Investing Billions - E207: Can AI Replace Your VC Analyst?

Episode Date: September 1, 2025

What happens when AI lets five people build what used to take fifty? Can you scale to eight figures in revenue without ever touching a “Series A treadmill”? In this episode, I talk with Henry Shi, co-founder of Super.com and creator of the Lean AI Leaderboard, about seedstrapping (raising once, then reaching escape velocity), outcome-based pricing, and a new, non-dilutive way to finance lean, profitable startups. We also get into how Henry “vibe-coded” an AI VC tool over a weekend, why survival rates should improve in the lean-AI era, and what founder traits show up again and again among these ultra-efficient companies.

You recently vibe-coded an AIVC tool. We used AI, my girlfriend and I, to build this tool that allows you to upload a PDF, the DIY will do deep analysis, competitive research, webcalling, and generate an investment memo. And you can also upload a forecast and Excel model, and I can do all the situational analysis, planning forecasting, and generate a term sheet automatically. It's incredible how someone with no engineering experience, never taken a CS class, doesn't know what a terminal is, doesn't know what a HTML is, is able to build this tool entirely end-to-end, front-end, backend, chat interface, web search analysis, API calls,

GitHub, GitHub actions, resell deployed, end-to-end deployed, all within a weekend. And what's the use case that you're building around? Is it to completely replace VC analyst? You get way more detailed analysis, the market competitive trends analysis. You get forecast built in. So it just reduces the process. and human biases to make it a much more transparent, fair, and efficient process. Because going back again to first principles, now with AI, if you can be a lean team, grow,

hit your forecast, and be profitable or not die, then I want to fund you on my support. You found it super.com and you just had a milestone. Tell me about where super.com is today. Started that company, 2016, grew up from zero to 200, 250 employees, over 200 million annual revenue and profitable in over 50 million users. You also run a cool leaderboard. It's called Lean AI Leaderboard. Tell me more about this Lean AI movement.

After I run the company for eight, nine years, after a point where we're hundreds of millions of revenue, profitable, growing, I decided to step back to the board and give other leaders a chance to shine and take the company for it. So since transitioning to the board at the end of last year, I've been spending a lot of time, helping founders, doing Andrew investing, sharing content, dabbling AI. And it's been a great journey. And in that process, beginning of this year, 2025, I saw a lot of people tweet on Twitter and LinkedIn about how these companies with so few people are getting to $10, $20, $50 million in AR and beyond.

And I thought there must be more than just these handful of companies like cursor, mid-journey, etc. So I decided to create this leaderboard to track all the super lean hypergrowth companies that post-AI that are growing extremely quickly with very small teams in an official place called Lean AI Leaderboard. So I built this leaderboard, launched it, and it just took off, had millions of impressions across social and the website. And now it's this sort of way to track these lean AI companies growing extremely quickly with very few people and a high revenue and oftentimes profitably. So it's incredible to see this new trend. Double-click on why AI is allowing these crazy high-growth companies that are grown on a very lean basis. Is there also a revenue and a cost side to the equation, or is it just simply less engineers?

That's a great question. I think it's a couple of reasons why you're seeing this new trend and it's a confluence of factors. One is it's easier and ever to start a company with these AI tools, coding, co-palets, customer service, marketing, etc. You're seeing companies instead of hiring people, they can just automate and augment themselves. So a small, lean, crack team can stay nimble, move quickly. get a lot more done. So you're seeing that on the cost side. Whereas before, you had to raise a lot of money to build your product to go to market. Now these teams can ship quickly and get to market extremely quickly. On the demand side, you're seeing there's also a higher willingness to

pay. Everyone is sort of interested in AI, interested in trying, AI, adopting AI, they're getting pressure from the board, any pressure from the markets. So there's a much higher willingness to pay from the customer side. And oftentimes, you're seeing higher pricing and higher AOVs because people are pricing based on outcome, not on necessarily software receipts. And for example, it's much harder to get to 10 million AR if you're selling a SaaS seat for $5, $10 a month. But if you're selling an outcome, you can sell the same thing for hundreds or thousands of dollars. So higher OV, higher demand, willingness to pay, and lower cost basis.

And you're seeing this effect of lean AI company scaling so quickly and oftentimes profitably. Give me an example of one or two outcomes that AI companies are pricing based on versus kind of this traditional SaaS model. So a good example is, I think, the company called Growth X, so that's a sort of animal service company, but it's incredible because they have 70% margins and it's AM power growth.

