Ep 115: Scott Wu, Devin, and a Trillion-Dollar Opportunity

22:18I was going to say, it's computer science classes, for example, arguably, they actually don't teach you how to go and build real-world software. Or their concepts. A lot of it is more just, yeah, how do you think about breaking down logical problems? How do you think about algorithms? How do you think about the model of a computer and what a computer can and cannot do? And I think a lot of the, people ask me all the time, my son or daughter is 16, should they even be studying computer science? And I always say, yeah, absolutely. And I think the reason is because these are the concept level things that actually allow you to be a really good thinker about deciding what to build.

22:54No, I think we're going to need more people who have good at logic and are able to build things, that's for sure. It's interesting because the demand seems like it's going up for software engineering. And the more you make it cheaper, the more the demand goes higher, right? So, right now, what is it? It's about a trillion dollars a year we pay engineers? Do you know what the numbers are? It's multiple trillion, yeah. It's multiple. There's about 30 million software engineers in the world. And my favorite stat that I always love to share is right around the turn, you know, the 1999-2000, you know, which was internet boom.

23:21Obviously, these things were, you know, these things were just, were becoming really, really big. There were actually less than a million software engineers back then. Really? Wow. The thing that's kind of interesting, I think, is to your point, it's we have never really run out of demand for software. And if anything, already over the last, from 2000 until now, if you just think about Python and React and Cloud, we've done a lot of things that have made it much easier to go and build software. And yet, of course, the number of software geniuses has gone way up because we've just done way more things with software.

23:54And I think we're going to see something similar here where it's, you know, imagine what we will do, you know, when we get to the point where everyone can just build products and websites and apps and whatever it is of that level of quality of some of the best apps out there. You know, we will just build a lot more of these. It's very interesting because a lot of people are worried, for example, the Indian economy has like these five giant software firms where it's like long-tail outsource software engineering. A lot of people are saying all these agents are going to compete with that, but there's a way in which the agents can just like make those people more productive.

24:25Is what you're saying? Yeah. And look, it's, I mean, the, the, the skills will change certainly, you know, and I think this kind of pure, pure implementation version, you know, is, is, yeah, I mean, it's, it's going to be different in a few years. But I think a lot of the fundamental skills of building software, you know, if you think about as a simple example, you know, it's even today, if we say, oh, this person, they're like a really great engineer, you know, what do we mean? Usually it's not that they like type really fast or that, you know, right. A lot of it is that they are just really good at thinking about these abstractions.

24:58They understand every case and every detail. You know, they know about all of the, you know, the kind of like higher level decisions that have to be made to build and architect something well. Right. And I think that is the general shift where over the next few years, things will move more and more to that in terms of what human engineers are spending their time on. Okay. So I want to ask you about the culture of cognition in this company you're building. You're hanging out with these obviously top minds in math and physics and competitive programming all together. And like all these cultures are probably there late at night together all the time and doing stuff.

25:30And this is Devin's growing all over the world. It's gone viral in Japan. It's gone viral all around the U.S. And as I was mentioning earlier, my little brother, at first he was critical of this when it came out. It just didn't work for what he wanted. And now his whole company is using it to be way more productive. And it's a really good sign because your little brother is always negative on things you're doing. So it must be good then. But so you guys have this amazing thing that's growing. What's the culture internally? And when you talk about the future, what are you guys thinking about it?

25:55And by the way, when you hang out, I hear you play math games with each other. Tell us about this. Yeah, yeah, yeah. So we do a lot of math games for sure. No, I think the, look, I was saying from the beginning that we started in a house and we did another hacker house and we did another hacker house. And in some sense, we never really stopped doing that. I feel like it's been a hackathon for like the last year and a half. And it's, you know, we have about 30 people on the team today. And one of the crazy things is actually, you know, yeah, we have a lot of people who came from this kind of like, you know, Olympiad background in math or programming.

26:26But we actually also, 19 of us, I think, were founded a company before, 19 or 20 of us. Wow, so you've got a bunch of former founders. A bunch of former founders. And I think it's an experience that's relevant, I think, in a lot of different ways. And I certainly had the same experience as well, building Lunch Club, which is, yeah, I mean, you do run into a lot of these challenges and learn a lot of these things. But also, it gives you a lot of fire, I'd say, for all of us to just be like, this is the one. We're going to make this the really, really big one. We're going to make this the massive success.

