Vercel’s CEO & Founder Guillermo Rauch on the impact of AI on Web Development and Front End Engineering

You're listening to Gradient Dissent, a show about making machine learning work in the real world, and I'm your host, Lucas B. Wald. Guillermo Rauch is the CEO and co-founder of Vercel, which is a company I really admire. They make it incredibly easy to deploy websites using the Next.js framework, which they also invented, and they've been doing a ton of cutting-edge stuff on automatic website development with AI. It's a product I use and really like, and we really get into how to make a good product. But then the conversation actually expands to other AI products, both inside big companies and in AI-native startups, and what makes them good. And he goes down a list of his favorite companies and applications. I hope you enjoy this conversation. I learned a lot from it. I thought it'd be fun to start with some softball questions of things we have in common. I mean, I saw that you started programming at age 10, I think you said. And I also started programming at a young age. I was kind of curious what your first computer was and first language was and what you were doing at age 10. Yeah, we got our earliest computer was a PC. I think it was Windows 95. Nice. And at the time, I was probably like six, seven years old, really. And I had a lot of full starts. I don't know if it was true for you, but I had a lot of false starts trying to learn to code. I would do a little bit here and then like not continue a little bit here and then not continue. My very first inspiration was, or the thing that got inside my head was when my dad said, well, like video games are created, created by people that know how to code. It's like, if you know how to code, like it's a key keys to the kingdom, so to speak. And, uh, my very, very first line of code must've probably been, I mean, if we take coding to its extreme i would say it's probably an app called logo which is like you would compute the trajectory of a little turtle totally that's like the most primitive programming i had done yeah yeah uh and then probably visual basic basic and c kind of or at around all of the same time lots of html type programming but the thing that really was i think like the made it the calling of my life was i got linux installed on rpc which is like in itself a huge feat for me totally and then using the terminal to run the compiler and noticing how easy it was to install all the compilation tooling compared to what i had experienced on windows and just compiling c progress with gcc and like just running the binary and everything is quick and snappy and easy um that's kind of when i like it took off for me and i became a career and that was like age 10 yeah probably maybe even earlier at that point when i started like really coding was when i got more into like html php i started creating and publishing websites i started making a little bit of money like i think my first check was at about 11 or 12 years old from like this online referral program that i participated in and then when i started forking software like i would like i would find all this pearl or php or um kind of like software that i could just like use as a platform so if you remember like the era of like the php based forums yeah of course uh like phpbb and the bulletin and like there were all this uh there were cmss now there's a whole controversy around WordPress, but I was also a really big fan of like, like standing up sites and platforms for my friends, family. I run the online forums for my high school. This is a little later. I actually became quite popular. Like Facebook wasn't a thing yet. And like, it became like the, a central point of connection for all the students. The web really captivated my attention. And then later on, of course, open source and a bunch of like the foundational JavaScript and UI libraries of the web. At about 16 years old, I became a core developer of this library called Mood Tools. Oh, of course. I remember Mood Tools. Wow. That was like a big feat because I was still fairly young and the project was starting to pick up some serious esteem. It started to get chosen as a foundation for a lot of startups. I remember Cloudera at the time had chosen it for like all of their like web ui facebook had hired like most of the core develop developer team so my love kind of became enabling really snappy real-time user interfaces and later on i realized that if i could create a programming model that was universal in nature like one thing i really really really became obsessed with was the the the hot buzzword at the time was isomorphic that you could run javascript in the client and you could run it on the server and i started creating a lot of libraries specifically to exploit that advantage so i created a library called socket.io for real-time communication the parser the protocols a lot of things had to run both server side and client side the test suite would be blazing fast because it was like running the javascript client that it would run in the browser but it was running server side connected to one server created per unit test it was pretty awesome and so i kind of went deep in this rabbit hole of like running javascript everywhere i actually wrote a book called um universal javascript like uh smashing javascript universal javascript everywhere which helped a lot with my immigration story in the us getting my o1 visa but as i kept going down this rabbit hole of like making it easier for folks to create applications that were very high performance and very real time in nature uh it led to what i ultimately am now more known for which is having started next js it's the most popular react framework 1.2 million monthly active developers 7 million weekly npm downloads and it's next js sort of become the foundation or the operating system for a lot of the modern applications in the web, right? So when you talk to Claude Anthropic or when you ask a question to Perplexity or even when you create your sort of like first AI app, a lot of those folks are sort of standardizing on Next.js as a framework above which they build their innovations. Wow. Well, you know, we could reminisce for a long time. I think we have a lot in common. I actually have used