Guillermo Rauch: Why Great Companies are Defined by How Many Things They Say No To | E1069

The job of a good VC will be to find a handful of the best companies in the world. We don't need to fight every battle. And this actually matters more as the company becomes more mature. You don't always have to be first, you have to be right.

Guillermo, I'm so excited for this. As we said, I've wanted to make this happen for quite a while. So first, thank you so much for joining me today.

Yeah, great to be here. Thank you so much.

Not at all. But I would love to start. You started developing at 10. Can you just walk me through how did you first get into computers? And what were you building at 10?

By the time I was 10, I already had a few false starts with programming. I always tell people like, getting into software engineering is really, really hard and it takes a lot of trial and error to like really get into the groove. The first thing I ever did was creating websites for my passions and my interests when I was a kid. So at the time, I think it was like Dragon Ball Z and I was learning just enough HTML to be able to put up a website online. I would use a tool called FrontPage. You can say that my passion has always drawn me towards the web and publishing things online. And that's how the world has gotten to know me.

Same for me. I mean, 3,000 podcasts in, I think we can definitely say that's the same. You then dropped out of high school and moved to SF super young. How was this process? That's gotta be a defining process for you personally.

Yeah, that's a funny story because I would've never imagined that I would drop out of the high school that I spent so much blood, sweat, and tears getting into. I'm from Argentina, and there's two high schools in Argentina that are well known. They're public high schools with an entry exam, which acts like a contest. And there's thousands of signups, lots of kids that, you know, have this dream of getting into these high schools because they're so prestigious. And I really worked my ass off to get into one of the two. I entered number 10 out of, you know, everybody that signed up. And I had an amazing Amazing start. I was a diligent student, but then my passion for studying math and linguistics basically got into odds with my work that I was already doing online and my reputation for software engineering in the open source community. So basically, I could stay up all night during my early high school days. Like, I had these two lives. I was trying to be the good student and I was trying to also be the entrepreneur, freelance developer, open source contributor at night. And these things get more and more and more into conflict as the years went by. The high school had a pretty difficult entry exam, but then it got even harder as the years went by with like physics, chemistry, all these things. And I had less and less time and my work, my side hustles of open source and work were doing better as well. And I was also starting to help my parents financially with, I would like work online, get bounties for solving different like problems in like existing open source or private projects. So by the time I was almost ready to finish high school, one of the open source projects that I was developing at the time called MooTools, this you can call it like my 5 minutes of fame was I got accepted to become a core contributor to this project MooTools, which is quite foundational in the early days of JavaScript on the web. And the company in Switzerland picked it as their primary framework to build a very innovative UI at the time. And then as you can probably tell, like my software engineering journey really took me toward the world of front-end development, open source and all these things. So I had to make a very tough choice at the time. I'm in Argentina, I'm 17, this company from Switzerland is inviting me to do a kickoff for a project on site in Lausanne, Switzerland. And out here, I'm also trying to like, I had two subjects in high school that I needed to complete. One was Portuguese. For whatever reason, I could have chosen English as my supplemental subject. I chose Portuguese and then Argentinian history. And yeah, my path took me to I actually lean more towards work. I flew to Switzerland, then that company opened an office here in SF. And once, once I got to know the startup world here in San Francisco, it was just a one-way street. I left everything behind, moved here, and here I am now.

Can I ask, at this age, you're very young and you are at this prestigious high school and you could go to university and get the blue chip education that is so hailed. Were you nervous to eschew traditional education in favor of, slightly a much more entrepreneurial but less secure life in many ways.

It's really interesting. Yes and no. So the very first time I made money from the internet, I was 12 years old. The eBay of Latin America, Mercado Libre, had kicked off a revenue sharing program. It was called Mercado Socios. So like Mercado Associates. I was building all these websites that were actually driving traffic because my interests were either, you know, as you could imagine, other kids and other people's interests as well. And I figured out how to send them enough referrals that I remember at the time I made like 100 pesos. So that was the very first time I showed my mom that my skills could be monetized in some fashion. And over the years, the evidence accumulated that on the internet you could do amazing things. And by the time I think I was like 13 or 14, I was already contributing to my family's finances because, and now it's gone viral on Twitter. The Argentinian economy has always been in shambles and there's been this huge discrepancy between the purchasing power of the US dollar and the Argentinian peso that is subject to hyperinflation. So without getting too much into the weeds of the new presidential candidate that's making the news here in the US, people in Argentina have always succumbed to hyperinflation. I would bring in, I don't know, even like $20 from solving CSS bugs on a freelancing website. And that would mean the world to my parents to make a bill or make ends meet here and there, or even just like some help, some tailwind in whatever they needed to buy or were short on. So over the years, I helped them out more and more. So by the time I was 17, me saying, oh, by the way, you need to sign this paper for so I can leave the country for this one trip. Like it wasn't that strange. So on one hand, it was difficult to like abandon that really curated yellow brick road to traditional education. But on the other hand, over the years, like everything was like showing us that this path of software engineering and the internet could change our lives. So at the end of the day, even for, for my parents, it was easy.

Did you feel the weight of responsibility? It's a lot to be contributing financially at 13 or 14. Yes. That'd be really meaningful. Did you feel that weight?

Yeah, yeah, 100%. It's like the more money, more problems. Because I think the one time that it showed up the most was my revenue stream was strong, but unreliable. Like I would have this project and it would like make a lot of money all at once, but then I would have to like find the next one. So what it created was a certain sense of like, we really can't depend on this, but it's really nice when it's there. And it was also so much fun. That's the other thing, right? Like, there's this intersection between like what you love and what you can make money with. And for a lot of us, I think software engineering was that thing. And so overall, even though it came with its own stressors over the years, I think it was an amazing choice.

You should be very proud of yourself. That's pretty amazing to have had that ability to help your parents in that way.

It really is. It's definitely, it's definitely an unusual story. I also give a lot of credit to my parents because they really believed in this, right? Like, by all accounts, it's crazy, especially— and I really haven't told this story much because getting the grades that I had to get to get into that high school was also really difficult, time-consuming. It's a little bit like the SAT race here, I guess, although I never studied it in depth. But I do know that people like really go out of their way to like do supplemental education. You do like dry runs of older tests. 'cause you don't know what math puzzle they're gonna give you. So you have to go through like all the old tests to try to develop some sense of familiarity with what the test is gonna be. So it was this, the whole family had to almost bet on like, let's leave that behind, even though we worked so hard on it to do this other crazy thing.

