Inside Devin: The world’s first autonomous AI engineer that's set to write 50% of its company’s code by end of year | Scott Wu (CEO and co-founder of Cognition)

0:00 Whole team is only like fifteen engineers, so you're we use a ton of Devon when we're building Devon. Most folks on the team are definitely working with up to five Devons at once. And so Devon merges like Several hundred pull requests into production in the Devin codebases every month. It's in the neighborhood of a quarter or so. Where do you think this will be at the end of the year? Honestly, yeah, we expect it to be a decent bit more than half. You guys are so ahead of how companies work with AI engineers. AI is going to be the biggest technology shift of our lives most of the big tech Revolutions that we've had over the last 50 years, like personal computer and the internet and mobile phone, they all had this big hardware component that was a big part of the distribution. Folks who were building for those industries kind of saw their market grow and grow and grow basically steadily year over year as the number of people with mobile phones increased, right? As the number of people connected to the internet increased. One of the things which was already I'd say different in AI is just how explosive the technology can be. There's no weight on hardware distribution. It means that the space is just growing so exponentially. How is the act of being an engine and building changing? I think there's gonna be way more programmers and way more engineers a few years from now. Pretty quickly, the form factor of what it means to be a programmer, obviously, is gonna change. But at the end of the day, of course, the discipline is all about

1:12 Just being able to tell your computer what to do. And so in that lens, I really think that programming is only gonna become more and more important as AI gets more powerful. Today, my guest is Scott Wu. Scott is the co-founder and CEO of Cognition, which makes a product called Devon, the world's first autonomous AI software engineer. Unlike other AI tools that I've highlighted on this podcast, Devin is designed to act like an actual remote engineer that you chat with. Like you would with any other human engineer through Slack. or through its dedicated website.

1:40 When Devin launched about a year ago, it was very much a junior engineer. Over the past year, they've made a lot of progress, and Devin is now being used by tons of companies in production. We chat about how their engineering team of fifteen uses Devons. to build Devon, including how every engineer uses about five Devons each to help them code and move faster. How a quarter of their pull requests today are committed by Devons. And that they expect us to be over fifty percent by the end of the year. We also talk about how Scott imagines software engineering is gonna look in the future, and how the role of an engineer changes from a coder to an architect.

2:13 We also get into the eight pivots that they went through before landing on this path. Why Scott believes AI tools like this will lead to more engineer hiring versus less. Also where the name Devin comes from, and so much more. This episode is going to blow your mind. I highly recommend you listen to it if you're at all interested. about where engineering, product building, and AI is going. A huge thank you to Claire Vaux for suggesting a bunch of great questions for this conversation.

2:38 If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. Also, if you become an annual subscriber of my newsletter, you get a year free of linear superhuman notion perplexity. And granola. Check it out at lenny's newsletter.com and click bundle. With that

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5:26 Scott, thank you so much for being here and welcome to the podcast. Thanks so much for having me. Excited to be on. I'm really excited to have you here because you are building and you've been building something that is very different. From what a lot of other AI companies have been doing for a long time, although they are starting to converge. To where you guys are now. We're gonna talk about that. And

5:45 It's also just such a unique point in the history of AI and just the journey of AI. And so it's really Cool to be chatting right now. And I feel like we're gonna chat again in a few years and be like, Wow, we were so right about so much and so wrong about so much. Yeah.

5:59 And so I'm excited to have you here. Let's start with Talking about Devon, giving people an understanding of what just what the heck Devon is. This is the main product that you guys build. What is the simplest way to understand what is Devin? Absolutely. And so Devon is a fully autonomous software engineer.

6:13 that is gonna work on tasks end to end. And so there are a lot of great tools for all all parts of the stack of the AI code workflow. What Devin does is it is a a a full asynchronous workflow. And so you can tag Devin on an issue in Slack, you know, you're talking about Dev an issue and you tag Devin, you can tag Devin in linear, you can have Devin and and Devin will make pull requests in your GitHub. And so it's very much built to To work with engineering teams a a as your junior engineer. Amazing. Okay. So I remember when you guys launched this, there was like this big pitch of this is your new AI engineer. And it was it was really good at a lot of stuff. It wasn't great at other things. It's been a year now about since you guys launched, is that right?

6:50 Yeah. Yeah. What's the best way to think about like the level of seniority that engineer had back in the day when you guys launched and then the level of seniority of engineer today, if that's I don't know, a measure of how to think about Devin. Yeah, and it's crazy to think about, by the way, because you know, a year ago when we did the initial launch, I mean, people didn't really believe that an agent was possible.

7:08 Right. And it was a very I mean it was a very different time. You know, it's uh Uh uh like start of twenty twenty four, you know, things with model capabilities were definitely quite a bit earlier on. Uh reasoning especially was was quite a bit earlier on. And uh and and yeah, I mean in in the time since then It's obviously developed a lot, I think, in terms of uh practical skills. You know, we we there there's some comparisons we make. Sometimes we kind of say, well, when we got started, it was kind of like a high school CS student, and then as time went on, it became more of like a college intern, and now it's like a junior engineer. But but I would say though that those those are more like rough guidelines because I I I really like the phrase jagged intelligence, for example.

7:46 Because there are obviously there are certain things that it is much better at than a human, there are certain things that are it's much worse at than a human. And I think over the last year we've We've learned a lot, especially about Not just coding agents, but agents in general, just like really building out like How

8:00 All of us should be working and interacting with agents as part of our flow. And so a lot of the things that we've built, I mean it's you know, there was no Slack. Uh, there was no GitHub integration, there was no linear, there was no interactive planning phase working back and forth, there was no way to touch up Devin's code. And and so a lot of the the the features that we've built on the product side since them have really been about Basically, yeah, figuring out how to how to make working with Devin and handing off tasks to Devin as smooth of an experience as possible. That's so interesting. So a lot of the work has gone not into

8:30 How do we just make Devin the best possible engineer, but it's had a work with this new type of entity that we haven't ever worked with. I think it's a fifty-fifty of both. You know, I I I think the uh the the capabilities obviously, you know, have have improved a ton and we've seen these get better and get measurably better. But I think the other side of it is everything to do with Yeah, really the product interface and the tools and so on. And and I think You know, I think today

8:52 Folks generally know how to use chat bots and to work with chat bots, right? And that's an interface that that people are familiar with. And and obviously with agents, it's you know, it's it it's it's still like a real curve, I think, to to learn how to use them and how to get the most out of them. And so it's it's really exciting to see a lot of others starting to to build and do a lot more in the agent space as well. But I I I I think this is the kind of thing that we're we're all really figuring out together as a space. What can you share about just the scale of Devin at this point, whatever you're comfortable sharing? And then just where do you think the level of Devin's coding abilities will be? in a year. So we work with companies of all stages and sizes. You know, on the smallest end, it goes to, you know, startups of just one or two people who are using Devon to to build out a lot of their kind of like a initial prototype or initial product all the way up to, you know, big public companies, Fortune one hundred companies or uh or public banks or things like that who are using Devon like across their

9:42 um across their engineering teams? In general, it's you know, we we've seen a huge range of of the use cases there. And obviously the kinds of engineering work that you're doing at a one or two person startup is very different from the kind of work that you're doing at a at a public bank. But but throughout it's all been Uh basically yeah, being being that junior buddy of yours that that that that makes you go faster and and really multiplies you, I would say. You know, I I I think there's uh It can multiply you as an engineer, obviously, by just like letting you work with your own team of Devons, uh, instead of having to be kind of like fulnous on a single task. And then it's also kind of like mo multiplying your team and multiplying your your team's knowledge base because Devon really accumulates a lot of the knowledge.

10:19 uh from from working with every member of your team and is able to bring that into each new session. Awesome. We're gonna show people how it actually works later in the podcast. We're gonna do a few live demos. Well let's actually go to the beginning of the journey. What's just the origin story of Devon? How did this all begin? The the founding team, I mean, most of us have known each other for for years and years and years actually. And and for for almost everyone, this is our first time working together, but we've known each other a long time. And we all actually had our own kind of journeys in in AI for the last last decade or so.

10:47 Um, and so for myself, you know, uh I I ran a company called this uh before this called Lunch Club, which was an AI for a professional networking product. And I ran that for about five years. And you know, my co-founders one of my co-founders, Steven, was was one of the first engineers at a company called Scale AI, which has obviously grown a lot and done very well. Uh, my other co-founder, Walden, was an early engineer at a company called Cursor. Which has also obviously grown a lot and done really well. And uh and our whole team kind of like was kind of like that. You know, many of us knew each other from from from competitive programming and math competitions, but we had stayed very closely in touch, you know, in the in the decades since then, and we've all kind of all had our own journeys. And so, you know, we had we had one person who was running teams that Neuro, we had one person who was at Waymo, someone who had their own Y C tool startup.

11:29 uh for for machine learning and and uh and we were really excited to build something together. And and this was around like late twenty twenty three, um, so about a year and a half ago at this point. And yeah, when we got started, I I mean I think There there were a couple of things that we felt really strongly about. And one was that

11:45 Reinforcement learning was really working and was going to be the next big paradigm shift in capabilities. You know, back then It was you know, the initial chat GPT launched in twenty twenty two and and and those models were to first order were you know what we would call imitation learning. I in in AI, right? Which is basically, you know, you have the model read all the text that you can find on the internet.

12:06 and then train it to talk like somebody on the internet would talk. Right. And and and there they're kind of uh obviously a lot more details on top of that, but that's that's kind of the first order pass of of what was really done. And it was amazing, right? I mean it passed the turning test, it it it it was able to respond and to to have encyclopedic knowledge about a lot of things. And I think this new paradigm which we've gotten into over this last year or year and a half is is really high compute RL, which is which is a very different paradigm, right? Which is basically the ability to go and do work on task and put something together and then be evaluated on whether that was correct or incorrect and use that knowledge to decide. what to do and and and to learn from that, right? And so

12:43 You know. We felt very strongly that that was gonna happen. I think it for us is Code was the natural thing to work on for a couple of reasons. One, because you know, we're all programmer nerds ourselves, and so Teaching AI to code is about as cool as it gets for us. But but also because you know, code has this whole automated feedback loop, right? Where you can run the code. And and that is the kind of automated feedback that really feeds into to the RL, which makes these models so great at coding. And then the other thing that we felt very strongly about was that the product experience was going to shift from, you know, what I'll call like text completion.

13:13 To agents, basically. Right. Uh and and and to first order I would kinda say You know, there there've been a lot of great experiences in text completion. You know, it's it's been used for marketing, it's been used for customer support, it's been used for education and in code, obviously, as well as you know, the GitHub Copilot was was was kind of really the the the the dominant product of yet that initial wave.

