Vercel’s Guillermo Rauch on What Comes After Coding - Ep. 47

Guillermo Rauch is one of the most prolific coders of this generation. But he doesn’t think of himself as a coder anymore. Coding, he says, is a specific skill that AI is becoming great at. Instead, he thinks the future of coding is more holistic, full-stack engineers who can ideate, design, and execute all together. Guillermo is the founder and CEO of Vercel, the creator of NextJS, and SocketIO. We spent an hour talking about the future of software development in an AI world—and the meta-skills that are essential for the coders of today to master—in order to use tomorrow’s tools to their fullest extent. Here are a few takeaways: One of the most important keys to his success is taste—and developing taste is all about paying better attention to everything you experience day to day. He’s great at recognizing bleeding-edge technologies with extremely practical applications but that have bad user experiences. If you can learn to recognize those and build with them, you might build the next NextJs or SocketIO. He’s already seeing enterprises use Vercel’s AI coding copilot v0 to replace all of their programming—they just send v0 demos back and forth to iterate on new prototypes. Why prototype cultures are becoming common in AI—and the benefits of written cultures like Amazon vs. prototype cultures like Apple for different kinds of companies. For developers building frameworks, always put the product first; a framework in isolation without a “customer zero” is never going to be a good tool. The theory of “recursive founder mode”—if you want to build a scalable business, you have to scale yourself by creating an atmosphere that nurtures talent and ambition. AI tools are shifting software toward consumption-based billing models, making us capital allocators who decide how much compute the AI consumes. The future of AI is agents with the taste, knowledge, and tools to perform specialized tasks. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper Links to resources mentioned in the episode: Guillermo Rauch: @rauchg Vercel: https://vercel.com/ Last week’s episode with Nabeel Hyatt: 🎧 The Venture Capitalist Who Finds the Best AI Products—Before They Win Dan’s essay about the allocation economy: The Knowledge Economy Is Over. Welcome to the Allocation Economy

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Dan Shipper?

  I think a lot of developers are probably thinking, okay, is it even worth it to be able to code right now?

• 0:04Speaker 01

  I don't think I would identify today even as a coder, even though that's what I obsessed about for years, since I'm like 10 years old. Trend has been away from the implementation detail, which is the code, and towards the end goal, which is to deliver a great product or a great experience. One of our enterprise customers for V0 is a company that has been in the cloud space since the cloud was born, like literally like in the room where the cloud was invented. And they told me, we have it as a rule that we don't do code. They showed me their Slack conversations, it's just them sending V0s back and forth. There's no GitHub, there's no infra, there is no anything. There's just building products.

• 0:45Speaker 01

  When things are specific skills, machines tend to take them over over time. If your skill when you were a kid was like, I can do math in my head really well, awesome, great asset to have, I love it. But also, there's a specific machine that can do that skill also very well and even better than you. And so what I try to separate is what are the meta skills that are not as easily replicated by machines that you should still nurture? And I think those tend to be more around very high level conceptual thinking. What's about to become possible that I can start cooking on now?

• 1:33Dan Shipper?

  Yerma, welcome to the show.

• 1:34Speaker 01

  Thanks for having me.

• 1:35Dan Shipper?

  So for people who don't know, you are the co-founder and CEO of Vercel. You're also the creator of Next and Sakurai O, which is very close to my heart. I told you when we met that Sakurai O is the reason I could build my last company. So I appreciate all you've done for the developer ecosystem.

• 1:53Speaker 01

  Just met some folks last night that said the same. It's nice to get recognition for open source, but I'm thankful to the people that maintain those projects.

• 2:01Dan Shipper?

  Yeah, so we have a lot to talk about. I really like, in general, in this conversation, want to talk about the future of programming with AI. I want to talk about V0 and what you're doing with Vercel. But where I want to start is, I was like, before this interview, I was thinking about like, the kinds of things that it seems like you're interested in building and the, and the kind of like taste that you have. And, and, and then think about how that might apply in this sort of AI era. And where I kind of came to, and I'll admit, O1 was involved a little bit.

• 2:37Speaker 01

  Oh, I was involved in the Brubert.

• 2:39Dan Shipper?

  What I kind of came to, to is, it seems like you're very good at playing at the edges of what's possible technically, looking for where there's like, something that's new and valuable, but like pragmatically valuable, but still pretty messy. And then coming up with like a very clean, opinionated, zero config solution to it. So like, I would put Socket A O in that bucket. I put Next in that bucket. I think for cells in that bucket. So one is, I'm curious if you feel like that's, that's kind of.

• 3:10Speaker 01

  I mean, if O1 came up with that, it's, it's over. That's pretty good. Like, I'll, I'll tell you, like, it's funny. I was having a conversation with one of my coworkers the other day, and I was giving them the example of Socket A O as, when I started the project, Web Socket was, which is the underlying technology that they later become a part of web browsers. For context, maybe everyone doesn't know about Socket A O. It enables real time chat, real time communication. It powers websites like Perplexity. And when I created that developer tool, Web Socket was in its infancy. So to your point, you kind of want to identify the wave when it's just a little, a few drops of water, but you have that, you see that potential. And

• 3:50Speaker 01

  it's also extremely messy. So being able to go from, I want to do something with real time, to I want to create an application. I think that's the vacuum that, or the huge gap that Socket A O filled out. And with V0, I think we saw the same thing. So. Models became good at writing code. Specifically, they were very good at writing, like being able to design with HTML and CSS and also writing React code. So even when GPT-3 was out, we started thinking about, well, this could be used for revolutionizing how design and code gets emitted. How the process of bringing an idea to life

• 4:35Speaker 01

  could be completely disrupted, but it was really early. So to your point, there's almost like a parallel between like Web Socket was a draft of a specification when I started Socket A O. And when we first thought about B zero, models could barely be coherent in outputting code. But there was that promise. And I think, you know, you kind of want to ride those waves when they're early. Yeah.

• 4:58Dan Shipper?

  Yeah, and I think one of the interesting things is like, it feels like, so everything that you've done so far has been like very developer focused. And it feels like you have your finger on the like, the vibe of like what developers want.

• 5:11Speaker 01

  Well, I'll tell you something I don't think I've shared before, which is the company was called Zeit. And then we renamed it to Vercel. And the reason I called it Zeit was a few things. One, I was obsessed with this idea that if you really want to capture developers, you need to capture the zeitgeist.

• 5:27Dan Shipper?

  Right.

• 5:28Speaker 01

  The zeitgeist is this idea of, you know, the collective conscious and how people are thinking about the future. And you need to really be on your toes. Because things change so quickly. The vibes change so quickly, right? Like you see this with models, like one day, one model is popular for developers. The next day, it's another model. And another, another point was Zeit means time in German. And I was obsessed with this idea of real time with my background in Socket A O. And what I thought is that the best way to build software would be in real time. And it has two meanings. One is real time in the sense of you're just typing and you're getting feedback instantaneously from the system. I think B zero is almost like the culmination of that idea.