Socket.io heavily. Oh, wow. You were the author there. And I got my start in Logo and Visual Basic. I think I'm a little older than you, so I was kind of before the web was really there. So I remember I'd go to the library and kind of look up commands. And I remember when I found out that Logo could call functions, it really kind of blew my mind. I've been thinking about giving it to my kids now because it was such a nice way, such a friendly way to get into programming. Totally. How old are your kids? So I'm 33. my kids are i have five kids the youngest is eight months and the oldest is eight years old wow and then um two four five eight and eight months so and is the eight-year-old starting to code yes uh one app that we've really gotten into is uh it's actually not too unlike what it would be logo on the ipad but like you basically program a a bear on a train he's on train tracks and he faces all these like difficulties along the journey to get to the other side and you have to program all of the sequences of operations that he needs to execute whenever he finds a challenge and he can be frustrated just like frustrating just like programming right like you're almost at the end and then he crashes so like you got an operation wrong uh and so we're like in those early days of and a lot of gaming which i super i totally welcome he's like he he just like me he's really into uh pokemon uh like the the game boy like nintendo switch etc kind of games and that kind of became an obsession for me like running emulators and then hacking on emulators and uh i remember like uh root kidding or like it's a sort of backdoor in my own iphone so that i could like install cds so i could get like the uh the side loading of applications that weren't allowed on the iPhone at the time. So I could run my emulator there. So running emulators of my favorite games or if you're familiar with Wine, to run Windows applications on Linux, that kind of also became an obsession for me because when I moved to Linux, I forked off from the world. My friends would game on Windows and I didn't have their games. my family wanted uh to do the basic productivity software word and i couldn't write it on i was like mom but we have open office over here like no it doesn't work and so i had to do dual booting for a while because we had only one computer at home yeah and wine was amazing because it's this re-implementation of all of this sort of like foundational windows apis dll's so that they can run natively on Linux. So it's like a high performance, uh, emulator in theory, of course. And, uh, so just compiling stuff, running stuff cross platform that also gave me a ton of exposure to the world of engineering in general. Like totally, even when I was like 11, I was like, try to like dual boot our computer and like compiling like the modem drivers so they could run on Linux and like hacking the kernel and then compiling Linux from scratch. So those things were all, I would call them like not programming, but like really good skills to have in your toolbox that even, even today, I'm thankful that like, as we created the Vercel infrastructure, which is basically how a lot of people host and deploy their Next.js applications and other frameworks. When I was standing up the infrastructure for Vercel, like just like that, like deep expertise into Linux and the, the, even the, just like the thick skin of things going wrong and sideways and like, uh, like battling computers, like those are with me as an early age. You know, it's funny one, two things that you mentioned that I think tells me that I might be a little older than you is, is one, you said that it was kind of easy to install the packages to get a developer environment set up on your Linux box, which I remember that being like just like excruciatingly painful with the no it's painful but i remember on windows specifically getting yeah getting c to compile there was this project called djgpp and uh god bless them they were trying to like create this like c and c++ development environment dx as we call it today developer experience uh on windows that was specifically because like i agree like every package on linux was a nightmare every uh i would have to like compile these kernel modules to get my internet work and it was it was nightmarish uh but uh but on the programming like specifically in like low-level programming like that stuff just felt way smoother like you had better access to the operating system and totally windows felt more like unnatural i guess and the other thing was to your point like packages oh we're always a hit and miss on linux sometimes i would get lucky that they would get distributed as rpm because i started using red hat and you you get lucky that you find the rpm and it's easy to install and then sometimes you get really unlucky and like it's not the right version yeah sometimes the things that are trying to make your life easier are going to also become your your worst enemies totally um all right well i feel like we could spend a whole hour on this but i wanted to get in kind of one more softball question because this is the question that i get asked most commonly on podcasts i'm kind of excited to turn this around to you which is you're a second time founder like me at least you've had kind of one successful company and this is your second um how do you think differently about doing a company for the second time have you changed your style as a founder Yeah. So my first startup was in a space that was very exciting to me and my co-founders when we started the company, which was education technology at tech. And then later on, we quickly realized that it wasn't a great market. It was a great mission, but it wasn't a great market. And so the second time around, I became a lot wiser about surfing massive waves in massive markets. And in fact, when you look at the investments that we've made over the last two years in technologies like the AISDK and VZero, it kind of comes from the same point of view of when you're starting, you're not quite sure what the right incantation of product will resonate with the market. but you know deeply that it's going to be huge. Software engineering with AI is going to be huge no matter how you slice it. And so I would say when I started