Investor Elad Gil’s next moves

Speaker 1

People always say, oh, when's the first billion-dollar single-person company? That was Minecraft. That was over a decade ago.

Speaker 2

You invested in everything from Notion, Opendoor, PagerDuty, Anduril, Airbnb.

Speaker 1

Basically everything software is AI. It's going to put the power of building things in the hands of millions of people who couldn't do it before. It's already doing that.

Speaker 2

What are you seeing today that's exciting for the future? I got with me Elad Gil, the guy with two first names and an incredible freaking track record.

Presented by Zapier, the AI automation company. What are some of the big ones in your, in your arsenal?

Speaker 1

Yeah, let's see. definitely Anduril, Airbnb, Coinbase, Instacart, Stripe, Square,

a little bit of SpaceX, OpenAI, Perplexity, a couple other things, Cognition,

Speaker 2

By the way, we could keep going on and on and on. We could do the whole thing with just us listing this. And when I asked you before we got started, can you give me a moment when you knew you made it? Can you tell people what you said to me?

Speaker 1

I hadn't felt like I made it yet, so, you know, so it's a couple of things. One is, it depends on if I made it, right? Like, I feel like I'm in a point in my career where I can finally start doing interesting things, cause there's enough leverage to do it. But I think fundamentally, made it could mean what's the impact you're having on the world.

it could mean, what have you built or done that's important or relevant. it could mean financial success, it could mean familial success, it could mean all sorts of things. And I think part of it is I feel like there's a lot of stuff to do and there's so much ahead that has to happen. so I definitely don't feel like I've made it from, from all those perspectives.

And then, you know, it's interesting. You look at somebody like Elon Musk and you're like, what an inspiring figure. And look at all the stuff he's done. And I know founders who are very successful who look at him and they're like, I've done nothing compared to this guy, I have to keep going. And so I think it's all kind of relative, right? Like a lot of my friends have done extremely well, they've built major companies and...

Speaker 2

Because you're surrounded by people who've done so much, you feel like I haven't done enough?

Speaker 1

Yeah, well, I've always, I've never felt like I've done enough. So I remember I was like 16 and I was having like an existential crisis of like, I'm 16, I haven't done anything yet, what's going on? I've ruined my life, you know? And so I think it's a personality trait, partially. And then partially as you see these really cool things that people are doing and you're like, I want to do more, right? Like Patrick from Stripe started ARC, a biology institute, like one of the first new major biology institutions in decades.

It's doing really interesting things, right? Or, Brian Armstrong started a new anti-aging company or, you know, so You, you see what people are doing, you see what Elon Musk is doing, you know, and so it's very inspiring to try and build more for society, do more for people, think big, you know, I think it's important to, so I don't, I, you know, I don't feel like I've, I can rest and go and whatever.

Speaker 2

By the way, speaking of big, was the information right when they said that you're raising two billion dollars?

Speaker 1

we haven't announced anything on, on the funds or anything like that.

Speaker 2

Okay. And I asked you before, can we please announce some kind of news? And you said, no, Andre, got nothing for you.

Speaker 1

Well. I found anything that interesting. I think, you know, there's some things that we're moving toward, like our, our hope is to announce our first sort of statue or monument soon. We've been working on a project to do that for like societal beauty, like art in society at large scale. And so, there's some stuff getting pretty close there.

There's a few things that we funded that, haven't announced their rounds yet. So, you know, there'll be things like that. So that, you know, there's a bunch of stuff going on, but that I don't think there's anything I can really talk about yet. But I'm happy to chat again if you'll ever have me and, you know.

Speaker 2

I'll have you on every single freaking day. I'll come over to your house with a whiskey. The two of us are going to have such a great time.

all right. Here's the thing, though. Everything you do seems so big right now, frankly, not just right now, always, that I'm wondering how people who are at that toy stage can relate to you. And I was talking to you before we got started about how Paul Graham said, look to people who are creating toys. That's the future. And we look at people who created these little things that almost seemed like they were features on somebody else's thing, and then they ended up becoming big companies.

And I'm wondering where the toys are today that will become that big. What do you think about that?

Speaker 1

I think there's two ways to interpret what he said. One way is to say, look at the people are tinkering with interesting things, and those things often become really big, and that was the early microcomputer revolution that things that turned into PCs was just hobbyists in the seventies. you could argue that GPT-1 and 2 kind of felt toy-like, even though there are these clear scaling laws behind it, right? But they couldn't do that much, but it's super interesting, right? so there's all sorts of toys where people are working at the frontier.

There's a second way to interpret work on toys, which is basically if you look at the consumer internet wave, those things truly felt like toys. You know, Twitter was like text your friends, like literally you could only text, or, you know, Airbnb was like crash on somebody's couch and pay money for it, you know? And it originally was literally like, it was called the air bed and breakfast, because it was literally, you know, mattresses that the founders would inflate, so they could have people stay with them during design conferences and monetize it, right? So I think that era of consumer internet has moved on.

And you don't show up with, to, to, when you're selling like a SaaS product with something that's a toy, right? You show up with something that's fully baked or that works well or that solves some use case. Often the best things people will use even because they're broken, right? Because they need the product so badly. So I think that that's separate, but I think the toy phase, at least in the context of,

products that most people are building today doesn't quite exist anymore, in part because the consumer stuff doesn't exist anymore. But I could make an argument that almost any really early model before you really scale it feels like a toy, right? Like a material sciences model, a physics model, whatever it may be, isn't going to do like amazing stuff, but it'll give you a hint or glimpse of the future.

