The Exchanges

Q Why would Anthropic want to collaborate when they could just own it? Sorry, I'm, I'm a VC.

A Yeah. No, no, of course, of course, I love it. They've all hidden me with all the hard questions. Look, I, I think the answer at the end of the day, Is what we focus on is very, very different, right? And, and, and the, the kinds of questions that we think about, for example, on, on both the Devon or the Windsurf side, by the way, is, is really just like, how should humans and AI work together to produce code? It's, it's one thing to just kind of like solve for Generally smarter and smarter base models. It's another thing to teach your specific model. All right, here's, here's how to go, you know, to Datadog and pull up the logs for this thing. And here's how you, um, you know, debug a front end live. And here's what the, the, here's our representation of the code base, which we're learning and iterating over time and so on. And I think at the end of the day, there's, there's, there are a lot of different verticals to work in and to solve for. I think we have parts of this equation and I think the foundation labs have parts of this equation, but I think the truth is you really need both.

AI assessment note: “what we focus on is very, very different, right?”

Q Why would Anthropic want to collaborate when they could just own it? Sorry, I'm, I'm a VC.

A Yeah. No, no, of course, of course, I love it. They've all hidden me with all the hard questions. Look, I, I think the answer at the end of the day, Is what we focus on is very, very different, right? And, and, and the, the kinds of questions that we think about, for example, on, on both the Devon or the Windsurf side, by the way, is, is really just like, how should humans and AI work together to produce code? It's, it's one thing to just kind of like solve for Generally smarter and smarter base models. It's another thing to teach your specific model. All right, here's, here's how to go, you know, to Datadog and pull up the logs for this thing. And here's how you, um, you know, debug a front end live. And here's what the, the, here's our representation of the code base, which we're learning and iterating over time and so on. And I think at the end of the day, there's, there's, there are a lot of different verticals to work in and to solve for. I think we have parts of this equation and I think the foundation labs have parts of this equation, but I think the truth is you really need both.

AI assessment note: “what we focus on is very, very different”

Q What have you not built that you would most like to build?

A The answer I would give today, which is, which is, I mean, the biggest thing that we've been thinking about in the last few days since this deal, is really in figuring out What is that combined experience of IDE and agent? Because I think there really is something here. You know, I, I think to, to, to, to what we said earlier, you know, I think years from now, all of these systems will look so different, you know, and, and we may not even have the same terms for them, but I think in, in, in the immediate future, I think both IDEs and agents will be an important part of a developer's workflow. And you can imagine all sorts of things of, Hey, I want to go and plan out a task in the IDE. I want to be able to use the intelligence and the retrieval and, you know, dev and search and, You know, read on the wiki to understand exactly what, what decisions I need to make or what parts of the code this is going to touch and, and what things I need to plan out. And then I want to be able to hand that off to an agent, have the agent go do the bulk of the work, and then I'm going to go and review the code. And naturally it'd be great to review the code locally in my IDE. If there's any touch up that I need to do, I can use that, you know, I can use my NIDE tooling to go and do that. But, but basically, um, you know, figuring out What is that combined experience where you can go from synchron…

AI assessment note: “figuring out What is that combined experience of IDE and agent”

Q Would you advise a new young student to study CS today?

A Yes, absolutely. People ask me this all the time, by the way. And, and the reason I say that is because, you know, if anything, I would say, I'll give you my hot take, which is the complaint that we've had all along about schools is they, they're supposed to teach UCS and software engineering, but it's, you know, it's like you, you, you go to school and you learn about garbage collection and algorithms and, and architecture and everything, and then you go on the job and then a lot of what you have to do is, you know, debugging JavaScript traces, right? And I think the thing that's kind of funny is, as we said, like, this fundamental skill set of how you solve problems, and how you think from first principles, and understanding the model of a computer, and understanding a lot of these kind of, like, architectures of, like, yeah, how does a database work, or things like that. Like, those are actually going to be the important things, I think, going forward. Um, and so, you know, maybe one way to say it is, at the end of the day, like, the degree in CS is more a degree in how to think. Uh, and I think that will always be valuable.

AI assessment note: “Yes, absolutely. People ask me this all the time, by the way.”

Q like, market makeup at an end state, because that's where value kind of also kind of accrues in my mind. When you think about that, and you think about, like, developer, where the market shakes out, is it that cursor win bottoms up developer minds, and windsurf win, and cognition now win top-down large enterprise Super solid blue chip clients. Is that how you think that developer market shakes out?