• 6:13Dan Shipper?

  Interesting.

• 6:13Speaker 01

  Because you're literally chatting with the system and getting feedback in real time. But the other one was chatting with your customers.

• 6:20Dan Shipper?

  Right.

• 6:20Speaker 01

  Getting feedback from the world and adapting. I sometimes joke that for early stage founders, their job is to, you know, chat on X with our customers and prospects, get feedback, fix things, and put a ton of quality craft and taste into their products.

• 6:38Dan Shipper?

  I want to stay with that idea of like Zeitgeist or like Paradigm or like having your finger on the pulse of something.

• 6:45Speaker 01

  Yeah.

• 6:45Dan Shipper?

  Because I think one thing that's interesting is, you know, to come up with Socket A O, to come up with Next, like you have to be developing stuff yourself all the time.

• 6:54Speaker 01

  Yeah.

• 6:54Dan Shipper?

  Realize that this is possible and that you want to make something.

• 6:58Speaker 01

  Yeah.

• 6:58Dan Shipper?

  Like it's too hard, so you need like a tool to help you do that more easily. And I'm curious how that has changed for you. Like, I don't know how much programming you're doing.

• 7:06Speaker 01

  It really hasn't changed, surprisingly. So, like I mentioned earlier, one of my goals is to like enable Vercel to do a lot of what I did as an individual, like come up with those ideas, being able to bring them to life. And so one of the things that I mentioned is, you know, kind of inspiring our employees with like, well, you could build the next Socket A O if you think about these principles. So I think a lot about principles that I can set for the company at large. And one of them is we're always customer zero. We dog food our tools. We put product experiences before tools as well. I was just having a conversation with our tech lead for the A I S D K. So A I S D K is a really interesting project.

• 7:49Speaker 01

  It's becoming the number one framework in the JavaScript world for how you interact with A I models. So it's almost like the Socket A O or Next Shays of L L Ms.

• 7:59Dan Shipper?

  Yeah.

• 8:00Speaker 01

  But it didn't come out because I was excited about A I or I live in San Francisco and I saw a lot of billboards about A I. I was like, hmm, we should have an A I framework. What it came out of is us building A I products. So we're building a lot of really cool demos of how to use Next Shays with A I. We're building V zero.

• 8:20Dan Shipper?

  Right.

• 8:20Speaker 01

  And we realized there's an opportunity to extract out the infrastructure of those A I products and then share them with the world.

• 8:27Dan Shipper?

  Yeah.

• 8:27Speaker 01

  And so the operating principle here is you want to always put the product first, not the framework first. A framework in isolation without having that initial sort of patient zero is never going to be a good tool.

• 8:42Dan Shipper?

  Yeah.

• 8:42Speaker 01

  And this actually came out of my fascination with how Meta put out React. So Next Shays builds on the open source UI infrastructure that Meta open sourced.

• 8:54Speaker 01

  And what I noticed is that I kind of reverse engineer why I liked React and why I was impressed with it. And I remember it first started with their product. I would go to the Facebook newsfeed and all of the things that they were doing that were very real time, like the chat thing and the notifications badge and it just felt snappy. I actually remember a specific moment when they announced that comments were going to start trickling in in real time. And I was like, that's hard because I built it. I was like, that's really hard at that scale. It's very impressive. And then I realized, okay, you ask yourself, okay, how did they build that? And this is actually something that a lot of people do unconsciously.

• 9:36Speaker 01

  And it's really good to tap into that sort of, it's almost like a primal instinct. When you see something good, you ask yourself, how did they build that? It's like when you walk in into a studio and you're like, oh, I really like the vibe here. Well, the next thing you do, I mean, maybe not everybody, but like, I guess.

• 9:52Dan Shipper?

  It's a very founder.

• 9:53Speaker 01

  They're creatives, people, whatever, like we can call them like, I wonder whether they got that chair? And I wonder what fabric is this curtain?

• 10:01Dan Shipper?

  Totally.

• 10:01Speaker 01

  And so developers do this all the time. And so start with the product. You almost don't need to promote the tool.

• 10:09Dan Shipper?

  Yeah.

• 10:10Speaker 01

  Because people are going to ask themselves like, all right, I want a product like that.

• 10:14Dan Shipper?

  Yeah, yeah, yeah, yeah.

• 10:15Speaker 01

  And that's how I still do it. Like I tried to use our products. But I also am always on the lookout for like really good things and then reverse engineer how you get there.

• 10:24Dan Shipper?

  Yeah, I definitely found, there's so much there to talk about. Like I've definitely found with every, so we have the writing and then we build software products. And a lot of the writing is about building new technology.

• 10:34Speaker 01

  Hundred percent. It's like a marketing strategy in its own right.

• 10:37Dan Shipper?

  Yeah, like honestly, like the best marketing for our articles has been building great products. Because people are like, well, I want to know how they think about it.

• 10:43Speaker 01

  Totally.

• 10:44Dan Shipper?

  Which has been really, really cool. And the other interesting thing that I think is, is sort of, it's your ethos. And it's also, I think uniquely valuable right now is like the sort of dog fooding ethos. We do that too, because I feel like AI sort of. It changes the landscape where there's still, there's now a ton of low hanging fruit of things to build.

• 11:05Speaker 01

  Yeah.

• 11:05Dan Shipper?

  Because like there's a new technology paradigm. And so you can just like wave a stick around and just think about like, okay, what are all the things that I want? And probably someone has not built that in a good way yet. Whereas like, I don't know, three years ago at the apex of the B two B SaaS wave, like all the low hanging fruit.

• 11:20Speaker 01

  There was a saturation and that's what you see when there's a platform shift.

• 11:24Dan Shipper?

  Yeah.

• 11:24Speaker 01

  AI is a new platform and when a new platform emerges, it's, it's kind of hard to even estimate how many new applications will emerge.

• 11:34Dan Shipper?

  Yeah.

• 11:34Speaker 01

  I remember the early days of the iPhone. It wasn't clear to people that it was the new platform.

• 11:41Dan Shipper?

  Yeah.

• 11:42Speaker 01

  In fact, it launched and, and there was kind of a hint that there could be apps of your own in that home screen. But it actually took quite a few years for people to be like, yeah, this is the platform. We have to, we have to claim a square in that home screen grid.

• 12:00Dan Shipper?

  Yeah.