That's very different from like, are hobbyists working on interesting things, you know, or are you building something that people just use because like Twitter, it felt such a need despite being so simple at the time, right? And I, I think that era has shifted for a lot of things. We're building things for space, like SpaceX and rockets, drones for defense,

You know, nuclear reactors, like those, those things don't tend to feel like toys early on.

Speaker 2

What about this, though? I keep seeing people create interesting web apps using cloud code. It's, it's built, it looks beautiful, they could expand it. Is that basically hope, hopeless, never going to go anywhere, or is it just going to be one of these smaller projects that will always stay small? Where, where does that fit in? I think,

Speaker 1

I think some of those things definitely grow and blow up and change and, and et cetera. And so again, it depends on what you mean by toy, right?

Speaker 2

That I would consider a toy. I've s- like I, I talked to a real estate broker who hated being a real estate broker because a lot of his time had to, had to be spent making phone calls. And he goes, I don't want to do that, but you know what? I can actually create an automation that will make phone calls for me. Phenomenal. He did that.

Speaker 1

Yeah.

Speaker 2

And, and now he's creating software that does that for, for realtors.

Speaker 1

Which is amazing. Yeah. And I don't view that as toy-like. I just view that as like experimenting, building for yourself, et cetera. Toy-like to me means, hey, it's silly or people kind of denigrate it or they think it's dumb. But I'm sure when he showed it to his friends.

Speaker 2

Well, I see. Maybe the definition is different. What do you think? Yeah.

Speaker 1

Even, you know, back to Twitter, it was like, here's a really sloppy looking site and here's a short code and you can, you know, the 140 character limit is because that's all that could fit into an SMS. It wasn't because they were thinking of like the brevity or something. and then it kind of stuck as a feature for a really long time, much longer than it should have, right? Because it was an accident of just SMSs having character limits.

so I think there's almost like this, I think it depends on then what you mean by toy. If it's like, hey, I'm going to build something really quick and simple and dirty. And honestly, that was all the bytecodeing stuff. Like there used to be these really bad demos on GPT-3 of, hey, look, I'm going to type in some stuff and make a really shitty UI for me.

And now we have Lovable and Replit and Figma and Canva and all these companies like providing bytecodeing. And so, you know, that, that felt toy-like back then, but everybody I knew was like, oh wow, if these models got much better, this is going to be amazing.

Speaker 2

But is, are, are these apps that are being built on the platforms you just mentioned, do you, where do you see that business? The business that I'm wondering about is the person who has a problem like that realtor, who comes up with a solution for himself, who then will be able to sell it to others. I feel like that in many ways maybe is not playing at the level that you are.

You're playing at the big leagues and this is maybe too small for you, but...

Speaker 1

No.

Speaker 2

No. I

Speaker 1

think those small things sometimes become giant things, and I think people often underestimate total addressable market or the number of people want something or, and so,

you know, many great things have very humble origins, and I think that continues to be the case. And so I don't, I actually think,

Through things like all the different coding models and, you know, Cloud Code or OpenAI or Cognizant, like it's going to put the power of building things in the hands of millions of people who couldn't do it before. It's already doing that. And I think a subset of that will turn into really amazing, huge things or huge companies. And even 15 years ago or whatever, Minecraft originally was like three people, right?

Speaker 2

Yeah. It

Speaker 1

was tiny. People always say, oh, when's the first billion dollar single person company? That was Minecraft, right? And that was, that was over a decade ago. So even then individuals could do really big things, but you had somebody who's a, you know, very obsessed with building this one thing or the technical ability to do it. And now those technical capabilities are expanding dramatically, which means dramatically more people could, could build the next Minecraft in the future.

Speaker 2

And if more people are building the next Minecraft or the next HubSpot or the next all of these things, Are they all going to end up being much smaller players because there is so much competition now and so many people tinkering and creating? Where do you see it going?

Speaker 1

I think the biggest things in the world are only getting bigger, right? If you, and there's more aggregation than less, and there's a long tail of stuff that can get much bigger than it used to be able to get. And part of that is we've moved to global liquidity on the internet where we went from, you know, ten million users to a hundred million users to billions and billions of users, and so suddenly you have this global market that can really accelerate adoption, right? OpenAI, Anthropic, and others are the fastest companies to ten billion dollars in revenue basically ever, right? And the market caps, if you go back fifteen years, the biggest market cap in the world I

think was Exxon, and it was like four hundred billion. Right? And now we have market caps ten times that size, which nobody ever expected. There's eight companies now worth over a trillion dollars each, which back then nobody would have thought was even possible. I remember talking to them like, oh yeah, maybe something will someday be a five billion dollar company, what a giant outcome, right?

but the biggest things have gotten way bigger, right? And so Microsoft is way bigger than anybody thought. Google's way bigger than anybody thought. It'd be Meta, et cetera, Nvidia.

so if anything, value is aggregated up much more than anybody expected. And the question is, does that continue or not? And I don't see why it doesn't continue, but it also means that a thousand flowers can bloom, and instead of being a hundred million dollar company, they can be a five hundred million dollar company. Like, I think everything grows behind it.