A So I think the honest answer I would say is I think it's far too early to call on any of these. Um, and I think that the reason that I say that is because I'll give you a hot take, which is none of us are that close to the future of software engineering, you know, and I think the future of software engineering is, look, this is going to take place over the next couple of years or so, but, but it really is this version where it is, it is not just, you know, we talk, we call it an IDE or a coding agent or this or that, you know, these are the terms that we use. I think if we're being real about what we're building here and what, what this is all going towards, I think of this as the next generation of human computer interface is the problem that's being solved here. Right. Which is basically, as we said, code, software, the whole point of that is just telling your computer what to do. At some point, telling your computer what to do is not going to take place with code. It is going to take place with you just expressing your intent. And there are a lot of things. Don't get me wrong. There are a lot of capabilities problems to solve to get there. There are a lot of, you know, interface problems to get there. But, but I think that is essentially what we get to is, you know, a simple thing I'd say is Tony Stark does not pull up his laptop. You know, Tony Stark goes and talks to Jarvi…

AI assessment note: “I think the honest answer I would say is I think it's far too early”

Q like, market makeup at an end state, because that's where value kind of also kind of accrues in my mind. When you think about that, and you think about, like, developer, where the market shakes out, is it that cursor win bottoms up developer minds, and windsurf win, and cognition now win top-down large enterprise Super solid blue chip clients. Is that how you think that developer market shakes out?

A So I think the honest answer I would say is I think it's far too early to call on any of these. Um, and I think that the reason that I say that is because I'll give you a hot take, which is none of us are that close to the future of software engineering, you know, and I think the future of software engineering is, look, this is going to take place over the next couple of years or so, but, but it really is this version where it is, it is not just, you know, we talk, we call it an IDE or a coding agent or this or that, you know, these are the terms that we use. I think if we're being real about what we're building here and what, what this is all going towards, I think of this as the next generation of human computer interface is the problem that's being solved here. Right. Which is basically, as we said, code, software, the whole point of that is just telling your computer what to do. At some point, telling your computer what to do is not going to take place with code. It is going to take place with you just expressing your intent. And there are a lot of things. Don't get me wrong. There are a lot of capabilities problems to solve to get there. There are a lot of, you know, interface problems to get there. But, but I think that is essentially what we get to is, you know, a simple thing I'd say is Tony Stark does not pull up his laptop. You know, Tony Stark goes and talks to Jarvi…

AI assessment note: “I think it's far too early to call on any of these.”

Q Those pieces are the rationale that lead to the decision. How do you actually execute it? Like literally, how does that work in process?

A Yeah, yeah, for sure. So, so, so we came to them and we said, look, I think there's a very natural partnership here. I think that the team pieces are very complimentary. I think there's a lot we can do on the product. The, the thing that just seems, you know, absolutely clear from both of our sides is if we're going to do something, we want to be ready to do this and announce it by Monday morning. You know, it's, it's kind of reminds me of like, like, you know, the bank goes into receivership Friday night. You gotta have an answer, you know, by, by Sunday and by Monday morning, right? And I, I, I think we thought of this as a similar situation, which is look, there's, there's a ton of value here, but, but everyone's wondering what's going on and we need to be able to give them a clear answer as soon as possible that look, we are going to do this. We're going to support, you know, the products. We're going to, we're going to make sure things, everything's going smoothly and running smoothly and so on. And, um, and, and so that's what we came to and, and, and we gave them, you know, our, our, our, our honest take of like, here's what we think we can do together. Um, it's, You know, we, we, we are not going to have time to, to get to go like as deep into the diligence and details as we would like to, but, but I think at a high level, we, we at least, you know, I think are in a pos…

AI assessment note: “get to a verbal agreement on Saturday, hash out all the details and the terms”

Q When you look at something that no one sees that everyone should see, when you think about the future of AI code and the future of software engineering, what does no one talk about? That you think more people should be talking about?