• 12:01Speaker 01

  Not obvious at all. And I think you can think of AI as almost like another new, it's a new home screen. And right now there's a handful of icons on that home screen. There is chat GPT. You could, you know, you could have like Google AI overviews perplexity. And the question you should be asking yourself is like, how many more of those are there going to be in it? And my guess is probably millions.

• 12:25Dan Shipper?

  Yeah.

• 12:25Speaker 01

  And so very exciting time for especially small teams like yours to be thinking about what are my pains?

• 12:31Dan Shipper?

  Definitely.

• 12:31Speaker 01

  That AI can answer.

• 12:33Dan Shipper?

  Yeah. I want to go back to the, the thing you said earlier about sort of transitioning from maybe like in the socket I O days, you have your finger on the pulse and you're the one who's solving your own problem to thinking about how do I enable an entire organization of people to think that way? So you're more like thinking about the principles underneath like that, that mode of thinking and then trying to infuse that in the culture.

• 12:55Speaker 01

  Yeah.

• 12:56Dan Shipper?

  Tell me about how that process has been for you personally, like, do you like that versus like actually coding a lot or like, yeah, tell me about that transition.

• 13:04Speaker 01

  Yeah, it's awesome. So I believe that there is seasons of a startup's life.

• 13:08Dan Shipper?

  Yeah.

• 13:09Speaker 01

  And in the early days, you need to be obsessed with getting a high quality product out into the world. And you live and die by product market fit. I think at some point you start realizing that you have it and there's other things to build to operationalize that product market fit. To make it into a machine, right? And I would say like that's a transition between a startup and a scale up. And think, and I think when you're a scale up, whatever that term means, but I guess like a larger, more mature startup, you realize that you no longer live or die by one individual product market fit. You're probably thinking about becoming a platform or you are a platform and you're thinking about multiple products. And so you start becoming more of a machine

• 13:53Speaker 01

  that outputs products. You're like essentially a Y combinator in, in the initial like recursive sense. Yeah. And when you're creating a machine, you still apply a lot of the thinking that you apply when you design products. It's only that the company itself is the product. Right. And you're still worried about all the things that you worry about when you want to create excellent products. For example, onboarding. If you're going to be hiring a ton of people, what do you want to have? You want to have an excellent onboarding experience, right? Just like when you first start using a new app. When people join Vercel, they need to be equipped with everything they need to succeed. So you start thinking about other aspects of the company.

• 14:36Speaker 01

  I think principles are kind of like the, sort of like product specifications of your company. And so thinking about what are our values, what are our ethos, what is our mission? What are the right people to pursue this mission? In terms of like that recursive product generation machine, I think a lot about what I call recursive founder mode. So there's founder mode. I believe founder mode fundamentally doesn't scale in the sense of if your aspirations are very large, the total output and creative output of a company cannot just be limited to the founder. Right. And so especially when you start having those ambitions of like being a, a company that can nurture new founders within it.

• 15:19Speaker 01

  And so I think a lot about what is the DNA that we can incorporate into the company? That is almost like the people that would start a company on their own. Yeah. But they can actually kind of do that within Versal. And so we, we select for a specific traits. We offer very unique things. So we build a lot of cool open source technologies. People know us for Next.js, but we also contribute to Svelte, which is a very popular web framework. We created a, or we, we acquired initially, but we support a tool called Turbo Repo. That helps companies to scale huge code bases to the size of like Google and Facebook. So people can come to Vercel to fulfill their dreams to reach millions of developers through open source.

• 16:04Speaker 01

  And so those are kind of the things that I think a lot about like, you know, how could I find not just the next socket A O, but how could create the environment that creates socket A O's and next J A's and the ecosystems around it?

• 16:17Dan Shipper?

  I think that's really interesting. And the reason I'm kind of like keying on that journey from like doing it yourself to making the machine that builds the builds the products is it's sort of this journey of like moving up the layer, moving up layers of abstraction in an organization.

• 16:34Speaker 01

  Totally.

• 16:35Dan Shipper?

  And I'm like, what I want to talk to you about is sort of the

• 16:41Dan Shipper?

  the future of developers in an A I world. And I think that there's something similar happening in in some aspects of being a developer where, you know, Cora, for example, we have this email product that I demoed for you. And Kieran, who built Cora, he didn't write like 80% of that code, right? He knows how it works.

• 17:01Speaker 01

  Yeah.

• 17:01Dan Shipper?

  Like 80 to 90% of it was like written by O one or Claude. And and and I think that's a very similar upleveling journey.

• 17:10Speaker 01

  Yeah.

• 17:10Dan Shipper?

  Right? Where the A I is actually typing the stuff and you're and you're thinking about what are the principles and what's the architecture that you want it to to write?

• 17:19Speaker 01

  Yeah.

• 17:20Dan Shipper?

  Talk to me about that.

• 17:21Speaker 01

  Yeah, one thing that immediately comes to mind is that it does seem like people are becoming full stack product builders. I don't think I will. I would identify today even as a coder, even though that's what I obsessed about for years. Since I'm like, since I was like 10 years old. My ego and my identity became tied up with I code.

• 17:45Dan Shipper?

  Yeah.

• 17:45Speaker 01

  That's my thing. And yet I think what I was lucky to have is also that aspiration to build products. And that's what allowed for things like socket A O to happen because it was like, I just want to make the web more real time and more interactive. It had like a product idea in mind. That wasn't just like only in the code. I think it's an important asset to have. And when I look at people at Vercel today, I've been noticing that they're just more full stack. They with V zero, for example, they can do design. They can bring context data copyrighting into their creations that otherwise would have required chatting with other people and crowdsourcing ideas. So we are going into

• 18:25Speaker 01

  a world where coding is a specific skill. And when things are specific skills, machines tend to take them over over time. If your skill when you were a kid was like, I can do math in my head really well, awesome, great asset to have. I love it. But also, there's a specific machine that can do that skill also very well and even better than you. And so what I try to separate is what are the meta skills that are not as easily replicated by machines that you should still nurture? And I think those tend to be more around very high level conceptual thinking. Your engineer who automated the production

• 19:09Speaker 01

  of that product to like an 80% degree, he still has a very good understanding of how all the concepts relate. He can prompt the right things to the AI. It's not that he just was like, okay, oh, six, please build me this thing. And then you just like checked out and like went on vacation. So the concept of symbolic systems comes to mind a lot for me because it transcends language, runtime, framework, coding. And that's extremely important to have. How things work and relate to one another. Interestingly enough, it's a skill that VCs kind of nurture a lot. Because like I've been with, I've been in rooms with

• 19:54Speaker 01

  a lot of venture capitalists that play by ear and you can tell that they play by ear because they have, and by the way, this is a skill in its own right. And it's very impressive. Like they have extreme, what I would call like token breath. I'm using token in the sense of LLM. Like they know 30 companies for the space of like continuous testing and they know 50 for LLM pre-training models.