26:55And that's what we're all motivated and excited to go for. There's a lot of agency from founders. like everyone's just taking it and running with it, which is cool. Yeah. Yeah. And I think with this, it's, I mean, there's, there's a lot of big decisions that we need to make, you know, this is true on obviously on the capabilities work, but it's also true on the product side. It's true on go to market and so on. And so, um, yeah, no, we, we have a lot of fun. I mean, it really is a lot of very, very late nights, you know, folks are, are, um, pretty often, pretty regularly in past midnight. Um, what's an example of a math problem you give the team that was too hard for our listeners.

27:27just yeah okay so so so the one of the games that we play is um there's a game called 24 where you you put out four if we have a deck of cards we can play but it's uh you you you put out four cards and and let's say it's you know eight seven four and two okay um eight seven four and two and so now the question is you have to yeah i'm gonna you're gonna i'm gonna make you do this by the way yeah let's do it let's do it okay so so you have to you can use any operations add subtract multiply divide okay and you have to use all four of the numbers you You can put them in any order. You can use parentheses or whatever.

27:59And you have to make that equal 24. You have to do an expression with all four of these numbers. Got it. So you have to use these four numbers as fast as possible to get to 24. Yeah, as fast as possible. But you can't reuse a number. You can't reuse a number. So seven times four minus eight over two. Great. Yeah. So eight over two is four. Seven times four is 28. 28 minus four is 24. There we go. Very fast. It's good. It's good. Yeah. So, you know, at some point that got too easy. And then we did it with six cards. And then you were making 163. And then there was like eight cards and making the current year and stuff.

28:25And then this is a game that we used to play all the time when we were growing up and stuff. But there's been some fun ones. Yeah. So I'll give a hard one. Give us a hard one for our listeners. Yeah. Yeah. Yeah. So you have the numbers 3, 4, 5, 8, and 13. Uh-oh. Okay. And you're trying to make 198. You're trying to make 198. Yeah. All right. And so we're going to pause and fast forward this now. Yeah. Then one second later, Joe comes up. Okay. Pause. Okay. but you can't just combine them you have to do operations basically that's kind of cool so it's like what is like for the power of yeah this is a lot harder than the other one this is harder yeah i can probably get it actually it's it's it's tough yeah yeah if i think it i think it would take a while yeah got it okay well we'll we're yeah no no hey hey turn it off i i can just i I can just tell you that.

29:23I'll just tell you that. Okay, tell us. So you do 13 divided by 4. 13 divided by 4. That's a really sick thing. That's actually crazy. I would not have intuitively gotten that one. Yeah, and then you add 5. 3.25, so 8.25. Yeah, 8.25. And then that times 8 is 66, and that times 3 is 1 and 8. Wow, so it's 8.25 times 8 times 3. Yeah, yeah. That's probably harder. There's no way to do it without doing fractions. There are a lot of fun ones like this. that there must be some other way where it's like where it's like you know three to the power of five and then do something else you just can't do it how you try it it's uh yeah yeah so so there's there's there's none yeah yeah usually it's uh you're not allowed to use exponents if you were you could do a three to five minus four times eight minus 13 that's that's what i was working um but but without exponents i think the only way you can do it is with these fractions so the fun ones i think are the ones where yeah it's it's not just integers you know that you're working with amazing amazing okay let's do an even harder math problem first person to solve in the comments we're going to send you some swag scott what's a harder one all right all right let's do it so i'll give another one of these uh making a number so if you have four five six ten ten and ten so three tens and then a four five and a six can you make 163 and again you can only use add subtract multiply divide you have to use all the numbers once each you can put them in any order but you know your equation has to have exactly three tens for example you can't have more or less.