A A focus on deep context. It's already better than us, honestly, at these sandbox problems. A lot of the tough questions are, you know, that, that, that we answer today are things like, well, You know, there, there was this, uh, there's, there's this project that we're trying to do today, and it's very similar to what somebody else actually asked Devin a month ago. And how do we use that knowledge and kind of improve on that, um, in order to make Devin smarter? Or there's these little things of like, you know, you, you want to go test the front end for, for your, your code base and make sure everything looks as expected. You know, you should be able to understand like, what is that supposed to look like? Or why is this different from what, you know, if you find a bug, you should be able to understand like how you found the bug. And that's a lot of the little detail of, Honestly, uh, of, of what makes, I'll call it the difference between code and software engineering, right? Which is basically working in a large complex code base, building some intuition and some representation of all the different pieces and how they interact with each other, learning how to use all the various tools at your disposal to, to actually understand what's going on and to, to debug and diagnose. Um, and I think that is actually the, the big problem, honestly, in AI coding. And I, I think that's, that'…

AI assessment note: “A focus on deep context. It's already better than us, honestly, at these sandbox problems.”

Q Would you agree with that in what you see with your customers and peers? One. And then where will that be in three years time?

A Yeah. Yeah, absolutely. So people, people often talk about the percent of code that's written. I think the, you know, the, the, the obvious thing to call out as well, It's, it's a little odd because for one, you have to, you have to factor in how important each line of code it is, right? If it's just like a ton of protobuffs, then that's, you know, that's one thing versus, you know, a lot of the core business logic is another thing. And then two of course is, you know, written with the help of AI is one thing, but, but how much, and so, so for, for those reasons, we often like to think about in terms of like how much faster is an engineer using all these tools, you know, and an engineer using the best AI tools and, you know, who really understands how to get value out of them. How much are they doing in one hour? Versus how much they would do in one hour with no access to AI. And I would say that something in that range of, you know, 1.5 to two X feels right to me today in aggregate. Look, I think in three years, there's no reason that shouldn't be a 10 X. And I think it's, it's the thing that's really fun, by the way, is I think we're going to have more than 10 X more code. It's something I've been saying recently is I keep track of every time in my daily life where software fails me, we become conditioned to be okay with it, but the truth is it happens All the time. You know,…

AI assessment note: “range of, you know, 1.5 to two X feels right... in three years... 10 X”

Q I'm just like, when you look at like scale, it's like, you know, there's a husk left behind, which kind of deteriorates and you're seeing that deteriorate in real time. Why did you believe that this was inherently different and that the husk was not a husk? It was actually a treasure chest of value in a way that was different to scale.

A Yeah, so there was definitely this conversation online, right, about, oh, like all the best, you know, all, all the best researchers left, and, and there's just nothing, nothing left behind, and I, I, we were, you know, I, I, I don't think so, is basically how we felt about that, and, and we looked at it, and I mean, it's, look, it's, here, here's, here's the thing, right, is, is, it's an amazing product that, that a lot of people use, um, it's the entirety of the customer book as well, right, um, it's, It's all of the code, um, a lot of the data and the proprietary IP, and then obviously it's a, it's a really incredible team. Um, and, and so it's an interesting, you know, I think it's an interesting state in the sense that you could call it perhaps like a somewhat incomplete piece, but, but I, I think that, uh, I mean, as it turns out for us, I mean, we, we had the very nice compliment of what were the pieces that were needed, right? Um, in order to go and do this.

AI assessment note: “it's an amazing product... customer book... code, a lot of the data”

Q Would you agree with that in what you see with your customers and peers? One. And then where will that be in three years time?

A Yeah. Yeah, absolutely. So people, people often talk about the percent of code that's written. I think the, you know, the, the, the obvious thing to call out as well, It's, it's a little odd because for one, you have to, you have to factor in how important each line of code it is, right? If it's just like a ton of protobuffs, then that's, you know, that's one thing versus, you know, a lot of the core business logic is another thing. And then two of course is, you know, written with the help of AI is one thing, but, but how much, and so, so for, for those reasons, we often like to think about in terms of like how much faster is an engineer using all these tools, you know, and an engineer using the best AI tools and, you know, who really understands how to get value out of them. How much are they doing in one hour? Versus how much they would do in one hour with no access to AI. And I would say that something in that range of, you know, 1.5 to two X feels right to me today in aggregate. Look, I think in three years, there's no reason that shouldn't be a 10 X. And I think it's, it's the thing that's really fun, by the way, is I think we're going to have more than 10 X more code. It's something I've been saying recently is I keep track of every time in my daily life where software fails me, we become conditioned to be okay with it, but the truth is it happens All the time. You know,…

AI assessment note: “1.5 to two X feels right to me today... in three years, there's no reason that shouldn't be a 10 X”

Q When you look at something that no one sees that everyone should see, when you think about the future of AI code and the future of software engineering, what does no one talk about? That you think more people should be talking about?