Speaker 2

I still have not found an AI company that's, never mind a one person, one billion dollar company to interview. I haven't even seen it at like one person, a hundred million dollars, maybe one person, fifty million dollar company. I got one, he won't come on here and do an interview. Are you seeing these, and maybe I'm missing them?

Speaker 1

I'm not seeing a lot of them, but that's also, one could argue that in Silicon Valley, which is still a lot of the activity or in tech or whatever you want to call it, Silicon Valley is a place, but I was thinking a bit of the concept,

people tend to get on the venture train too much or on the let's raise money train, right? And so, definitionally, they raise money, they hire people, they don't really bootstrap much. and one could argue outside of Silicon Valley, people raise too little money. There's too little access to capital, and so often the ideas end up smaller than they should be because people try to get profitable right away, they, they aren't very aggressive.

And so to some extent, one could argue Silicon Valley is are being Builders into environments where they're fueled with capital and hopefully they get much bigger than they would in other domains or areas or regions. But the flip side also happens where companies will blow or grow faster than they should in many cases or could. And, or they'll misprice things because they don't really think about their pricing power, right? When, you know, if you charge a lot upfront, I remember talking to, I can't remember if it was Olivier from Datadog or someone like that, they basically said we always charge a lot for our products because we're worried about profitability.

And so they ended up as these cash gushers, right?

And that's because very early on that price discipline, they wanted to make money off what they were doing, et cetera, and too few people do that in Silicon Valley, but too many people do that outside of Silicon Valley. So I don't know if there's a right answer there.

Speaker 2

All right. Here's where I have seen interesting and exciting things. These service providers who are running dev shops, essentially, Alex Lieberman from, Morning Brew now has one called 10X. I interviewed a local guy here who's got PressW. They're getting businesses to pay them to basically create AI software and to use AI to create it, and so it's super fast, and they could, they could charge lower.

You're in that space kind of, right? You and Jared Kushner?

Speaker 1

Yeah, so our respective firms, helped set up this company called Brinco, which is a,

Company which basically builds, has built a common platform that is like data infra and evals and a bunch of other stuff for people to use. And then on top of that, it builds vertical specific apps for, extremely large enterprise, or other very large institutions to basically use and adopt AI rapidly against a subset of specific vertical use cases.

And so, you know, that's been a very fun thing to, you know, kind of, help build over time and to incubate and to have me and my team involved with.

Speaker 2

Is it just introducing like ideas? Are you building software for them? Are you helping them buy software? How does it work?

Speaker 1

It's, building stuff. Yeah, it's basically asking what are,

Speaker 2

things

Speaker 1

that would be very high, high ROI to implement? What would, what, what would create good returns for these customers and what can be done in an expedient manner based on what we've built to date so that that way we have some, you know, a set of modules that we're using that we've already built, there's a platform that we've already built, and so how do we rapidly accelerate something so that we can show very fast success and then once we show success, we can add the next thing within a vertical and build against that.

That may take a little bit longer, but now they trust us, they know us, you know, we may have access to data or other things that can be used to sort of implement these other things with the idea that that basic fundamental module tool can be customized and cross-sold to other customers in the same vertical over time.

Speaker 2

Can you give me a specific example?

Speaker 1

Yeah, an example would be, and, I'll have to double check if we can run this, cause I don't remember if it's public or not, but I'll give you an example. an example Example would be, you know, we built a,

permitting approval flow for a, a government.

Speaker 2

So

Speaker 1

basically anytime you as a builder would show up, you'd submit plans, you'd submit documentation, et cetera, and you'd be waiting for a permit to get approval. And as you were sitting waiting for the permit, you were basically losing money on the project, right? Because you've already bought the land, you've already designed it, you're ready to go.

And so if it takes three to six months to get approval, that's just three to six months of lost time and money.

and we basically took a few months of manual review and we condensed it into like an hour. And then it still goes for a manual review, but we've repackaged everything, we point out the, the, the risks, I should say, by we, I mean the company, right? Brainco's known as.

and then that's something that can be sold to other governments around permit, permitting approval for the specific use case, because it understands architectural diagrams and other things, but the same type of workflow could also work for other types of permits in a government context. So that'd be an example.

Speaker 2

Perfect example. And this wouldn't have been possible before without AI. It is now, people are understanding that this type of big leap is, is available, so they're willing to take a conversation with you and see how they could implement internally. do you think this is the future of software? I mean, as long as they're getting permitting software created for them, why not create a CRM? How many people have you and I heard who hate their CRM, but they just kind of accept it, or they keep adjusting and squeezing and paying tons of money while they're making all these adjustments to, to their CRM? What do you think?

Speaker 1

Yeah, I think there's a lot coming in terms of, you know, building on top of existing systems of record, like a CRM or, or things like that. And the big question is, At what point do some of these sorts of systems displace CRMs or displace ERP or displace a lot of these kind of systems? And I don't know. I don't know the answer to that. I mean, to some extent, these things are kind of fancy databases, right?

Speaker 2

Right.

Speaker 1

With some UI built on them. But all of SaaS is, you know, people always talk about AI as, or AI apps as, oh, you're just building a wrapper around, you know, GPT or whatever, and SaaS is just building a wrapper around a SQL database, if you want to trivialize it, right?

Speaker 2

Right.