13:33 Right. But I think I'm not sure. the the the big shift that we really thought we would see is Moving from kind of this this text to text model to

13:42 an actual autonomous system that can make decisions, that can interact with the real world, that can take in feedback, that can iterate and and take multiple steps to solve problems. And you know, now we call that agents, but but but that was what we were really excited about at the time. So it was always coding, it was always agents And in some ways that kind of feels like it's it's it should have been, you know, like been been clear from the start. But even with that, it's I feel like we've pivoted like eight times or something within coding agents, you know, over the last year and a half. So I just noticed recently all the AI, top AI companies Sort of, not all, but many of them. The product that is winning is different.

14:16 has a different name from the company. Which is not typical cursors, any sphere spol to stack blitz. You guys are cognition labs. I like V Zero's versal. And it just tells me like these all emerge later in the company's journey and they tried a bunch of stuff and like oh wow, this thing worked.

14:32 And it's so interesting that it's so common amongst these. Yeah, and there's even I mean open AI and Chat GPT, Anthropic and Cloud and Google. Yeah, it's it's it's it's funny. Yeah, yeah, yeah, I agree. So so you know, when we got started, it it wasn't even really a company. I mean it's more like a project or a hackathon almost. You know, we we got uh a bunch of we we booked an Airbnb basically for a couple of weeks as we were on Thanksgiving time and and and Just got a a a a bunch of people together who were just excited to to hack on some projects and build something cool. And it's funny, actually the first the first thing that we were building for actually was more like solving like

15:03 Uh these more like contest programming problems and using like an agentic loop to to really do better on that. And so obviously if you run your code on the test cases, you can evaluate, you know, there there's a lot of agentich work that you can do there. To try and do better and And that that we spent some time on that initially. And then you know, we

15:19 We've kind of gone from I mean, the the the the story of the whole company for us in some sense has been going from hacker house to hacker house, you know? So so so after that, you know, we had another hacker house and that's where kind of some of the initial ideas for Devin came and and really building like a software engineering agent and not just like a a coding agent and having it interact with a lot of these tools. But But even then there were so many iterations and you know, even like The idea of talking to Devin, for example, was like uh, you know, it was something that we had to come up with, right? Initially it was just like you hand off a task. And then it works and then it shows you like this whole finished code, right? And now obviously it's like you can jump in at any time, you can give feedback on the plan, you guys can scope out the task together. you know, when you're working with Devin. And and and a lot of these things we had we had to develop, obviously. And certainly we've learned a lot about the use cases, the form factor. We've made a lot of big improvements, uh, and and step function improvements on the capabilities and

16:08 And Devin's ability to use tools and debug and make decisions. And and so it's yeah, it's it's been a fun journey. I mean, I think like I I I would say the the grounding question for us really is the which is one that we think about all the time is is really just like what what is the future of software engineering? You know, and and how how should we be working with AI to write code?'Cause I think at the end of the day of course that's That's that's what underlines all of the the the the product decisions that we make.

16:34 So I like that you're asking the juicy question I wanted to get to. Before I ask it, it's Just for the history books, how when did you guys start kind of hacking around and when did Devon launch? What was that how long was that period? Yeah, so we started in November of twenty twenty three, which was an

16:48 Yeah, just like hackathon mode. We officially made it into a company around the start of twenty twenty four. And then our our initial launch was in March. And so it was like nonstop. I mean, it's it's been nonstop for the entire last, you know, seventeen months, but but you know, it's it's getting getting to the launch and then obviously working with enterprises and uh developing the product a lot more. uh building in uh building it and and and getting it to work for a lot of practical use cases.

17:13 And then doing g you know, getting it making it fully available self serve in December of last year. And and now we've rolled out two point oh obviously just a few weeks ago. And so Been uh been a very busy time for us. Understatement of the century. Let me ask this question'cause you touch on it a bit, this whole idea of Devin as a person and this idea of creating a personality. For Devin it's unlike any other.

17:34 I believe AI app. No one else has like a name and like a You don't think of it as a person? What made you guys decide to go that approach and just how do you design it to work well that way? I would say we're it's a decision we're pretty proud of, I would say. I I I mean I think there's a lot of different product experiences out there. And I think the thing that really makes Devon unique in what it does is that you can really hand off and and and more and more what we've seen, honestly, is uh That

17:59 That I I I think a lot of kind of explaining the the the Devon experience to folks is really just explaining to uh explain it as yeah, this is your junior buddy, you know, and and and that goes for a lot of the the parts of the flow where in the onboarding, for example, you know, initially I would say like we've definitely had a lot of users come in and just kind of see the blank screen and not really know or Or they'd they'd ask, hey, like I'm gonna do this whole big re architecture of the whole code base. And and basically, you know, what what what we've learned over time is to basically get folks to think more like well, well, well. You know.

18:28 Let's work on getting the re repository set up first. Like let's make sure we we hand Devin a couple of one pointer tasks so it can get familiar with the code base. You know, let's get it the thing. If Devin needs to be able to test the code or run the linter or CI or or things like that, obviously we want to make sure Devin's got its own virtual machine set up to be able to do that. And and similarly, like I think the usage pattern You know, I I I think o often it wasn't clear and and obviously you can sit and just kind of watch Devin do it action by action. Uh and work that way. But

18:56 But we we found that the you know the the best workflow really as a team building off stuff was to to work with multiple Devons and to run them asynchronously and to to kick them off and and to only jump in basically as you needed to provide feedback or Or or or steer the plan or anything like that. And so in many ways I think it's I think Devin as a name really is is is our attempt to kind of capture the soul of that as a product, where it really is, you know, treating it like a A a bit more of an autonomous entity that that you can you can hand off tasks that you can work with that you should be teaching and learning with over time.

19:28 I wanna come back to an area you started us down and then I took us away from, which is Impact on software engineering and they have software engineering is gonna change. So there's kinda two parts of this. Just like When people are using Devon today, say in the n like this year.

19:42 How How is it the act of being an engineer and building changing for those companies. What does that look like? You know, by the way, we're all we're all software engineers ourselves. You know, it's like I I'm a programmer by training and still a programmer at heart, certainly. Uh and and you know, I I think the way that we've always thought about it is there's layers of abstraction and there's tools.

20:02 Uh and one way I would say it at a high level is kind of You know, I I I think of AI in general as yeah, I mean computers are obviously getting more and more intelligence and are able to do more and more. And You know, it's it's possible there may come a day where Computers truly do everything that we do, and humans are not responsible for any of it. You know, I I don't expect that to come particularly soon. Um

20:23 But but but I guess what I would say is you know until that point For as long as we're still part of the equation. One of the most important things to do, obviously, is, you know, for for us as humans is is to instruct our computers on on what we want and what we want to build and what we want to do. Right. And And software engineering is, you know, we think of it today obviously as Python and C plus plus and JavaScript and and all these things. But at the end of the day, of course, the discipline is all about just being able to tell your computer what's due. And so in that lens, I really think that programming is

20:51 If anything, it's only going to become more and more important as as AI gets more powerful. And and I think the thing that's really that that's that's that's really exciting for us is yeah, is it's like really like seeing that that kind of iterative transformation. And so you asked how what things look like today. And I I would say Yeah, it's it it really is like having like a junior buddy, uh or really a team of junior buddies that you can work with, right? And so every engineer on our team for you know, we use a ton of Devon when we're building Devon. And so Devon merges like several hundred pull requests into production. in the Devon codebases every month.

21:23 You know, uh which is I mean, our whole team is only like fifteen engineers, and so it's it's a it's a pretty sizable fraction of all the code that we write. Yeah, and and the way that we use it is basically, yeah, everyone's got their whole team of demons. You know, if if you're going to be like looking through various issues, if you're going through feature requests, if you're going through bugs, if you're going through new paradigms that you want to build. Um, then it is naturally the case that there's a lot of handoff points where you just say, Hey, at Devin, here's what's going on. Can you Uh please take a take a pass at this, right?

21:47 And sometimes Devin will be able to do the the task a hundred percent autonomously and just makes the PR and then you merge the PR and that's great. sometimes you wanna be able to to to jump in for the ten or twenty percent that really needs your help. Maybe there's uh a few details with how exactly you want to scope it or how you're architecting this feature, or maybe you want to go and test the front end at the end yourself to make sure it looks exactly the way that you want and and give your your one or two lines of feedback after that, right? But a lot of it is is really is kind of like Yeah, learning learning to learning to work with Devin, uh to to be able to just do more in parallel and build

22:20 What percentage of your PRs are Devin? versus humans right now. Yeah, I I I'd have to look, but it's in the neighborhood of uh of a quarter or so of all of our yeah. That's and then what was it like? Six months ago.

22:35 Oh it's uh yeah, it's it's it's grown a ton for I mean we've seen it grown ex exponentially internally ourselves as well. Uh and and so it's it you know, it's it's kind of an interesting one where Again, it's always both the capabilities and the product inter interface. And so you know, I think the intelligence has incr increased a lot. But the other thing, of course, is that Yeah. We we spent a lot of time in figuring out how to build and Um to to really

22:55 kind of build for an interface where you can Get Devin's value. on tasks where Devin is able to do the eighty or ninety percent. So Devin's obviously not, you know, is obviously not perfect and it'll make mistakes and so on. And a lot of the question is basically Yeah, how how do you scope out your initial task with Devin and then just kind of set Devin off and and have it go and do the things that you want to do? You know, how do you come in at the end and review and give feedback?

23:17 How do you make sure Devin learns over time? How are you able to kind of just check in as as as needed and course correct if you want to? Okay, so today about quarter of your PRs are Devons. Where do you think this will be at the end of the year? What would you guess? I think by the end of this year we expect it to be more than half.

23:34 And and and I mean I a as time goes on, you know, one of the things that we've seen is just It's you're you're able to do more and more and more work, uh uh asynchronously, right? And you're able to hand off more and more. You know, I I think the soul of programming, the soul of software engineering has really been about Um thro through all the areas, you know, not just now, but you know, even when it was assembly, right? And even when it was uh it was Pascal and even when it was punch cards or whatever. I think the soul of it has really been

23:58 Basically just about defining the problem that you're you're facing and really thinking through exactly what is the solution you that you want to build. you know, thinking through the architecture, thinking through the details. And really kinda mapping out in your in your mind exactly what you want. To build, basically.