A A focus on deep context. It's already better than us, honestly, at these sandbox problems. A lot of the tough questions are, you know, that, that, that we answer today are things like, well, You know, there, there was this, uh, there's, there's this project that we're trying to do today, and it's very similar to what somebody else actually asked Devin a month ago. And how do we use that knowledge and kind of improve on that, um, in order to make Devin smarter? Or there's these little things of like, you know, you, you want to go test the front end for, for your, your code base and make sure everything looks as expected. You know, you should be able to understand like, what is that supposed to look like? Or why is this different from what, you know, if you find a bug, you should be able to understand like how you found the bug. And that's a lot of the little detail of, Honestly, uh, of, of what makes, I'll call it the difference between code and software engineering, right? Which is basically working in a large complex code base, building some intuition and some representation of all the different pieces and how they interact with each other, learning how to use all the various tools at your disposal to, to actually understand what's going on and to, to debug and diagnose. Um, and I think that is actually the, the big problem, honestly, in AI coding. And I, I think that's, that'…

AI assessment note: “A focus on deep context. It's already better than us, honestly, at these sandbox problems.”

Q So what did you believe in the world of AI that you have subsequently changed your mind on in the last 12 to 24 months?

A I think one thing which is, it's just really started to change in the space. 24 months ago, actually the story was all about data and just more and more and more data, right? And quantity of data and just figuring out how you get even more. And I think that has changed a lot actually towards figuring out a small set of highly curated data for exactly the use case that you care about. And that's been a fun one. You know, I'll just give an example. We, um, a lot of our research work, we obviously You know, for, for, we, we obviously can't talk about publicly, but, but we did, we did share one project, which was, um, uh, a model that we released called Kevin. Um, I'm not sure if you saw it. Kevin.

AI assessment note: “changed a lot actually towards figuring out a small set of highly curated data”

Q It's been pretty insane. I just want to start, and we're going to start, like, at present day, and work our way around, but I just want to start with, like, how did you learn about the potential ability for you to acquire Windsurf, and how did that opportunity arise?

A We found out, honestly, on Friday, the same time everyone else did, that all of this was happening, and that this was the split, and that it was Google, and And, and here's what happens next. And here's what happens with the team. And, and we were kind of talking about it, which is, you know, on the Devon side, I think in a few ways, it seems to be a pretty natural fit. One, because I think obviously there was an incredible, um, you know, team left behind. And if anything, I think the, um, you know, what, what we have at Cognition, I would say is especially focused on the, the core engineering and product team. Whereas obviously like, um, you know, I think Windsurf has built an amazing, um, go to market team. Um, you know, marketing team, finance operations, uh, and then similarly in terms of the products, you know, we found that actually it was, there was a very naturally complimentary lean. Um, and so we reached out cold, um, uh, Friday evening and our first conversation was Friday night. And, uh, and it was, I mean, I, I'm glad.

AI assessment note: “we reached out cold, um, uh, Friday evening and our first conversation was Friday night”

Q I'm just like, when you look at like scale, it's like, you know, there's a husk left behind, which kind of deteriorates and you're seeing that deteriorate in real time. Why did you believe that this was inherently different and that the husk was not a husk? It was actually a treasure chest of value in a way that was different to scale.

A Yeah, so there was definitely this conversation online, right, about, oh, like all the best, you know, all, all the best researchers left, and, and there's just nothing, nothing left behind, and I, I, we were, you know, I, I, I don't think so, is basically how we felt about that, and, and we looked at it, and I mean, it's, look, it's, here, here's, here's the thing, right, is, is, it's an amazing product that, that a lot of people use, um, it's the entirety of the customer book as well, right, um, it's, It's all of the code, um, a lot of the data and the proprietary IP, and then obviously it's a, it's a really incredible team. Um, and, and so it's an interesting, you know, I think it's an interesting state in the sense that you could call it perhaps like a somewhat incomplete piece, but, but I, I think that, uh, I mean, as it turns out for us, I mean, we, we had the very nice compliment of what were the pieces that were needed, right? Um, in order to go and do this.

AI assessment note: “It's all of the code, a lot of the data and the proprietary IP”

Q What have you not built that you would most like to build?