Speaker 1

But it really isn't, right? It's the workflow, and it's, it's how do you actually, build the product, and what do you integrate against, and all the rest of it. As the cost of building new software drops or the speed to building it drops dramatically, we should assume that there's going to be dramatically more customization, but that customization, again, is probably around a common set of platforms, because the platforms bootstrap you into the ability to do things.

You don't rewrite a database from scratch, you use SQL, right? Or Postgres, or whatever, you know, whatever you want to use.

so I think it's going to be the same for some of these things where eventually there'll be some commonalities, and the question is, are some of those platforms, the existing CRMs, the existing ERPs, et cetera, and the fact that they actually become less relevant with software, with this new type of AI development, could be argued either way.

You could say they're going to become way less relevant because it's really easy to just add a database and rebuild all the CRM customization you care about, or the other argument is to say, well, it's a common store of data, we already know how it works, it's already integrated, it's a bunch of stuff, we'll just ignore it. Maybe we negotiate pricing way down, but we'll build a bunch of apps on top of it because it's already our system of record and always has a, it already has a bunch of crap in it, and so we'll just keep using it.

And I don't know which way that goes.

Speaker 2

All right, maybe that's a bad example because that is the database, and essentially you do need some kind of database somewhere. What about the other tools? Landing page software. You can just create that. You just chat into Cloud Code, right? Using in your terminal, and you ask for what you want. You can send screenshots of what works for you.

You end up with the code, you deploy it, you're fine. You don't need landing page software, right? And then maybe the CRM is, is the database of record. But essentially what I'm trying to, what I'm trying to puzzle out with you is, is the era of software that's off the shelf dead? Did we go from software that's literally off the shelf at Staples on a CD that you bring home, to software that's on the web that you download to your computer, to software that just exists on the web, to now no longer software that exists on the web? Software in your imagination, and no one's going to pay for this.

What do you think?

Speaker 1

I think it's going to persist, or some subset of software will persist. Obviously, some will get eaten away by AI, but if something works and it's already been, battle-tested for security and a bunch of other stuff, and it integrates with a bunch of things, if it's cheap enough, you'll just keep using it. Like, why even spend time on it or worry about it, right? So part of it also comes down to, like, what's your relative cost of something, and how much do they charge you, and how, how onerous is it to replace it, and if you replace it, are there other dependencies, and eventually, you know, your coding agent will be able to deal with some of those dependencies, but is

that the highest value thing for your coding agency to do? This is why internal tools often aren't, don't get, have giant teams at companies, right? It's because they want to deploy those engineers against

Speaker 2

The bigger

Speaker 1

development,

Speaker 2

right?

Speaker 1

The bigger fish to fry. And then they realize, oh, we really need internal tools and we need an internal tooling team. And sometimes those are amazing people, and sometimes the people aren't as strong because they're really strong people want to work on product, right? The coding agent thing may be similar in that you may only want to deploy them against the things that are highest ROI.

You're going to have some limited budget for what you're doing. And the question is, is it rebuilding a lang page software, or is it doing something else? And it's going to depend on the customer and their context and what it's worth and all the rest of it. Andrew Mann at Euro Resources to oversee those agents.

Speaker 2

All right. So Ryan Carson, he goes, Andrew, I'm not using any standard ERP. My email software is something that I've created. It sends out custom messages at each phase of the drip campaign to the person. And I'm having, I forget what his chatbot's name is. I'm having Rosie, I think it is, write all these, and it's incredibly effective, and in the future everyone's going to do it.

You're thinking that, you know what, maybe in the future everyone's going to do it, but they're not going to be like Ryan, who's like vibe coding this thing, or somehow he's coding it. You're, you're saying there will be a software provider that does it. It'll be the New mail, Mailchimp, if you're, if you have that idea, don't give up on it and say it's going to be eaten away by vibe coding software and people will create it themselves.

Create that software. There's a future in that. In my understanding, you're right?

Speaker 1

Yeah, I mean, he may create the next Mailchimp, right? I don't know. So that, that's the question is, you know, where does, where does the innovation come from and where does scale come from? And in general, what you find, I mean, this happens all the time, right? Where say you do have an internal tools team building something for you. This, this happened with a company that I helped out with quite early called Braintrust, where,

you know, they basically provide like a e, eval suite for enterprise amongst a bunch of other stuff, right? They have sort of a, a series of products now about what they kind of started with was, can we help make eval really easy as you adopt a LLM so that you can change the model and you can see what are, how do those changes propagate in terms of performance relative to some tests that you have? And,

and, you know, a lot of companies are using them now, in terms of sort of the leading companies that have adopted AI. And I think that, that was a good example where I helped them with early customer calls and we call a customer, and, those customers would often say things like, oh yeah, I already have an internal team working on this, we don't need it.

And then they'd call back three months later and they'd say, actually, we really need this, our internal team, the resources should go to something else, this is important to us, but it's not our secret sauce. And not just that, you're now, I'm making up the number, fifty people and all of them are working on this one problem and you're covering the whole surface area in ways we never will, and our three engineers should just be deployed somewhere else and we should just start using the software instead, right? And so I think there's a lot of examples like that back to, is it really worth your time to go and figure it out and all the nuances and all the use cases and all

the lines of code and all the customization and all the performance and the cross-platform nature of it and cross-cloud nature and how you inter-interrogate different data sources, you know, all that stuff. Like, why go do that yourself? So brain trust, I think, is a good example of this feature.