24:13 And what you want to have your computer do. And I think that's uh you know, that's that's what makes software engineering really great. And I think that's like the funnest part of software engineering. I I think at the same time that's probably Yeah. Of ten percent. uh of the average software engineer's time, right? Because 90% of the time is, you know, you've got this Kubernetes error that you've got to debug and you have to see what went wrong and the system crashed or

24:35 you know, you left some port open and this is, you know, messing up, or you know, there's a there's a bug report that you have to take care of, or you've got to migrate your code or you've got to upgrade to a new version, or or things like that. You know, a lot more kind of like implementation. And one of the the the ways that we've kind of thought about Devin Uh in building covenants. Is is really allowing engineers to to go from bricklayer to architect, so to speak. And a lot of it is is yeah, just uh getting to the point where

25:01 Where you can do the high level directing and you can basically specify things exactly how you want. You know, I I think it is very much about Still having the human in control and having the human able to do the full specification, but just multiplying the magnitude of of what you can do and what you can build, you know, in in one day or one hour or however long. So in the future, say someone is Trying to get into software engineering, thinking about becoming an engineer.

25:24 First of all, do you think people should You know, classic question everyone's getting these days. Should you Still learn to code. So it's just I love your perspective there. And then two four people that are engineers today, what skills do you think will be more and more important and then less important in this discussion of moving from bricklayer to architect.

25:40 Yeah, for sure. I I love this question. First of all the question of, you know, whether you should Still learn to code my answer would be absolutely yes. I I think to a large extent, you know Computer science, w when you take computer science classes and when you learn these fundamentals, sure, you're learning a little bit about you know, how a particular language's syntax works or something like that. But but honestly, most of what you're learning really is about The ability to logically break down problems for number one.

26:04 And two, I would say, is Just yeah, the model of a computer and and a lot of these decisions and a lot of the abstractions that we've built over time, right? Like what is a database and how should you think about a database? You know, what is a garbage collection system and how do those work and all these different pieces. And and the reason I think that's important is because It's it's the same with a lot of these other, you know, uh arguably we've already gone kind of gone through these these these phases in programming, and I think this next one is going to be. You know, somewhat faster and somewhat bigger, but but in many ways a similar flavor, which is You know, when you work with Python today, obviously.

26:36 A lot of things are already abstracted away from you and in some sense Yeah. Someone from fifty years ago might already call Python, you know You just get to explain in English what you want and now the computer does it for you, right? And and and that's great and I think it's it's really powerful. It's it's it's opened it up. I mean we have

26:52 far more programmers obviously than we ever have before because of that. But but I would say Certainly, you know, I a as you're building your skills as an engineer, it really helps a lot to to understand the abstractions and to be able to peel the layers beneath, right? And so, you know, folks will use assembly, for example, if they're really performance open. Optimizing a piece of code. But also, you know, it's in in order to build good systems and to understand these things, you certainly want to understand these abstractions of

27:15 you know, how how how does networking work? Wha wh what is T C P I P like exactly, or what happens with this Python code when it gets interpreted, or or all of these details. And I think similarly I think we will get to a state where, yeah, you know, with with no experience at all, you're gonna be able to build some pretty cool stuff and uh and to do some pretty amazing work just by explaining what it is that you want. But I think that you know, for for quite some time you'll you'll really want to be able to To think precisely about the details, to peel back the abstractions, to to be very

27:44 Very very precise about what it is that you want to build and how. And then for skills that you think are more and more valuable for engineers? Like where should engineers today be leaning? More and more into And versus like, you know, forgetting forget this. I don't need to think about this anymore. For sure. And I and I think architect I mean it's you know, we already have a term for architect in engineering and I I think it is uh directly the directionally the the right term.

28:07 And I think a lot of it is really you know, it's it's I think one thing to kind of just do a routine implementation and and write boilerprate code and things like that. And I would say that uh, you know In many ways, AI coding has already made us much faster at that, right? But I I think a lot of the core questions of understanding very complex systems and and working in the context of the whole company and thinking about you know, the product that you're building or the work that you're doing, uh and understanding, okay, what are the problems that we wanna solve, how do we wanna solve those problems, what is exactly the solution that we wanna build, what are all these key decisions and trade offs that we're gonna be making. And basically I I I think folks who are able to do that really, really well are just gonna be

28:44 be able to leverage themselves more and more. And so if anything, I think there's gonna be I think there's gonna be way more produ uh maybe way more programmers and way more engineers, you know, a few years from now than there are today. And I think uh I think pretty quickly the form factor of what it means to be a programmer, obviously is gonna change and in some sense it already has But but but I I I I think there's just gonna be so much more for us to build. You know, I think one of the great things F folks talk about Jeffin's paradox all the time. I mean software is truly the the kind of uh the shining example of Jevon's paradox where we have always managed as a society to To find more and more things that we want to build software for and build more code for and

29:19 And and I really think there's there's there's a lot more out there to do. For people that don't know Jevin's paradox, can you briefly explain it? Absolutely, yeah. So Jevin's paradox just says that As the the the price of something goes down. It can still be the case that

29:33 uh the total spend on it actually goes up. And and and so, you know, you can think about this with money, you can think about this with time or resources, but but Uh the direct version here is I think As it becomes easier and easier to program, and as programming becomes more and more effective. I think we're gonna have a lot more programmers. You know, it's it's I I I think in a kind of zero sum view, you might say, Well, we're gonna be we're gonna be ten times faster at software engineering. And so it means that we're gonna need ten times fewer software engineers, right? But I think in practice what really is gonna happen is actually

30:02 We're gonna build even more than ten times as much code. And because, you know, all all all of the work that we do is so capped, obviously, on on on our ability to actually build and execute and iterate. We're gonna have so many great ideas out there, we're gonna have so many great products out there. Uh people are going to build a lot more personalized experiences, for example. And and and and uh and there's gonna be a lot to do. Going back to the way you guys use Devons, so you said that every engineer has kind of this fleet of Devons. How mans per engineer do you find most people are working with these days at at your company? Yeah, so it's very asynchronous, and so obviously you can kick them up.

30:35 uh and start them up and and shut them down basically as as you see fit. But but most folks on the team are definitely yeah, is are are often working With with up to five Devons at once, I would say. Uh and and it's a nice flow where it's you know, it's you you think through all right, what are the five things that we wanna get done today. uh one, two, three, four, five. You have Devin one do number one, you have Devin Two do number two, Devin three. And and and the thing about it is A lot of it is it it it and for what it's worth, you know, I I think it's it's taken us some time to to really kind of like

31:03 to to adjust to it and get to the point where it's uh it's really intuitive for us. But I I I think it's uh Yeah, it's it's it's it's definitely a different experience where you're you're handing off most things asynchronously and and the goal for each of your tasks is to be there for the parts that really need your expertise, where either you really, really need to define exactly what it is that you're solving for and what you're building. Or maybe some of the more complex parts where you want to

31:28 To to steer Devin towards you know, particularly what kinds of changes you want to make. You know, I want the class to be set up this way, and I want uh uh you know we should go and change all the downstream references to this as well or whatever, but basically have it having Devin do the bulk of the work. Asynchronously with you. And then how many engineers do you guys have roughly? Yeah, so our engineering team today is about fifteen people.

31:48 Fifteen one five. One five. Holy moly. Okay. And then each one has five ish Devons. Yeah. Uh, so there's five times the number of Devons as engineers. What I love about this is this is just like a glimpse into where the future is going. You guys are so ahead. Of how companies work with AI engineers. And so seeing how you operate is gonna be it's a sense

32:08 Essentially how most companies will end up operating. Yeah, and and and for what it's worth it, you know, it's we've we've already seen this shift, I would say, ourselves, where It's uh In terms of the team, obviously it's you know, folks don't spend that much of their time just writing out boilerplate or uh or or or just kind of doing pure like implementation of features and uh and and people get to spend like the much more of their time focused on really just

32:32 Yeah, thinking about the core questions of yeah, how how do we make Devon better? What is the right interface for Devon? You know, what is the right flow or or or or or the right set of features that's that's really gonna make this uh uh as creative an experience as as possible and and that's that's how we like things. Do you when is the point you reach where your there's takeoff of this being the bite, you know, like your Devin. starts moving so much further ahead of everyone else. Like once you have enough Devons doing all these things, they're just like, where and you're ten years twenty years, thirty years, a hundred years ahead. Honestly, I think as a community, you know, I I think the the the

33:03 Kind of all all all of us as engineers around the world, I think we're gonna have to think about this and build for this and kind of adapt to these new technologies. But what I would say is is yeah, I I I I think more and more And especially as capabilities get better, but but certainly. Yeah. Even in steady state today, I think.

33:19 you know, I think more and more I think things are going to shift towards this kind of asynchronous flow. And and one of the reasons I would say for that is I in the real world, you're just capped by real world constraints, right? And and I think that's one way to put it is is kind of like And and don't take these numbers exactly, but but you know, it's it's kind of like the the first sort of math of it is Of of course, you know, being able to to to write files or to complete this function or complete this line or things like that, you know, it it helps a ton. It's it's a really great experience, right? There's a lot of parts of of of building software that obviously are almost not that at all. Right. It's you know, you have a bug that you're trying to fix and so you

33:54 Uh you you you spin up the local server, you click around on your own product on the front end and try to reproduce the bug yourself, you know. Once you have the error, you you take a look at data dog and And you see what happened and You try to find other errors in the logs. you know, you look at those files and you see what went wrong.

34:10 You make some edits, maybe you go and like rerun the whole process again now that you you know, to just make sure your change looks right. Right. And that's a lot of You know what it means to be a software engineer. Right. And and you know, these are processes that take real time. I I think we're going to shift more and more towards this agentic workflow because

34:27 You know, that's in some ways it's kind of like the The way to really get to that, you know. two hundred percent, five hundred percent, a thousand percent gains that that that that we'll be getting to you with software engineering over the next few years. Okay, enough talk. Let's show people what the heck this actually looks like. Let's yeah. Uh you've got a couple of demos prepped that show A few use cases that you found helpful.

34:47 So you're gonna pull up your screen and then it will Let's kick it off and then we'll talk as it's happening. And so so the whole process, obviously, of working with Devin is Working asynchronously. Uh and so uh I I I I I thought it'd be cool for us to actually just watch Devin a little bit in action and then you know, we can we can go through some other examples of of of work that Devin's done or things that Devin does for us, even on our team, for example, but but but but then we can check back in asynchronously with our with our Devin after. So I'll share this real quick.

35:14 And the the the key thing I I uh you know that I would just emphasize here is a lot of it obviously is really just about Yeah, th thinking about a as a software engineer Or as engineers ourselves or engineering teams. Um um engineering teams, PMs and so on. You know, ha what are the what what are the things that we would want to build that we would want to hand off. And so uh uh you know we have Devin set up with our own Devin code base, for example. So I'll I'll go ahead and and kick off at Devin for that. And so I'll just say hey Ad Devin.