• 20:18Speaker 01

  And that skill actually is super helpful when you're prompting.

• 20:20Dan Shipper?

  Yeah.

• 20:21Speaker 01

  Because you understand how the concepts relate to one another. You can point the agent to use a specific technology that might be the right solution.

• 20:29Dan Shipper?

  Yeah.

• 20:29Speaker 01

  But you're not actually doing the coding. And so that's, I think, the biggest step that's gonna play out in the ecosystem.

• 20:36Dan Shipper?

  Yeah, I think that I love the idea of meta skills. And sort of one of those being like, okay, how do things fit together? How can I be a little bit more full stack? How do I think about things from end to end? Another thing that I've been playing around with is like, I have this whole idea of us moving from a knowledge economy to an allocation economy, where you're in a knowledge economy, you're compensated based on what you know. In an allocation economy, you're compensated based on how you allocate the resources of intelligence. And that the skills in that economy that are valuable are the skills of human managers today.

• 21:10Speaker 01

  Yeah.

• 21:11Dan Shipper?

  So like an example, which I think is kind of interesting, because I think a lot of developers are probably thinking, okay, is it even worth it to be able to code right now? And I think, like, when you think about being a manager, let's say, being a technical manager,

• 21:27Dan Shipper?

  you always have to, there's this line between, okay, am I gonna be in the details and know everything in micromanage? Or am I gonna completely check out and like, just let them do whatever they want, basically? And both options are bad. And you have to be able to know, okay, when is it important to be in the details? And when is it important to just delegate?

• 21:48Dan Shipper?

  But in order to do that, you kind of have to know the underlying like, skill. It's very hard to know that if you're not technical.

• 21:56Speaker 01

  I love this concept, by the way. The idea that you're allocating resources and delegating to these agents is already happening. One of the things I think is really, really interesting. So, Vercel has two parts broadly. One is our managed infrastructure. We basically host websites. We deliver them through a global CDN network. We make it so easy for developers to deploy and build, et cetera. And that has a usage-based model. So, for example, we host UnderArmour.com and OpenAI.com. If they have more traffic, Vercel costs more for them. And if they have zero traffic, it costs nothing, which is awesome. On the other hand, we have V0, which is more like a design engineer tool

• 22:41Speaker 01

  in the in the sense almost as like VS Code or Figma would be and almost like if they had a child. And those products you typically pay by subscription, not by usage. I think AI is actually disrupting that and it goes back to that idea of allocation. So I'll tell you a concrete example. You have users that are draining AI tokens and running this GPUs super hot, day in and day out. They're like AI-powered engineers. And there's users who use it in a more casual way. They're like, oh, I'm on my phone. I want to create a personal app. I'm going to use V0. And what happens is that at the end of the day, we're seeing the first category of apps, I think,

• 23:24Speaker 01

  that are tools that have a consumption billing model attached to them. Because what you're doing is you're not simply using it as a system of record. It's not like Salesforce. You're actually setting machines in motion to perform tasks. And I like that metaphor is it's almost like you're doing management in capital allocation. Okay, how much computation am I going to allocate to perform this given task? And you even have to think about risk, right? Because it's true that AI is really exciting and capable, but sometimes it's not that capable, right? So you have to think about like, am I going to burn, you know, like lots of inference time compute?

• 24:07Speaker 01

  Am I going to set this entire like 500 billion data center on fire to try to solve this task? And actually don't know if the AI will perform? Is this on the customer side or on the like? It's on the customer side. So like the user of AI will have to think almost as if they were a cloud infrastructure user. I think it's a leap that is maybe the closest thing to that in today's like sort of product development world would be CICD, where a given engineer can say, okay, I'm going to run 100 machines to test my program. But it's a lot, it's a lot less fluid. It's a lot less elastic than this kind of thing where like you can sit down and say, okay, five agents, go at it.

• 24:49Dan Shipper?

  Yeah.

• 24:50Speaker 01

  And it might or might not give you the right result. And so you have to think like a capital allocator and you have to think like a manager of these agents.

• 24:57Dan Shipper?

  Yeah. What that makes me think of is like, yeah, in this world, you're much more likely to, it makes much more sense to pay for tasks to be done.

• 25:06Speaker 01

  Yes.

• 25:06Dan Shipper?

  And, and for the price that you pay to reflect the level of risk that the

• 25:10Speaker 01

  Yes.

• 25:10Dan Shipper?

  task will get done well.

• 25:12Speaker 01

  Hundred percent. Which is like hiring any other human for that matter.

• 25:14Dan Shipper?

  Exactly.

• 25:15Speaker 01

  I go to Upwork and I'm like, I don't know if this is the person, right? I don't know if this is the agent or is this the task for this agent?

• 25:21Dan Shipper?

  Exactly. And then what that makes me think of is like, well, at that point, like if, if you have a market where like different agents can bid from different companies to like

• 25:30Speaker 01

  Yeah.

• 25:30Dan Shipper?

  do any particular task, that's like actually really

• 25:32Speaker 01

  Yes.

• 25:33Dan Shipper?

  interesting market.

• 25:34Speaker 01

  Hundred percent.

• 25:34Dan Shipper?

  Yeah.

• 25:34Speaker 01

  Because I think also that we're going to see specialization in, in agents. That some will have better context, some will have better taste.

• 25:41Dan Shipper?

  Yeah.

• 25:42Speaker 01

  A lot of that deals with like the post-training process. And so there is definitely a marketplace and a competition that happens in who is the right agent for this problem?

• 25:53Dan Shipper?

  Yeah. I want to go back though to just you saying, I don't, I don't think of myself as a coder. I think that's so interesting. And, and also you serve developers, right? So where do you think that term goes over the next like five or 10 years?

• 26:10Speaker 01

  Yeah, you know what's interesting? Coder as a word used to be more popular

• 26:14Dan Shipper?

  Yeah.

• 26:14Speaker 01

  in my community.

• 26:15Dan Shipper?

  Yeah.

• 26:15Speaker 01

  And I think even before AI, people were starting to realize that their job was not just to introduce keystrokes into an IDE. There's a history of this. One example that I like to give is before automatic code formatting tools became popular, people used to care a lot about what their code looked like on the screen.

• 26:39Dan Shipper?

  Hmm.