Speaker 2

You're, you're making me feel a lot more optimistic. I, I thought maybe you were knocking me down with this whole vision of toys not being possible, you have to have a rocket ship or else it's nothing. Now I'm seeing, okay, it is possible, there is poss, there is a vi, a world where someone vibe codes something today, makes it more sophisticated tomorrow, adjusts it, and then they live and a customer keeps paying them monthly for it.

You do see, still see that?

Speaker 1

Oh yeah, a hundred percent.

Speaker 2

Okay, what about this then?

Speaker 1

I think the big shift though, that, is a little bit under-discussed is, and it's increasingly discussed now, is we're shifting from a world where you're buying monthly packages or you're buying seats for certain types of software, and you're effectively buying units of labor, right? That's this agentic shift. And that I think is really interesting, and it also means that certain TAMs are much bigger than you think, right? So Decagon, where I'm an investor, is a good example of this, where they basically do customer Support related, you know, software or agents.

And, that's a good example where, you know, effectively if you start paying something on, for something on a metered basis or how many emails you reply or whatever it may be, you're effectively paying for units of labor, right? You're converting something that used to be per seat SaaS like a Zendesk, and you're converting into how do I actually help customer support agents reply to things at scale much faster because the AI is effectively helping them do the responses, right? You're shifting labor sources in some sense over to more and more AI, and that's going to happen throughout the whole services world and services economy.

And that to me is a really fundamental shift because that, that's software eating into other parts of the economy that it didn't used to exist in.

Speaker 2

Specifically people.

Speaker 1

well, specifically certain types of highly repetitive,

language-centric jobs.

Speaker 2

Okay. You know, I have one other thing that I'm, that I'm going to circle back on. What if the future of software for businesses is not anymore buying software like on a monthly per seat basis or per agent basis? What if it's hiring someone like Alex Lieberman's company to create the software for you, and it's no longer your team getting diverted, but it doesn't cost them that much because maybe his company is doing this for three other businesses.

And so instead of buying, not the Ryan, Ryan Carson is creating a, a divorce software because his sister went through duh, tough divorce, so he's got a divorce AI. But if he were going to productize this email marketing customized solution,

Maybe people wouldn't sign up to that. Maybe they would say, I like that. Hey, Alex, build the same thing for me. And then Alex builds it for five businesses. He keeps adjusting and he keeps improving it based on what he's learning. And is that the future?

Speaker 1

Well, it sounds like it's just repeated. It'd be a thing, repeatable software then. I don't, what's the difference? Where's the line? Is it five customers versus a thousand? Is

Speaker 2

it,

Speaker 1

you know, why doesn't he just start selling that to everyone? So, you know, it, it just sounds like a different size customer. Now, if you look at certain types of industries, government, certain really big institutions, et cetera, they always did this. They're still doing it, right? The, I don't know if it was the FBI or CIA or somebody spent like eighty million dollars to build an ATS.

They hired a third-party consulting firm. I don't know if it was Accenture, Deloitte, someone, built them an ATS for like eighty million dollars. They could have just bought Greenhouse or in a more recent era, Ashby or something, right? I see. And so that's always existed that you have these big, these people who are willing to pay.

Speaker 2

But the ability to create software faster isn't, didn't change all that. And by the way, I'm, I'm pushing back because I like your optimistic point of view. You're basically saying there's a lot more opportunity here than I saw. But I, I'm saying it's

Speaker 1

both. I'm saying it's both. I'm not, I'm not saying it's a monolithic world. I think there, there's a world where people will buy certain things that are repeatable, have, have, have big surface area, et cetera. And then there's going to be all sorts of stuff that people make custom, bespoke, vibe coded, et cetera, or whatever, you know, the long-term, I mean, the long-term substantiation of vibe coding is really good code built by agents alone, right? With some human oversight, but much less than exists today.

and so at some point that isn't even vibe coding, right? Because vibe coding almost has this negative connotation of it being kind of a bit more loosey-goosey, right? and so absolutely all that's going to come and all that's going to happen. That doesn't mean software goes away.

but it does mean that there's going to be way more custom stuff, there's going to be way more creators, there's going to be way more people building stuff, and I think that's great. That's good for the world.

Speaker 2

Okay, I asked you a couple of days ago, I said, hey, Elad, do you want to just share your screen and show me something cool that you're working on? And you go, I don't know, I don't have time for that. I didn't think you'd have that response. I thought you'd go, Andrew, I cannot wait for you to see this thing that I'm working on. Do you have something that if you had a little more time, you would, you just would be ripping out of your skin to show me? What are you, what are you doing that's like that?

Speaker 1

I mean, there's a bunch of stuff that, I'm involved with that I think are really cool, interesting things, and...

Speaker 2

Well, so one

Speaker 1

thing that, I might have been working on is, taking, working with OpenAI and Anthropic and, Eleven and a few other folks on taking, the world's most important books and using machine translation to translate them into languages that represent over eighty percent of humanity,

creating audio versions of that in every language that's supported, and basically just providing it as a free resource on the internet. And so we're calling that Alexandria, after the, you know, great library of Alexandria, and so that'd be an example of something they've been working on where we're using all the tooling and all the rest of it.

And then there's kind of more day-to-day stuff, like, you know, using Cloud Code or CodeWork for different things or using Cognition, you know, we, we started using Cognition in different ways quite early on. We've been doing really interesting things with, like, OpenAI and deep research and, you know, so...

