(22) Scott Wu, CEO van Cognition, over de overname van Windsurf: het proces, de deal en de redenatie - YouTube https://www.youtube.com/watch?v=Xz060_Kn0F0

Transcript: (00:00) I think there's an unspoken covenant that as a founder you go down with the ship and I think that for better or for worse it's changed a bit over the last year and I and I think it's a bit disappointing to be honest. I think there's some real truth to your point that often there are actually a lot of really valuable pieces that get left behind. (00:19) The only thing that anyone wants to talk about this week is cognition buying wind surf. We unpack it all today with Scott Woo, co-founder and CEO at Cognition in AI code. To be truly honest, if there was zero progress, the world would still be entirely different. Ready to go. [Music] Scott, I am so excited for this dude. (00:49) I was literally just telling you it is a cool prep when you get to call up like Vinob Kosler, Joe Lndale, and you call them and you're like, "Hey, what should I ask?" And they're just like, "Ah, I love this guy." Um, so thank you so much for joining me. Yeah, thanks for having me. It's uh it's been a crazy few days for us all. It's been pretty insane. (01:07) 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 Windfur and how did that opportunity arise? 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 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 (01:41) 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 (02:14) so just 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? Yeah. Yeah. And so I I mean we basically said look it's uh it's 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. (02:33) 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 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 that we kind of saw it was well you know you could talk about the um the the the product the team and the business right um and what is the right thing for each of those and I think for the business the thing that h that you have to call out is sooner the You could (03:05) 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 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 interview here um and so you know we kind of just came to this conclusion look a month long is (03:34) is not the way to do this. I mean, even like a week long, you know, it's it's it is Friday night now. We want to have something ready to go by Monday. I I'll pause because it sounds like you have a you have I'm just intrigued 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. (03:53) 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 scale? 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. (04:12) And I we were, you know, I I don't think so is basically how we felt about that. 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 I think (04:42) 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 those pieces are the rationale that lead to the decision how do you actually execute Ed like literally how does that work in process? Yeah. Yeah. For sure. (05:01) So, so, so we came to them and and we said, "Look, I I think there's a very natural partnership here. I think 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. (05:19) " You know, it's it kind of reminds me of like like, you know, the the bank goes into receiverhip Friday night. you got to 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 product. We're going to we're going to make sure things everything's going smoothly and running smoothly and so on. (05:44) And um and so that's what we came to and and and we gave them, you know, our our our honest take of like here 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 position to understand the business very well and and let's just figure out if you know like get get to a verbal agreement on Saturday hash out all the details and the terms and the legal on (06:14) Sunday get everything signed and done on Monday morning and then we're ready to announce like that's it's it's there there's there's no other way you know to to make this work out and and and Jeff and Graham and Kevin and and the whole crew honestly like I mean it's a huge shout outs to them because they really they they really worked around the clock for for their team. (06:36) So um it's now we get to do this all together, right? Were they left in the lurch by this deal? What's that? Were they left in the lurch by this deal? 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 ton of uh advanced 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 (07:08) 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. (07:20) I think most people see this as a really epic deal make from you respectfully. And I mean, total hat tip and respect to you for it. The question that I have is, and actually I think it was Roocci at at South Park who asked this, but she said, "Was this a Google blunder by leaving such a valuable asset up for grabs and not seeing the true value also in the asset?" I think there's some real truth to your point that often there are actually a lot of really valuable pieces that that that get left behind. Um, and so (07:53) can I ask you given that you've been through this deal structure that's different and novel, do you think this becomes a new norm for how companies are acquired and how people join companies today? I think there's an unspoken covenant that as a founder you go down with the ship, you know, and and I think that uh for for better, for worse, it's it's it's it's changed a bit over the last year and I I think it's a bit disappointing to be honest. Is the talent war getting a little bit out of hand when you look at Meta's hiring (08:22) spree and just how much might is it getting out of hand? Yeah, you know, I 