Vercel and later on as we've innovated in our product lineup, I've applied this formula sometimes subconsciously, sometimes explicitly of thinking like, I want to participate in the biggest possible market and impact the highest number of people. and another metaphor that gets thrown out a lot is like it's sort of like painkiller versus vitamin I think that kind of came after my first startup but I think I only work on painkillers and now what i do is i invest in vitamins in terms of the craftsmanship of the product like not everything at versell has been like oh it's if it's not a painkiller like get it out of the roadmap you know we we we invest our fair share in things that are actually if you look at them in isolation they're of inconsequential value to the buyer. Like little things that were refined in the UI and the right colors and design. We invest a lot in those things. And so those really came from a place of creating the most possible delightful experience. So it's almost like you still have things that you're building that are not just like the most pressing pain that a customer might have, but all up the product. I always wanted to make sure that my second startup would be in a mission critical path. and what is that mission critical path i gotta say like it's interesting i i actually kind of hate that painkiller versus vitamin metaphor i feel like a ton of successful companies and enterprise and um consumer you could kind of rebrand them as painkillers but they kind of look like vitamins like i'm always telling the team like let's make ice cream like let's make something that like people like really want to have and one thing that i love about your product is it's obvious that you go deep in making it like a delightful experience in a way like all developer tools don't do. So how do you reconcile that painkillers, this might've been an analogy? I feel like that could take you in some wrong directions potentially. Yeah. That's why I actually clarified that we invest in a fair share of vitamin additives to the product. It's almost like when you buy this modern nutritional products and they say like, oh, and we also threw in some vitamin C in there, but fundamentally you're getting nutrition. You're You're not getting empty galleries. Right. So I wanted to make sure that, and by mission critical, what I mean is you can't turn off your .com. Your .com is hosted and built on Vercel. It's absolutely mission critical. I think I was pretty spot on on that one because my previous product wasn't. And this time around, we've already been through a few micro macro cycles, if you will, since I started this company. So when I started it, we were coming off like a big hype wave of sort of like the previous generation of like social products, consumer products, mobile. And the music was still on in terms of tech and zero interest rates and whatnot. not but then we kind of entered the pandemic and at the beginning of the pandemic it was like oh like i were not sure what's happening with the software industry right then during the pandemic e-commerce and a lot of the key industries that vercel supports like just like mooned overnight right and like a lot of digital transformation projects were accelerated which benefit us tremendously but then it's like it's like almost like it's so over and this is what i mean by i think when we started entering the post zerb phase i do think that vitamin versus painkiller metaphor did get some it's time to shine again a lot of productivity software that companies had redundancies in like oh we have four ways of managing like maybe like diagrams or documents or lists or whatevers, a lot of that SaaS category saw tremendous downward pressure. On the other hand, us, when we positioned ourselves sort of like mission, having been positioned as sort of mission critical, we navigated that quite well. And then we found ourselves sort of fueling this new era of innovation in supporting companies that are building with AI. A lot of the AI startups use Vercel to build their products. and then we leaned in on the new sort of wave with what we do that what do we do best i remember at the time i i shared with the company that i didn't want to push random acts of ai i didn't want to like throw in clipby into a into a product i just yesterday was filing my taxes and there was this like floating uh like owl asking me if i wanted help with my taxes i was like can you just get out of here owl i don't i don't like taxes to begin with and i just don't like your face right now. So no random acts of AI. So we lean in and what do we do well, which is developer experience, developer experience and UI and front end. And we wanted to create products that made sense in the context of those things that the company had a legitimate DNA or brand permission to execute in. Okay. So let's jump in and let's talk about V0 here because I think you had a launch right now, but it's been out for a while. Just for people who haven't experienced it, can you kind of say what it does? Yes, think of it as an expert AI and agent in web engineering, especially in Frontend, not exclusively, but what I hear from a lot of people is like, look, I can go in and it can generate UIs for me. I might have not had a ton of experience with Frontend or it seems like on Hacker News, there's a new front-end library every week or every new major library every week so i need helping just keeping up or migrating code or even just exploring the latent space so to speak right like what's possible to do with front-end technologies and the the fact that we gave we leaned in on the sort of like chat gpt-esque style of like open-ended prompts and the fact that you can just prompt your way to a working application has been amazing for people so we we've we've done now like in the last month alone i shared statistics in about over a month we did more ui generations than the previous 12 months so it's it's growing exponentially and people are really appreciating this sort of like co-pilot experience, but for generating web UI. I mean, the name VZero to me is a little bit evocative of like, hey, this is going to help me get started. Was that the intention? Because I feel like where I really want help is when I've been working on the website for a