35:40 I'm pawn. With my friend. Hi, Devin. Mm-hmm.

35:47 Um, can you modify Devon WebApp? Let's let's let's feature let's feature your um your your newsletter as part of the uh as part of the Devin Uh Let's do it. Like on the real Devin website. Lenny's site. And so we're gonna kick this off.

36:07 As you can see, Devin gets started instantly and and and goes ahead and respond. And again, you can work with this asynchronously, you can work with it synchronously as well. For for this, we'll we'll just kind of go in a little bit and see exactly what's going on. But As you can see here, Devin's going through files and uh and taking a look through a lot of stuff. And so we we can we can follow here basically a as we need to and and see what makes sense. You can see Devin's already Uh

36:30 called out a few particular pieces, right where There's the sidebar. uh which we have implemented on the on the front end. And there's pieces there. And we're gonna have

36:39 Uh a new component. And that component's gonna link to Lenny's website. That all sounds good. Devin's asking us any questions if there's anything that we have here. Same story here where it's kind of you can let Devin make its own decisions and and hand off, or you can um Uh you can go in and and and be

36:54 Uh kinda kinda give some more thoughts. Right. Um should the button open in a new tab or within the application. I'll say let's let's open it in the new tab. And you could answer these at any point, like is it waiting for the answer? But it's not gonna be like just goddamn, I just wrote it this way. Why why didn't you tell me earlier? That's right. Yeah, one of one of the may one of one of the big pieces, you know, with with Devin is Devin will always be enthusiastic, you know, we'll always be ready to put in the hours. Thanks, guys. Uh and so we'll we'll give Devin a chance to work and it's gonna go through these files and it'll make a pull request for us and we'll see.

37:29 uh and go from there. But I I thought it'd be fun to to show some other examples of of Devon in action as well. One of the uh the the examples actually this morning, which I just used Devon for is I asked Devin to to help Me brush my own facts up. uh for this podcast. Um and so obviously a huge fan of the podcast and the newsletter. Uh I asked Devin, hey Devin.

37:49 gonna be on the podcast, could you please Research everything you can about him. And make a nice website quiz for me. So that I can uh make sure I know my facts, right? And so Devin, this was just this morning. I I asked him to do this and I'll kind of just show what Deb did.

38:03 It looks like. Yeah, went to Wikipedia first. Uh unfortunately it's not a page on Wikipedia, which is uh Lenny we'll work on that, I guess. They they did you dirty. I mean we need uh we need a page for this. And and and so then, you know, then it went and and found it on Spotify. Uh you're watching what it's researching live. Yeah, yeah, yeah. So so this is uh this was this morning, obviously. And this is a playback of what Devin did. This is like part this is part of Devon. You could just like watch what it did. Yep, yeah. Uh and so uh you know, especially when you're building engineering projects or something like that, you can see kind of like each of the steps that Devin was doing, or if Devin tested the code locally, obviously.

38:38 You want to be able to go and look and see, you know, what what what Devin was clicking around with and testing or or things like that. So it it found the newsletter, it's going and looking at this, right. And it's it's going and reading all of this. Uh and then it says, Okay, let's get started with uh with with putting the code together, right? And so it says, Hey, I've researched, you know, it's it's going through and and writing all of this, putting the app together. It plays its own quiz itself, actually, which we should just we should just play this quiz, actually. Let's let's see. Let's see how much what is the name? Uh What is the name of the podcast? Lenny's podcast.

39:10 Let's for people not watching, so to say approximately how many subscribers? A million, very good. Yeah, yeah. What is what are three main topics Lenny's focuses on? Oh, product growth and career. Very good. It's a good quiz.

39:27 What does Lenny's do pod besides podcasting? Okay. Writing angel investing. Writing, angel investing, and advising. Okay. How often does Lenny help this? Once a week, right. And so yeah, so so we can we can go through all these and do all these. I and I I took this quiz, by the way, obviously to to make sure that I was well prepped. But yeah, this is kind of one of the more fun examples, obviously, of just like Scott, how many how many how many subscribers do I have at my newsletter? Uh over a million, actually at the time. Yeah. And then and then one one last one I'll show and then maybe we can come back to our initial run after, but uh is is

39:59 You know, uh a and like I was saying, like a lot of this is really built to to work with all of the the existing code workflows out there. And so You know, for example we were doing uh some exploration with the deep seek repository uh on GitHub. And Uh, we we imported it into Devon and we we got our own fork of it set up in Devon. And a couple of things I just wanted to show here. You know, one is Devon sets up its whole wiki with all of its internal understanding. And so when Devon indexes the code base, obviously

40:24 Building a representation of the code base and learning it and improving it over time is one of the big things that Dev does. Uh and and and funnily enough, we found that Naturally, humans really are interested to understand this code base representation as well. And so so so you know, Devon Wiki is something that we built here and you can take a look at all these different pieces and and see each of these different things. Here are the FPA operations, you know, here's an SG leg integration. There's diagrams of of how the different layers are built and put together. There's you know deployment operations, there's a lot of details about the architecture as well.

40:55 And you can ask questions about it as well. And so for example, you can say how does Deep Seek handle multi token prediction designed for spec deck. And it'll go through and it's it's able to kind of search through the entire code base and give you an informed answer based off of that. Uh and so so we use this a lot. And you know, it's it it helps when you're when you're scoping out a task for Devin and doing an initial prompt. And it also helps, obviously, just in a vacuum, like you often have questions about your code base that are really nice, right? This episode is brought to you by Atio, the AI native CRM.

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42:11 go to attio.com slash Lenny to get fifteen percent off your first year. That's ATTIO.com slash Lenny. Something that I've I've learned as I've been talking to more and more AI. Uh

42:25 building companies and apps. is there's a big difference in how large of a code base they could integrate into. Yeah. And that's a big deal for companies that are existing versus startups, people that have large existing code base. What's the how should people think about how what kind of code base Debian can plug into?

42:41 Yeah. Yeah. So we go all the way to to the biggest code bases possible. Right. And one way I'd kind of put it is, you know. How the way that That that we as engineers would think about a large code base is certainly You know, when when you're making changes or when you're thinking about a particular task

42:56 You're not Uh, you're not bringing in every single line of the code base at once, right? You have a high level of abstraction that that you're able to think about and look into, right? And and then you're obviously able to zoom in and get to kind of higher resolution on each of these different things, right? And so Devin

43:11 Works in much the same way. The first thing is it's gonna Kind of. figure out like the high level architecture of of what's going on here and what this is built for and so on. But within each of the comp uh each of the components, it's obviously also gonna be able to to zoom in and and give some more detail.

43:27 about each of these. And so here's you know FPA to be float sixteen, uh and how exactly a lot of that is set up, right? Here's each of the Uh the different parts of the code base. And so similarly it's you know, we've we've built this to to be scalable. It's essentially going back to the engineer as architect is now it's helping you understand the architecture. Yeah.

43:44 Just kinda circling back to that. Yeah. Yeah, exactly. And one of the fun use cases that we've seen actually with folks is is they'll often actually Uh use Devin uh get Devin's help to to onboard new engineers on the team. Right. And and you know, when you're new and you're joining, there's obviously a lot of questions that you have about the code base or about how things are set up. It also sometimes can be a little bit awkward to, you know, to ask your mentor or your manager the questions and if you're worried that they're gonna be really dumb questions, right? And and so It's nice to just be able to ask Devin and to to to go through Devin's wiki and to understand these internal representations, right? I think that's really interesting because it comes back to your point that Devin is not just a junior engineer. It's what you call a jagged uh jagged engineer. A jagged intelligence.

44:22 Jagged intelligence where it like it's almost an uh Like a staff engineer at understanding the code base. Usually you have to ask an engineer that's been there a long time, what does this do? Where's this thing? How does this work? And it feels like Devin's very good at that. Yeah. Yeah, yeah, and obviously and the the the retrieval and kind of processing a lot of code and and a lot of tokens at once is, you know, something that that language models are really great at, right? And so so basically being able to get those gains.

44:46 And in the places that you need them is is really great. Yeah. Sweet. All right. You got a couple more useful. Yeah, one one last flow should've just you know, we we just rolled this out last week actually, but it's uh Uh a four kind of Devon automation set up with linear, right? And so you know, if you have tasks that you're doing on the deep seek repository, for example, and it's all set up. All you have to do is you just add

45:05 Did you have a label? And Devin will come through and it'll give you this, right? And it's gonna give you its thoughts on what the tasks look like. And you know, you can take a look at each of the particular files that you see, or it'll point out snippets that it thinks are important. Um and from there, if if you feel good about Uh if you feel good about what was built. Uh or or or or the conclusions that we came to, then you can just start off a Devon session that will go and actually do that work.

45:29 Yeah. That is insane. Like that sounds like such a simple Idea. But essentially what you're saying is there are tasks. In linear.

45:37 that are fixes and features And now Devin just goes off and can just do them for you. Yeah, yeah, and so so it's definitely like it's it's uh it's a hands on process. You know, you sort you certainly want to be involved when Devin is scoping out the task or giving you its thoughts. And the nice thing too, by the way, is Devin will give you its confidence level and you know, here's how likely I think Uh I I I am to to to really understand this piece or that piece or whatever, right?

46:02 But uh Uh but but but it helps make things a lot faster, right? And and and to your point, you know, it's like uh a a a lot of product managers, for example, obviously love to to be able to use Devon and Linear to understand things better, the code base better or or or things like that. And you know, Claire Vaux from for example from uh from Launch Darkly is uh is a big Devon user and and she loves Uh basically going and scoping out tasks or asking data questions or asking, hey, what's you know, what's going on, or or or like is this merged into production yet? Or, you know, uh is this a feature flag right now or what percent of people are are getting this or that feature. Yeah, it's it's a it's a clear basically to to

46:37 To to make that intelligence much more accessible. I love just like with the integration with linear that you can still keep it really simple. You know, you add a little ticket like hey, uh this link to this homepage would do this. And Devin will be really good at understanding what you mean and then show you here's what I'm thinking. Is this right?

46:53 Yeah. Yeah. Cool. Okay. So so so yeah, so Devin did finish working. It seems like there's something going on with the CI and it's debugging that right now, but it went ahead and put up the initial first pass pull request and we can take a look. Yeah. Uh this is the Devon website obviously in in this custom deploy and

47:09 Uh we have Lenny's newsletter right here. Let's ship this to production. Let's go. Yeah. Uh that's amazing. Okay, show it again real quick. So just added it to the homepage of Of Oh, Devin. Yeah, yeah, Devon. Devon obviously has access to our Devon code base. It does a lot here, and so it's super familiar with all the pieces here. Beautiful. And it's that yeah, I like how that looks. We've got Devon search. We've got Devon.