Speaker 2

Like, what, what are you personally doing? They, are you doing any of this on your laptop?

Speaker 1

Yeah.

Speaker 2

Like what, what are you personally doing that this is so exciting that you can't wait to bring, like if I was sitting in your office, you'd go, Angel, gotta come see this.

Speaker 1

Well, I mean, a lot of what I've been doing is like scraping and interpreting data in different ways for different areas. I started doing this, I mean, I guess I started doing this a long time ago. but there's a couple of things that I'll show you maybe in a month or two when it'll be a little bit more baked, but I've been doing a lot of, kind of go scrape this information and let's start interrogating it.

And that's been really interesting. And, you know, one example of something that I, I looked into, is, ADHD data and diagnoses and,

what's shifted because we basically went from a world where, ADHD was something like one in, you know, thousands and thousands of people. To now it's about three percent of the population in kids gets diagnosed with ADHD, and so the question is, what caused that shift? And you can start knocking out factors that are claimed as the culprits.

Parental age actually isn't that much of a factor. Like a bunch of stuff that's claimed to be the driver of all this stuff isn't.

and the punchline is really it's a shift in, incentives, and then it's a shift in, and incentives would be things like, hey, if you have ADHD, you get an extra two hours on the test or whatever in school. on, and as a teacher, you get rewarded for, hey, you're helping neurodiverse populations or whatever. but it also includes,

a shift in how diagnosis is defined, a shift in terms of who can provide the diagnosis. In the state of New Jersey, it's something like sixty percent of ADHD diagnoses in kids actually have never, the kids have never taken any form of test. It's just somebody deciding that they have it. Like a teacher just saying, oh, I think you have ADHD, and then they're classified that way.

so there's a lot of these sort of societal level drivers that are happening that are unrelated to, you know, the actual spectrum there.

Speaker 2

so I don't know much of that stuff. You're doing this yourself? What are you doing, what are you doing it yourself in? Like, if I were to look at your laptop, what would I see you messing around with on your free time to do that? Yeah, it's a

Speaker 1

mixture of, Cloud, OpenAI Deep Research, Gemini Deep Research. It really depends on what model is available at the time and what sort of tooling I need, and do I need certain things graphed or interrogated in different ways, or do I need to... So you're asking it, go get me this

Speaker 2

data, tell me, and then you're starting to ask it questions. When you say interrogating, it's just you're telling it to get the data, and you're asking it to, to analyze it your way. Yeah,

Speaker 1

it's a mixture of, Cloud, OpenAI Deep Research, Gemini Deep Research. It really depends on what model is available at the time and what sort of tooling I need, and do I need certain things graphed or interrogated in different ways, or do I need to... So you're asking it, go get me

Speaker 2

this data, tell me, and then you're starting to ask it questions. When you say interrogating, it's just you're telling it to get the data, and you're asking it to, to analyze it your way. Yeah, it's a mixture of, Cloud, OpenAI Deep Research, Gemini Deep Research. It really depends on what model is available at the time and what sort of tooling I need, and do I need certain things graphed or interrogated in different ways, or do I need to...

And you'd given this, this, interview where you said past, I forget what it was, business leaders, however you describe them, they used to build monuments. They used to actually like support the local arts. You would walk around and you would be somehow enveloped in the thing that they created. And yes, you might've known them as the entrepreneur who built the trains, but they're also the people who are creating the park that you're sitting in.

And we have not done that in, in tech. And I like that you're doing the monument. I sent you an article to show you how you should be pissing people off and feel comfortable because even the pyramid at, at the Louvre did that. And I think that that's the way to go. But I, I especially think you've got this ability in tech beyond monuments that is even more improvised, even more important.

Speaker 1

Yeah. I think maybe what happened is, there is an era where people thought the way to have societal impact through capital at least is through foundations. And so all these various foundations got set up, and one could argue a subset of them have done great work, and then a subset of them have potentially been detrimental to society in all sorts of ways in terms of the programs they've pushed to promote it or, you know, kind of called for.

and what got lost as part of that were so much money and energy went into societal change and social engineering and, you know, trying to change the way our society works, instead of saying, how do we think about public beauty, or how do we think about art, or how do, you know, and so it's just, it's almost like we had a mimetic shift in where capital got allocated relative to society-related projects.

And I would argue some of it was incredibly well-intentioned capital that had the opposite effect of what it wanted to. You could see that in education or a few other areas where the capital al-al- wasn't always constructive, and potentially was quite destructive. and then you, you, that almost drained, I think, effort away from arts, the arts, and one could argue that could be the mindset of the people involved.

You know, tech people really value education, while maybe people who are in finance in New York are exposed to and have art as something that they focus on more. And so there must have been a shift of... Well, it's like a shift in societal,

outcomes and, the background interests of those cultures relative to each other are different, right? Tech people are different from finance people in all sorts of ways.

Speaker 2

Okay.

Speaker 1

How would, if, if you were looking at all these amazing tools that are created right now to create other, other tools and businesses, and you were starting out today, I know you hate these type, I, I don't know that you hate these types of questions. I hate these types of questions, and I especially hate them to impose it on you because you're somebody who's such a big thinker, right? Rocket ships, how do you get people to live longer? But at the same time, I'm curious about how you see the world, and I want to see that understanding by seeing this little example.