• 26:41Speaker 01

  How many columns? Is, are the words neatly aligned? People would have discussions about this. It was actually considered to be a productivity drain, but it was a huge subject of debate within companies. Now we look back and it's like, of course, people should not be discussing the, if the aesthetic arrangement of the code is right or not. And so people introduced this tool called the formater. I think, I don't know who the exact

• 27:09Speaker 01

  project that popularized the most, but I remember when Go Lang came out, out of Google, it came with very simple code, automatic code formatting. And then in our community, in JavaScript and TypeScript, prettier came out. It's called prettier because it makes your code pretty with no discussion, like objectively prettier. And then that whole category of quote unquote problem disappeared. And I would say, look, format, how your code is formatted, that, that felt appropriate to the word coder. It's just a person that like makes their entire purpose to like write code. And then we kind of, I think, developer, engineer,

• 27:50Speaker 01

  then product design, which is a role that sort of came out of Facebook, became more important. So the trend has been away from the implementation detail, which is the code, and towards the end goal, which is to deliver a great product or a great experience. And it's in that context that our company has become, has become popular because one of the things that we came to market with is like, started focusing more on the front end.

• 28:16Dan Shipper?

  Right.

• 28:16Speaker 01

  Started focusing more on the customer experience, on the site speed. We've demonstrated to companies that you make your website faster and you just sell more things, you make more money. So we started trying to like divorce ourselves from the code and, and put the focus on the experience.

• 28:32Dan Shipper?

  Okay, yeah, that makes sense. How, how do you, talk to me about how you see V0 fitting into that? And just generally where you see V0, V0 sitting in the whole ecosystem of?

• 28:42Speaker 01

  Yeah.

• 28:43Dan Shipper?

  There's like Replit Agent, there's like Claude Artifacts, there's all these different, there's Cursor Composer, there's all these different tools. Talk, talk to me. About that.

• 28:51Speaker 01

  Yeah, it's exactly in the context of that idea, right? We look at V zero as code last rather than code first. When you come to V zero, you prompt with your idea or your intention. You can import a Figma file, so it can bring your designs alive. That's for companies that already can relate to that mode of working. V zero will make a lot of sense that way. But you can also just come with an idea. Build me this thing. You can, we're about to introduce templates. You can already can start with, for example, an AI chatbot. Like you can use AI to like produce AI products. And so the biggest difference with those is that those started with the code. They look at themselves more like IDEs.

• 29:33Speaker 01

  And we look at this more as a product development environment that merges what you would expect from a design tool. Because the things that V zero produces, we aim to make them great. It should work great. It should be accessible. It should be mobile ready. All the things that I've been trying to teach our customers in a less scalable way by means of customer support, I would say, or professional services, you could call it, or enterprise agreements where a big company will come to us and say, look, you're the experts in building storefronts. Help me have a killer storefront for Nintendo. And a lot of that process is just manual.

• 30:16Speaker 01

  Like ultimately, we would have to, of course, we had the framework. Next, Chase tries to set up the right foundation. But on top of that right foundation, there is a ton of business logic that needs to live. So the idea of V zero is could I partner you with an agent that is an expert in web development, has taste and produces things that we're legitimately proud of, which is harder to do in the AI world because AI has become a little synonymous with, well, you can get a lot of slop from different products. So we're very focused on the outputs have to be great.

• 30:50Dan Shipper?

  One of the things that, so I had Nabeel from Spark on the show last week. And one of the things that he said that I thought was really interesting is when he looks at these sort of agent products. There's, every agent has to make a decision about how long the leash is between the user prompt and when the agent like gives a response back.

• 31:13Speaker 01

  Yeah.

• 31:13Dan Shipper?

  So like Copilot's a very short leash, right? Devon is like a very, very long leash.

• 31:17Speaker 01

  Totally.

• 31:18Dan Shipper?

  Her cursor is like sort of somewhere in the middle, maybe.

• 31:20Speaker 01

  Yeah.

• 31:21Dan Shipper?

  How did you think about that? And how do you think about, yeah, like when, when I put something into V0, right? Like what my experience with it is it tries to build something like immediately and like give me the result.

• 31:31Speaker 01

  Yes.

• 31:32Dan Shipper?

  How do you think about that versus other ways that you can, you know, maybe check in halfway through or whatever?

• 31:38Speaker 01

  Yeah, it very much depends on the task. I believe that the future of AI will be sort of the classification of an estimation of the difficulty of the task and then taking different strategies. But also getting feedback from the real world. So a concrete one is when you give us a prompt, we have to give you feedback right away because you're almost in the taste making part of the, part of the job. It's, it's like you hired an interior designer and like they're checking for your vibes of like, okay, what, what do you like? Let's get deeper into this. But then you have very specific functional requirements. I've sometimes told the zero, make this faster.

• 32:15Dan Shipper?

  Yeah.

• 32:16Speaker 01

  And it does. And sometimes actually it's taken me a few prompts, no, no, make it faster again. Like it's amazing how good it is at optimizing React code. So I had a very intensive animation that it rendered and it was just expensive in how much it was recomputing. So I literally just told it, make it faster. And then I told it, make it faster again. It did whatever. And it was all vibes from my side. This is why I was telling you like the coder thing is, is interesting. It's like, it's strictly less important because I didn't care how it just made it faster. And so I would expect that for that type of task, we can give V0 a longer leash. And I think there's a precise technical distinction is one feels like more in the one shot world where you're getting knowledge

• 33:01Speaker 01

  plus rack data out of the LLM. And the other one is more the feedback loop of thinking.

• 33:07Dan Shipper?

  Yeah.

• 33:08Speaker 01

  That can have an arbitrary length.

• 33:10Dan Shipper?

  Yeah.

• 33:10Speaker 01

  And that, that to me is. One, the thing that has allowed us to increase the quality of the product. V-Zero actually fixes a huge amount of error that comes out of the models. It has error correction loops because it looks at feedback behind the scenes. Another careful balance that we need to strike is how much do we expose of that process to the end user? You kind of want to learn, but you don't want to be overwhelmed by everything that the agent is trying. So we just, we have, I mentioned earlier, we have a product called AISDK, which is kind of like the infrastructure underneath V-Zero and it's open source. And companies can use it to build their own agents and their own products.

• 33:54Speaker 01

  And we have a playground for it and we just added the DeepSeek R1 model, which people are raving about right now. And you can see when you use that model that you can see every thinking token. And it's actually completely overwhelming. It's so overwhelming that it's, and the classic demo that people are doing is they count the number of Rs in a strawberry. And then you see it, think through that process and it's overwhelming, it's nauseating. It's almost like peeking into the mind of a mad person. And so that, and now extrapolate and bring that into your product. Like you don't want to emit every thinking token into the user,

• 34:36Speaker 01

  but you kind of want to give them an overview of why the leash is longer and how the agent is using your time and resources.

• 34:43Dan Shipper?

  One of the things you made me think of in this, in this sort of like transition from coder to something else. I don't know, what word would you use?

• 34:50Speaker 01

  I like to use product engineer or product developer. Another role that has emerged a lot is design engineer. I love design engineer because I care a lot about design and I want to make things work in the real medium. So those are the two roles that are sort of emerging.