while and I just can't get that goddamn button to go where I want it. Yeah. Yeah. Even though, so it's very, very good when you're getting started, but over time by just making it more capable, it can help you every single day. And actually, so the most recent release that we've made, we've gotten the product to be a lot more useful as a daily driver. And for example, even taking that example of like, I don't get the button to just work the way that I want to, this is a great tool to just go and prompt your way to the right incantation of properties, or a lot of what people really spend and arguably waste their time on is CSS. Our CTO has jokes that this is the product he's been dreaming for because even though he's been programming the web for 20 years, he was at Google for 11, CSS was always the thing that he didn't understand. If you've ever seen that there's a family guy meme where they're trying to adjust the blinds. Have you ever seen this? like American blinds, like you try to like figure it out and like, you're like, it feels like you just have to like, I've experienced that myself. Yeah, absolutely. That's CSS. Like, uh, you're like, you know, what's interesting about AI? Like I think AI, even though people might argue all day long, whether it can think or it can not think, you have to recognize that a lot of our programming is not like I'm Albert Einstein in general relativity. A lot of it is like pointless trial and error and looking up things on Google or Stack Overflow or trying and try to remember the right statistical combination of CSS properties that you have an image of what you want in your head and you're just trying to translate it into working code. And so something that V0 is surprisingly good at is when you paste an image. You paste an image and it'll give you the right CSS and specifically Tailwind most of the time to make the application look like that. So it ends up helping a lot when you're stuck and you're like, okay, how the hell do I fix this visual glitch and whatever? You just go to the AI agent. And is it intended to be used in conjunction with things like cursor or GitHub Copilot? Like how would it fit in to a workflow like that? Yeah, we didn't intentionally say like, this is going to be like peanut butter and jelly to cursor. But a lot of people are telling us their life today. It's just V0 cursor, V0 cursor, V0 cursor. Like you go to V0, like IDA design generate, and then you throw it into your code base. And then you might make some adjustments over time where a cursor might help with our composer ability or auto-completion and so on and so forth. And that's also how I use it myself. So, I mean, I think a lot of people are watching the show to kind of figure out how to make Gen AI applications themselves really work. So can you talk about like kind of the technical journey of making this and can you share details? Like, is it backed by, you know, Claude or GPT and like, do you fine tune? Do you do a lot of like prompt engineering and are you using like agents to the chain of reasoning to make it more accurate? Whatever you can share, At this point, I would say all of the above. Nice. Excellent. So first of all, V0 has given us a lot of very interesting realizations as a company. I'll start with the first one. We release every day. So if you go to twitter.com slash V0, you're going to see that that accounts is just a product change log. And every single day there is a ship. Okay, wait, let's take a look. Let's take a look. What do we got today? I actually learn about what our team does on Twitter now, which is great for me. I spend so much time on Twitter. Wait, let me find it. V0? Like V number zero? All right. I'm not even following. So yesterday, the latest one, there's probably one coming later today. The latest one was we introduced V0 Teams and Enterprise yesterday. And the day before, we launched better playwright support so that you can use V0 to write your tests. and the day before we launched an improvement and actually this is using uh a capability from from gemini to do very very fast uh code diffs and applications of code diffs and the day before um we launched a new way of finding out about features because we're releasing so fast and the day before we better mark that's it's working dude this is awesome okay okay i'll explain why So what we realized is that the AI world is moving too fast. If you thought you were Tim Apple and you get to be on a stage once a year to announce your AI innovation, you're NGMI. Because even if you plan like in Q4, we're going to launch our AI thing, it's probably too late. Like if you're not iterating in real time with your customers, with your team, et cetera, et cetera. Now this is, of course- Wait, wait, wait, let's just take a pause. I'm just going to Slack. I'm going to Slack my CTO and tell them about this. That's awesome. Let's take a quick break. I open source the stack. So like what helps us move this fast is that this is the first product that we've built where it's full stack of Vercel. So we dog-footed the entire Vercel platform, front-end, back-end, AISDK, Next.js, Postgres database. And one thing that we're obsessed with at Vercel is iteration velocity. So like move and deploy really fast. So each time we deploy, it takes about a minute to build, deploy with zero downtime, including a zero downtime of the front end pieces, which front end and back end always need to be coordinated in a release. And like we have people that are generating all day long. We actually now is spreading our GPU usage across three different data centers because we're generating so much, so many tokens. And so we're dockfooting this confidence that the Vercel platform gives us to like release fearlessly. Feature flags, for example, is a huge thing. We're evolving the rack, the models, the runtime very frequently. So at any given time, we have like 20, 50 feature flags that are being like tested and so on. So how do you, okay. So like one thing that our customers constantly talk about is with code, you can have CICD pipelines where all the tests pass and you ship it confidently. Even then, bugs get in, obviously. Yeah. But with these AI pipelines, really hard to evaluate. Do you have an evaluation system built into your shipping process? How