Dude, what drives you? I spoke to many of your investors, your team members, and they said about the incredibly high bar that you have of yourself. What drives you from like earning money at 13 to pay for the family, to staying up late beyond belief while doing side jobs when you're a teenager to get into schools, to moving to SF on your own with no friends? What drives you? And has it always been the same?

Yeah, good question. I think it's been consistent in that there is a few personality traits. Like anytime I see something great come to fruition, I think I don't dwell as much on it. I'm just like thinking about like, what is the next thing that we can do? So it's really exciting to be able to unlock the next thing, which acts as a launchpad of the next thing, which acts as a launchpad of the next thing. Yeah, like there is all this that we can do and accomplish. And then there is another thing that that sets you up to do. And part of me coming here was it really expanded the horizon of what's possible. The access to capital, the access to the network, the access to frankly, a lot of people that have the same passions and interests. That's, I think, the big unlock for me. I felt that in my previous path, I just had a lot fewer people that I could relate to in terms of this obsession.

Can I ask a hard one? Do you think that decision would be the same today, given the state of SF back then being such a hub, such a great place, versus today where, forgetting all the political, it's just less of a hub? Let's put it in that way. It's just more decentralized. Do you think it would still be that needle mover, or do you think actually less so?

I think there's two components to it. I think part of me being from Argentina, the step up— and I don't really believe in the labels like third world, first world, whatever. But I wrote an article about this. It's, you can't forego efficiency. The step up from going from a very inefficient system to a very efficient one is very significant in your quality of life and what you what you're set up and enabled to accomplish. I notice this when I travel to countries where I have a great time because of all the novelty and all the places that I can visit. But 2 weeks in, I'm like, ah, I miss this efficiency and this efficiency and this efficiency of the new life that I have. Meaning in order to be in an environment constantly where I can execute at my best, that's really what I miss. To your point about decentralization, I don't think SF is the only environment in which people can now develop companies and ideas and things like that. In fact, I'm not even from the city of Buenos Aires. I'm from the outskirts of the city of Buenos Aires, which is even less, let's call it like efficient to give it like a good label. It was like very bare bones of a place where I grew up and there were a lot of safety issues and a lot of other things that we had to deal with. So I think there's something about the baseline of what you can equip a person with in terms of access to information, connections, wellbeing, things like that, I think the US is so much better in that sense. But in the specific place, I still think that SF has a significant advantage, but it's not the only place in which you can do things like this.

You speak about kind of the baseline there being tough. There's problems of safety, there's problems of basic infrastructure. I'd love to know your thoughts on immigrant founders. And why we have a disproportionate number that are successful and why you believe immigrant founders are more likely to be successful than not.

That's excellent because I truly believe that only immigrants can have a very in-depth appreciation for the unique qualities of the place that they immigrate into. That's my overarching hypothesis. And I do think that appreciation for what's unique, different, special awesome about a place or even a company is something that really empowers the individual. In fact, when I think about who would I recruit to be a part of this journey of building a startup, I really think that the people that appreciate what you're building and the mission even before they join the company are the ones that are most motivated and driven to make that company succeed. Let's think of a country as a super company. In fact, folks like to call the US an experiment because it's so young. It still is a system, right? So it's like this massive startup that draws people in, that there's still a high bar to even get in. First of all, like, it was really hard for me to even immigrate. So you really have to have this appreciation for what's already here and what that can set you up to do. So you called it infrastructure. And that starts tying it into more of the story of Vercel. And like, I really do believe that building the infrastructure on top of which people can do amazing things is what sets companies and countries apart. What you can do in your lifetime will be a function of the underlying infrastructure that you're given. And if you're not given that infrastructure, the best thing you can do is move to where you can find that.

Do you believe you have that in the US today with all the political changes?

I think so. And I think that despite the turmoil, there's something very compelling about having the right framework that sort of governs the, and sort of keeps the system in balance over long periods of time. So really what I'm betting on is not the present state of a local micro measurement that you could make about the system. I'm a bigger believer in the rules, checks and balances of the overarching system. Something that a lot of folks will point out about Argentina that's broken is the justice system. And I noticed that even though like things can be in the short term unjust, I think the system coalesces into fairness and justice much more frequently here than where I come from. So I think really you're not betting on like what you read on the news or on the front page of a newspaper on a given day. You're betting on how does the system evolve over time? And which system seems to be more likely to honor its foundations and its checks and balances. Those are the things that I look for when evaluating systems in general, let alone engineering systems, but also countries.

Can I ask you, if like immigrant founders have this higher propensity to be successful, I spoke to some of your team and they said that across the board, the talent within the company, and Jeff said this too, but the talent within the company is just consistently exceptionally high. And they asked in particular, What are some uncommon or unexpected signals that you see in the talent that you hire, given that you may hire people who society or like traditional tech companies may overlook from the Stanfords or the Harvard or the MITs?

I think a lot about our mission as working backwards from what outstanding products look like and work like, right? So you come to Vercel because you wanna build a great product. And you want our infrastructure and our tools to enable that. So I'm constantly thinking, okay, what does incredible look like and work backwards into the implementation? And that's why actually we posited the market that frontend is so important, even though it was overlooked for years and years and years. It goes back to like when I even started, my dad was like, why are you wasting time with like JavaScript? You should be learning hardcore backend languages and things like that. But in reality, to me, that's so upside down. It's so inverted because the thing that matters the most is the look and feel and the capability of the application, the device, and then how you make that happen. I couldn't care less as an end user, right? So let's bring that back to how I evaluate folks that want to join the company or companies that we acquire or folks that we reach out to is that what are they putting out into the world that is tangible? What can I use? What hyperlinks have you shared with the world about your creations? And this is a beautiful thing about the internet, right? Like, you could be anywhere in the world and a hyperlink travels to me within 100 milliseconds, especially with the tools and platforms that we're creating. So it really ends up being that you're communicating your capability through your creations. And so I start with that. Of course, it's not a silver bullet. There are folks that are more, they have more theoretical basis under which they contribute to the world. And I can't use my Swiss Army knife of trying to ascertain what products they've built and things like that. But that helps a lot. And I want to see more of that in the world.