A The answer I would give today, which is, which is, I mean, the biggest thing that we've been thinking about in the last few days since this deal, is really in figuring out What is that combined experience of IDE and agent? Because I think there really is something here. You know, I, I think to, to, to, to what we said earlier, you know, I think years from now, all of these systems will look so different, you know, and, and we may not even have the same terms for them, but I think in, in, in the immediate future, I think both IDEs and agents will be an important part of a developer's workflow. And you can imagine all sorts of things of, Hey, I want to go and plan out a task in the IDE. I want to be able to use the intelligence and the retrieval and, you know, dev and search and, You know, read on the wiki to understand exactly what, what decisions I need to make or what parts of the code this is going to touch and, and what things I need to plan out. And then I want to be able to hand that off to an agent, have the agent go do the bulk of the work, and then I'm going to go and review the code. And naturally it'd be great to review the code locally in my IDE. If there's any touch up that I need to do, I can use that, you know, I can use my NIDE tooling to go and do that. But, but basically, um, you know, figuring out What is that combined experience where you can go from synchron…

AI assessment note: “figuring out What is that combined experience of IDE and agent?”

Q So what did you believe in the world of AI that you have subsequently changed your mind on in the last 12 to 24 months?

A I think one thing which is, it's just really started to change in the space. 24 months ago, actually the story was all about data and just more and more and more data, right? And quantity of data and just figuring out how you get even more. And I think that has changed a lot actually towards figuring out a small set of highly curated data for exactly the use case that you care about. And that's been a fun one. You know, I'll just give an example. We, um, a lot of our research work, we obviously You know, for, for, we, we obviously can't talk about publicly, but, but we did, we did share one project, which was, um, uh, a model that we released called Kevin. Um, I'm not sure if you saw it. Kevin.

AI assessment note: “changed a lot actually towards figuring out a small set of highly curated data”

Q Just take me to it. Then you reach out to Jeff and you're like, Hey, figure something's going down. Should we jump on a call?

A Yeah. Yeah. And so, I mean, we basically said, look, it's, uh, it's, it seems like there's enough here that it's, it's worth having the conversation and talking about it. We got on the call together. We were talking about, um, um, you know, the ways to partner and what things would look like. And I think what we came to pretty quickly, um, you know, I, I always think about these things in terms of, uh, call it like, what, what is the, what, what is the correct way that things should happen here? Right. Um, and, and I think from Windsurf's perspective, the way that, that, that we kind of saw it was, well, you know, you could talk about the, um, the, the, the product of the team and the business, right? Um, and, and what is the right thing for each of those? And I think for the business, the thing that, that you have to call it is, Sooner the better. You could do this, and you could have like, you know, months of diligence and everything, and obviously that has apparently happened multiple times already, you know, in, in Windsurf's company history, and I think in this particular case, I, I, I think it's, look, it's, it's, everyone is scrambling, you know, all, all the customers want to know what's going on, the whole team is, wants to know what's going on, everyone in Silicon Valley is reaching out to them saying, hey, like, I, I heard the news, you know, you want to come intervi…

AI assessment note: “We got on the call together. We were talking about”

Q I watched this, uh, actually TikTok, um, and it said, if you want to build a relationship with someone, ask them about the trait within themselves that they are most proud of, or they like the most, because in future interactions, you're able to refer to it, and it makes them feel good. I'm intrigued. What trait are you most proud of? What's your favorite trait of yourself and why?

A Yeah, um, that's a fun one. It's, uh, I, I actually am very curious to hear your answer to this question as well, by the way. Um, but, but, but yeah, I, I think my answer, funnily enough, is I actually would say it's like a surge emotional calmness, I guess. I get very, you know, for, for, I, I get very, you know, I get very salty. I'm a very competitive person. I get very frustrated and things like that, but, but I, I think for, for better, for worse, we've been in a lot of stressful situations. As you can imagine, we've been in a lot of them in the last six days in particular, but honestly, that's been the entire story of the company. It's, This is probably a bit more than average, you know, than, than, than an average week, but like not by that much. And I, I think the, um, yeah, I think, I think for, for better for, I'm, I'm proud that I'm just able to, to stay composed and, and, and the situation.

AI assessment note: “I'm proud that I'm just able to, to stay composed”

Q Just take me to it. Then you reach out to Jeff and you're like, Hey, figure something's going down. Should we jump on a call?