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. (08:48) Um you know I 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 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 think (09:16) 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. (09:34) And the thing that's crazy about AI, and by the way, I don't think it's going to freeze. I think it's going to keep moving even faster. But the crazy thing about AI is there really are so few people that are really just determining the trajectory of AI. But I think in aggregate I I I think the view is right which is you know there's so few people interrupt you is it I'm so sorry I'm totally agree in terms of what is it like a hundred is it like 10,000 just what quantum is it it's a great question um somewhere in between those two is right you know I I think there are at least 100 folks that that that that really matter and making a lot a lot of difference certainly less (10:07) than 10,000 and and probably a good bit less than that if I had to guess. Okay, so we've got like a 100 to a thousand is kind of a range there. Do you need those people unless you're working on the most cutting edge frontier models if you're in the application layer which is very hard I'm not den but like do you need them if you're in the application layer? I think the level of talent and the fierceness of competition is in many of these is actually like greater even in the application layer which is crazy to say because I think the competition at the foundation labs is extremely strong. (10:41) When when you think like holy [ __ ] anything can happen style which it is today. One of the like oh shits that could happen that's very obvious to I think me and everyone is like the dependency now around anthropic you know obviously wind surf yeah you know when I had Verun on the show you know they were very much reliant on them then and then they got cut off when the open AI deal was done is the reliance on anthropic greater than it's ever been. (11:08) Yeah, I mean look, we we we work very closely with Anthropic. I I I think Anthropic is a great company and and you know, I think the foundation labs in general are great companies. People always ask this question about, you know, where does the value occur in AI? Does it you know is is it chips? Is it semiconductors? Is it um you know foundation models? Is the application layer? Is the infra layer? And and I I think the boring but true answer is it occurs wherever you are able to establish real differentiation in your space. Um, and I think there will be a lot of spaces for which that's the case. (11:38) And, you know, to be honest, I I think the Foundation Labs as businesses will do extremely well, right? But, but I I think the thing that we own is um, and that we spend all of our time on, I think is is actually a nicely complimentary piece, which is in some ways really thinking about how to best optimize for very particular capabilities within software engineering and how to deliver um, and ship like a a really great product experience around that, right? Do you not want though the developer products for these foundation models to commoditize because then you (12:08) gain leverage if anthropics include continues to be so much better than it is their leverage is gone. Do you not want that commoditization? Yeah. Yeah. Look, I I mean I think it's uh it's to be honks are folks are pushing ahead in the foundation model space and making a ton of progress. (12:29) We've seen a lot of launches even in the last you know week or two, right? I mean there's Kimi and Grock and um and a ton of great progress that's been happening and and I think that is the natural way of things um which is you know there will be competition in in that layer and I think some folks will you know especially in particular verticals and use cases be able to establish differentiation and there will be competition in our layer and then some folks will be able to establish differentiation a as this equilibrium develops you know I think it is just naturally the case that that that folks in these layers want to (12:56) collaborate um you know and figure out the right ways to work together as long as that that that holds. Why would Anthropic want to collaborate when they could just own it? Sorry, I'm I'm a VC, so I'm naive. No, no, of course. Of course. I love it. All hidden me with all the hard questions. (13:15) Look, I 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 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. (13:39) All right, here's here's how to go, you know, to data dog 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 a representation of the codebase which we're learning and iterating over time and so on. And I I think at the end of the day there's there there are a lot of different verticals to work in and to solve for. (13:58) I I think we have parts of this equation and and I think the foundation labs have parts of this equation, but I think the truth is you really need both. You preface that one with you can ask the hard question. So, [ __ ] it. It's It's the end of the day in the UK, so I'm like using that as an excuse. What percent of your revenue goes to anthropic, do you think? Ballpark. (14:15) I I I have to pass on that one. I love it. I don't It's like with children, you know, where they'll push and they'll see how far they can go. Yeah. When you speak about that progress and the incredible progress that we've seen, some think that it will take the same route as self-driving cars where there is this kind of plateauing and then we'll see again another inflection point. (14:39) What gives you such confidence that we will see the continual progression in models that we've seen over the last 12 months over the next 36 