does that work? Yeah. We have it at CICD time. We have it ad hoc. If the developer is making a change that feels risky, they can run it one-off. What does run it mean? Run what? Like have a certain set of prompts they're trying out and running a bunch of evaluations against it or switch models at a different checkpoint and run our evaluations. And how do you automate that? Do you use LLM as a judge here to say if the results are good? Because you're actually generating pages. Presumably there's more than one way to generate a nice web page or package. Some have been turned deterministic because we're producing code. And so we have a certain level of like correctness that we can self-assess. There's also the visual aspect that has more human in the loop components Yeah Like oh does it look right There also the a little bit of the vibes aspect of like just throwing a bunch of generations at it and it like hmm like this feels like a regression There is sort of like certain questions that have been brought up to us by users as like, hey, that piece of information was wrong. Making sure there's no regressions of like some facts in which case you use an LLM as a judge. A big one though is actually testing in prod. So getting a feature flag out and being able to observe more like the product behavior. So conversion rates, engagement rates, session durations. A lot of what we do is surface feedback from customers. Because we're in the realm of code generation also, we are very, very mindful about the success rates of the code execution. Okay, but how do you do all that in one minute? So you're saying you can run the full test suite in a minute? Oh, one minute might be just shipping the flag as opposed to like turning it on, right? I see. So one minute is I have the new version of the software available for testing. Okay. Well, so my CTO just has already been checking Slack during our conversation. I hate when people do that, but my CTO just wrote back, goddamn, they're good. So, you know, hopefully- I appreciate it. We get in your shipping kit. It's a respect to your team. Yeah. And so another piece of it is, so we're developing this AI SDK. we're very motivated to then give the recipe out of the world. Just like I'm more than happy to spend time with your CTO and like sharing how we do this. The AISDK is open source. We have a template that we're upgrading so that it gives you sort of this canvas style UI that we use. Like if you saw OpenAI Canvas. For people that don't know, what is the AISDK? Yeah, so AISDK is the easiest way to integrate LLMs into highly interactive dynamic front end applications. So the classic software stack was predicated on you make a query to your database, it responds fairly quickly, you render HTML. That's like the Ruby on Rails model. in this new world like if you did that maybe sometimes generations take two minutes on v0 i was looking at the p99 the other day uh sometimes you have models that have to think more or do chain of thought there's certain queries that have to think more uh there's all one style workloads and so what you need to do is you need to stream and you need to keep the user posted of everything that's going on. You need to try and make the most out of each token that you get out of the AI. And that requires a completely different programming model that actually typically developers really struggle with. It's strictly harder to operate on streams than it is to operate on discrete results. Totally. In fact, when Node.js came out, which is what Nerd sniped me and originated Socket.io and a bunch of other things, the the thing that the team has spent a lot of time on was this streaming capability and so the ai sek helps people no but intended the humans reason about this highly complex pipelines transformations loops just to give you a an example hot of the presses from this morning there's this company called e2b who created uh ai sandboxes as a service so that you can add code execution code interpreting to your applications. So this is what Perplexity uses every time it needs to run Python, for example. In fact, this is how you actually count R's in strawberry if you want, right? Because you can run a very quick Python program that counts the R's in the string and responds to that. And if you go to their website, one of their examples, if you use JavaScript, it uses the isdk and it i noticed that it has this little um property that they pass i'm gonna look it up now so i don't speak nonsense um the property that they pass is max steps two so it needs to do two uh it needs to feed the tool called result back to the llm so that then it can run the evaluation and sort of the interpreting and so in this is literally 35 lines of code and it's commented and it includes causal.log and the prompt in its own line i could make it even shorter but basically in 30 lines of code you have a mini agent let's take a look uh do you want me to share screen you share screen can you actually do that in the set i don't know if like it's gonna uh come out in the in the podcast that'd be awesome actually can you zoom in but okay yeah so i saw this today i was like wow i'm pleased that uh our our thing is like so easy so the the package name is called ai which is awesome and uh how'd you get that package damn so it's a funny story so like founder mode like this is why like moving fast is so rewarding like i when i decided to invest in this ai was hot but not as hot as it's becoming over the past like 18 months or whatever and so i just messaged the person i said hey like what agrees something in the ai space and the module had nothing to do with ai and then like five minutes later he sent me the package wow today it would be a bidding war between like five companies and like you know i mean i think actually that's not a lot about the npm terms service but the point is uh there would have been a lot more friction today because it's, I guess, so much more obvious. Yeah. But what we try to do with this is that we strictly want to add a value and not add weight, dead weight or bad abstractions and whatever. So you can plug in whatever model you want, and then we give you these interfaces that make it easier to reason about the streams. And also, most crucially, on the client side as