It also solves the big problem of attribution, which is like when they're publishing personal projects, attribution is quite clear than when you're like, I was 5 years at brand name company and you're like, well, What did you do? Totally.

That's why I said it's not a silver bullet. Although, you know, there is something even about like your writing. Your writing could be that front end to your mind. So the ability for you to convey your thoughts, you know, do you have the discipline to actually follow through with your writing? Like, do you consistently write? Like, what is the quality with which you present yourself and your experience? I mean, your front end could even be the way that you talk. And the stories that you tell. I actually encourage a lot of folks to, with the attribution problem in particular, right? Like I was at Apple for 25 years. I can't even say what I worked on. And, but there's still a narrative of where did you move the needle? Is it measurable? How are you able to relate the business impact that you're in and express the business impact that a certain contribution you made to even maybe some internal of a distributed system or compiler, like how did that actually permeate? And if you can connect the dots all the way to how you made someone's experience better, because I think this is the other thing is at the end of this rainbow, there's either you're making some end user experience better, whether it's a visitor or a user of your app, or some internal process, like I made the life of a developer better. So you have to be able to connect the dots from technology to sentiment and even the way you talk about it.

Okay, I'm with you. But the trouble that I have, and I'm loving this conversation, but where I fuck up is on the front end when they're so good at selling and articulating that and they can say all the brilliant words and stories. Yes. And I'm taken in. And it turns out that the founder is much better at articulating the story than actually doing the work.

There's no doubt. Okay, so that's a great pushback. What I do sometimes is, I mean, this is probably an advantage that we have at Vercel, right? Like, you want to talk details? Let's get into the details, right? Like, let's go into the specific, down to the syscall of how you implement it and solve the certain problem. Let's talk about what cloud infrastructure you use. Let's talk about what options you weighed on the table. Let's hear your awareness about what vendors and what alternatives existed. If you, if you read a certain paper, let's get into that. What were the other, the other papers that you looked at? Like, I think being able to dive into like the absolute depth of the problem is, is something that everyone should be able to, to do. That doesn't mean that you have the complete texture But you have the ability to, I think really what you need is the conceptual understanding. You might not know exactly how like writing a custom module for the Linux kernel works, but you should be able to understand how the parts fit together if you're evaluating a systems engineer that's joining your company. That texture is what allows you to discern better whether someone is just telling you a good story, Or there's actually depth to the story.

Can I ask what have been your biggest mistakes on talent identification? Like there, I really can fall for a sales pitch.

I have an easy one. I have an easy one because I have betrayed that rule in the past. Sometimes I've placed more weight than I should have on this stellar linked list of awesome brands that you worked at. I did X at, let's just name random companies for the sake of it. Apple, Google, Amazon, Netflix. And you look at that and you're like, well, 4 companies in a row couldn't have been wrong on this candidate, right? And I'm not gonna just call it skepticism, but there has to be a lot of curiosity about what that candidate can bring to the table. And when I've overweighted the brands on the resume. And I think this for other folks, this could happen with universities, I think. I think I've never placed too much weight on that one in particular. I think that's one way where looking back, I think I could have done better with a few candidates. But yeah, I think at the end of the day, it comes back to can you evaluate the opportunity in its more objective and measurable merits? Than the approximations of merit, uh, if you can.

Okay, so I totally agree with you. I fucked up in that way too. I think it is the biggest mistake that first-time and young founders make, where they place more weight on external credentials because they view that as kind of a validatory source of, you know, what they maybe don't know what they're looking for. So my question to you is, I as a result favor second-time or serial entrepreneurs because I believe that there are so many things that you fuck up the first time that you will not to do the second and third, and I then might have to pay for those learnings. So I basically only like second and third time founders. Do you think I'm taking— Am I right or wrong?

No, I think you're right. I think the only risk there is that the pool could be constrained, but you don't have to get every single opportunity right. You just have to get a few great ones. And I think as a way of constraining the state space, the search space, I think that's a very good technique. I would, Add to that from my own personal experience, like someone that had an experience being an early member of a startup and was able to learn a lot about like, if their story is not just, oh, I had this idea and I happened to work there. But my story was with one of the earliest jobs that I had was I had seen decisions A, B, and C get made where I would've chosen the exact opposite. And I was like, okay, I wanna start something because this non-obvious decisions that I would've taken a different path, I can now take the right path. And it felt like that was almost like an unfair advantage in the marketplace. It really is all about finding whatever alpha you can across a number of dimensions, right? And to me, I was like, okay, like I wanna do hiring very differently. I wanna do product development very differently. I wanna just move faster, period. And I, I felt that even without even getting into the weeds of the technology, I would set up different foundations for success for what I would start. But yeah, I think to your point, I had my first startup, which had a moderately successful exit, and my second startup built on the learnings of the first startup. So it is, it is a good heuristic.

I totally agree that you said there are product development done differently. And we spoke about frontends earlier. I have this question always, which is like, is simple always better in product? It feels like we always just aim for the least number of clicks, the least number of buttons. Simple, always better, Guillermo?

No, and it's for the same reason I said I think the approach you described is good because it won't get you 100% of the great companies, but that's not your job. Your job is to even just find a few of the greatest companies, right? And I think that's also true for product development. Like the inspiration for me is like Google Search where like there is nothing to do except for an input and like everything is so simple and like the magic is in the implementation and there is all this unfair advantages of access to data that gets constantly refined and all that. If your job is, okay, I want to find a few of the greatest products that will be produced in this generation, I do think that a lot of those will be this deceptively simple things where the interface of the user is just magical and the company took on the burden, right? So one of my earliest investments was Auth0. And it was one of those things where I was incredibly skeptical and yet I was like, I'll do it. Like, this is all about asymmetric upside, right? But I remember the thing that I rooted myself in, and this is true for Stripe, which I didn't do, but I admired at the time, a simple API call that hides a tremendous amount of complexity behind. So I never want to deal with like MasterCard and Visa and like all these payment gateways and all this nonsense retries and work workflows. And the other side, you have like this awesome simplicity of like, here's the API call, here's a curl command that you can run to get started. So I do think that a lot of companies will follow that. Now, where it gets more complicated is the famous, like, what got you here, what gets you there, what got you to Series A or what got you to Series B. Is not necessarily what gets you from Series B to IPO. So I think we, and I mean like in the entire like tech industry, we can become so formulaic to our own detriment. I think in the early stages, a company's trying to find its wedge into the universe. I actually remember a fascinating conversation that I had with the original CEO of Snowflake. Whose point of view was that open source was overrated. And by the way, I'm super open source filled, Next.js, even before Next.js, I built Socket.IO, I contributed a lot to Node.js since like 0.1, Mongoose, the most popular ORM for MongoDB. So I'm like drinking the Kool-Aid of open source, I'm drunk on it. And I have this guy saying, well, you know what? Like to me, open source solves a concrete problem, which is market positioning. In developing market awareness. It solves a 0 to 1 problem, but open source doesn't necessarily solve the 1 to 1 million problem, right? And if you look around, this is certainly true for every successful open source company, right? Like the reason that GitLab, Mongo, Hashi, a lot of these companies are successful is not just because they did only open source. So I think it's really important to understand that we are operating in a sequencing. In the beginning of my career, I tended to look at like serious Seed A, B, C, D is so silly, like so arbitrary. But I do think we have to think more in terms of sequencing and there's a long journey ahead and you have to be very adapted at each step of the sequence.