months? Sure. Yeah. So I'll give you two thoughts there. The first thought is there's very strong signs of this continued progression largely because by the way there's there's a lot of specific work which is you can call it research you can call it engineering you can call it info or whatever you like but but there's a lot which is roughly that we know the techniques and we have a lot more to do to go and scale those you know it's it's RL for example is I would say the the biggest breakthrough (15:11) of the last year and a half call it um and it's it's really amazing that it's it's crazy to think that you you roughly can solve any benchmark I mean that is that it is almost it is it sounds insane to to say but that's that's really what RL is converging on right which is basically if you have a clean enough set of here are exactly the behaviors that I want here are the environments that you need to be able to operate in here's what it means to succeed or fail you can just train a model that does that uh and (15:37) and naturally that is just such a powerful capability which I think is going to be applied to more and more spaces and so I I think we will see that progression the other thought I would give though and and I mean this truly sincerely is look there are a lot of spaces you know, and a lot of different things going on in AI. (15:54) In AI code, to be truly honest, if there was zero progress, you know, the the world would still be entirely different. You know, I I think there are a lot of spaces that that are early today that you see AI making progress, it's getting better and better, and you're going to the next step and the next step. (16:12) In code, you you are just slower as a software engineer if you're not using AI. That that is the truth. And and it is a no-brainer already today. and and look, I think it will be more of a no-brainer and I think we'll be able to make engineers even more efficient, you know, be able to do even more with code. Um, but but but I I think that is already the case. So many things to unpack there, dude. (16:30) Do you think tools like Devon and others make 1x engineers 10x engineers or 10x engineers 100 engineers 100x engineers if I were to put you in one camp? Interesting. It actually really does depend tool by tool. I do think that the product experiences for the, you know, for for the 1x to 10x and the 10x to 100x or even, you know, the 0x to to 1x or or whatever you want to call it, you know, um are are are somewhat different project experiences. I've interviewed Benny off at Salesforce. I interviewed Vlad at Robin Hood, both very recently, and they both (17:01) said that 50% of their net new code is created by AI. Would you agree with that in what you see with your customers and peers, one, and then where will that be in 3 years time? Yeah. Yeah, absolutely. So, people people often talk about the percent of code that's written. I I think the you know the the the obvious thing to call out is 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 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 (17:31) 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 engineering using the best AI tools and you know who really understands how to get value out of them. (17:51) How much are they doing in 1 hour versus how much they would do in 1 hour with no access to AI? And I would say that something in that range of, you know, 1.5 to 2x feels right to me today in aggregate. Look, I I think in 3 years there's no reason that shouldn't be a 10x. And and I think it's it's the thing that's really fun, by the way, is I think we're gonna have more than 10x more code. (18:13) Something I I've been saying recently is I I I I I I keep track of every time in my daily life where software fails me. We've become conditioned to be okay with it. But the truth is it happens all the time. you know I and it's you think about products out there and you know the way the way I I like to say it is you know there there are I say this top tier of products which are in some sense like I'll call them the the best made products in the world and I'm thinking of like YouTube, Tik Tok, Instagram and so on and you can really feel every little detail um that that that that (18:47) they've done with a ton of care. You know it's the they're streaming in tons and tons of data and it's always super efficient. It never goes down and it's super reliable. The algorithm basically knows you better than you know yourself. The UX is super intuitive and that is like you know I call it like hundreds of millions of hours of engineering time you know that went into building that that piece of software right and then you kind of go down to the next layer of you know the next order of magnitude of of of software that has tens of millions (19:16) of of of of hours spent and then singledigit millions and so on you know a and you see the differences really quickly. I mean, when you're logging into your bank or when you're dealing with your healthcare, you know, you know, working with your insurance and trying to get things going or when you're trying to go and like um you know, navigate your your customer list or things like that. (19:35) And and and the truth is all the software can be 10x better, you know, and I think there actually is 10x more of it to write. And I think that's one of the fun things in in code, right, is that it really does have this Jevans paradox. When you think about that developer efficiency, what are agents not able to do today that they really need to be able to do? 