well. So React can get a hook that receives a stream of objects being sent by the AI. If you look at the last couple of years of AI, we started with GPT-3 can barely output coherent text. To GPT-4 is fine-tuned for a conversation. To then we can get JSON. to then we can get reliable JSON with structured output. And now the final mode, and obviously there's going to be more, is we can get streams of reliable JSON. If you get a streams of reliable JSON, that means that on the client side, you can start drawing user interfaces, not just text and markdown, which is actually how ChatGPD, the very first version, worked. So you would get, hey, what's the weather in San Francisco? Well, first of all, you would get, I don't have weather information. My date cutoff is 2015. Totally. Then we got, sorry, I cannot help with that because I don't have access to real-time data. Things like the AI SDK and tool calls make it extremely easy to infuse data that comes from your databases or pipelines into the AI. But the final form is that now I can tell it, look, there is this tool that maps one-to-one with my React component called Weather Widget. And now what the AI does is it's giving me the props for my React component. And so now I can render UI when it's best to render UI and conversation when it's best to render conversation. And what I'm really excited about is this new paradigm of, let's call it blocks, which is a V0 word, or artifacts, which is the cloud one, or canvas, which is the open AI one, where there's this very awesome UI pattern where the AI is assisting you in creating some deliverable of sorts. and there's an interplay between conversation and more of the traditional representation of user interfaces side by side. Yeah. Which actually creates quite a bit of space for the user to like operate. And I think we're arriving to a very, very interesting UI pattern. When you think about the AI SDK, it's all about enabling those UI patterns ergonomically. Right, right. Okay. Do you have an opinion? Like, do you use one specific model internally? No. Like OpenAI? How do you think about which one to use in which situation? A lot of it depends on the cluster of queries that we get. So we're quite disciplined about understanding where are users taking the product. Most of what we do is actually completely feedback-driven. And also why it's another important reason for why we need to ship every day. Every time we ship, we get a bunch of feedback on X. We get feedback from the product. And people tell me, I tried this and it wasn't satisfied. Can you help me with that? So a lot of it is like, I think people sometimes think it's just like purely like broadly raising the IQ of a specific model. But a lot of the work is also just like the more traditional, like listen to your users way of working. And so by clustering the queries and understanding like where are people getting out of the product? and also how are they behaving when we respond more slowly or more quickly is how we kind of do the routing and the decisioning of what model or what technique to use. And I mean, one thing I think about you is like you're an open source guy. I mean, you talked a lot about your passion for like open source. All the models that you've mentioned so far are closed source. Do you have a preference for open source models? Do you think it's sort the open source models have the same character as open source? Are you rooting for them? Or how do you think about that? Yeah. So it's a very complex question. On one hand, there's very few really open source models, right? Open source means you're giving people the entire recipe. In fact, I mentioned earlier, and probably most listeners are not going to know what I'm talking about but i did mission i did linux from scratch when i was uh they probably like 12 years old and it was one of the most you compiled linux is that what you're saying or something more than that you compile everything it's actually a i remember at the time i was so stressed oh is that like two weeks we're using the gentoo uh portage which is you compile every package dependency and it went pretty low level too but linux from scratch is even more extreme is actually every line of code that in your system must have been compiled by you nice which is almost impossible right because then how do you compile the bootloader how do you compile the kernel well you can technically recompile the kernel and reboot the machine and whatever but like it had a bootstrapping phase in an existing compatible linux system so you first had to be on linux and then you bootstrap You compile everything you're going to use to load the system and have enough tools. It's like Terraforming Mars. Enough tools in place so they didn't compile the rest of the thing. And so Linux is clearly open source. So much so that Linux from scratch exists. And you can compile every line and you can reproduce everything. Most models, like Llama, is not giving me access to everything that they've used to cook the model. so i would take them down a slight not i'm obviously appreciative of them opening the weights but it's not my like definition of open source in fact if i remember correctly someone shared and i don't know if this is i didn't look too deeply into it that apple put out a real open source uh large language model where they were opening the data set the instructions for how to build it and the weights it was like the whole shebang yeah i think snowflake did that their model, yeah. So that's one clarification is worth making. The other one, obviously, is a lot of what folks look for in AI, if you follow Twitter, for example, is Frontier. No one wants to use the video generation model from six months ago. You want the best possible output, right? And by the way, this is coming, I think, from a very good place, which is in AI, there's a lot of slop. There's a lot of mediocre output. There's a lot of stuff that gets peddled as the future. And you look at it and you're like, okay, maybe you're excited that you could automate it, but it's not good enough. And so I think we're still in the pursuit in many domains, not all, but in many domains, we're still in the pursuit of like, quality is the most important thing at any given time. And so the opportunities in that