What do you mean by sequencing? Sequencing by funding round, sequencing by stage of product market fit by—

The reason I like this A, B, C, and D things, they're arbitrary, but they help us anchor and they help give us a common language to evaluate and pressure test different frameworks. The simplicity of your product from 0 to 1 might not be the simplicity of your product from 1 to 2 and 2 to 3, or let's call it serious seed to A to B to C to D. This is very clear in that companies become multi-product over time. And it's really easy to look at AWS and say, whoa, what a cluster F they have going on there with like they have all these products and like they have all this complexity. Yeah, but like that's where they're at now. And certainly if you're trying to compete with them, you're not gonna replicate their approach. You're gonna try to bring a simplification to the market, but over time you have to reevaluate your priors because the challenge, the market, the growth, like things are changing over time. So you asked me the question of, is what I should be looking for only really simple products? And to me, the answer is very much stage dependent, very much market dependent. And there is no universal truth to the question.

Is that not the biggest challenge though, which is like bluntly, everyone struggles to retain simplicity with products over time and feature creep is so real. And now we also serve enterprise as well as SMB. And so we need this and this, and now we serve this and suddenly the product looks like fucking Workday.

We don't need to fight every battle. Ultimately, right? It goes back to like the job of a good VC will be to find 2 or 3 per fund, right? A handful of the best companies in the world. My job will be to create a few of the best products that I can bring to my category. I don't need to solve every single problem my customer has. I can partner, I can push solutions to user space. I can not enter every market. I can wait and hold, meaning whenever there is a temptation to solve a problem with urgency, sometimes you're better off waiting, right? Like, this is something that Apple does remarkably well because they don't react to every trend that emerges. They pick their battles. Yes, sometimes there is an opportunity that you have to catalyze at a given moment, But sometimes you're better off letting the truth emerge from all of the experiments that are constantly being run, and then you pick your solution. And this actually matters more as the company becomes more mature, because again, you don't always have to be first, you have to be right. And that's what I think companies over time optimize more around.

How do you pick your battles?

So number one, culturally, there's an expectation at Vercel that we will go deeper into what we consider to be complete or ready for a product than I think most people are willing to go. We spend a lot of time on what we would call the internal testing of a product before we feel it's ready to get to market. So setting up a really, really high bar for what gets to the customer's hands. And now this is really tricky because I think some people might confuse having a high bar from being— with being slow. And I really think this is the crux of the problem. I actually had an entrepreneur reach out the other day and he was saying like, the number one problem that I have is I wanna move really fast, but my customers are telling me that I'm breaking their stuff too frequently. So, my advice was you can find ways of reducing the blast radius of your experimentation such that when it's the time that you bring the product to everybody, you've accumulated enough evidence of success that you have an overwhelming amount of confidence in what you're bringing to the market. So it's easy to dismiss when like these keynotes happen and say like, this is the best photo we've ever made. And like you can dismiss some of those statements as just an effective product marketing team that has written out a few formulas, or you can actually earn that confidence yourself. And when you've done all of that pressure testing, sometimes I talk about this awesome video that I come back to on YouTube. I send it to a lot of people of Boeing bending the wings of the airplane inside the factory beyond the point that is actually realistically possible that a turbulence event will bend the wings. They will bend them so much that it looks like the plane has like molded into like a, a cylinder. But that gives them the confidence that, you know, you can do millions of flights a year and tolerate any storm and tolerate any weather event. And yet the wings will bend, but you've gone above and beyond to certify and sign off. This is the plane that I want, that I want people to fly and feel safe inside.

I get you. But when you have that level of validation of testing, it does just mean you can't ship tomorrow. Do you worry that you'll lose an inch on speed if you are? I didn't say this, your team said it and your investors said it, maybe a slight perfectionist when it comes to the level of quality that you need to ship.

I think that if you're rigorous in your process and you do it very frequently and you make it a part of the culture, you'd be surprised because like in a way your best outcome is that people are carrying it, carrying that idea and that approach in their work. I'm not the one that is like going after every single project and applying this rigorous testing. You know what I mean? I'm the one that is saying, this is the bar. These are some of the techniques. These are some of the stories. So I think there's a lot of power to storytelling, to sharing to people like, how do we even get here? What are the things that we've learned have worked well? How have we been successful in the past in moving fast and shipping with quality? I think if you don't have those stories that you can actually give people, like it almost sounds like, it sounds so contradictory that you could move fast and ship with high quality that if you cannot offer people those stories of like, this is how we did it for Next.js 1.0, or this is how we did it for when we launched the new deployment infrastructure, it almost sounds impossible.

Can I ask you a bit of a weird one? But I've been thinking more and more about the integration or the relationship between front end and AI. And I think more and more UI will matter less and less with the increasing prominence of AI, creating this kind of chasm between consumer and UI. Doesn't remove the importance of UX, but UI for sure. Do you agree? Or do you think I'm missing it?

I think UIs will change. I think you're right on a certain level, right? Like if we can go to a chatbot and that chatbot is again acting as a simplification of what used to be a very complex dashboard, let's say, of lots of menus and submenus and like you're like, where did I go to find this and that? But at the end of the day, the information has to be surfaced to you. I'll give you an example. I just saw this incredible approach to surfacing data with AI that you just interface with this system with natural language. And then the system is basically guiding you to where the data is, right? Like it's surfacing what otherwise would have been maybe like 20, 30 different clicks. Now the AI is just like serving on demand. With some of our products, we're basically going in that direction, right? Like what used to be dragging and dropping and like spending like hours or going into a text editor and like going through like all these autocompletions and like errors. And now it's just, you go into a UI that expects that you type in English. But our point of view is that now people will be creating a lot more of those UIs. It's a new tool in your toolbox. So our job is to actually empower you to create those new kinds of interfaces.