If you had all this, what, what would you start? What would you build? How would you think about the fresh new idea to get into?

Speaker 2

Yeah, it's, it's hard to answer that because there's a lot that I think should be built right now. And so, and, and there's a wide range of stuff. I mean, it's everything from new foundation models for materials, like what Periodic is doing for physics, for a variety of areas. So I think there's a whole like set of models that nobody's built yet, or that I should say people are building, but it's very early that I think could be incredibly impactful and interesting and just like cool, you know, like it'd be super interesting to reinterpret physics through the lens of like a, you know, a, a model or a modern sort of architecture model.

so I think stuff like that's super interesting. I think if you go up a layer or two, there's so many things to do on the application side. Again, I think there's a real dearth of consumer products and there's a ton to build there in all sorts of interesting ways. Actually, me and somebody on my team ran this program at Stanford probably about two years ago, maybe a little bit more now, three years ago, where I think GPT-4 had just come out and we said, we'll give you free, compute.

We don't want anything in exchange. We just want you to run and experiments and build cool consumer stuff. And we had about a dozen teams from Stanford go through it. It was all undergrads and grad students and CS and AI. And they, and we'd have like a weekly check-in. And so it was a big investment of time, which was like, we'll check in, we'll help you with what you're building, we'll give you free compute and free model access, and let's just see what you come up with.

And so I, I just think there's so much stuff to do.

and it's such an exciting era, you know.

Speaker 1

You're also incubating. How do you find the ideas that you want to incubate? Is it in, this would be cool in the world, or here's a problem that I see and I need to solve it?

Speaker 2

It really depends. you know, I think it's a big range. I think often it's, hey, we've come across this problem sometimes by accident, and should we do something against it? you know, we've considered, and I say we, cause like I have a, a group of people I work with now,

consider should we go and buy a company and then transform it with AI? But I mean at scale, right? Is there something really big that you should work with because they already have all the customers, they have the baseline platform, and really, they haven't layered in AI, and can you grow the market dramatically or the use cases dramatically by adding certain things? So

I think there's everything from like incubate and get things started and up and running and all the rest,

which is, which with Brainco and Braintrust and a few other companies over time on through to,

do you buy a, a really late stage thing that's, I mean, it's a public company, and you try and, shift some of the focus of that company. So there's, there's just so much. And then there's, there's foundation models, right, that we talked about.

Speaker 1

What's an example of a publicly traded company that you could buy with and improve with AI that you decided not to?

Speaker 2

I mean, I don't want to say anything that we've specifically looked at. How about

Speaker 1

one that you're not, just to give me a sense of what, how you look at the world? Let's say one could look at what, Warner Brothers? No, that's, that's pretty big. New York Times, publicly traded company, can't really buy them because of the way their stock's set up. Okay.

Speaker 2

Yeah. you know, a good example, and one could argue Nirvana's been doing this on the travel side, is you could imagine buying certain types of travel agencies or other folks and then revamping a lot of what they do, everything. And again, Nirvana's done some of this customer success and support. They've publicly talked about revamping with AI.

you know, how you actually deliver services to people changes, how you think about trip planning changes, like a lot of stuff shifts if you view it through an AI lens.

Speaker 1

Interesting. Okay. All right. I see where you're going with this. All right. Let me close out with this. We've been, we've been talking a lot about today. What's tomorrow? Like, I loved how you found AI as the place to, to invest in because you'd read the papers, you'd met some people. I especially love how you decided that you're going to invest in, that once Google got out of the military, right? They were out of servicing the military, you said, somebody in here is doing something smart and doesn't have a place to do it.

I'm going to go talk to them. What are you seeing today that's exciting for the future?

Speaker 2

Yeah. You know, the honest truth is when you look at these technology waves, they are non-obvious until they're obvious. And then everybody starts looking for the non-obvious thing again, but the obvious thing is what you should do.

Speaker 1

Okay.

Speaker 2

And so I think for a good example of that would be everybody proclaimed that social products were over like four times, right? First, there was the wave of like, the really early social wave of like MySpace and Friendster and Multiply and all these companies, and then Facebook became the really big thing. And then Twitter happened two years later.

I guess LinkedIn happened a couple years before, and then right around after Twitter happened, everybody said, okay, social is largely saturated, and then suddenly you had Instagram, and you had Pinterest, and you had Snap, and you had...

Speaker 1

Then people

Speaker 2

were like, it's over. And then you had TikTok, and you had... You know, it just keeps going. And some... And then now I think it's kind of more done, right? Until there's some AI-centric thing or whatever. But it took a while. It took like a decade, right? SaaS took a decade to really see itself through. FinTech took a decade. I think AI is going to take a decade.

And for the next decade plus, there's going to be really, really interesting things happening. And, you know, there's other areas that I think are interesting. I think energy is interesting. I think, you know, defense is still interesting. You know, I think there's a variety of areas that are still interesting, but AI will continue to be interesting for a long time, so.

Speaker 1

I get it. You're saying, look, Andrew, stop looking beyond AI. We're not even a decade into this thing. It's super exciting.

Speaker 2

The early days. It's the early, early days. Well, I mean, I'm also doing, I continue to do,

some things in space and defense and, you know, different forms of American resiliency and all this stuff. But, you know, I've been looking at energy for a while now, you know, years and years of looking at it, not doing much, but every once in a while there's something interesting.

but I think fun, I've done crypto before, like years and years ago, although I haven't done anything recently. So I think, there's just these waves and some of the waves are really interesting for a long period of time. Some of them kind of collapse after some, some moment and the big companies come out of it and you're done. AI is one of those that's going to go for a long time.