30:45All right, audience, go to it. All right. Well, thank you. Thank you for showing us that when you're not doing math problems together, which I think is really cool. I think I remember last time I was, I was, you guys were talking about the future and debating and you say you're an optimist. Cause a lot of people in my world, there's like this messianic branch where it's like, we're creating this God and everything's gonna be totally different in 10 years. And then like other people are like, Oh yeah, it's really negative. It's going to like be centralized power and control and destroy everything.

31:11Whoever gets in charge, the top but yeah, it's going to be negative. And then there's also the optimistic points of view. What's your optimistic point of view here? Yeah, yeah, absolutely. In one line, my co-founder Walden says this all the time, which I love, which is, we've been spending our whole lives in Minecraft survival mode, and now we're going to get to play Minecraft creative mode. And that's like the, yeah, I think that really is the really exciting future that we're heading towards. I think the main thing I would just call out It's like, I think human creativity, human passion, you know, desire to build things and meaning.

31:48I don't think that stops because we have some really smart AI or anything like that. Right. And I think we're, if anything, we're going to be able to spend a lot more time doing that. You know, we're going to do really cool things. You know, one of the things that I always think about is like, if you just imagine folks from thousands of years ago, you know, looking at us today, like sitting here talking about this, right. And it's, it's funny to think that in the sense that like, probably most of, of what, You know, most of these white collar jobs out there, it would be crazy for them to even think about it as work.

32:14You know, it's like you sit there, you have, you know, you're talking in the room with other people. Maybe you're pushing buttons on this thing or whatever. And you call that work. You know, you're not in the fields. You're not actually like pushing things around. And I think that we will go through like another level of that, honestly, with AI. Where it's, similarly, it's, you know, we might still call it work and think of it work. But it's going to look more and more like really pursuing your own passion and building great things and building really cool things. And I think that, yeah, and I think that that's going to, you know, it's like it's at the end of the day, I think we've made a ton of progress over the last, you know, thousands of years.

32:49But there is still like a lot of suffering. There's still like a lot of, you know, things that we don't need to have, basically. And I think getting to the point where people can really just do what they want to do and build really exciting things and put things into their life's work that they create is really exciting. I mean, with Devon especially, I mean, we're all programmers ourselves, obviously. And so, we love coding. You know, we love building software. And I think one of the big things that is really, really exciting about it is, yeah, you don't stop building software just because, you know, you can have AI that helps you write code, right?

33:24I think if anything, yeah, we're going to have way, way, way more great products. And we're going to have way more great ideas that we're going to be able to bring to reality because it's so easy. Everyone has so many ideas that they have of what they want to do and what they want to build. And being able to turn that into reality is just really exciting. So we're recording this before the Reagan Economic Forum I'm going to this week. So I'm thinking in economic terms right now. And I love what you said with this positive Minecraft trader mode. And so in economics terms, that means that productivity goes way, way, way, way up.

33:51And it's massively disinflationary. And you just create things cheaply, whether it's farming, whether it's building, whether it's health care, whether it's education. How do you think of the timeline? I know it's kind of an unfair question because you're thinking a very positive vision of this 10 years out. Do we start to see productivity just shoot way up in the next few years? When should we expect this? Or how do you think about that? Yeah. And I think we have, honestly, we have a special lens into this because I'd say code is honestly the fastest growing use case of AI out there. And I think it is representative in the sense that, look, in code, it is real.

34:25It is very clear that if you're not using AI, you are just slower. But I don't think that leads to kind of a negative for us in the sense, if anything, it means that we all get to build a lot more and we all get to do a lot more. And so, I think that is kind of the shift that we're going to see in a lot of these fields. I think on a per-person basis, each person is just going to have their own team of AI assistants that's going to help them do a lot more. And it's actually amazing if you think about it. The U.S. economy is, well, it's like a$20 trillion economy, depending on different ways of measuring it.

34:57So if you make productivity go up 10%, that's a$2 trillion a year, which equity-wise is a$20 trillion thing in one year. So even 5 % is in the order of$10 trillion of equity value. So it's actually fascinating. The positive sum nature of this stuff works, it's worth tens of trillions of dollars. And so how do you think of the possible value and opportunity of something like Devin? I think this actually is a multi-trillion dollar opportunity because it's fixing such a big space. Is that the right way to think about these things? Yeah, yeah, for sure. I mean, I think for us, it is the, you know, the central question that always roots us in basically all of our product decisions and all of our strategic direction and so on is, it's just like, what is the future of software engineering?