Do you worry about the commoditization of UI when you, as you said, have the explosion on the supply side of new user interfaces created, which means actually you lose the creativity, you create a discovery problem of sorts, and actually the explosion of supply means a reduction in, in price, so to speak?

I think it'll be the opposite because my, my hypothesis of how I look at the entire AI space right now is very simple. There are a lot of jobs to be done that people will have to perform no matter what, right? Like there is decisions that need to be made. There's data that needs to get visualized. There is communication that needs to be made. Like I need to send you an email. I need to make a phone call. Like a lot of those things won't go away, but how we do them is going to be profoundly transformed. So let's say that I want to create a new email client. I want to make my, like, basically what Superhuman did, I want to do again, right? Like, what's really fascinating about what's happening today is that when we were creating software over the past 10 years, part of our input into the design space, meaning part of what I thought was possible when conceiving a piece of software, didn't involve AI in the past, didn't involve the fact that we can have this reasoning machines that we can invoke on demand, call them the large language models or the AI as a service. Now that I have those, how profoundly different will my design be? So if I have to create the next Notion, the next Superhuman, the next Figma, my bet is that it certainly is gonna look completely different because before I would reach for what I would call like software 1.0 solutions. Now, what makes someone really good at product design, frankly, is that they looked at a lot of designs over their lifetime. They looked at a lot of data. They have a good instinct. It's almost like a good Go player. What made Lee Sedol a formidable adversary to AlphaGo is that there was this instinct, this pattern matching. But now it's almost like the board has shifted. What made you a good software 1.0 designer, it needs to be actualized. It's not that you're not going to be good at a software 2.0 design, but you need to say, okay, now Now when I sit down with my conceptually empty canvas, now I have this other set of tools that I can use to solve the problem. And it's exciting because startups don't have any priors. They don't have any legacy software in which they have to retrofit AI onto. So it's a great opportunity for incumbents potentially because they can now say, I added AI, ship it. And they can increase their TAM. They can say, I'm AI ready. But it's also a really scary situation to be in when someone can come in and produce a completely different design, if that makes sense.

Can I push back on you and say, I think, I think that's like a transitory phase. Like Miles Grimshaw said it on the show from Benchmark very well. He said Copilot's an incumbent strategy. And actually, you know, the things that you think we will need to do, that new marketing copy, that new accounts, that phone call that needs to be made actually won't need to be made. You'll say, I want this CAC to LTV across Facebook, Instagram, and Twitter. Here's $1,000, go do it. And there will be no decisions on where it's spent, which micro-influencer, and it'll just do it. And actually selling the work and not the tools is what the true transition will be. And incumbents will win in the intermediary.

I think I agree over a long enough timeline, but But that doesn't actually result in practical advice for what to do over the next 3 quarters or even couple years. I think the most successful innovations tend to meet the world where the world is. So when I think about the iPhone, I was actually recounting this story of my team that I found fascinating, which is that famously there were 2 concurrent experiments for what would become the operating system of the iPhone. IPod OS evolves and it was a fresh new code base. It was already on like mobile devices in the sense of like it was already being deployed to like smaller miniaturized hardware that was portable. And concurrently was the strategy of let's retrofit macOS to fit it into the iPhone. And obviously macOS being forked into iOS is a strategy that won. And it meant the world where it was. The first killer app was being able to to downsize websites and put them into a smaller screen and then find new evolutions within that, which became responsive design and so on and so forth. And then new native things happened within the context of that platform, namely new applications that weren't possible by just retrofitting, new applications that took advantage of the medium and new capabilities that were unique to the medium. But even fast forward to today, like 20 years later, We're still in that world of there's this hybrid of the DNA of what already existed with all of this new DNA of what's now possible because you're on a mobile device and they continue to co-evolve. I think this will be the co-evolution of AI and traditional software as well. But again, going to like what makes practical advice possible, I think a lot of those chat type interfaces will have to meet the customer where they are. If you say to the AI, please help me make an advertising that's going to be deployed onto X in Meta, in Instagram or Facebook and Instagram, it'll have to give you some UI as feedback of what's proposing back to you. And then you'll have to interface with the system further. So I think it's still all UIs all the way down. Now, the key magical part of this is that they are UIs that are unique to the AI problem space. And those UIs will definitely be different.

How do we think about great UI in an AI-first world versus not in an AI-first world? I've never thought about that before, but if we think about that where it's like it sells the work, it completes the, the project, and it delivers it back to you, is that a world of visual-first, chart-first, aesthetic beauty by data and data relayal versus simplicity and beauty. I'm just trying to understand, like, does it change the way we think about great UI?

One of my hypotheses is that we actually in some ways have to give people more UI. I'll explain why. So there's two things that I, two references that I give my teams a lot. One is Minority Report and Tom Cruise, you know, historically and like famously being in this AR interface of the future. Where in order to detect crime, he's in charge of the pre-crime forensics. He can predict crime and he gets all of this data in front of his visual cortex in this 3D space. And he's like, I'm going to zoom in here and get this data point and this data point, et cetera. Forget science fiction for a second. We don't have AR that works at scale yet and we're not Tom Cruise. Let's actually look at what's succeeding in the AI world today. We have Midjourney. Midjourney gives you this text interface, but as a result of your text prompt, gives you 4 choices of what you could possibly like. This is really interesting, right? Like, that's what I mean by it's actually giving you more UI, not less, because it's uncertain about what it is that you actually want. So it needs to give you more choices. This is very different from software 1.0, which is the world of determinism, the world of rule following, the world of predictable algorithms. You give me a form and I put A, B, and C, I give you result D 100% of the time. And if it's not D, someone gets paged because we monitor it, right? Now, Software 2.0, AI, I don't know if what I'm giving you, you're actually going to like. I don't even know if it's offensive. 'Cause like there is all this craziness that happens when like you give this AI that is like not supervised and you gave it a lot of data and you can't even comprehend the amount of data that it has. So you actually have to create UIs that tame the craziness of the machine. You have to create UIs that give the creator feedback. Another easy to dismiss thing about the brilliance of some of those products is that because they're giving you choices, they're now feeding data back into the system to make it better in the next iteration by once again relying on new kind of capabilities that are more in this realm of probability rather than certainty. So I think that's a very important departure is that now we're entering the realm of I can assist you in the creative process. Again, that means that you have to think about software differently.