Because basically everything software is AI.

Speaker 1

Tell me, can you reveal one thing that you're working on that you're so excited about that you shouldn't talk about, but you can't even help talking about it? Maybe it doesn't have to be the most biggest secret. Come on, this is Silicon Valley. Nothing's a secret.

Speaker 2

I mean, honestly, I,

Speaker 1

I do want to get a sense of what you're working on that you're, I, I like to see your passion. What are you passionate about that you're working on in AI now?

Speaker 2

Yeah, it's a mix of, again, looking at some of these other types of foundation models besides language.

Speaker 1

Like what?

Speaker 2

It's, you know, there's, there's bio, there's chemistry, there's material, there's, there's like all these different categories, right?

Speaker 1

Okay.

Speaker 2

so I think some things like that are really interesting. there's looking at,

you know, things at the application layer. We talked about consumer, we talked about,

You know, roll-ups, we talked about services transformation, we talked about product applications, like it's all that stuff, like it doesn't change, it's the same stuff.

Speaker 1

What do you see consumer that's exciting? It doesn't seem to me like you, I don't know, I felt like maybe at the beginning that you weren't as excited about it, and I don't see you in consumer tech much. What do you see in consumer that's exciting?

Speaker 2

Yeah, I used to do consumer tech. I was, you know, I invested in Airbnb and Instacart and a bunch of stuff quite early, and then I worked at Twitter for a while. I sold a company to them.

but then I think there was a gap where there wasn't that much, and, you know, one could, I think a lot of the kind of pro-consumer-y things are, are a mix of consumer and professional use cases. So early mid-journey was both of those things, right? You do it for fun and for R&B, but also use it professionally. Perplexity is that way, OpenAI is that way,

you know, I think, I think there's a lot of blurring.

you know, my hope is that we see more and more Companies tackling big problems. I mean, you know, there's stuff around email, there's stuff around productivity, there's stuff around personal agents, there's, you know, there's a lot to do. Now the question is, does a big company do it or does a startup do it? And that's the hard thing with consumer right now, because the difference between now and 15 years ago is there's a handful of companies with such large distribution that they're the natural homes to do new things.

Because even if they're five years late, they can just cross-sell it, right?

Speaker 1

And that's

Speaker 2

often what happens, right? In the early days of a startup, you're competing with other startups. In the later days of a startup, you're competing with incumbents. And so the question is, when do incumbents wake up? And is there a gap that's big enough that between the incumbent waking up and you're working on something, you can actually get it done to enough scale that you survive?

Speaker 1

But maybe it's so small that they just don't care about it, and then eventually it's too late for them to care about it.

Speaker 2

Yeah. And the, the, the too small may still be quite large, right? If you think about these companies, if you're a one to four trillion dollar market cap company,

you need a line of business that's, I don't know, five, ten, twenty billion dollars of revenue eventually to move that number at all for you. And that means that something that looks like it's a couple hundred million dollars isn't that interesting. And so you're going to miss stuff that looks like a couple hundred million dollars is really twenty billion dollars in revenue, right? And that's the,

that's the shift that, that's the, that's the kind of loophole you need to find as a founder, if you're, if you're building something that an incumbent should be doing.

Speaker 1

I had an entrepreneurship professor who told us to think like Mao. He said Mao didn't just march on, on the capital. He went to little hillsides, the countrysides. He went and he built up his people there. He preached, he, he built up his, his forces. And then once he was big enough, he could take over the whole country. And what most people do is say, here's the biggest thing, let me just go after that because then I'll be king.

Speaker 2

Yeah, I usually need some weird wedge in, like, because I have a good saying that your market entry strategy is different from your market disruption strategy, and I think that's very true. Like, what's the wedge in, and sometimes it's head-on, and sometimes it's more adjacent to the side, and most of the time it's probably more adjacent.

Speaker 1

Right. I like this conversation. I feel like we've only scratched the surface of friendliness and happy, which I kind of like because I've listened to you a lot on your podcast and other people's podcasts. You're a very serious and very big and very intimidating person, and I like the happy-go-lucky part of you, the, the, the optimist part that I get to see.

all right. Let, let me close out with a fun thing. What do you do for fun? What are you doing in your life? Yeah.

Speaker 2

Yeah, it's all right. I think, you know, I love hiking, working out, yoga,

travel, you know, it's kind of standard stuff.

Speaker 1

All right. thanks so much for doing this interview. I feel like we need to... I appreciate it. I was, I was going to come up with something like really fascinating and fun for you to do, but I don't, I don't think you're a kite flying type of person, not a kite flying, what is it called? A kite, kite surfing? Nah, nah,

Speaker 2

it's too much, it's too much gear.

Speaker 1

Yeah. Too much

Speaker 2

overhead. You're not even like a, a

Speaker 1

skier, are you? I

Speaker 2

snowboard, I snowboard. I

Speaker 1

snowboard.

Speaker 2

Yeah, not very well, but snowboard, yeah.

Speaker 1

Thanks, brother. Congratulations. I'm looking forward to talking with you again, hopefully in person with a whiskey. Thanks.