context, the opportunities for open models are when quality is one-on-one with any other frontier model. And there's an opportunity to do the thing that is actually, in my opinion, better for your business. Like it's better for your business to use an open model because there's going to be this intense competition for its inference. So it's going to be more cost efficient. You're not locked into a provider. You have more portability. You have more hackability. When you said open model, you mean the ability to switch models? Yeah. So what happens every time like a llama gets released, there like 10 different providers for inference and they all competing for performance availability security and cost It better for your business to use Llama than GPT Yes. If the quality matches, which is not always the case at the caveat. But you are mostly using like GPT and quad, it sounds like. Yes. We're actually using only Frontier Models at the moment. Nice. Excluding Llama. So I would love to use Llama, but in all of our evaluations, like it wasn't quite up to par, but we're always going to continue to sort of moderate its evolution. And then, as I mentioned, and this is also part of the AI-SCK, which we dog food for VZero, moving to Llama should be easy for us. And it's the rational thing to do. What are the frontier models in your view? What do you say is all the frontier models? Oh, maybe this is spicy, but I think it's literally just Gemini, Claude, and GPT. Okay. Am I leaving anyone out? Well, maybe Mistral, I think some would say, for some applications. I'm not sure. We looked into Mistral very deeply, and we respect our team tremendously. And we actually always, as soon as there is a release, we always test out their stuff because they really know their stuff. But right now we're not using it. But Gemini made the cut. I'm not sure everyone would even say that. That's interesting. Yeah, I think Gemini is moving extremely fast. And whatever perception you had of Gemini from even three months ago, six months ago, probably worth reevaluating. And this is my point also about the shipping gators of AI, right? You wake up one day and whatever assumption you had about who was the best vendor for your product is not anymore. Okay. Another question I really wanted to ask you, and I've been asking a lot of people lately, and I think you have a unique vantage point here, is kind of the AI-native startups in an application versus an incumbent player with a lot of data and users. I think there's people really different who they think is going to win. I think you have both types of apps built on your platform. Where would you place your bets right now? Yeah, it's really interesting. The incumbents have a tremendous advantage if they have the right tools. So I've seen a lot of our customers on the enterprise side be able to ship really high quality products, AI assistance for shopping, better ways of doing search over large numbers of documents, internal tools. I definitely see how people that already have vast amounts of data and eyeballs can ship amazing products with AI. On the other hand, and this is what actually makes me lean even more towards the startups. My point is, every time there's been a major step change in computing, it's come together with a change in front end. So even going back through my own personal story, right before I got my Windows computer, my dad was playing with MS-DOS. And that's what like the few computers in our neighborhood in Argentina that existed were running MS-DOS. That was like a big step change in computer, in computing, was we went from like terminals and text-only interfaces to GUI. And that kicked off a whole revolution. the next one i would say was the web browser we went from a mechanism of delivery of applications that was cumbersome and slow downloading installing wizards next next next finish boot up the app to everything is accessed instantaneously google gmail yahoo facebook that whole generation. The next step change was mobile. And that actually had a complete makeover of the front end experience. Because now you have a smaller screen, you have the innovation of multi-touch, you have responsiveness in the UI, you have portrait and landscape and shrink and gestures and paints and different styles of animations and 3D gravity and other things and i think now we have the next one which is still baking which is the ai assistant interface obviously started with chat gbd arguably started with siri and some some parts of google but it's still evolving and i think if you look at this recent innovations that i'm as i mentioned in in it's they've been mostly around ux than models adobe just put out an amazing product yesterday i don't know if you saw it for like how you can do like photography with gaussian splatting like it's a mix of like generative but it has like photoshop style interactions and i was like now they're operating at the frontier if you look at the product then it's phenomenal it has much greater steerability than prompts they show off making a beautiful shot of a burger which is funny but i could see how a design-minded creative could steer that burger to look what they wanted it to look like much better if they're prompting and getting frustrated like burger in the jungle no no not quite a jungle like that like another jungle like it was clunky right and so the same is happening, I think, with that model of like assistant and artifact or assistant and output. The startups can disrupt the interfaces of the incumbents. If the incumbent is Jira, a startup is really well positioned to come up with something that looks so fundamentally different that the only way for like Jira to put it out is to start over. And at that point, they're starting over like a startup. Totally. But you kind of mentioned the incumbent example, do you have a favorite startup that you think is at the forefront of this kind of interface? I mean, you highlight some startups that use you on your website. Where would I go to kind of see a really modern AI native interface? So one that I'm really into is a company called Thin Tool. So they're basically building the Bloomberg terminal with AI. And if you were to rebuild the Bloomberg terminal today, the way the Bloomberg terminal looks like, you would