My question to you, I love the book, you know, The Paradox of Choice. I believe that too many options make an enemy of us all. How do we think about kind of actually simple and telling users what they need versus this kind of explosion of options that any consumer can choose between one of 8? Fuck, is that really a better user experience?

I don't think it, I don't think it It depends on what stage of the problem-solving sort of workflow you're in, right? If it's in a very creative side of the process, I do think having more options is better. The other reference I mentioned, I like to give the Minority Report reference. I like to give the Rick Rubin reference of like his contribution to the world is telling the artist if they like something or not, right? Like he says in that interview, like, I'm not an expert in the specific music techniques. I don't know how to play an instrument. The feedback that I give to the artist is what's valuable. What I like and what I don't like is what's valuable. So if the tool is very much in the creative sort of stage, I do think having options to go through is really good because I was mentioning in my experience, what's made a designer of a certain piece of software or UI really good is just how much they've rejected over time. What makes a company good is how much they reject over time, how many things they say no to, how many attract— seemingly attractive on the surface ideas they rule out before they decide, yes, that's the one that goes to market. Yes, that's the one that earns the position of being in our product lineup. So it's really going through lots of iterations of yes and no that it gets you to the point where you can say confidently, this is what I like. So I do think that accelerating the iteration loop and turning down things could be really healthy provided that the trajectory is good. What really matters in these AI systems is that the system is learning when you're turning things down. Because to your point, I like the pushback because At the end of the day, the best assistant in the world will have rich context about what you already like and will over time propose better variations of the solution that tailor to your preferences and tailor to the context that you're in. But we can't be too absolutist in that process because otherwise we're just gonna give you garbage. And notice that a lot of the successful AI systems so far have been in the realm of being suggestive rather than authoritative. Copilot suggests a completion to your text. Gmail Smart Compose suggested what to reply to the email. Notion AI is saying I can go ahead and like complete or give you ideas or finish the bullet points for you. When it gets into the realm of authoritative, like agents, like I'm just going to let an agent go into the world and act on my behalf. Without supervision. We haven't seen a lot of products that are successful in that space.

What do you think it takes to make that transition to agent? And do you think we will?

I think we absolutely will, but it requires the close feedback loop with the person that that agent is acting on behalf of. It requires that the person is still in charge. The metaphor that I like to use is being the editor in the newsroom and you're having the agents bring you the ideas and you're saying, nope, go back to the drawing board. This is the feedback. Nope, this doesn't make the cut. And you're the one that's also setting the creative direction. This week we have to go after AI safety. That's a hot topic that people are interested in. Next week we have to go into this. We have to go into that. So you're still in charge. And this is why, you know, ultimately this is the healthiest version of an AI future after all, right? Because we don't want an AI future that inverses and puts us into the— we are the agent, the AI is calling the shots. That's what people actually get scared about. So I very much like this idea of AI in the assistance of the creative process and AI just making processes more efficient.

I don't, I don't because it plays into incumbents, I feel. Who have the distribution, who have the existing product suite and can service that incredibly well. And as a venture investor looking for value creation, it makes startups with limited data pools, limited moats fucking impossible to fund. That's my problem.

I'll give you, I'll give you a good example, right? Like incumbents are in a very problematic position when, as I mentioned earlier, the new AI alternative is just really disruptive. To their historical approach to solving the problem. The best example would be I have a competitor to Microsoft Word coming to market, right? And instead of having to build, I don't know if you remember the infamous bad design or I don't know if it was, it would end up having to design, but like Word shipped with a really thick toolbar that exposed every option that used to be nested within menus. They made it visual. So as a result, like 30% of the screen real estate was tools, copy, edit, highlight, background, foreground. And I remember a lot of the reactions at the time was like, holy crap, like I didn't even know you had all these options, Word. The way that a company like that was looking at the problem of making the best processor, best possible word processor was very additive. It meant it was a more is more approach to the world. What does this mean? That adding more utilities gets you promoted. Adding another way of changing the color of the text or even adding more colors. Now look at Notion, for example, it doesn't actually even give you every color on the spectrum. It doesn't even let you input a custom hexadecimal. The designers of Notion said there is 8 or 16 colors that mostly work well for the purpose of writing this Wiki-style documents and whatnot. So they actually said, we're gonna do less. We're gonna have a lot fewer text editing and text formatting options. And that's gonna give people agility. That's gonna make them feel more focused on what they're writing. Like, I don't know what assumptions they had, but like, I'm making some up. Now, there's an extreme version of this, which is that, can I actually not implement any of that? Because AI exists now. And my Software 1.0 simplification strategy, which was creating fewer options or creating options that are more general, pales in comparison to an AI that can actually just like do exactly what you want, even without having the options. Like I actually didn't software engineer any of those utilities and icons and blocks and whatever. This is completely hypothetical. I'm not saying there is such a product that can be conceived. But what I'm saying is that the entry players can win because they do a lot less and because it's so disruptive that the incumbent has to say, holy crap, we have to delete everything? I feel so invested. I crafted every icon. I crafted every menu. I crafted every piece of documentation for how to use this. I recorded all the videos that taught you how to use those. So I think that's the generational disruption that happens in software. That is extremely problematic for incumbents.

I agree, I agree normally, but I feel this set of incumbents are better than ever, stronger than ever, and faster than ever. And we look at your— yeah, I think Notion would be considered an incumbent now. Let's put them in that category. But your Notions of the world, your Adobes of the world, have moved faster than ever on integrating AI very well and actually disregarded a lot of, I'm sure, existing product strategy, I'm sure existing roadmap, in favor of moving fast, getting shit done, and have killed a generation of companies in, in between. I'm like shit. We didn't— everyone was like comparing it to mobile. Well, we had Apple, BlackBerry, which was an accidental pager that worked, and Nokia, which was a failed division of a Swedish, you know, Scandinavian company, and, you know, a division in a corporate. This is fucking FAANG. Like, they're gonna come and kill you.