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 I think in the (20:07) 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 (20:31) 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 where (20:55) they are basically that hight touch and that kind of understanding of context that you can give them that level of instruction and they'll just go and do that in a world like that what skills become more valuable and what skills become less valuable. Everything that you you do is going to be about essentially this this kind of core thing of deciding what is the the the solution you're going to build. (21:16) You know, what is the problem that we're facing? What is the solution that we want to build? How exactly do we want to architect that solution? And I think that's going to be the most important skill. There's so many things I want to ask. I do just want to go back before I forget it. You said about the one and a halfx more efficient and more productive. Yeah. (21:32) Do you think we are struggling now in a value chasm gap? And what I mean by that is how much do you charge for Devon today per se average? So it's all usage based, but it's it's it's essentially by the hour. Um and and we we try to make things so that they're about 10x cheaper than um you know than than basically the value of your time and going because if you think about say a software engineer being 300 grand a year give or take uh 150k then would be that.5x that you're adding. Yeah. (22:04) Are these tools going to be sufficiently paid for the value creation that they are enacting? Yeah. Yeah. Um, look, I I I think the value creation is a beautiful thing. Um, and and to this point, by the way, of of where does the value acrew in AI that we were talking about earlier, there are 30 million software engineers in the world. (22:24) You know, we're going to make them all 10x more efficient over these coming years. We're going to be writing 10x more code. We're going to be doing a lot here. And and I think that, you know, we could talk about whether it's 5% or 10% or 20% or 30% of, you know, the value that that actually gets collected um by the companies doing this, but but honestly, I I I think that that the the highest order bid is actually less that and more about um just, you know, getting the technology and and and building the products to to a point where where everyone is is is is going a lot faster with them. When you (22:54) 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 focus on deep context. It's already better than us honestly at these sandbox problems. (23:17) A lot of the tough questions are, you know, that that that we answered 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 Devon a month ago and how do we use that knowledge and kind of improve on that um in order to make Devon smarter or there's these little things of like, you know, you you want to go test the front end for for your your codebase 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 (23:41) 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 of of of what makes I'll call it the difference between code and software engineering, right? which is basically working in a large complex codebase, 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 (24:07) to to debug and diagnose. Um, and I think that is actually the the big problem honestly in AI coding. And I think that's that's that's the big thing that folks will work on next. The thing that's fun by the way it's a very practical problem you know and so it's a you can call it a research problem obviously in many ways it is a research problem um in terms of like how how to push for these capabilities and make these things better but it's not not the kind of thing that you can solve in a sandbox you know it's a kind of thing that you actually really just need to (24:32) think about the practicality of software engineering to to to get it to you said there about kind of hey coding agents was what you saw before other people saw and what no one was discussing it's a hard one and I so I don't know how blunt I can But it felt like Devon fell out of the zeitgeist a bit if we're honest. (24:51) 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? Yeah, so it's it's funny because I I think there's always an external perception and then there's an kind of internal what's actually going on with the numbers. (25:09) And without going too much into detail, what I can say is that in the last 6 months, you know, between January and and now, you know, like even aside from this, you know, obviously the latest deal this week with Windserve, um the usage of Devon has actually grown something like 5 to 10x. Um and that's been the case in both self-s serve and enterprise. (25:27) 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 and linear and so on and then they kind of you know use it and and grow it and share it that way. (25:44) And so it 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 but it's not the majority of our usage, right? I think the majority is is really just kind of like real teams using it. (26:04) But but I think the point that you're saying I think does get to I think an important thing which is that look idees um and the IDE experience are obviously you know they they came and and they really started working I think about a year before um before the agent experience really did you know I kind of think of agents as having taken off in the last 6 months or so and I think of idees as you know sometime last year um as when they really started to become kind of like no-brainer obvious let's say in terms of the value that they provided. (26:32) And I think what we're kind of seeing is is an artifact of that. Uh which is that um which is that yeah like f folks are more familiar with ideides because they've been around for a while. I think you fast forward 6 to 12 months from now and I think people will be familiar with agents to the same level um that that they're familiar with today. 