35:37You know, I think it's, I think in startups, people often get caught up in, you know, kind of figuring out fancy tactics and things like that. But it always, obviously, it always starts from what is, you know, what is the future and what is the value that we're going to provide? And a lot of it for us is just that the fun thing about this space is that the answer to that question basically changes every couple of months in the sense that, you know, you hit a new tier of capabilities, you build models that can do these crazy new things. And that changes the whole experience of like, what is the right way that humans should be working with AI to write code?

36:07What's a recent tier that you feel like you've hit? Can you give us some insight? Yeah. One of the big ones that we've just rolled out actually is basically the ability for humans and AI to just, you can use AI to interactively plan and scope out the task. And then once that's ready, you can just hand that off and go. um the similar thing is just even you know getting to the point where every time you file a ticket in slack or a linear or grr or whatever service you use you know it's you just you just have your coding agent go and work on that right and i think it's crazy to think about because you know a few years ago for example like the um you know github copilot and others were kind of some of the first to really kind of pioneer the ai coding space and you know this single line where it would give you a suggestion which you could tap complete like that was all you could do in code you know it was Because we had models that were pretty exciting, but obviously they weren't good enough that you would trust them with these bigger things, right?

36:58And I think one of the really cool things actually is a crazy stat, which is if you look over the past few years since that kind of tab completion era, you can kind of think of an AI model or an AI system in terms of how much work it can do in between interventions from a human, if that makes sense. and so it's like you know can it do five minutes of work of human work straight in between you know an intervention and because once the errors get to be too much it just has to stop basically but doesn't always know to stop right yeah yeah yeah it's like until like the human has to step in and give more feedback or something like that and the crazy thing is over the last like three four years that number has basically it's doubled approximately every three months wow um which is you know two x every three months is four doubles every year which is 16x right and it's i mean it It is kind of, you know, over three years, that's about 4 ,000x, which is correct.

37:48What is it over a decade? Two to the 40. Which is a lot. It's about a trillionx. That's a big number. It's a big number. And so, obviously, we'll see how long that continues. And so far, it shows no signs of slowing down. But, you know, it really has, over the last few years, gotten from systems where it can just complete the line for you and just do that two seconds of typing for you versus now we have systems that are going to do hours of work. You know, they're going to go build a feature or solve a bug. I think it's about a quadrillion, by the way, Scott. Not a trillion. It's a quadrillion, right?

38:16Am I wrong? Two to the 40? That's a million square. Damn it. Can we delete that part? I'm just kidding. I keep trying to get him. I lose. I'm terrible. Yeah, it's a million square. This is a million square. This is really bad. I shouldn't challenge him. You had me worried for a second. That's funny because that would be a big deal. Yeah, yeah. Okay. I was going to ask you to cut that in. No, yeah.

38:43you know don't worry you're right scott and what does this mean for large organizations because there are a bunch of them adopting it they're getting more productive yeah like are they gonna you know there is a question like people have stopped hiring quite as many engineers the last few years maybe they over hired in 2021 though like what should we think about that yeah i think there are certain economic factors economic factors that came into there but but i would say it's it is very clear if with with every engineering team you know i've never met an engineering team that's told me, all right, you know, we have this project and then we're going to do that project and then we're done.

39:12No more software, you know, that's it. Right. I mean, every team has a hundred things that they want to build and that they want to ship, but they have to pick, you know, four of them to do this week because that's, that's all they have bandwidth for. Right. And I think that the, um, yeah, I really do just think that the demand for these things is going to grow. One of the things that I think about all the time is, you know, if you think about these, the best products in the world out there today, right. And in my mind, that's probably, you know, YouTube, Instagram, TikTok, things like that. And obviously they have tons and tons of hours and tons of usage, but, but they're about as close to perfect as, as we get in software today, I'd say where it's, you know, the, the algorithm is amazing.