I do think that, uh, a lot of these companies can be underestimated. Uh, one thing I'll, I'll give some kudos to Microsoft for is that they told the company they had to work and focus and, and have a look toward AI. AI much earlier than a lot of other people. So they have years of strategically thinking in the direction of AI. Now, a lot of these companies have the right strategy, the right foresight, the right internal talking points, the right investments, and they still get disrupted because the new way of doing things is so radically different that initially they don't even look at the alternatives as a competitor. The best example would be potentially Midjourney, to Photoshop or to something like that. Like, I'm actually very impressed with Adobe's incremental addition of AI, like Firefly and tool, or like you select and whatever. It seems high quality, well considered. It gets the job done. Like it's strictly in a measurable basis, like better. But there's a chance that like, again, there's such a platform shift towards now the interface is go to Midjourney where all of the other tools just don't exist. They literally don't exist. Like all of the drag and drop and magic wand and selection tool and color switcher, people just go and spend their time elsewhere. I think this is how desktop software sort of became less important than mobile Apple apps when that transition happened. It's not that the right tactical determination was stop improving the desktop software, delete the desktop software. It was that, and this is what Meta ended up doing well. It was that the user minutes and the attention and the growth was going to go to a different way of expressing their mission in the case of Meta, which was connect the world, they needed to go and almost start over. You needed to go to mobile and start over because everything that you built for desktop, it still exists to this day, very much like AM and FM radio still exist, but the growth is elsewhere. The growth is in this new approach. You can have an incumbent that does that really well, but historically, Most don't, which is when the platform shifts and they need to do things very, very differently.

Can I ask, thinking about needing to do things very, very differently, uh, and then we will move into a quickfire because I could talk to you all day, but business models have not changed at all in many, many years, largely on a per-seat basis. Does AI like solidify the shift away from per-seat pricing and entirely change the business model of software?

I really like what's happening with AI because I think it's an acceleration of what was already happening with cloud. If you look at Vercel, Vercel offers you two very powerful things for your organization. Number one is the most obvious and the most visceral to a lot of developers, which is that you give us your frontend project, Next.js, Nuxt, whatever, and we host it. We give you infrastructure to scale it autonomously. And that's traditionally a consumption, you pay for what you use business model, like Snowflake. But what Vercel also gives you is the iteration velocity and agility, very much like what Google Docs or Figma give you, which is like, now I can collaborate really fast with hyperlinks and I can share around my entire organization what everybody's working on. It's almost like a Jira type thing. My maybe narrative violation is that businesses that only do one half of the equation are going to become less and less popular over time. Because when I buy software, I expect to buy a comprehensive platform that solves business problems. And solving business problems is never about just procuring a very specific material, a cog. I want this to do more for me. I want it to be like an operating system. For my organization, especially as you hit scale. You're like, oh, I'm using Vercel for this little thing here to like host this, but I'm using Azure here and Google here and give me the foundation to level up my product development organization. That's what most of my customers actually want. So the way that we've built against that is that we've done a combination of like SaaS that is by seat. And purchasing platform capabilities with infrastructure that grows when your visitors use the software. I think AI from the outset is doing this because AI is about getting some workflow or some tool, but it's also spending GPU cycles on very expensive outsourced intelligence, so to speak. And the more I use it, the more it costs, right? If I use a lot of GPT-4, it doesn't matter that you're charging me like $20, $30 a month. You have to somehow model the fact that I'm piggybacking on your infrastructure for intelligence a lot. So I think we're going to see a lot more of these hybrid models where you give me a baseline of utility, but I can also burst to utilize more of what you can automate for me, if that makes sense.

Dude, you said about open there, and you're the master of open source. You have been for years and years and years. The question is, though, if you just say there about buying that platform, that validated product set, who wins in the next 10 years in terms of AI development? Is it open or closed systems? Because closed systems are the ones that can deliver that packaged Microsoft tick bundle with a ribbon, and closed and open is like, ah, I mean, it's great in many ways. But we both know it's not the packaged product that Microsoft is.

Yeah, I need more data to be able to make an accurate prediction, which is a total cop-out.

You're not a VC then. If you were a VC, you'd say, I have no data, but I have a thesis.

I can tell you the frame— I'm a frameworks guy. So like my whole life I've been all about creating frameworks that give people the right foundations to scale. So I can tell you what my framework is. With this problem. When Kubernetes was coming out, there were a lot of alternatives, some proprietary, some open source. What ended up winning was what every company in the world decided was the standard on top of which they were going to build an ecosystem. This happened again with React. So React is the most conversation that developers will have today, almost like tabs versus spaces. People love to talk about if React is difficult, if it's easy, if it re-renders too much, if it doesn't re-render too much, if it wastes cycles because of the virtual DOM, if it doesn't. But React won the hearts and minds of the ecosystem. In fact, a lot of people, there's an internal meme in the community called like React Brain. It makes you think a certain way. And detractors call, accuse other folks of having React brain because once you get used to the tool, it's even hard to adopt other tools. In a way, even going further back than Kubernetes, it's almost like having Linux brain. When I learned Linux, like even though it could have been inferior in some benchmark to the proprietary alternative, over time, the ecosystem value And all of the people that got Linux brain was so powerful that the proprietary alternatives all collapsed one after the other after the other. And the most famous capitulation is Azure is a Linux-first cloud as opposed to a Windows Server-first cloud, right? The proprietary alternative. So one part of my framework is saying Llama becomes Linux. Right now, Llama is not as good as GPT-4, not even close. But with the ecosystem saying, this is what we're going to bet on. This is what we're going to throw all of our AI researchers. This is where we're going to throw all our hardware, AI chip accelerator budgets. This is where we're going to throw in all our software acceleration budgets. This is where we're going to throw all our documentation. This is where we're going to throw all the user space frameworks like LlamaIndex and LangChain and this and that. Like now you have this entire community that's saying we're going to bet on this thing becoming better. But the counter thesis to that is that, and this is the famous Jeff Bezos quote and why AWS got so far ahead of the competition, even though the competition knew full well that cloud was a strategic place to go, is that even a 2-year advantage Lethal, meaning like 2 years in tech is very hard to overcome. 5 years in tech, it's just exponential. 10 years, like good luck catching up to that company if they got, for whatever reason, you ignore their advantage for 10 years. This has certainly been true in our space. When we were betting on dynamic frontend rendering technology, a lot of folks were betting on static. I feel like a lot of folks have now said like, oh, like Vercel, you're growing so fast, you did this and that. And like, they think like it's some act of magic, but going back, we just were willing to like bet on what was a little less popular, especially among VCs in the Valley at a few crucial points. So yeah, like I can't tell you like Llama will win or GPT-4 will win because I have evidence in favor of both, but I can tell you that Every day we're getting more data and it's one of the most fascinating open questions to me right now.