• 35:06Dan Shipper?

  Okay, so let's say like product engineer and design engineer, from coder to product engineer and design engineer. One of the things that I think that transition reflects is if you have machines that can build things really cheaply. In a world where that was really expensive, you care a lot about how all of that works. And you want to do that by hand because you want to like optimize that really, really well. But in a world where that's really cheap, you go from caring about how like how it's done to how the end result feels.

• 35:35Speaker 01

  Yes.

• 35:36Dan Shipper?

  Which is why you kind of want that rapid prototyping loop.

• 35:38Speaker 01

  Yes.

• 35:39Dan Shipper?

  And it sort of occurs to me that that's actually also like a really long running process like. I don't like it. I don't code in assembly or like I don't do garbage collection, you know?

• 35:49Speaker 01

  Totally.

• 35:50Dan Shipper?

  And so like.

• 35:51Speaker 01

  It can be, it can even, it's so funny, garbage collection is such a good example because when people naively try to do memory allocation to make things faster, sometimes they actually underperform garbage collection.

• 36:01Dan Shipper?

  Right.

• 36:01Speaker 01

  It's, it takes a lot of skill and knowledge and a domain and specific task to get the right ROI out of a manual memory management.

• 36:09Dan Shipper?

  Yeah. And like sometimes that's, that's useful, but like.

• 36:11Speaker 01

  Yeah.

• 36:11Dan Shipper?

  More, more often than not, it's not.

• 36:14Speaker 01

  Yeah.

• 36:14Dan Shipper?

  Um, today. And I mean, but 10 years ago, if you use Python or JavaScript, people were like, I don't know. That's not, that's not real programming.

• 36:20Speaker 01

  Yeah.

• 36:21Dan Shipper?

  And I think today probably something similar is happening with some of these underlying like JavaScript or, you know, Python languages.

• 36:27Speaker 01

  I have a lot of thoughts in this. One is AIs need to today, let's call it like this product development AIs. Need to sit on top of significant infrastructure for them to be useful and productive. They need to be on top of a platform. That's why it makes sense for Vizier to sit on top of Vercel and NextJS. Because think of it just from an economics point of view. The AI either re-emits all of the code necessary to like render the thing. Or it says, I'm going to use NextJS and I'm going to render the thing with it.

• 37:00Dan Shipper?

  Right.

• 37:00Speaker 01

  One would take you millions of lines of code of tokens to output if you needed to reinvent the framework. The other one might take you like a hundred lines of code to produce a really good result. And so you have to think about AIs as a collaboration with infrastructure and platforms that already exist. Most of which are human made, very much like a Waymo self-driving car needs to interoperate with the real world. We couldn't modify the streets and say like, we're going to build new streets for self-driving. No, we needed to put the cars on top of that infrastructure. And so another thing that your comment made me think of is. It is true that there are certain skills that will yield,

• 37:44Speaker 01

  for example, better performance or better safety, such as using Rust instead of using JavaScript. Now, my question is, is optimizing something in those languages, something that AIs will be able to do in the future? Everything seems to indicate that that would be the case, because when you use these languages, you're also respecting very well-defined rules. Like, in the case of Rust, the borrow checker, lifetimes. And I think it's going to be the case that AIs can do a lot of that optimization work for us better than a human could do. It's going to take a while to get there, but I'll give you another concrete example. There's a project out of Google called Project Zero that seeks to unveil security vulnerabilities

• 38:29Speaker 01

  in the entire world, not just Google's products. And it's some of the most cracked security engineers on the planet. And there's a category of bug that they always find that is in C code. There's memory corruption bugs that lead to catastrophic security vulnerabilities. Sometimes it's one line of code that you get wrong. And in our global encryption infrastructure, OpenSSL, such a line of code was found that did a very unsuspecting MCPY, one line of code that basically made the entire universe vulnerable to a really, really, really bad vulnerability. And now, the problem is, we know that C is not the right language for that kind of infrastructure. It's just so easy for human beings

• 39:13Speaker 01

  to sneak in those vulnerabilities, either by mistake or tinfoil hat on, some, like, dark, secret agent. It just sticks one line to create a massive backdoor. And so, the problem that we have is, how do we rewrite all of that C code in Rust? And I know that this is a meme of rewrite everything in Rust or like any other memory-safe language, for that matter. Will AI agents do it? My bet is yes. Will AI agents help us uncover those vulnerabilities? Because Google has maxed out on how many cracked engineers that can sort of like read all of this world code and identify those specific bugs. So it's going to be exciting to see that AI will also have a very profound

• 39:54Speaker 01

  impact on the underlying infra, but it'll be a different kind of task, I think.

• 39:59Dan Shipper?

  Another way, I think, to say what you're saying, and you tell me if you think this is right, is for any task where you can quantify whether the task is done well along one dimension.

• 40:09Speaker 01

  A fitness function.

• 40:10Dan Shipper?

  A one, like, well-defined fitness function where the steps are verifiable.

• 40:16Speaker 01

  Yes.

• 40:16Dan Shipper?

  That is going to be like very easy to automate. And then anything else that's much more, much higher dimensional, which we usually call like taste.

• 40:25Speaker 01

  Yes.

• 40:25Dan Shipper?

  Sort of like this aesthetic thing that's like, this actually just feels good.

• 40:29Speaker 01

  And it has social effects, right?

• 40:31Dan Shipper?

  That's going to be a little bit more, yeah, you just need to, you just need to figure that out.

• 40:35Speaker 01

  You need to be the vibe sky above the machine. Yeah.

• 40:39Dan Shipper?

  How do you cultivate that in yourself?

• 40:43Speaker 01

  A lot of practice, I think. I remember one of the best engineers I ever worked with, he was also a very good designer. That's how it kind of became infatuated with the idea of like, we can do more. Common wisdom in Silicon Valley was like, you're either like a, like a knee-deep in, in the data center room and writing backend code, or you're the designer like super polished, like Mostat, you know, like, you can do both. And this guy TJ kind of taught me that. And I remember having a conversation with him and he was like, "Well, look, I just train my taste a lot. I look at a lot of things. I look at what people like. I seek a lot of feedback." So I do think that you can work on your ability to discern what people are going to like.

• 41:27Speaker 01

  There's obviously some rules underneath, and this is what we're trying to sort of uncover with B0. It does turn out that, you know, how you distribute spacing on a page does lead for more pleasant outcomes on the viewer's eyes. And we try to sort of like yield those out of the box. But I do think taste can, can be worked on in sort of like the higher dimension. I like, I like the metaphor you use of like bringing in inspiration from multiple sources and multiple things. I think like radically outside the box can be super helpful. And then the art of Understanding what's possible and what you can sort of like start to push the boundaries on. So it's kind of funny, but like being terminally online kind of like answers

• 42:09Speaker 01

  for this for these two things. One is you want to consume this stream of consciousness of like what good design looks like and what the avant garde is. But you also want to be at the forefront of like, what's about to become possible?