47:32 And we got a nice newsletter. Drive some great growth. I'll link to your site. You link to my site. We'll get some page rank going. Yeah. Yeah. Yeah. Okay. Is that a good example? Oh there it is. What a beautiful website. Is that just like a good example of the kind of thing Devon is very good at?

47:47 Like here is a very specific thing to change on the website. How do should people think about what Devon is very good at and maybe where it starts to fall apart? You know, the the way that we often describe it is I think Devin is best when It is working on tasks that are well defined. You know, it's a one way to put it is we you know you wanna be giving Devin tasks, not problems, right? And a lot of these things, you know, like what what what you just saw, which was kind of like a a quick frontend feature request or a bug fix or adding testing and documentation or or things like that, you know, one of the things that that makes a loop really nice, obviously, is A quick way to iterate and test. And so with something like this, obviously super easy for us, for example, to just go pull up the the preview uh and see that the link worked, right?

48:28 obviously would be easy for Devin to do as well. Devin will often go and log into Devin and start a Devin session and make sure it's you know it it when when it's working on our own code base, which is Kind of hilarious. But yeah, you you generally want something that is kind of like eas easy to verify and easy to test, is is the main thing. And you can work on bigger projects or bigger ask as well, obviously, but in that case you should certainly expect uh to need to steer Devin more to make sure you're really you know, to to make sure it's it's going the right direction. It's interesting'cause that's very similar to the way people talk about synthetic data and

48:58 Reinforcement learning. creating data that's very easy. There's like a very definitive answer, yes and no. Yeah. It's very clear. Hm. Yeah, yeah.

49:06 Okay. Let me ask you this question. What's something that You guys debated a lot as you were just Designing and building Devin. I'll give a couple that come to mind. You know, one I would say is um

49:18 Yeah, a question of I'll I'll call it like how opinionated we should be. You know, we had the workflows that we used to Devon for, which was very much as you can see for you know, basically integrating to our Slack and GitHub, making pull requests uh for us in our repos, responding to issue reports or or things like that. And Naturally, you know, we've we've had

49:37 certainly a lot of other, you know, kind of different things that have come up that folks have tried. I mean, uh we have we have folks who like order their DoorDash with Devin, for example, even and we have folks who who who Certainly, you know, a lot of people who who are Kind of. building cool cool websites from scratch or or or working on things like that. And and yeah, I mean it it's it's been an interesting trade off for us where I think The way that I would describe it is, you know, in in our product.

49:59 Certainly uh you know the the large bulk of the features That we build. are for this kind of like Got. making pull requests in engineering teams use case.

50:08 But I think uh basically our our kind of general stance with the others is obviously if if folks want to use Devon for that, that's great. And we wanna just kinda make sure that they're they're fully aware about the limitations and about where things get caught up. It's it's it's funny with with AI and especially because you know, I I would say one one of the I would say the most common pieces of startup advice out there I I'd say is, you know Focus on a really niche cohort, you know, do things that don't scale, you know, make

50:32 Make make one use case that's really great, right? And then you grow from there. And I think that's Uh, you know, I I I I I I I think that's great advice across the board. But yeah, it's kind of interesting because, you know, I I think with generative AI, you you naturally see this where a lot of product experiences can turn out to be More general. Yeah, and and so it's it's an interesting trade off for us. You know, this is something that we still

50:52 always go back and forth on and how much do we want to Yeah, yeah, to to to to to do more to to support all the other kind of use cases out there and to to handle other things that that folks might want to do with Devin. I think another one that comes to mind is how much Devin should be Let's say like a single comprehensive project experience versus like a suite of tools. Um and as you can see here, you know, we have we have Devin Search, we have Devon Wiki, you know, we have the linear ticket scooping. And certainly, you know, these these tools interact with each other, but I I I think as time's gone on, we have we've we've

51:24 We've seen it more and more as as really building this suite of tools. And I I think that's you know, I think the core agent experience and the core kind of agent that will go off and build each of these. bu build things for you, for example, is always of of course going to be, you know That's Devin and that is like the the core piece, I think that will always be what's really special about about our work. But but I I think that All of the other features out there.

51:44 You know, the the the it's it there is a complex suite. Uh uh of Of work that's required for real world software sharing. And and engineering's just messy at the end of the day. Right. And so so I think there are a lot of different flows and a lot of different use cases that make sense. And you know, an obvious thing to point out is is You could ask the same questions to Devon Search as you could to

52:04 Devin. Right. And Devin will go through and it'll do the same thing. It'll go through and look through the files and give you an answer and stuff. But but with that said, you know, on the one hand, I think on the capability side, there's certainly a lot you can do to really optimize things for very specifically question answer about this repository. And that made sense to to really kind of built into a specific kind of feature. And then on the other side I would say

52:24 Uh we found that users actually really Uh really like having this this access of control, right? Sometimes you Sometimes you have a a a task that you're thinking about, but you actually don't want Devin to get started on the task just yet. You want to ask Devin and understand what parts of the code base might be relevant, right? And so you want to be very direct about saying like this is just an ask and I I just want to see the snippets of code base that relate, right? Or I just want to look at the the wiki and understand the existing representation. And so it's kind of on on both the capabilities and on the the the UX side we've we've found that. That's kind of what what's naturally made sense over time.

52:57 Let's talk about the landscape then of just other companies in this space, which is something a lot of people are always thinking about. There's all these different approaches. You guys are going full on AI engineer. There's obviously IDE companies. There's also just like models being built that are really good at engineering. Uh. Everyone's kind of starting to build agents now. You guys are ahead on this in a lot of ways. Like OpenAI just recently said they're gonna build a software engineering agent.

53:19 Andropic's got something there. You know, Cursor and Windsurf have their own little agents and replet. Thoughts on just kinda where you guys fit in in the landscape and then where you How do you think you win long term? How do you think about That

53:31 Yeah. Yeah, and for what it's worth, you know, I I think all of these are incredible teams. I think uh you know really smart and really forward thinking folks who are who are building a lot of great products out there. And and it's uh I I I think there's there's there's a lot to do, honestly, you know, over the next few years with with the advent of HEI or or whatever you wanna call. You know, I think Uh one one of the quotes that I love is is In twenty seventy, if you asked if we had AGI, the answer is no. And in twenty twenty five if you ask do we have AGI, the answer is well, you have to define AGI and you know, it depends on your subject. Yeah. Right. And and I I think it does kind of get to the point of of I mean, there there is a lot of really amazing stuff happening, you know. I I I think

54:08 That it it's easy to underrat, I would say, just just how how big of a shift it is that we're seeing, right? Where I think there are a lot of of great products out there, for example, over the last ten years, twenty years, thirty years that have made each of these kind of like uh

54:24 Of the the the life cycle of building a product a little bit easier, for example, right? There's there's great products out there for instant response, there's great products out there for logging, there's great products out there for billing. There's you know all these different tools, right? And and and the obvious thing is, you know, what we're seeing with AI is All of these spaces are are going to be moving multiple times faster, you know, and the this it's going to be like an order of magnitude shift, if anything. Right. And so I I think from our perspective, You know, we've uh obviously had uh a very specific lens that that we've bet on this whole time, and that is, you know, autonomous coding agents and There's there's a lot of problems to solve there, to be honest, right? Like the the

55:01 There's still a ton to do on the core capabilities, certainly. And you know, we see ex cases all the time where it's like, Wow, why did Devon make that decision? That seems you know, no human engine would have ever done that. You know, there's there's all sorts of spots where You know, with the product interface there's obviously a lot to think about and I think it's it's By the way, not just like a single thing that that that we're working towards, but something that will change with every addition of capabilities. Like I kind of think of it as like There's there's twenty generations of agent product

55:27 You know, agent coding experiences to come. You know, I I think that I think the one that we'll get to over the course of several years is probably something where You don't even look at the code at all, right? And you're actually just looking at your own product and you're just able to look and and specify and say, Hey, you know. This button should be a little bit rounder. Let's do that. And and by the way, let's add a new tab here. And and maybe we should save this information. Let's let's start up a database table and let's index it on X, Y, and Z columns. And you're just, you know, basically working with your products in real time and and having your agent build out those things for you. Obviously, there's gonna be a lot of generations, you know, in between the here and there. But but I think the product experience itself is gonna change every single time. And then obviously, you know, there's there's all of the practicality of just getting it out there in the world.

56:08 And so You know, that folks folks obviously need to need to learn how to use the ne the new technology. There's a lot to do to to deploy into all the messiness of real world software. You know, there's a lot of Cobalt out there still. There's a lot of Fortran out there still. There's you know, there's lots of kind of abstractions and and details that folks have done. And so I think from our perspective You know, we have

56:30 We have been been since the beginning have been laser focused on Agentic coding. And that is the one thing that we've really believed in, and it's one thing that we've designed for and You know that goes all the way to uh even the revenue model with ACUs and and and having the usage based setup. It goes into obviously all the product experiences of thinking how

56:49 Okay, like where do you want to talk to Devin? You know, you wanna be able to talk to Devin in Slack, you wanna be able to to spin this up from your issue tracker, you wanna be able to all of these things and and then of course the capabilities. And so I I think it's uh I I I don't think there's any one easy answer. I I think it's obviously a combination of things, but but This is really the this is this has been the space that we've lived in and and spent all of our time in for for the last year and a half. And it's it's gonna be that way for the next five or ten years, too. Along these lines, a big question everyone always has in AI's motes and defensibility.

57:19 It's a question I've been asking every founder that comes on. How do you just think about how to build a mode in the space when it's so much easier to build and these models are you know, so much is built on these models that are themselves advancing so quickly. I I'd give one slight uh kind of tweak on that, which is I I think it's often less about motes and more about stickiness. And what I mean by that is, you know, motes are in some sense

57:40 Typically what folks mean by mode is something that means that a competitor couldn't even enter. You know the market. And and and I agree that at a high level, you know, a lot of different folks had different layers of the AI spectrum. You know, uh the the the foundation labs or the application layer or so on. You know, I I don't think there's any kind of like hard barrier that would prevent others from entering. I think what does exist is stickiness, which I would kind of define as you know, once you have a product experience that you really like. Are you excited to keep using that experience or is there a kind of like, you know?