5 to 10x is is mega. Um it's fantastic. (26:56) The hard thing is if you compare it to like a rapid or a lovable, the growth is just [ __ ] nuts. Like I'm in lovable Scott and I just look at the numbers and I'm like what? Like what? How does that work? Um is that not a fair like for like comparison if you're thinking about growth rates? The reason I would say that it's not also but actually I don't even know the the number what what are their numbers over the last six months or what are their uh they've gone from basically zero to 80 million an hour. Yeah. Look I I I don't want to get into exact numbers but even with with the (27:33) wind surf deal aside like not including that at all we we basic we've we we've done roughly that as well in the last 6 to8 months. I stand corrected on my consumer zit guys comment. Okay. And the which is I I think an important point to consider which by the way I think these are great companies and you know I I obviously I think they're but then it's a marketing problem. (27:52) Dude, I'm saying this to your as now I you know I hope we can be friends. So I'm projecting forward this relationship as a friend. I would say you guys should be better at selling yourself. That's nut. That's great. Yeah. Well perhaps we should be. And you know the great news is we've just now inherited a great marketing team. Um and we get to do that. (28:12) Um but but you know the the only thing I'd call out like I I I know Amred from Replet I I've I've met a lot of these folks before. I think of it as actually quite different um um products and businesses and so on which to to the point that we were saying earlier is you know there are a lot of things uh a lot of different product experiences that you can solve for and code right there's like bringing a 10x engineer to 100x there's a 1x engineer to 10x there's you know someone who doesn't know how to code and bringing them to 1x um and I think it is a bit of a different um for better or (28:41) for worse I I I think repleted lovable to my understanding at least are are a much more consumerry lean right and perhaps that's why you hear about them more on Twitter or on YouTube or things like that. Whereas Devon is really, you know, just it's it's it can be it can be anywhere from startups to some of the biggest companies in the world, but it is really focused on specifically engineers on engineering teams trying to do um to to do their work and to go faster that way, right? And so, you know, you can see this in in in how this is all set up, right? Most Devon sessions are started through through (29:13) Slack or through linear and Devon makes these pull requests in GitHub that you go and review and merge and Devon works with your whole um you know your your whole development system, right? And and learns how to get onboarded to your repo and so on. And I think that's that's kind of one difference there. But with that said, I you know, point taken. I I I I take the feedback. (29:31) Yeah, I think it's a very fair point. Dude, I'm always here to show you how to do a good tweet. Uh after 10 years, I now know how to do a good tweet. That's all I know. I mean, you're you're the master at it. I was going to say, so I you know, after this, we'll talk and I I want to get your tips, dude. Honestly, I have so many for you with those numbers. I'm like, wow, dude. (29:50) You need Yeah. Anyway, um can I ask you my job as an investor also is to think about like market makeup at an end state because that's where value kind of also kind of accrrews in my mind. And you think about that and you think about like developer where the market shakes out. (30:10) Is it that cursor win bottoms up developer minds and wind surf win and and cognition now win top down large enterprise super solid blue chip clients? Is that how you think that developer market shakes out? So I 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 I think the future of software engineering is look at this is going to take place over the next couple years or so but but it really is this version where it is it is not just you know we talk we call it (30:46) 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 says 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 (31:09) expressing your intent and there are a lot of things and 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, but I think that is essentially what we get to is, you know, the simple thing I'd say is Tony Stark does not pull up his laptop. (31:25) You know, Tony Stark goes and talks to Jarvis, right? Like like I I I think there's there is a point at which you um um you you just have you you just have a very clean connection, the ability to express your intent and do these things. People talk about generative UI. People talk about senior single use software and so on. (31:45) At the end of the day, what it all really boils down to is you to have a very clean connection and able to just being able to tell your computer what to do and it'll do that for you. And I think if we think about where everyone is today, like I think there are 10 or 20 levels of what the product experience looks like until we get there. And the fun thing is every level is like 2 or 3 months. (32:04) And so if you kind of just multiply that out, it means we're going to be there in like a few years, you know, if this pace keeps going. I believe a common enemy is a very important thing within a company. If I were to push you, Scott, and say, "Hey, who is the competitor that you most look to and think about, respect even, who would that be?" Jet Jensen said this once and it always stuck with me of when you have figured out a way for your company to win that means that no one else has to lose, then you