A Yeah. Yeah. And so, I mean, we basically said, look, it's, uh, it's, it seems like there's enough here that it's, it's worth having the conversation and talking about it. We got on the call together. We were talking about, um, um, you know, the ways to partner and what things would look like. And I think what we came to pretty quickly, um, you know, I, I always think about these things in terms of, uh, call it like, what, what is the, what, what is the correct way that things should happen here? Right. Um, and, and I think from Windsurf's perspective, the way that, that, that we kind of saw it was, well, you know, you could talk about the, um, the, the, the product of the team and the business, right? Um, and, and what is the right thing for each of those? And I think for the business, the thing that, that you have to call it is, Sooner the better. You could do this, and you could have like, you know, months of diligence and everything, and obviously that has apparently happened multiple times already, you know, in, in Windsurf's company history, and I think in this particular case, I, I, I think it's, look, it's, it's, everyone is scrambling, you know, all, all the customers want to know what's going on, the whole team is, wants to know what's going on, everyone in Silicon Valley is reaching out to them saying, hey, like, I, I heard the news, you know, you want to come intervi…

AI assessment note: “We got on the call together. We were talking about, um, um, you know, the ways to partner”

Q Is the talent war getting a little bit out of hand? When you look at Matt's hiring spree, and just how much money, is it getting out of hand?

A Yeah, you know, I, I'll give my, um, maybe crazy opinion, controversial opinion, but I actually think it's, it's, it's, it's quite reasonable, is, is my view, and the reason I say that is because I think AI I, I think we are truly on the cusp of the greatest technology shift in our lives. Um, you know, I, I think that's already clear. And I think this is, you know, crazy thing is even if you froze all the capabilities today, you know, and then the question was just, you know, if you said that there were no new research breakthroughs, no new discoveries, you know, you don't even have to bet on that. And you just said, all right, we're going to, you know, grow products and, and figure out how to build the right experiences and, and get those out to users and, and, and, you know, meet, Meet users where they are in all these different verticals all over the world. I think it would still be the biggest thing, you know, I, I think the biggest thing in my mind, the biggest technology shift in our lives has been the internet. Um, you know, I think there are some others which are obviously pretty massive as well. The mobile phone, the personal computer and so on. Um, but, but yeah, you know, I, I think even if you froze all the capabilities today, I think AI already would be bigger than that. And the thing that's crazy about AI, and by the way, I don't think it's going to freeze. I thin…

AI assessment note: “I actually think it's, it's, it's, it's quite reasonable, is, is my view”

Q Is the talent war getting a little bit out of hand? When you look at Matt's hiring spree, and just how much money, is it getting out of hand?

A Yeah, you know, I, I'll give my, um, maybe crazy opinion, controversial opinion, but I actually think it's, it's, it's, it's quite reasonable, is, is my view, and the reason I say that is because I think AI I, I think we are truly on the cusp of the greatest technology shift in our lives. Um, you know, I, I think that's already clear. And I think this is, you know, crazy thing is even if you froze all the capabilities today, you know, and then the question was just, you know, if you said that there were no new research breakthroughs, no new discoveries, you know, you don't even have to bet on that. And you just said, all right, we're going to, you know, grow products and, and figure out how to build the right experiences and, and get those out to users and, and, and, you know, meet, Meet users where they are in all these different verticals all over the world. I think it would still be the biggest thing, you know, I, I think the biggest thing in my mind, the biggest technology shift in our lives has been the internet. Um, you know, I think there are some others which are obviously pretty massive as well. The mobile phone, the personal computer and so on. Um, but, but yeah, you know, I, I think even if you froze all the capabilities today, I think AI already would be bigger than that. And the thing that's crazy about AI, and by the way, I don't think it's going to freeze. I thin…

AI assessment note: “I actually think it's, it's, it's, it's quite reasonable”

Q what no one was discussing. It's a hard one, and I, so I don't know how blunt I can be, but it felt like Devon fell out of the zeitgeist a bit, if we're honest. Cursor and Windsurf owned consumer attention and owned the brand. Do you think that was a case that Devon just wasn't very good at marketing, or do you think that was like a product misstep?