58:09 I is there an effect where it is it is just as easy from now on to just switch onto a new one and learn a new one and so on. Right. And I think From that perspective, I think there's a there's a few things that are really great about coding agents in particular. You know, one I would say is There is a lot of just inherent kind of stickiness in learning and build up over time. Which is that

58:27 As you use Devon and as your whole whole team uses Devon. It's the same thing with with an engineer, right? If if you're joining on day one versus You know, so it's you you've been at the company for five years. You know you wrote half the code yourself. Yeah, you you've touched every file, you've built every single piece, right? You know all the engineers. And so similarly, it's like Devin will really learn and build its representation of of your code base and of your stack and of your process over time. Um and we'll be able to do a lot more with that. And then the other piece of it which I think is really uh is is really uh exciting, I I'd say, is

58:57 There really is a lot to do. Uh of what I would kind of call like a multiplayer aspect of of code, which if you think about it, is is how a lot of things get done in the real world, certainly. Right. And so um you know, it's it's one thing to have, you know, your own experience, which you use yourself as just an engineer, but Yeah, for example, ourselves, like we see this all the time where uh some engineers who are working with Devin and teaching Devin things and as I mentioned, like folks will have Devin onboard their new engineers and and kind of convey that knowledge to them. Right. Or similarly, it's like you'll, you know, I'll I'll start a session with Devin and Slack.

59:27 And I'll say, Hey, uh, you know, it'd be cool if if we could do this thing, and some engine other engineer will chime in and say, Oh, by the way, like the reason we did it initially was X and Y. And so Devin, just make sure when you do this change that you you know, still support that workflow. And Devin will say, Okay, sounds great, right? Or Devin will make a PR, you know, I'll be working with Devin, we'll make pull requests in GitHub and somebody else will be reviewing that PR or give some comments and and Devin will work on that too, right? You know you'll you'll be in linear. So all all these kind of spaces, it it really does just kind of set up for an experience where

59:57 Basically where where where Devin can just grow in the value that it can provide for your whole work over time. And so I think from that perspective, like If anything, you know, it's We we want there to be a a lot of innovation and a lot of new products and and so on. You know, I I I I I don't think that the goal is to try to lock other people out of uh uh building. You know, I there's a lot of stuff to build and I think there's gonna be a lot of different experiences. I think from our perspective What we think about is more like

1:00:22 How can we make Devin more and more and more useful? As you're using it. It's very similar, uh we had Michael From uh Cursor, the C of Cursor, on the podcast, and he had a similar point of just he thinks smotes are just kind of like consumer like Google is the way he thinks it's like Google. Where people can easily switch.

1:00:40 You just have to say the best. And that's the answer. Yeah. Uh and it feels like you're adding to that of just like but also if you can create some stickiness where it is uh very hard to leave because it's so good at what it's doing and it's built knowledge and and integrated to your workflows uh that and builds on that.

1:00:56 That's the case. And and I think one of the things that's that's that's you know, that's nice about our space too is Software engineering for better for worse is is Is is has a very clear tie to value. Yeah. And what it means is

1:01:09 I I guess one way to put it is is There is always kind of like a clear next level, at least for the next while. You know, I think there there could be some point where you're just like All right, just build the entirety of YouTube for me, you know, and Devin just does the whole th it's like There's probably been like a hundred million hours of human engineering time built building YouTube, building the algorithm, building all the infrastructure, all all the the everything, every little detail. And like, you know, th the maybe there's some time where Devin just does that out of the box. You know, that that's that's obviously going to be a long time from now.

1:01:36 I I think On the interim on on every level in between, obviously it's You know, it it it makes a difference, the the the quality of of software engineering. And I think one of the cool things with developers, obviously, is Developers are really willing to to to to learn new experiences and to put in effort

1:01:53 If it means that they're able to have a higher and higher quality experience. So Awesome. I'm gonna spend a little time on the tech. That enables Devin. Without divulging

1:02:03 Uh, trade secrets. Just what what allowed you to make Devin so good? Was there like an unlock with a certain model a lot of some folks have shared like three points on it, three point five was a huge unlock for a lot of their products. Just what What's kind of the key to s the the way you've architected or built Devon that makes it work so well. Uh we obviously you know, we we've we've been betting on agents for a long time. I I I think that agents were

1:02:26 Uh were doable and workable like a lot earlier than most folks might have thought. But certainly I I think As the as the community has really rallied around it, I mean you see the impacts of that in the pre-training, you see the impacts of that in uh in in a in a lot of the work that's that's done with these models. I I I actually don't think there's been any

1:02:44 Like from our perspective, I don't think there's been any single uh like step function base model shift or anything that has been kind of like a night and day difference in Devon. But I certainly think that the curve of, you know, every every point on the chart, I mean there's a new model that comes out every like every week now has uh has has obviously made a big difference in in terms of what we've been able to do. And then obviously on top of that, you know, we work with with with the research teams at all these foundation labs to to to do a lot of our work on top. And so I I think that My my hot take here, which I would give, is I think the

1:03:16 I think in terms of base intelligence, we're honestly Basically already there. And and and I think a lot of what we see actually and and what we spend our time on Uh Is less so obviously we we don't pre train our own models or things like that. You know, it's it's is less so like increasing the base IQ of a model, for example, and more about kind of like teaching it all of the idiosyncrasies of real world engineering.

1:03:37 Right. And uh and thinking about here's how you use data dog and do this and and here's how you might diagnose this error and here are the different things that you could run into and and here's how you handle each of those. And when you're ready, here's how you make GitHub PR and you know, it th this is true in engineering, it's true in every other space as well. I mean there's so much Detailed to to the work that we all do, obviously, uh day to day. And and and a lot of it is kind of like Like

1:04:03 Teaching the model to mirror the complexity of the real world, I would say, rather than r rather than kind of like getting it to some some higher fundamental level of problem solving, which I think the foundation labs are doing a really great job. There's something you shared when we were chatting before we started recording around the growth Of Previous kind of transformative technologies were very hardware oriented and they there was like a limiting factor to their growth and AI is not that.

1:04:28 You share that insight. For a number of reasons, I think AI is going to be the The the the biggest technology shift of our lives. But but I think one thing which is what we were just talking about before this, which is is is You know, most of the big tech

1:04:43 revolutions that we've had over the last fifty years. I mean, I'm thinking about like personal computer and the internet and the mobile phone and stuff. You know, they they all had this This this big hardware component that was that was a big part of the distribution, right? And so you know you had the internet, and initially it was just these universities that were talking with one another, but obviously. Over time we got the whole world plugged into the internet and it took years and years and years. Same thing was true with mobile phone, the same thing was true with PC, right? And Yeah.

1:05:07 You know, the the the thing that's interesting about that in particular, which is I would say we're we're already seeing the effects of that. Is You know, in these hardware distribution regimes You're obviously there there's a lot that pens on real time, right? And so, you know Folks who were building for those industries.

1:05:23 kinda saw their market grow and grow and grow basically steadily year over year as the number of people with mobile phones increased, right? As the number of people connected to the internet increased, right? And and and many of those businesses It's it's it's still crazy to think about but but many of those businesses got started right in the beginning. I mean like Apple and Microsoft were started like right around the same time, you know, and the same is true for a lot of the great internet businesses or or wherever. But but but certainly it was kind of like a It was a It was something that touched the whole world.

1:05:49 you know, with time or or or a large fraction of the whole world. And Uh And it had a really massive impact, but but it it it took place over several years, right, because of of the time that it took. And I think one of the things which is already I'd say different in in AI is Just how explosive the technology can be.

1:06:07 You know, once Once AI could you know, and I and I think we're firmly in the, you know, in in past the inflection point at AI could, right? Where it's As an engineer, you know, if you're not using A AI at all, right, good. I mean you're Uh You know, you're falling behind, honestly. And and it is a technology that everyone should have and should be using. And and there's no kind of like

1:06:26 Uh. There's no weight on hardware distribution that that there's causing that and it means that that It it means that the space is just growing so exponentially, basically. Michael Pollin has this interesting point that uh

1:06:38 Cliches are cliches because they're so true. And you that's why you they're like cliches, like I heard that a million times. And I think it's like people hear this like yeah, I know I know, but Like it's actually insane what is happening. Yeah. That's why that's why you're here to help us through this transition. Yeah, no, I mean it's it's a fun time and it and and I think there will be uh you know real real investment and real work that it takes but I but I I think from the perspective of us as engineers, for example, I think it just means it's it's It's so important to to

1:07:05 To stay in the loop with everything that's happening. And and it's you know, as we're seeing it's not only because uh of your learning and your ability to work these technologies. But it's also, you know, about basically like Teaching teaching the AI, you know, what what there is to know about your code base. In order to make it really effective at building with you and uh and and and doing more of the things that you would want it to do. So

1:07:26 So along those lines for company p people listening that they're like, Hey, we should be using Devon at our company. What are What are things you found to be helpful in helping an engineer at a company get adoption and be able to use Devon? Either culturally or logistically. Uh so so a pattern which we often see with folks is there will be a few folks at the team

1:07:47 who are really excited uh and wanna try out the new thing and they wanna put in the the the investment and and and and are really excited to get it going. And they'll go through all the setup, you know, they'll give Devin the repos, they'll Teach Devin how to run the Lint and the CI and and all of those details, right? And they'll start it by by giving it those initial tasks and kind of like Help Devin build a foothold, basically. And as time goes on

1:08:09 Uh eventually folks will see wow, Devin's writing all these PRs, Devin's doing this. Who's this Devin person that just joined the company is just knocking out PRs? Yeah, and they'll see that and then naturally they'll get on and they'll get an account. And one of the cool things, of course, is by the time they join, Devin already knows a good amount of detail about the repositories that they're already working in. And they're working with that. And so so one of the the really cool things which we often see is yeah, that they the early adopters themselves can really pave the way, I think, for for everyone else on the team. But but yeah, I I I think the main thing I would just kind of call out is yeah, it it really does take it's a very different product experience, right. Yeah, and I think it's uh

1:08:45 for what it's worth, you know, I I think there's still a lot more that we should be you know, that that that we can do to to make it as intuitive and as clear as possible to folks like how to use Devin and and and what the right steps are and how to really maximize value out of Devin. But I think that uh Yeah, it's it's the kind of thing where if you if if you put in the investment and understand exactly

1:09:05 you know, what it takes to to get down to to be successful. It's like you know, we've we've found ourselves that As time has gone on, we just use Devon more and more and more with with every uh with every Kind of every next update, so. So let me follow that throughout there is a question I ask every AI app building founder.