will know that you have found your your your path. (32:40) And uh do you think do you think he's done that? I think that's a huge I certainly think he's done that. Yeah. I mean, you know, and video is an incredible business. Jensen obviously has done it's a freaking monopoly. Like the Well, and and I think his point, right, is is that I think at the end of the day, there are so many different verticals to serve. (33:03) There are so many different niches to own, right? And there are a lot of businesses which of course will work in adjacent spaces and we'll see things and you know you'll you'll you'll run into folks on a deal or or whatever it is but at the end of the day people have the things that they specialize in and and and I firmly believe that like I I I think the thing that's been fun I think throughout the history of cognition is for better or for worse maybe it's cuz we're insane I don't know but we've always had a pretty unique approach and a pretty unique view about like here's here's what we think the future is going to be here's what we want to build for and that's different (33:29) from you know it's different from a cursor that's different from a um um you know open or anthropic themselves and how they think about these things and so on right and I think like the the fun thing about that is is I think there is so much to build in code and and I I actually truly do think there will be more than one winner um and and obviously agents are you know what have you not built that you would most like to build 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 (33:58) figuring out what is that combined exper 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 these systems will look so different, you know, and we may not even have the same terms for them. (34:15) 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 (34:40) 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 in IDE tooling to go and do that. But but basically um you know figuring out what is that combined experience where you can go from synchronous to asynchronous to synchronous um for for you know and and be there for whatever parts need you and and be able to go and parallelize and do more for for the (35:05) parts that don't need you. Um I I think that's going to be a really fun question to figure out in terms of you know what happens with the the combination of wind turf and Devon. (35:18) I think in the immediate short term obviously like I think there's a lot of Devon to run and a lot of Windsorf to run and we plan on kind of like uh you know we certainly plan on on maintaining the philosophy of both of those products but I think kind of finding that intersection in between of how do you make it a really smooth experience to to go between for the folks who use both um is going to be the fun one. Dude, I've so enjoyed this. (35:37) I it was yeah it's just been a really fun conversation. I do want to do a quick fire round if that's okay. So I'm going to say a short. Okay, I have to say I'm I'm a bit underslept and so it's please please pardon me if I need like an extra, you know, one or two seconds for the fireworks, but I like how have you been sleeping? Next question. (36:01) No, look, I mean it's it we had some crazy we had some we've had some crazy days and I mean Saturday, Friday, Saturday, Sunday obviously was figuring out, you know, if there was a deal to be done and and making that happen and Monday, Tuesday, Wednesday has been figuring out how we bring the teams together and how we build the the really great thing. (36:20) And obviously like the the immediate thing is going out to the customers and letting them know, look, it's like we're we're here, you know, we've got the the engineering firepower and the work to to be able to support things. We're going to make sure you guys have um you know a super solid experience and um and if anything we're going to be able to make it better even faster um and figure out the better way you even upleveled the engineering team. (36:38) Hey um and uh and look long story short not not a lot of sleep this week. I love it. Uh okay dude what's one widely held belief about AI that you think is completely wrong? Yeah, I'll give you a take. You know, it's Sam Alman had this post 10 years ago called bubble theory. (37:03) Do you remember it? He was basically saying this was in his YC days and he said, you know, everyone here says that all these companies are overvalued and we're in a bubble and it's obviously fun to talk about bubbles and all, but I don't believe that and I'm going to give you a bet. And he said, here are the It looks hilarious, by the way, when you read it in retrospect, which is like here are the top, you know, YC companies today. (37:21) And it's literally like Uber and Airbnb and like, you know, whatever. And it's like today these are worth this much. I predict that five years from now they're going to be worth, you know, 3x more, you know. And then it's like here are these kind of like emerging, you know, mid mid-level companies. (37:36) And then that list was like, you know, Stripe and um and some of these others. And it's like today this is worth this much and I predict these will be up at least 3x, you know, and and he basically said, everyone says we're in a bubble. If you'd like to go and bet on that and put your own money down, I am happy to put, you know, money on this. (37:54) And I have to say in AI I really feel this I I I feel this I think now more strongly than ever which is over the last 2 years people kind of think of it as this this Gen AI wave again like we're saying like lots of incremental jumps but the truth is RL is is is the master like the the the the the big story I'd say over the last year or two in capabilities