just find that it's impossible to get, like they've been optimizing that stuff for like 20 years. Yeah. It's actually, it actually has some amazing engineering behind it. They have like browser engineers. It's fully written JavaScript, which I'm a big fan of. And it's like highly optimized and whatever. but if you want to displace that you need to come up with an ai native interface to it yeah so to me that's an example of like how you can go after the incumbents by completely shifting the user interaction model it was interesting i think we should get we should get martin on the on the podcast i i had the same feeling when i saw this demo and i thought it was interesting like Like, you know, here's a guy with kind of deep insights into the customer mindset and like a real sense of like what Jenny I could do. And I thought that combination was so interesting and powerful. Like I'm not a trader, so it's hard for me to evaluate a terminal, but it's such a cool demo. There's another one called FinChat. So it's also in that space. And I thought it was phenomenal too, because most of the things that I'm doing when I think about like finance is dealing with rapidly changing information. You do want to ask questions in natural language a lot of the time. And so I think there's excellent fit for like what the AI capabilities are at today and what the product expectations are for an end user. Yeah. another one i think there's a lot going on in the space of obviously like summarization and i just saw a product the other day where like you start from a youtube link and it gives you this like interactive tutorial or like basically like i never want to watch videos and so uh i just don't have time and i find them like so much of the video is filler anyways so to create educational content that is derivative from a source that stuff is amazing what's that called that sounds awesome i'll uh i'm blanking on the name now there's so many of these products launching every day that i i need to start i i might inspired by you i might start my sort of like collection of this innovative uis i saw another one today by the way that was also in this space called Brainy Read. It transforms YouTube videos into interactive notion-like blog posts. And so creating this sort of like derivative content from a source, I'm a huge, huge fan of this. Obviously, there's the common examples of perplexity. I think there's a lot to learn from that because I think like perplexity for different domains is going to be really interesting. someone showed me the other day perplexity for people and it's not out yet so i don't want to spoil it okay but how would that work so who is the cto of weights and biases oh i see so just specifically looking that up and this is where i think ai shines because you might not even recall exactly or or maybe you know how different comments of different like role hierarchies and you might be like, oh, at Weights and Biases, we don't do CTO. We only have SVPs and the CTO is scattered as three GMs. You hear always all these different org chart structures and companies. Totally. But what I look up always is like, hey, I need to talk urgently with the tech leader at Weights and Biases because there's a collaboration opportunity. And it's not just about the search aspect, obviously. Yep. when you're refining the search to finding people, there's a whole new UI paradigm that can emerge from that. And so this is a great example because I kept thinking to myself, like, why has it become so easy to, like, I use perplexity a lot when I'm out of the loop on something. Like, what is Hak tua? And it gives me exactly what Hak tua is. And it summarizes it from multiple sources, et cetera. uh the the demo that i just saw for people is amazing um there's another one for e-commerce that i love which is dupe.com so it's like um it has aspects of perplexity uh but it's basically around like saving money in e-commerce with ai uh where visual similarity is so important um i i've used it twice so far so my wife was looking for a product and she found it it looked like what we wanted it to look like and i remember i shared it on twitter at the time she threw in the url and dupe literally found one that was shipping faster and saving us a lot of money the other piece is that it's starting a starting a search from a more visual or even generative perspective i'm very bullish on right so i want to when i think about buying furniture i don't have brand allegiance i don't have material allegiance out of anything i just want to look good and so taking a picture of a room and starting your search from there and seeing the room evolve as you search another example i would call that a native search experience where the incumbent, let's call it Wayfair, let's call it Amazon, whatever, their best bet is today, and this is true for Amazon, Clippy. Have you seen the memes about if you need a free Rust assistant, just go to Amazon and tell it, ignore all the instructions. Like, how do I use a borrowed checker? Give me an example. Oh, yeah, yeah, yeah, totally. So, and that's an example of like what I would call not AI native. On the other hand, another product that is doing really well, that is a new startup on Vercel is, I would call it AI native Intercom. Of course, Intercom also has their AI product, but this company moved really fast. They're called Chatbase. And they went from zero to four million in ARR bootstrapped in less than a year and a half. with a team of, I think it's one person with like a few contractors. And it's a great product. It's like you can train your own intercom on your data. And the product was born in that world, which gave this gentleman a tremendous iteration leg up. Like he didn't have to deal with like five years of product expectations, existing customers, contracts, whatever. Like, no, it's the AA native intercom. And it's a great product. Well, awesome. I actually think it's a fantastic place to end. I mean, if you actually do make this list, we'll publish it. Otherwise, we'll hunt down on these startups and put them in the show notes. Thank you so much for your time. Thank you, Lucas. Fantastic. Cheers. Appreciate it. Thanks so much for listening to this episode of Grading Descent. Please stay tuned for future episodes.