1:09:21 Which is if you could sit next to every new user of Devin. And whisper something in their ear to help them be successful. with Devin, like one or two tips. What would those tips be? I I think the biggest thing I would say

1:09:33 Is It it really is just You know. Treat Devin like your new junior engineer. Um I think that's that's the biggest thing. I think folks come in and you know they they see the the blank

1:09:46 The blank page and they think of all sorts of kind of like uh various things that they want to try out. They think of lots uh where Yeah, I I I think Typically the flow that we see that works Best is

1:09:56 Obviously, you know, you can try demos and you can you can do things, but but a lot of it is just like Yeah, let's let's figure out what tickets we want to get done today or this week and and let's have Dev get started on those. And you know, let's start with the kind of the the the easier ones and then work with Devin and understand like what what things Devin needs to get set up to be able to test its own code and do this well. And and then let's let's scale up over time. And then I obviously it's yeah, you know, as you work with your engineer, you understand better kind of how to communicate with them or Or what what are the right

1:10:25 Tasks or projects to bring them in on. But I I think that's um that yeah, that that really is the one liner for us. Okay. Uh, there's a question I've been meaning to ask. I just want to get back to this'cause it's something I think a lot about.

1:10:36 With With Devons. Everyone's gonna have five Devons, let's say, ten Devons. Everyone's kind of turning into a Basically an engine manager. With a bunch of junior engineers.

1:10:46 Yeah. Which isn't necessarily the best job in the world. At least you'd have to do performance reviews and ones. But you know, it's like sitting around checking a lot of PRs all day. I there's a sense of you become an architect and which is a kinda what every engineer wants to become eventually, right? They're all like, I just want to think about the architecture. I don't wanna code all these stupid fixed bugs. So I get that that's uh you know, there's a good part side to that, but just how do you Uh.

1:11:11 I imagine you're thinking a lot about this, just like how how do you make life Pleasant and fun and enjoyable. as basically an edge manager of say five hundred Stevens in the future. Yeah, I can just imagine the performance re you know, it's Devin, you've you've done a really great job on your task. I I really would like you to be more proactive in the team meetings. I just yeah, it's no so what I'd say It's funny actually, because it's something that that, you know, in in terms of the the wording that we thought a lot about as well. It's just you know, we we've used the term like manager of defenses in the past, which which of course I think is it it it is a big part of it, but

1:11:41 But I I think that The the only thing I would point out here is I I do think I th I think that the bricklayer versus architect is closer to the experience than being a manager because I think a lot of the difficulty of of you know, management or or you know, the the reason that you know that that that that people shy away from it is is more because

1:12:00 Um You know, a a a lot of the kind of various, let's say, like I there's there's kind of like all of the kind of like the context and the ownership and kind of like the responsibility and stuff. And then there's also kind of all of the the the the emotional aspects of it, right? Where I think working with Devin is a little more like

1:12:18 Just being Kind of like Having More is like having an interface to to hand off tasks and build tasks, right. And so so, you know, I the the the parallel that I would kind of draw is, you know

1:12:30 When we invented Python, obviously. Like We we didn't you know, it's it's it's like i i in in many ways, you know, the description of the and the outlining of tasks was obviously it was like a different paradigm. But but I I think it certainly it was it was nowhere near you know what what folks typically think of as kind of like management bureaucracy today, right? Um and I think that with Devin

1:12:51 A a lot of it is just kind of like It it's it's more like finding the right levels of of abstraction that you could work with Devin on and and just kind of like finding the workflows that work really well. And and and and the obvious thing to say here is is It's it's a very you know.

1:13:08 It's it's like you can always have Devin take a first pass at things, right? And so, you know, you you can take the first pass you you have Devin take the first pass, you know, if it's great, you merge it right away. If it's you know, if it needs some touch up, you could obvious give that feedback, for example. Uh but but but a lot of it is is like It's more about Basically like making Devon part of your flow than it is, you know, losing control. Which I think is the i is the is the main thing that that folks are scared of with with

1:13:33 with management. Are you thinking about a manager Devon? Like a Devon that manages other Devons? Yeah, yeah. So so for what it's worth, Devon can start other Devons through the API. Right. And so so we we've seen this happen quite a bit of times where naturally it if if you have some big task that you want to do, like, you know, Devin will do this all the time. It'll it'll chunk up. And then I'm paralyzed into smaller debits. And so it's the kind of thing that you need to give Devin the credentials to be able to do that. It's not currently something that is kind of like default enabled.

1:14:00 But uh but I can certainly imagine as time goes on that there's more and more of that. Devon's all the way down. Yeah, yeah. I I think the thing that's kind of interesting too is like, you know, with humans, the way I almost say it. in in in in technical terms. It's like there's this coupling of A context

1:14:15 And a thread. And what I mean by that is is like Basically Uh each human can only operate, you know, single threaded. on on the work that they do and they have their set of contacts. And then there's other humans, obviously, who can do other stuff at the same time, but they have their own contacts, right? With agents

1:14:32 One of the cool things is you can have an agent that's doing multiple lines of exploration at once, but is sharing all of the context of everything that they find. And so I I I think that this is very early, and I and I think we'll see this, but but but folks obviously love to talk about Basically like systems and agents communicating with one one another. And and I think that uh there will be a lot of new paradigms to build for once once we get there.

1:14:55 And it's so interesting what you said about the this the decision between having one Devin And only when Devin do all the things and you just tell him things and they kinda fire off jobs versus You have five Devons and they're each doing individual things. It's such an interesting decision to make. Yeah. Yeah, yeah, for sure. Okay, two more questions.

1:15:14 What's maybe the most counterintuitive thing you've learned so far? Building. Devin that maybe goes against startup. wisdom, common start up wisdom. Something I've thought about a lot lately as as we've built this is

1:15:25 You know, it's not my first company. Actually for a lot of us it's it's uh it's not our first company, like I think of of our twenty six or twenty seven people total on the team. Like I think Eighteen of us have started our own company before this. And yeah, like one one of the things I think about is You know, there's I actually your point about cliches, I think really uh really spoke to me as well, which is

1:15:46 There there's kind of the the the really common things which you hear all the time in startups where it's like, you know, you gotta move fast or you gotta hire great people. It's like okay, well obviously you do, you know. I wasn't planning on not hiring great people, you know, I wasn't planning on going slow. And similarly it's like yeah, you you really gotta build build something that that people want. Right. And there's kind of these like three to five things which are always repeated, and and they're always the the the common wisdom in startups. And I definitely had this this idea as a founder when I was starting initially that

1:16:16 Right, so those are the kind of the three to five basic things. But as you get really deep into it, you spend a lot of years into it, you know. You you learn all of the thousands of other things that you have to learn. to be, you know, to to to build a company, right? And and I think to some extent that's of course true. And there's lots of little details that you'll get into with all these different things, right? Including um including team building and and product. And strategy and engineering decision making and Yeah, fundraising and

1:16:42 uh and sales and a and every other component, right? But but I I also s realize that as time has gone on, more and more I Felt like building companies well sometimes just comes down to Doing those three to five things just Even more

1:16:56 than you could possibly expect. And so with us it's like You know, it's yeah, everyone says to go fast, you know, but it's like yeah, we we had a hackathon in November, we had another hackathon in December, we started the company officially in January. We like uh got the prototypes out to initial users in February. We did a launch in March. We got our first customers in April. You know, it's just like Basically like truly pushing the pace and Every spot where we possibly could.

1:17:19 has really made a difference for us. And similarly, it's like yeah, everyone always says, you know, you should hire great people, but I I I think That the the truth Within that truth is basically like You should fight.

1:17:32 to to all ends, basically, you know, to to to to get the folks that you really want to to to to bring in. And it's I uh you know one of my favorite stories to share is we had Uh, we had a candidate who came and interviewed he was a junior at MIT. Um so he was very, very young and we gave him our interview and he he did way better than almost any of the full time like the the the the full time candidates that we had ever talked to. And so we said, Hey, you know, what do you think about Taking some time off from school and and working with us and building out Devin, like we really think you're just gonna be able to come in and just have a ton of impact already from day one. Yeah, he thought about it for a while and he came back and he said, You know what, I I like I I'm down, I wanna do it, but

1:18:07 My parents really want me to to graduate from school and I I'm just not sure there's a way to make it work. And so and and and and and so so we talked to him more and kind of just understood the situation and then Um Yeah, and then we We flew to North Carolina. Uh, went straight from the airport to to h his parents' house, had dinner with him and his parents, we talked a lot, and you know it's uh a really really nice goodrassi family. Uh kind of gave them some gifts and just talked to them about it and tried to understand right like what what what what would it take and what what will we need to make work and They just said, you know, it's it sounds like a great opportunity, but we really want uh our son to be able to graduate, right?

1:18:44 And And and we talked that through and we figured out a a a a s a setup way basically where he could work for us. Essentially full time. But then come in for his required classes and and in

1:18:55 Do what he needed to do to get the diploma, basically, but no more than that. Uh and and we talked that through and then, you know, we got to a point where where Where Where everyone was happy with that and then Yeah, we went straight back to the airport and flew right back basically. And that was you know, that was a that was the the first and only time that I've ever been in North Carolina, but it was just a great trip, you know, and it it's the kind of thing where it's like You know, I hiring great people is one thing, but truly just never never giving up and and and and really giving it.

1:19:20 everything that you can to To make it work. for for people who who really make sense for be to be on the team. And you know, he's been with us on the team for for over a year now and he's been An incredible, incredible engineer and we wouldn't be here without him. Similarly, we had someone else who was Again.

1:19:33 really, really talented candidate, you know, did amazingly well. very young and and had a lot of great offers at a lot of other companies and You know, we were talking to them about, you know, he he he wanted to start his own company someday as well. And uh we were talking to him about, you know, Certainly uh you know, a lot of the obvious things which are kind of like having him meet our investors or work with you know

1:19:52 do get to do work with customers or see a lot of these other components so that when the time came, you know, that that he would have all the experience he needed to start his own company. But the other thing that, you know that one of one of the other things that was big is like he really, you know, he he wa he was talking with a lot of great companies already. He didn't want to burn any bridges. And so we actually worked with him and and basically hand wrote all of his rejection responses to each of the other companies and kind of worked with him on it to say like You know, here's how you should say it in a way that's

1:20:18 You know, gonna gonna come off as like, you know, that that you really did appreciate the time with them and that you obviously, you know, you want to remain close with them and stay in touch. And and it was the kind of thing, obviously, where it's it's like look, I obviously it's our our job is to make sure that he's happy enough that that he he doesn't want to leave any time in the near future. But I I think it's the kind of thing where You know, the the the way that you put together a really, really great team is by Is by really what's what's

1:20:43 But by fighting for for what's right for them too. So wow. Those are incredible stories. And it makes so real these, you know, as you say, cliches, hire the best people. Like, this is what it sounds like to hire the best people. This is what it takes

1:20:56 Yeah, no, and I was just saying it's just like, you know, a a lot of things, yeah, we've we've we've fought very hard to just kind of like yeah, like reimagine things from the ground up because it's uh you know, a a lot of it really is just thinking about like Yeah, like w where where do we think the technology is going over the next five to ten years? You know, w what is the the place that we wanna have? I wonder if people are gonna be fighting for the best Devon someday. There's gonna be next Devons. Yeah. I'll give you overtime pay and benefits, you know, free healthcare and everything, and then the Devin's like, yeah. Devon's like magic the gathering cards. Yeah. And then just going back to your three to five things, so essentially this is incredible advice. Essentially it's like

1:21:37 You always hear, hire the best people, move fast. Build things people want. Yeah, build build something people want, you know, stay as close as possible to your customers, right. I I feel like those are kind of like the the five things where she's you know.