I totally agree. I also love that in terms of going against the popular narrative. I always ask companies like, you know, with the problem that you're solving, what do you believe that no one else believes that you have?

Correct. Most important thing.

Yeah, I really think it is. Listen, I want to move into a quickfire round. So I say a short statement and you give me your immediate thoughts. Does that sound okay?

Fun.

Let's do it. Okay. So is 99% of the cash going into AI companies today going to go to zero? False. Wow.

Why? My prediction is just like what happened with Web 2.0, where you have, because of the platform shift toward mobile and social, you have countless successful IPOs from that generation. You have the Ubers, you have the Airbnbs, you have the Facebooks. We're gonna see the exact same thing happen with AI. I can't tell you exactly what the ratio will be, but I, I would be willing to bet that 20% of investments will be productive ones. Now productive means companies that then get merged and acquired. Like we might buy an AI company. That doesn't mean 20% will be unicorns, but I think we will see a lot of positive ROI.

I hope so. Okay, tell me, what's your biggest lessons from angel investing? You're secretly one of the most successful angel investors investors, I think, in the Valley. What's your biggest lessons from doing so?

I think people underestimate just how much their own time goes into thinking about important problems that need to be solved, but you just don't have the bandwidth to solve them. If I look back on some of the most interesting investments that I've ever made, there are things that I would've loved to do myself. I just didn't have the time and I wasn't in the place. Maybe I was working on another project, maybe I was working at a different company to actually execute on those. So just to give you some examples, I invested in this company called Scale AI. I really badly wanted to work on a product like Scale AI. I don't know if I would've been the person to build it. And I think I got really lucky by, you know, I chose the right horse in that particular space. But I do think that your own experiences are very validating, especially I think this is what's making a lot of founders, CEOs successful in angel investing is that the things that you see, the things that you perceive, and this is also why I'm so bullish on AI as well. Like there's so many AI products I want our company to, to buy. There's so many AI products that I want the world to benefit from. There's so many inefficiencies, there's so much repetition that's happening. There's this mismatch between supply and demand, and that's how a lot of great investments happen.

So I worry when I think I could do that. Like, you know, I saw a company the other day and I was like, I'm better positioned to do this than the founders. Do you not feel that it's a requirement when investing in a company that the founder's uniquely positioned to the extent that no one else is?

The founder needs to be uniquely positioned in a number of dimensions, uniquely willing to go through the grind. Uniquely positioned to either have the background or learn really fast what it takes to solve the problem. That's one that's kind of messed up about angel investing. Like, you can lose a lot of deals if you just look for expertise sometimes. And this is also true for my hiring philosophy. It's about the slope. It's about how fast people can learn. Here's, here's a universal truth is that ultimately it's all about the market., right? It's all about people's willingness to buy a certain thing that determines winners and losers. That's why I wouldn't underestimate your own ability to judge what it is that you want to buy, what it is that you ultimately need. Now, you might be actually really bad at judging the solution, so you have to be extremely open-minded. I made a quick comment earlier that The thing where I got lucky with Auth0 is that I just didn't feel like 100% confident about their solution, frankly. And if the founders are listening, they're going to hate me. I felt at the time, holy shit, outsourcing auth to a startup? How does that make sense from a chicken and egg point of view? How does it make sense that your homes and your companies door and the lock, you outsource to what, the lowest bidder, like a startup that has 3 people. So I was like, okay, it's kind of crazy that you want to turn auth into a microservice. But at the same time, I do know that implementing auth is a freaking, it's freaking hell. So this is the other advice I would give people is that unfortunately, people overestimate their own capacity to solve in an excellent way. What do I mean by this? Every company I would advise, every startup that would start, I used to set up a chat server in IRC. I would set up an IRC server so that people could collaborate. I knew the right problem to be solved. I knew that in order for software engineers to be more productive and collaborate with the rest of the company, they needed a chat medium to collaborate with others. I had the wrong solution. The solution was not to set up an IRC server. Very few people know this, but when Slack was coming up, a few competitors to Slack were actually giving you IRC as a service with some UI. So the market knew that there was a great opportunity around collaboration with chat for organizations, but the spectrum of solutions is incredibly bizarre.. Some involved IRC hosting, some involved a hybrid of Slack with IRC. Slack even for a minute had an IRC proxy to help people move from the old world to the new world, and then they discontinued that. It's the solution that I think becomes kind of like the tricky thing to, to like, where do you place your bet? But it's fascinating to like look back on those examples because they have so many where like I remember when Matt from WordPress, I sold my company to WordPress, said we have to install Slack and deprecate IRC. And at the time I was like, whoa, are we really going to trust this company with all of our communication? Same visceral reaction that I had with my own investment in Auth0. Are we going to trust this company with all of our X? So you can almost see a pattern there when you know that the problem is so painful, but your only hesitation is whether you can offload it to somebody, there might be a huge opportunity there.

I love Mullenweg. What a fucking hero. I mean, what a dude. Listen, final one, Guillermo. I've so enjoyed this. Final one. If everything works out with Vercel, where are we in 10 years' time?

The way we talk about this is we still live in a world where there are a lot of bad products.— there are a lot of bad experiences that you have on it on a given day. Our dream and our vision is that Vercel has raised the bar of every experience that people have with software, with applications, with products. It has to permeate all the way down to the average person doesn't have applications they hate, processes that bog them down. Why? Because we empowered every creator, every developer to fulfill their creative dreams and we gave them the tools to turn those dreams into the best products that they can. And I think AI will play a huge role in this. I think part of what we're doing now is creating a bigger funnel, bringing this technology into more and more people and putting the creative process in charge.

Guillermo, listen, I've loved it. I mean, the breadth of this conversation from infrastructure in Argentina to the future business model of artificial intelligence, credit to both of us on this one. This was real breadth. I've loved it. Thank you so much for doing it, and you've been fantastic.

It was fun. Thank you so much.