• 42:25Dan Shipper?

  Yeah.

• 42:26Speaker 01

  That it can start cooking on now. Kind of goes back to like the beginning of the conversation with Sagario. I became aware that a real time communication channel API was about to become possible in every single web browser on the planet. And I could start cooking on it before it was real.

• 42:43Dan Shipper?

  Right. Like, tell me about that now. Like, what are you, what are you, what's buzzing in your ear right now that's about to become?

• 42:49Speaker 01

  Yeah, we kind of touched on a few. It's like this idea of like domain specific agents that are infused with taste and tools and knowledge for even even tasks that you would you would think, okay, maybe I could solve that with chat GPT. But it's a ton of work and maybe the result is not that great. And it can like infuse a lot of quality into that vertical. This idea of agents that have the long horizon like work, but also can give you rapid feedback when necessary. I think there's a big opportunity there. Broadly, I continue to think of AI as this like iPhone home screen on top of which we can deliver

• 43:25Speaker 01

  lots and lots of applications. And yeah, I think the the idea of chat GPT for X continues to surprise me. I just heard from a, I believe it was a cardiac surgeon that said, I basically spend a lot of time during my professional life using not chat GPT, but this so called open evidence, which is infused with all the healthcare data used by 250,000 medical professionals in the US. And it kind of makes you think, right? Like, if you're a medical professional, are you gonna go to the general purpose AI that is sort of like the lowest common denominator for everything?

• 44:10Dan Shipper?

  Yeah.

• 44:10Speaker 01

  Or are you gonna go to the thing that is constantly improving for your domain and field?

• 44:14Dan Shipper?

  Yeah.

• 44:14Speaker 01

  So encourage entrepreneurs to think about it that way and also find the opportunities to bring creativity into tools that are always pretty plain. Of course, Copilot could autocomplete code in your IDE, but V0 took that way further. As you mentioned earlier, like, it's not just about the little bit of auto completion, but bring a lot more ambition and creativity into what the AI agent can do.

• 44:38Dan Shipper?

  Yeah, I think there's all this talk right now, or it's probably a little bit less so now, but especially like a year ago, where everyone was like, well, incumbents are just gonna win, like, if you have access to AGI, like, distribution is all that matters and blah, blah, blah. And I don't think that that has panned out, and I don't think that will

• 44:55Speaker 01

  It has not.

• 44:56Dan Shipper?

  that will continue to pan out, because like, part of what you're saying is like, for example, the doctor issue is like, it's not just that maybe O1 or ChatGPT is like not tailored for doctors, it's that it has to be a general purpose tool, so it has to say like, I'm not a medical professional, right? And like, you prob- and it has to have guards against like what it says.

• 45:16Speaker 01

  There's almost like a principle there, like, every refusal of ChatGPT can be turned into a tool that doesn't have to refuse, because it's actually going the extra mile, whether it's with better data, with, you know, maybe even human in the loop, whatever it is, every refusal is my opportunity.

• 45:33Dan Shipper?

  Exactly, yeah, I love that. And I think another way to say that is startups get to take risk, and the intelligence that is available

• 45:46Speaker 01

  Yeah.

• 45:46Dan Shipper?

  is not necessarily a technical limitation anymore. It's often like a risk calculus by a particular kind of company, serving a particular kind of user, and big companies have to serve everyone, and so they have to take lower risks.

• 45:58Speaker 01

  And in terms of disruption, there is a very concrete one that I think a lot about. The history of SaaS has been I start out creating a product that's really good in its category. And then I expand its feature set to beat out my competitors in enterprise bake offs. And so you become a competition of checklists. And there is a precise correlation between product maturity, enterprise maturity, and amount of UI. Like you can actually quantify the number of buttons, the number of dropdowns, the number of nested dropdowns. And so all of that UI can vanish without a trade off in functionality.

• 46:41Speaker 01

  If you're thinking from first AI principles. And that gives the startup a very concrete wedge to attack the incumbent. I'm going to underdo you. I'm going to underwork you. I'm going to under UI you. Right, it's like, and I actually will beat you on functionality.

• 47:02Dan Shipper?

  Yeah.

• 47:02Speaker 01

  Because if you're solving problems with classical engineering alone. And if else branches, this is, I love the Carpathia software 1.0 to software 2.0. Software 1.0 is if else invert binary tree. And algorithms and data structures in AI is like, well. Maybe that competition ends up happening, but we don't know why.

• 47:26Dan Shipper?

  Yeah.

• 47:27Speaker 01

  And so we have that agility that comes.

• 47:29Dan Shipper?

  Space of possible programs to solve the problem.

• 47:31Speaker 01

  Yes.

• 47:32Dan Shipper?

  Of like having a recipe.

• 47:33Speaker 01

  And that's a, that's a concrete way of underdoing the competition.

• 47:35Dan Shipper?

  Yeah.

• 47:36Speaker 01

  Because you're just having the AI produce better or equal outcomes with a lot less manual code.

• 47:42Dan Shipper?

  Yeah, and I think that that's such a, it's also an important like thing that I think startups sometimes get wrong in this era, which is like. Trying to do, let's say like an email product or like, I don't know, any, any, any classic like productivity software, maybe like PowerPoint or something like that. Where what you're trying, what you end up, some products end up doing is. Doing the classic version plus AI, like plus, plus a chatbot or whatever. Which is exactly what incumbents do too, where I think. Like what you actually want to do is figure out, okay, what's the totally new

• 48:17Speaker 01

  Yeah.

• 48:18Dan Shipper?

  factor? And how do I be worse on all of the checkbox dimensions?

• 48:22Speaker 01

  Yeah.

• 48:22Dan Shipper?

  But so good on the thing that matters that

• 48:25Speaker 01

  Hundred percent. That Actually, I would say there's two models that I think a lot about. One is actually you can be better at eventually every checkbox. But in the meantime, you're overwhelmingly better and simpler.

• 48:36Dan Shipper?

  Exactly.

• 48:36Speaker 01

  I think eventually you do need to do more because companies just want to like another thing I've learned with Vercel and when you go to enterprises in larger companies, they want to buy only a handful of software platforms. This is why Microsoft and Amazon and others are so prolific is like they provide like broad solution spaces.

• 48:57Dan Shipper?

  Yeah.

• 48:58Speaker 01

  So eventually you need to get there, but I like your idea of like, in the meantime, like you're just like a killer.