1:21:54 U especially in AI with things moving so fast and there's so much great talent. You know, I feel like a lot of these are even more true, where it's kind of like Uh You know, it's it's not just thinking about where things are gonna be in ten years, it's like thinking about what's gonna happen next week. You know, and and and it's it's obviously things are moving very quickly and it it is very hard to predict, but you really have to You you really have to be very, uh very rigorous with yourself, I'd say about like

1:22:18 thinking through those things and And evaluating all all of the the kind of the decisions that you make in that lens. And staying focused is the big takeaway to me here. Is like It ends up feeling like there's a thousand things you should do, but it's always these five things. Yeah.

1:22:33 Scott, we covered a lot of ground. Oh yeah, it went through every question I had, which is great. Is there anything else that You wanna share anything else you wanna leave your l listeners with, maybe a final nugget. Or something really.

1:22:44 You wanna double down on that we said, uh before we Let you go. The biggest thing that comes to mind for me is You know, there's there's a lot of different perceptions about AI, right? There's there's I think every basically every emotion under the sun right now, you know, there's there's a lot of fear, for example. There's also a lot of skepticism and uh you know, it's we're very skeptical types as well, and we always want to kind of try it ourselves to to to really see it and believe it. And

1:23:08 I I think the main thing that That comes to mind for me is Yeah, I I I I'm honestly really optimistic about what we're building here with AI and you know, not just with code and with Devin, but but

1:23:19 But Yeah. the the the whole space and and and everything that's getting done. And I I think one of the cool things that that Is is really actively happening is just

1:23:27 The ability for everyone to multiply themselves. And and that's that's how we've always thought about it. It's how we thought about what we're building and and it's You know, I I think The There is a lot more to do out there in the world.

1:23:39 You know, I I'm not too worried about us running out of things to to do. And from that lens it's It's I I think the the thing that we've always been most excited about is is How can we all do that?

1:23:52 I hear you, Scott. Well, with that optimism, we've reached our Very exciting lightning round. Are you ready? Yeah, let's do it. Okay, here we go. First question, what are two or three books that you find yourself recommending most to other people?

1:24:07 In terms of nonfiction, I I think uh Uh For for for folks in startups, I I think one of the things that I've really enjoyed is just learning and understanding the history of Silicon Valley. And there's such you know, it's all all these things that we think about. Somebody invented them. I mean it's it's one of the great realizations, I feel like is like You know, it's somebody invented the idea of a seed route, right? Somebody invented the idea of venture capital. Somebody invented the idea of like product market fit. All all of these different principles that we talk about. And and so for that, I there there's uh book called The Power Law by Sebastian Malibu, which I I I really like.

1:24:39 It it basically is just kind of like a yeah, a tour of of Many of the the the great businesses and the great products that have been built over the last Um sixty seven years in Silicon Valley, which I really love. I think in terms of fiction it's uh I actually have always really liked the The Great Gasby by F. Scott Fitzgerald.

1:24:57 Do you have a favorite recent movie or T V show that you've really enjoyed? I have to admit I have not watch. I I can't think of see a single movie or TV show that I have watched in the last while. So I I'm sure there's I I I I I I'm looking forward to to watching a lot of great ones post AGI. That's gotta be in the trailer. That's great. I like that. Uh and that sho just shows how hard you're working, just how much it is going on and how fast everything's moving.

1:25:25 Do you have a favorite product you've recently discovered that you really love? Could be an app. Could be something physical, could be toothbrush. One I would say is uh you know, I I have a I got an aura frame recently. It's just like uh you know a frame that shows photos. I've actually I've I've I've really enjoyed it a lot. I I think it's uh it's a it's a nice way to just have Basically. picture frame memories that come up. And then the other thing I would say as as like a general purpose thing, you know I I I it's

1:25:55 It's not particularly new, but I would say I I think AirPods are actually extremely well built and well designed. I realise now that it's like I I basically use them for all sorts, you know, I I I'm taking calls on a walk and I'm using airples, I'm I'm obviously I'm Like

1:26:09 doing work at my computer at my desk. I'm I'm plugged into AirPods and and and it's It it works quite well, I don't see for for a lot of different situations. And it's it's it's they're they're very comfortable. They're they're they're very consistent. Yeah. I got one of these for my mom and my mother in law. And they're so great for just like sharing photos of your kids with

1:26:30 Your family. And people have like, you know. They've heard of picture like digital picture picture frames, but the Orid just does it really well. And it's really easy to add photos and they're just really nice looking. You can imagine, you know, not that long from now we'll have the Aura frame except it, you know. Studio gamifies every photo that you have in it and then you know it's uh Yeah. Or just imagines things you've done that are really cool. Sweet life.

1:26:51 Yeah, cool. And it's or it's A U R A, I believe, is how you spell it. If you want to check it out, we'll link it. Not affiliated. Okay. Uh two more questions. Do you have a favorite m life motto? that you often come back to and find useful in work or in light. Yeah, you know, something I've thought about a lot is

1:27:09 A lot of the Uh uh. A a lot of the proverbs out there are actually contradictions, right? It's like you know birds of a feather and then you also have like opposite attracts, right? You have all you know, and and it's kinda funny uh because It's You you feel that both of them are true, and often they both are true. And a lot of it is about like understanding why. And and one of those that that I feel like, especially in the world of startups that I think about like all the time.

1:27:31 Is I think It. is very important to be focused and driven and to really kind of maximize your potential.

1:27:42 And then at the same time, it's also very important. To not let your own personal emotion get tied up in your success or failure, you know? I a and I think especially strong because There's always ups and downs, honestly, even in the most successful compan. Like it it is it is just like

1:27:59 You know, it's it's a rocky road. There's there's a lot that happens and and a lot that That goes down. And I think one of the things which I've I I thought A lot about is that Somehow it's

1:28:09 You know you you really want to Do your best and put your ever put put everything you can into it and and and Do everything you can to to to basically you you want to put it all out on the field. You know? But at the same time, you want to be

1:28:23 Okay. With. With with both wins and losses, right? And and you want to be able to to to to to to to to move on and go into the next one w each time. And and something yeah, I I mean It's it's funny, but uh

1:28:38 What I've found personally is that Obviously it's uh you know, it's it's really important for your for your your own emotional state and mental state to be able to do that. And we've had lots of mistakes and you know, I've had a a lot of you know, I I had my first company, which is obviously which was cool, but but you know, there are a lot of like tricky spots there and then over the course of cognition, I mean it's been feels like it's been already like eight years compressed into like one year and you know, it's still going at that pace. But but It's it it it's somehow it also actually makes you More successful, I I think too.

1:29:09 You know, it's it's like you you are just more able to to give it your best and And and to do the things that will lead to success if you're not tying it up in your own personal worth. So That is so interesting. I just had a podcast recording recently where With it and executive coach Jerry Colonna. That I think will come out before this, might be after this.

1:29:28 That is That's one of his big pieces of advice. And it's a it's a very Buddhist approach of just not a clinking and attaching to to to an outcome. Yeah. Okay, final question. I'm curious if there's a story here, but we could keep it short. Is there a story behind Devin as the name?

1:29:42 And or or is there another contender for Devin. Being the agent. Devin was the name from pretty early on. We were interested, I uh you know, we were working on coding agents from the beginning, and you know, my co-founders are Steven and Walden, for example, and we had this idea, all right, let's get started. And

1:29:59 You know, let's not uh let's let's try to kind of like Uh Kind of like expand the the box as much as we can to have everyone kind of think out of the box and do their own thing. And let's have everyone do their own thing first for a bit. And then we'll kind of like consolidate and take everything that we've learned. And so

1:30:13 Yeah. Walden made a a virtual, you know, developer version of him, which was called Dev Walden, and then Steven made one of him, which is called Dev Steven, and you know, had all these and then and then we were kinda combining it all into one thing and we're like, Okay, you know, it's it's Devin. And that was the thing. And so so Devin was like yeah, Devin stuck for us like quite early on, I would say. One thing which we did have a big decision on there actually is what the What the image of Devin would be? And so as folks know, there's the the hexagons, and then people might have seen this more recently, but there's actually also an odd

1:30:43 uh like a little otter with a laptop and and its lap. Uh uh that that is uh that is Devon as well. And and we had this debate over over what to go with and what not to go with and South News. Uh It's It's been a while now, but somehow we still we still have both uh the hexagons and the otter. You skipped over where the Devon it's like did you just ha just kill it? Yeah. And and and and so it was kind of like when we were uh consolidating all the names, it just kind of seemed clear then that this would be the the universal dev that we all need.

1:31:17 Yeah. Incredible. Scott, this was so much fun. Oh my God. I learned a ton, which is always a really good sign. Two final questions. Where can folks find you slash Devin slash anything else you want to point them to? And how can listeners be useful to you? Awesome. Yeah, no, we're at uh we're at app.devon.ai. Um Um and uh you know, you can you can find us as well on Twitter or a lot of other social media.

1:31:38 Um we'd we'd obviously love to hear any feedback you have about the Devon product. Like there's there's so much to figure out and I I I think the Like like I said, I think we're all still like twenty steps away from really the the future of software engineering and so so it really means a lot to to hear what folks think uh uh about the product as they're trying it out. And so please please let us know anytime if there's things that we can do to make it better. Scott, thank you so much for being here.

1:32:02 Thank you so much for having me. I had a great time. Me too. Hi everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review, as that really helps other listeners find the podcast.

1:32:21 You can find all past episodes or learn more about the show at Lenny's Podcast.com. See you in the next episode.

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