39:50It knows every little detail about me. You know, the it's, it's streaming a ton of data and it's able to do that super efficiently. It never goes down. The product UX is super, super intuitive. It always, you know, it's really easy to understand what, how to do what you want to do. Um, and, and, and that's kind of the top tier, right? And, And, you know, let's say that's, call it 100 million hours of engineering time that we've put into that, you know, across tens of thousands of engineers or something, right? And so, that's kind of the absolute top, right? And every tier, you know, every order of magnitude that you go down, you feel it.

40:21You know, there are products out there that have tens of millions of hours. And I'm thinking about a lot of, you know, banks and healthcare products and things like that, which, you know, I use these all the time as well. And you can feel like the difference of the bugs that you run into or little things that are unintuitive or don't quite work or really should be easier. And then you go to the products that have 1 million hours and then 100 ,000 hours and so on. Right. And, you know, eventually you get all the way down to your, you know, your local like school website or something, which is like.

40:46You can't use it. It's from like 2001 or something. You know, and so it's, I guess what I would just say is like, it is, there's so much more out there to build. And I think it is very clear that there are a lot of products and a lot of product experiences that could really use like a lot more care and a lot more effort. And if anything, we're only bottlenecked by how much we can build. I'm seeing later today my friend who's like using AI to like build roads with like construction machines and stuff and other things. I feel like, do you think like all these new possibilities are going to be made easier from what you're doing?

41:17Like are we going to be able to all of a sudden train things to do things they couldn't do before? Yeah, yeah. So I think it's, we're entirely focused with software engineering. And there's, I think, a lot of bespoke problems in code. And that's what we want to spend all of our time on. But yeah, I think it's happening everywhere. And to your point, I think there is kind of this cross acceleration, right? I mean, there are a lot of companies that hire software engineers, not just software companies, right? And I think in general, there's a lot of things that we can just continue to make more and more to just keep accelerating.

41:46Software engineering does seem to be the highest level of abstraction for doing things in the world, I guess, is the leverage point for everything else. So, you know, what are you most inspired by in terms of like recent breakthroughs otherwise? Like what else is most exciting to you? Yeah. Yeah. I mean, it's honestly, it was a pretty exciting moment for me to get to see. There's been a few things that came out over the last year. Google had a really amazing result where they got a silver medal at the International Math Olympiad. And then OpenAI had a really great result where they got to approximately the top 100 competitors in the world in competitive programming.

42:18And it is really, it's, it is. Yeah. Yeah. I feel like I've had my AlphaGo moment over the last year to kind of seeing that. And it is really, really cool. And I think what it kind of shows, I would say, is actually, I think we're at a point now where intelligence actually isn't the bottleneck, if that makes sense. I think these models are capable of solving some really, really hard problems. And a lot of the work that's being done right now is just figuring out how to make the models really good at your hard problems. And there's obviously a lot of specificity. This is true in software engineering.

42:47You know, there's things that you spend years and years on learning all the details of how does this thing work? How do you use this library? You know, what does this mean? How do I debug this error or whatever? Right. And that's a lot of the kind of more practical work, I think, that's happening everywhere in AI right now, where it's, yeah, we've shown that the models are capable of doing some really, really hard stuff. And so, Scott, to end this here, you know, I love that you're building probably one of the most advanced companies in the world in this space, creating the future. You're doing it in America.

43:14You said you're an optimist. You're an American. Why is America the right place for this? Like, are you proud to be an American? Like, what's it have to do with what you're doing? Yeah, well, I'm very proud to be an American, I'd say. And I mean, I think a lot of it is just, yeah, is believing in merit, I would say, in one line. I mean, I think that innovation is incredibly important. And I think that it's, if anything, over the next few years is only going to become more important. And I think making sure we have the right culture and the right circumstances and everything that allow folks to just build new things and come up with new ideas and iterate and try things.

43:51And, you know, many of those will not work, but some of those will. And I think that's a lot of what's really beautiful, I'd say, about the American spirit. I love it. And if it does work, it looks like it's going to create a really bright future. Were we going to, you said, would you say it was Minecraft what? Minecraft creative mode. I love it. That's a very positive vision to end on. Scott, thanks for joining us. Thank you so much for having me. Music Music