A Yeah, so it's, it's funny because I, I think there's always an external perception, and then there's some kind of internal what's actually going on with the numbers, and without going too much into detail, what I can say is that in the last six months, you know, between January and, and now, you know, like, even aside from this, you know, obviously the, the latest deal this week with Windsor, um, The usage of Devon has actually grown something like five to 10 X. Um, and that's been the case in both self-serve and enterprise. Um, and it's, and so it's been fun to see that, you know, it's like, I think, I think the pattern for, for what it's worth is it's really like real engineering teams that bring on Devon and they, they tag Devon all the time in Slack, they tag Devon in linear and so on. And then they kind of, you know, use it and, and, and grow it and share it that way. And so in many ways, it is not the same kind of like, um, you know, Single non-engineer just going and, and signing up for an account can immediately just like build something like really cool with it. People do use it that way, but it is not the majority of our usage, right? I think the majority is really just kind of like real teams using it. But, but I think the point that you're saying, I think does get to, I think an important thing, which is that, look, IDEs, um, and the IDE experience are obviously, yo…

AI assessment note: “there's always an external perception, and then there's some kind of internal what's actually going on”

Q Were they left in the lurch by this deal?

A Oh, I see. So, yeah, so, so I think they had known about the, um, I, I think they had known about the previous, uh, thing, you know, maybe a few days in advance. Um, um, it, it was not a time of, uh, advance notice, and, and, and I think they were honestly really thoughtful with, with how they went about it, which is, look, here are the options. We can operate as an independent company. You know, we can go and raise a new round of venture capital now that there are actually no investors, or, or we can find someone who we think are going to be the right partners to work with. But either way, you know, it's going to be, we're going to have to do this quickly and we're going to have to, to, to figure out what we think is the right long-term fit for it.

AI assessment note: “they had known about the previous thing maybe a few days in advance”

Q Those pieces are the rationale that lead to the decision. How do you actually execute it? Like literally, how does that work in process?

A Yeah, yeah, for sure. So, so, so we came to them and we said, look, I think there's a very natural partnership here. I think that the team pieces are very complimentary. I think there's a lot we can do on the product. The, the thing that just seems, you know, absolutely clear from both of our sides is if we're going to do something, we want to be ready to do this and announce it by Monday morning. You know, it's, it's kind of reminds me of like, like, you know, the bank goes into receivership Friday night. You gotta have an answer, you know, by, by Sunday and by Monday morning, right? And I, I, I think we thought of this as a similar situation, which is look, there's, there's a ton of value here, but, but everyone's wondering what's going on and we need to be able to give them a clear answer as soon as possible that look, we are going to do this. We're going to support, you know, the products. We're going to, we're going to make sure things, everything's going smoothly and running smoothly and so on. And, um, and, and so that's what we came to and, and, and we gave them, you know, our, our, our, our honest take of like, here's what we think we can do together. Um, it's, You know, we, we, we are not going to have time to, to get to go like as deep into the diligence and details as we would like to, but, but I think at a high level, we, we at least, you know, I think are in a pos…

AI assessment note: “get to a verbal agreement on Saturday, hash out all the details”

Q When you think about that developer efficiency, what are agents not able to do today that they really need to be able to do?

A I think there is, um, a real point at which agents are truly able to take over Ownership, I guess is how I would describe it, of, of the work that is, is, is done. And the way I kind of want to say it is like, look, I, I think in the future we will get to a point where you're not looking at your code. You know, you're looking at your product, right? And you're, you're looking at your product. And at the end of the day, code, software engineering, this whole thing is just telling your computer what to do. And code is the language that your computer happens to speak. And that's why we all have to learn how to write code in order to do it. Right. But, but, but, but I think over time, yeah, you, you get to the point where you can just say, all right, yeah, like this website, you know, let's, let's add a new tab here and, you know, let's put this, this and that information and maybe let's go collect this, this info from the user and we'll save it in the database this way. And, you know, this button should be a little bit rounder and you're just able to make those calls and make all those decisions. And, and, and I think we'll still call it programming, you know, but, but I think it's going to transition into being more of like, A technical architect, a technical product manager, you know, someone who's really owning these decisions. And, and I think agents have to get to the point w…

AI assessment note: “agents have to get to the point where they are basically that high touch”

Q Were they left in the lurch by this deal?