• 49:04Dan Shipper?

  Yeah.

• 49:04Speaker 01

  At a specific dimension, you're way simpler.

• 49:06Dan Shipper?

  Yeah.

• 49:06Speaker 01

  And perhaps you'll never have to have the UI complexity of those incumbents.

• 49:11Dan Shipper?

  How does that sit with you? Because you're just stylistically like a minimalist simplicity guy.

• 49:17Speaker 01

  Yeah.

• 49:18Dan Shipper?

  And Vercel like kind of has to be a little, if you want to be enterprisey, you have to have all the checkboxes or something like that. Like, how are you thinking about that?

• 49:25Speaker 01

  Yeah, you can think of V zero is almost like the AI native interface into the Vercel world, and I expect the next billion developers to sort of come in through that door. And then there is the eject button into Vercel, very much like Vercel kind of did that to AWS. And people still need AWS and we have great integrations and many more coming where we create a bridge to the lower level. I like your concept of like, you're basically like raising the abstraction bar, very much like we did with manual memory management and garbage collection. We're saying, look, at the very, very bottom, there is the rock solid foundation. There's a bedrock, literally, of hyperskater clouds like AWS.

• 50:09Speaker 01

  And then you have the developer infrastructure on top. I believe most of the world will want to interact with developer infrastructure. Because you don't want to go to the raw materials and do like alchemy there.

• 50:18Dan Shipper?

  Yeah.

• 50:19Speaker 01

  Most, and this, the success of Vercel speaks to that. But now there's another level. It's almost like a self-disruption that we're doing with V0, which is like, look, most people are going to want to interact through these agents. They're going to make it more accessible, more design oriented, less infrastructure oriented. And what's nice for us is that you still have the two sort of like levers to pull. Some more mature organizations say like, look, I, we're not ready for AI. I've talked to folks in like super regulated markets where we're running a lot of their web projects. And they were like, please don't say the AI word in my office, like literally like during an onsite.

• 51:00Speaker 01

  And then there is the people that are like, don't say the code. I actually, fascinating, one of our enterprise customers for V0 is a company that, without giving away too many details, has been in the cloud space since the cloud was born, like literally like in the room where the cloud was invented. And they told me, our new organization is just a V0 organization. We have it as a rule that we don't do code. Most, they showed me their Slack conversations, it's just them sending V0s back and forth. There's no GitHub, there's no infra, there is no anything. There's just building products going back and forth and having shared channels with their clients where they also send them V0s.

• 51:43Speaker 01

  And so they're trying to even innovate in how the company altogether works. And so there's people that are going to live in that level of abstraction, just like there's so many companies that only use Vercel. There's companies that combine both, a lot of enterprises use Vercel. It can connect into AWS through a product called Secure Compute, and they kind of live in two worlds. Most startups live only in the Vercel world.

• 52:05Dan Shipper?

  Yeah.

• 52:06Speaker 01

  And so it's going to be interesting to see like, and perhaps is there another level of abstraction coming? Where like the result comes to you in, in a much more sort of objective way? And, and you're giving less feedback, yet to be seen.

• 52:23Dan Shipper?

  That's interesting. Yeah, one of the things that, that sparks for me is, um, I, I watched, I, I watched a talk by Eugene Wei, um, that he did it. We ran a conference called Thesis and he, uh, he spoke at it and it was an amazing talk. And he was talking about, um, The different kinds of company cultures and how that affects the kinds of products you can build. And he made a distinction between a written culture and a like prototype or demo culture. And in a written culture, which he would say like, um, Amazon is a written written culture. I think Stripe is a written culture.

• 52:54Speaker 01

  How interesting.

• 52:56Dan Shipper?

  You're like, you're building products that can be expressed cleanly in in writing, right?

• 53:04Speaker 01

  Yeah.

• 53:04Dan Shipper?

  And what that lends itself to is if you look at like AWS, for example, it has all the specs, like all of the, all of the like logic and rigor is there. But like the Amazon phone like just feels like shit because it like, like it has the like specs, but like it doesn't feel good, right?

• 53:19Speaker 01

  I think people don't even appreciate the extent that they're so good at writing correct, highly available, secure infrastructure and what goes into making that sausage.

• 53:29Dan Shipper?

  Exactly. And that's an output of like being able to have everything written down versus he he makes the the example of um, Apple, where like the early iPhone, like Apple is a prototype culture. Like every time you do something, you go and give a demo to Steve and Steve like rips you and then you like make it better, right?

• 53:45Speaker 01

  Yeah.

• 53:46Dan Shipper?

  And and I think V zero and this company you just you just mentioned, like it allows us to like move.

• 53:51Speaker 01

  To live in that Apple world, 100%. It's so interesting. I think to each their own, right? Like for each role that you play in the ecosystem, you need to like lean more towards one or the other. So for example, AWS, not only do they have a written culture, they have an automatic reasoning team that that writes TLA plus proofs of correctness of all their cryptography and durability. I can trust him with my clinical records. I can trust him with like anything. And I know that those who have like written mathematical proofs of the certainty of that code and the distributed system that supports it. And then, on the other hand, you need tasks that are so creative that imagine writing a mathematical proof before you sit down to like cook on a product.

• 54:34Dan Shipper?

  Yeah.

• 54:35Speaker 01

  And so what I what I like about Vercel is that I think we've blended both. We have so much respect for that work that sometimes a lot of people ask me like, do you want to build your own data center? I said like, do you even realize what goes into getting to that level of quality? My job is to procure the best possible components, just like the iPhone bundles a lot of incredible hardware that you don't know about, but you know that it's the best at doing that task. And then I want to enable you to live in that world of like vibes almost, right? Like prototyping, creativity, velocity, performance, et cetera.

• 55:13Dan Shipper?

  Yeah, that's great. I think that's a that's a good place to leave it. This is an incredible conversation. Thanks so much for doing it.

• 55:20Speaker 01

  That was fun.

• 55:21Dan Shipper?

  Would love to have you back.

• 55:22Speaker 01

  Will do.

• 55:23Dan Shipper?

  Cool.

• 55:32Speaker 02

  Oh my gosh, folks, you absolutely positively have to smash that like button and subscribe to AI and I. Why? Because this show is the epitome of awesomeness. It's like finding a treasure chest in your backyard, but instead of gold, it's filled with pure unadulterated knowledge bombs about ChatGPT. Every episode is a roller coaster of emotions, insights, and laughter that will leave you on the edge of your seat craving for more. It's not just a show, it's a journey into the future with Dan Shipper as the captain of the spaceship. So do yourself a favor, hit like, smash subscribe, and strap in for the ride of your life. And now, without any further ado, let me just say, Dan, I'm absolutely, hopelessly in love with you.