and I think people have really underappreciated how much is power possible with RL and what do people what do people not see with RL that they should see because I candidly I don't. Yeah. So, so look again RL is we've had (38:25) a few years of I would call imitation learning before RL which is that's what went into GBT3 and 3.5 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 and it's crazy. I mean it was obviously chat GPT like shocked the world and it was a huge moment for everybody. (38:45) Um but um but but but but yeah, you could kind of see why well, you know, talking like the average 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 I actually got a lot of the way there to be fair, more than people might have guessed. (39:02) 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, 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 did a (39:32) good job, you know, but but obviously, you know, you want to be able to constrain it to shorter feedback cycles than that and think about, you know, what are the ways that you can determine if an agent's work was a success or a failure. But what once you have that it turns out that you can just train agents to do all sorts of things and that's what we've seen by the way. (39:50) I mean, we, you know, um, we we've seen like folks getting gold medals and these these international math competitions and things like that with AI and and and the truth is that this is really hard stuff, right? And and obviously you have to go and apply it to every vertical, but it's going to happen. (40:07) And and and so so I guess on that point, I guess I was just going to say it's like you think about the companies today, there's the foundation layer companies, right? There there's the the application layer and there's a lot of the tooling. I would happily bet like take all the foundation labs today, right? It's it's the the the the private ones, right? There's there's OpenAI, there's anthropic, there's X, you know, let's put in SSI. (40:26) Um we could include thinking machines in that list as well. If you add all their valuations today, what is that like 500 B something like that? I I think that's going to go way up in the next 5 years. And then if you take all the application layer companies, you know, as the top ones that come to mind are, you know, there's Perplexi, there's Sierra, there's Decagon, there's Harvey, there's us, there's Curser, there's, you know, a and you you take that list of companies and today that's list of companies is probably worth, I don't know, 50 to 100 billion. And I think that's going to go (40:50) way up in aggregate. And obviously it doesn't mean every single company is going to go up, but but I think that the value that we're going to produce is is is so massive here that you you can invest in Open AI at 300 billion or Anthropic at 60 billion. Which one do you choose to invest in? Honestly, and I mean this sincerely, I think both are great investments. (41:10) I I think I think I think I think both are great investments at the price. Amazing. You can put money in one. Oh man. Well, Anthropic has quadrupled their revenue since they were valued at 60 billion. So, it see it seems like a fair one to to pick. (41:30) Do you think we will have you mentioned there like six in the foundation model there? Yeah. Do you think we will have six? Do you not think the consolidation already be I think the consolidation happens and obviously you know there's there's Google and there's there's Meta. Um I I think the consolidation happens and I think in total we probably end up with something like two to six players pro. (41:48) I I'm I'm I'm trying to hedge to be conservative. It really is probably, you know, I I think three to five seems pretty reasonable, but Well, you're making a face of me. I want to hear what two two. You think just two? You got chat GPT and OpenAI on consumer and then you've got anthropic on enterprise. (42:09) Really? You think it's just those two? You might have like really tertiary ones. It's just like search or like you know provide. You have like minor ones like your duck duck goes of the world but like Yeah, the duck duck go of AI. I'm sure someone's looking forward to winning that elusive title. Um, look I so so I I think the thing is funny on consumer I totally agree which is chat GPT. I mean everyone knows just chat GPT as the term. (42:34) I I think there's an interesting effect which is obviously you know companies want choice and and and I think this is going to happen in a few spaces as well which is you know it doesn't necessar it is always a power law distribution where number one is like 75% and number two is 20% and number three is like 4% and everyone else combined is 1% or or things like that but but like I I think in terms of folks in terms of like market share let's say but but in terms of people getting there on capabilities and being able to offer something which is at least competitive enough that you know (43:02) 4% or 20% of people would consider it. I I think there is reason um to believe that there will be at least a few folks that that that get there. Yeah. For the acquisition, what was the percentage between stock versus cash? It was a mixture of both. Uh I I probably can't comment on the exact split. I'm so enjoying this constant game of like push. No, I know. (43:31) Well, I'm very happy to you could ask all your I I'll push back what I what I need to push back. Can I be honest? I think you missed a trick with your acquisition video. I'm just going to I just totally I didn't I didn't know you from [ __ ] Okay, obviously. And I watched it and I was like, no offense, it's a bit personalityless. And meeting you, you're like a [ __ ] riot. (43:49) Like I' I'd love