A Oh, I see. So, yeah, so, so I think they had known about the, um, I, I think they had known about the previous, uh, thing, you know, maybe a few days in advance. Um, um, it, it was not a time of, uh, advance notice, and, and, and I think they were honestly really thoughtful with, with how they went about it, which is, look, here are the options. We can operate as an independent company. You know, we can go and raise a new round of venture capital now that there are actually no investors, or, or we can find someone who we think are going to be the right partners to work with. But either way, you know, it's going to be, we're going to have to do this quickly and we're going to have to, to, to figure out what we think is the right long-term fit for it.

AI assessment note: “they had known about the, um, I, I think they had known”

Q When you think about that developer efficiency, what are agents not able to do today that they really need to be able to do?

A I think there is, um, a real point at which agents are truly able to take over Ownership, I guess is how I would describe it, of, of the work that is, is, is done. And the way I kind of want to say it is like, look, I, I think in the future we will get to a point where you're not looking at your code. You know, you're looking at your product, right? And you're, you're looking at your product. And at the end of the day, code, software engineering, this whole thing is just telling your computer what to do. And code is the language that your computer happens to speak. And that's why we all have to learn how to write code in order to do it. Right. But, but, but, but I think over time, yeah, you, you get to the point where you can just say, all right, yeah, like this website, you know, let's, let's add a new tab here and, you know, let's put this, this and that information and maybe let's go collect this, this info from the user and we'll save it in the database this way. And, you know, this button should be a little bit rounder and you're just able to make those calls and make all those decisions. And, and, and I think we'll still call it programming, you know, but, but I think it's going to transition into being more of like, A technical architect, a technical product manager, you know, someone who's really owning these decisions. And, and I think agents have to get to the point w…

AI assessment note: “agents are truly able to take over Ownership, I guess is how I would describe”

Q What do people, what do people not see with RL that they should see? Because I, candidly, I don't.

A Yeah, so, so, look, again, RL is, we've had a few years of, I would call, imitation learning before RL, which is, that's what went into GPT-III and III.V and so on, which is basically, you take the entire internet, and you read the whole internet, and you get a model that sounds like somebody on Reddit. It's crazy. I mean, it was obviously ChatGPT, like, shocked the world, and it was a huge moment for everybody. Um, but, um, but, but, but yeah, you could kind of see why, well, you know, talking like the average is, is not necessarily the thing that you need to Do to go build a great, you know, medicine specialist or a great, um, um, you know, software engineer or any of these things. And I, I actually got a lot of the way there to be fair, more than people might've guessed. Um, but, but I think that the next big thing with RL is, as we said, you can take any benchmark and solve it. It is crazy to say, but, but, but, but I think the next step of that is honestly an open question for everyone in every application, which is, Hey, what is the benchmark? You know? Well, if you're, you're, you're an accountant, you know, the benchmark, I mean, in real world terms, the benchmark is roughly like, all right, you submit returns on behalf of the client. And, you know, if you get audited by the IRS and something comes up, then, then that was a fail for the RL. And if you don't, then you di…

AI assessment note: “the next big thing with RL is, as we said, you can take any benchmark and solve it.”

Q what no one was discussing. It's a hard one, and I, so I don't know how blunt I can be, but it felt like Devon fell out of the zeitgeist a bit, if we're honest. Cursor and Windsurf owned consumer attention and owned the brand. Do you think that was a case that Devon just wasn't very good at marketing, or do you think that was like a product misstep?

A Yeah, so it's, it's funny because I, I think there's always an external perception, and then there's some kind of internal what's actually going on with the numbers, and without going too much into detail, what I can say is that in the last six months, you know, between January and, and now, you know, like, even aside from this, you know, obviously the, the latest deal this week with Windsor, um, The usage of Devon has actually grown something like five to 10 X. Um, and that's been the case in both self-serve and enterprise. Um, and it's, and so it's been fun to see that, you know, it's like, I think, I think the pattern for, for what it's worth is it's really like real engineering teams that bring on Devon and they, they tag Devon all the time in Slack, they tag Devon in linear and so on. And then they kind of, you know, use it and, and, and grow it and share it that way. And so in many ways, it is not the same kind of like, um, you know, Single non-engineer just going and, and signing up for an account can immediately just like build something like really cool with it. People do use it that way, but it is not the majority of our usage, right? I think the majority is really just kind of like real teams using it. But, but I think the point that you're saying, I think does get to, I think an important thing, which is that, look, IDEs, um, and the IDE experience are obviously, yo…

AI assessment note: “The usage of Devon has actually grown something like five to 10 X.”