeah. That that's super interesting. I'm curious if you think, like, let's say you had 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, had just, like, done trading from the very get go. Would you have been by the end of your trading career, would you have been more success successful in the counterfactual where you've been the trader the whole time or 1 where you have the experience from engineering? And then, you know, same with consulting. I mean yeah. So I I guess, is the career path with a lot of these specialties but changing what that specialty is over time, Is that does that lead to a higher peak in the end or the 1 where you just focus on 1 career? Yeah. It's a good question. I think it probably varies by person. Like, if you are, 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 kinda go down that road. But, well, maybe maybe I'm gonna I I might edit that because 1 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 2 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. 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 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 2 you might you might be. Yeah. Okay. So the book is the laws of trading available on Amazon. And yeah. Do do you wanna give your Twitter handle plus any other place where viewers can find you? Sure. So, yeah, it's Augustine LeBron 3. I don't know why 3, but that's what it is. I mostly talk about trading, sometimes talk about software, sometimes talk about random things in the world. 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 I I would still be a social media nonexistent person. But I I've kinda gravitated towards Twitter. It's where where I end up having interesting conversations. Yeah. Yeah. I've enjoyed being a follower. Is there anything is there anything we didn't touch on in the conversation that you think might be might be interesting to close on? Or Well, I mean, selfishly, wanna ask you, Durkash. Like, tell me about what you're doing. Like, what what is this that that you're building here? That's a good question. Yeah. So this was to give you the backstory on this, this was I I think my sophomore year of college or maybe my junior year, COVID hit, and I was really bored because classes went online. And so I just, you know, started the podcast. I just cold emailed my 1st guest. 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, And then I graduated, like, 4 months ago. Actually, technically graduated, like, 2 weeks ago, but I was done with classes 4 months ago. And then I thought, alright. I have a little bit of money saved up from an internship and then another grant. And so I thought, alright. Let me just do this, like, full time for a few months and see what happens and got some traction. So I I don't know where this leads, but, actually, the comments you made about the, you know, going deep on 1 particular thing and then maybe you have using the the skills you learned there to transition to another, That that makes me feel a lot better because I don't think my long term term trajectory is being a podcast host or writing a newsletter. But I do so, like, you know, I'm I I would like love to go back to tech and startups, you know, like, in the future. I have a computer science degree. But yeah. So we're 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. Love it. Sounds like a great plan. Yeah. Yeah. Thanks. Awesome. Yeah. Thanks for coming on, Augustine. This was 1 of my favorite podcasts I've done. It was it so many insights. Awesome. Thanks, Rakesh. Really enjoyed it.