to hang out with you and you're like amazing personality, charisma, you're awesome. I I think I I I think that I think that an acquisition video could have been more like personable. That's fair. I I uh I I I I agree. The thing So, so dude, we were in between like the lawyers all pulled an allnighter as well going and getting this because it was like, yeah, I mean, we need to get this ready to go by, you know, and there's just all the various little things of this term, this term. But yeah, it was it was in between that (44:24) and in between sorting out all the questions with the team and then, you know, we basically had like 20 30 minutes to go just film something real quick. Chat GBT, write a script for an I was Yeah, I was going to say I I was pretty happy with the output relative to the amount of effort that was put in, but I fully agree that there was there's more to it. I'm 100% with you. (44:49) Uh my favorite my favorite bit was funnily enough we did have one competitor who we thought really highly of. Um 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? I 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 (45:27) fun one you know I'll just give an example we um a a lot of our research work we obviously you know 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 32B yeah yeah and so basically kernel bench is you know um a benchmark that involves your ability to write CUDA kernels um I'm going to be I'm going to be honest whoever names your your products really needs to be fired Devon and Kevin like (45:57) no no offense dude like that's not very creative we we'll work on that we'll work on that but but um Yeah. So, so, so we rolled out Kevin 32B and um and and the whole idea is basically with RL on agent trajectories on very specifically CUDA kernel, you know, agent trajectories, you can make it way better than than the soda based models on this stuff. (46:23) Um, and this is kind of the this is a story that we're seeing in a lot of these um which is rather rather than just this mass volume of data. If you have a very particular use case and very particular behavior that you're looking for, honestly, it turns out that like a small amount of data in exactly that vertical and you you you know set up the environments correctly and you set up the feedback loop correctly is is is more what you need. (46:41) So it's a lot of compute, not a lot of data, I think is is what we're seeing and and it's like quality of data over quantity. Would you advise a new young student to study CS today? Yes, absolutely. People ask me this all the time, by the way. And and the reason I say 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 you CS and software engineering, but in you know, it's like you you you go to school and you learn (47:11) 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 h 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 I maybe one (47:40) way to say it is at the end of the day like the degree in CS is more a degree in how to think and I think that will always be valuable. Scott, I want to finish on on one which is I think really important. Uh I' I've so enjoyed this and I I watched this uh actually Tik Tok 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. (48:09) I'm intrigued. What trait are you most proud of? What's your favorite trait of yourself and why? 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 surged emotional calmness. I guess I get very, you know, for for I I get very, you know, I get very salty. (48:40) I'm a very competitive person. I get very frustrated and things like that. But but I 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 it's probably a bit more than average, you know, than than an average week, but like not by that much. (48:59) And I I think the um yeah, I think I think for for better for I'm proud that I'm just able to to stay composed in in in the situation. Dude, I love you. You're great. Like uh seriously I I think you are like the most underdisussed personality in this business. Like you need to do more like the Scott brand needs needs to be a bigger personal brand. (49:23) What what what do you what do you suggest? I'm looking to you as the you know interim chief marketing officer at uh at Cognition. The thing I think that's nice with your product is actually that you fall into the Nike bucket. (49:42) And what do I mean by the Nike bucket? The Nike bucket is their success was they make you feel like a superhero. They tell you that everyone is an athlete that even if you don't have the skills, you are able to do things you never could before. And I think that you and Devon fall into that similar bucket of kind of human enhancement. Um and so I think you should tell the stories of that much better. (50:02) And then I think you should also bluntly very clearly tell the story of your own growth much more deliberately. People want to be part of a rocket ship and gossip is very vicious and it happens when you don't shape the narrative yourself. (50:22) If you shape the narrative, gossip doesn't really happen because I can't say you're at 20 million in revenue when you're not. You're much higher. Yeah. And so don't let other people shape your narrative for you. Yeah. No, fair enough. I I think the I think it's there's there's been a real shift which is I think like a few months ago it's like we were like you know it's it's almost better if people don't hear that agents are working you know and we'd rather it that way. (50:44) I think in the last few months everyone in their mother is now trying to do agents anyway and so we might as well we might as well be more public. But I also think just for talent I think for funding I think people also just want the brand. Yeah. Yeah. Yeah. No it makes sense.