They were able to scale from zero to, I believe, 7.2 million AR within a year and a half and 13 people. And that's an example where if you're just selling a SaaS tool for tracking your growth in analytics or something, right you couldn't charge that much and grow up so quickly but because they're charging based on outcome they're charging i believe five 10 000 or more a month for clients but they're delivering into outcomes and they're doing able to do it efficiently and leanly with AI automation across entire back office and keep 70% plus margins tell me about the ideal capital structure for a very

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accounted for 77% of capital raised in the first half of 2022. And these billion dollar funds needs to own 15% of 21 billion dollar companies to just return 3x. but there were only 22 public companies with a 10 billion plus market cap. So the question becomes, how do you return these mega funds? Well, these investors have to chase more and more extreme outlier outcomes. But being a unicorn isn't enough. You have to be a decarcorn and beyond. But realistically, most companies are not decker coins.

So venture capital chasing these extreme outliers and makes it such that everyone is forced to talk these large narratives, hire these massive teams, target these massive competitive teams. And that's just not the right vehicle for most companies and founders. And for the lean-eye companies, right, if you can be five people doing 10, 20 million an hour year, you're probably doing better off than most venture-backed founders. You have way more control, way less dilution, way more possible outcomes. And by the way, these are not lifestyle companies, right? These are not lifestyle founders who are spending an hour, working an hour a day.

in Dubai or somewhere, but there are hard working founders who are driven, who are business more motivated, but who recognize that there's a better way to start built and fund these companies. So I've been planning a lot of different ways to try to support these founders where I think the fundamental premise is, if you can grow and you can hit milestones and you can stay alive, which is very much possible now with AI, right, you should get funding. And maybe it's not traditional equity. Maybe it's rev share, roads, or something else, but it's much less It's not equity, it's non-diluted, it's not a recourse, not loan, and it gives a founder optionality while still giving investors a good return, faster DPIs, and you don't have to

wait 10 years for an exit, you can get, you can recycle the capital right away. So happy to that I'm more into it, but these are some of the things I'm piloting to explore new ways of funding and seed strapping companies. So you popularized this term called seat strapping. What is seat strapping? So seat trapping is a interesting alternative way. of building a single company where you raise a sizable nice seed round and then you get to escape velocity from there on. So you no longer need to raise consecutive rounds of funding like

pre-seed c-chures a, B, C, D, etc. And there's lots of benefits on why c strapping I think is the ideal model for many lean AI hypergrowth scaling companies. And we can go into the differences in terms of revenue, founder dilution, ownership control, founder liquidity, etc, etc. But I think there's a lot benefit now with lean AI that you can see strap companies and you're seeing a lot of founders do this. Give me a sense for what kind of company should be using seat strapping strategy. I think almost all the lean-eye company should consider that because the good part of seat strapping is you don't need to dip into your own pockets. So you can start the company without having to dip into your own savings. But you don't have to constantly dilute yourself

and chase investors and be on the VC treadmill. You can own control, grow over time, get more liquidity throughout the process and maybe even buy out some investors over time early on. So it's a benefit in many ways. In terms of the companies, I think if you're a lean AI a native company, it's a great bet. If you're in consumer PLG, I think that's also using a lot of companies successfully do that. If you're AI-in-able services company like Rothex, I mean, you can raise money, but it's a C-Srapings a great way to go. And I would say pretty much most companies, except for maybe certain industries like deep tech or heavy enterprise sales where the AI sales agents aren't quite good enough yet. But as the capabilities of AI's AI agents get

better and better, I think we'll see the appeal of C's dropping for more and more companies. You recently vibe coded an AIVC tool. So first of all, what's your definition of vibe coding? And then tell me a little bit about this tool. Okay. So basically, we used AI, my girlfriend and I, to build this tool that allows you to upload a PDF, the DIY will do deep analysis, competitive research, webcalling, and generate an investment memo. And you can also upload a forecast and Excel model. And I can do all the situational analysis, planning forecasting,

and generate a term sheet automatically. So that's sort of what we built. And it's incredibly, it's incredible how someone with no engineering experience, never taken a CS class, doesn't know what a terminal is, doesn't know what a HTML is, is able to build this tool entirely end-to-end, front-end, backend, chat interface, web search analysis, API calls, GitHub, GitHub Actions, Reselle deployed, Enten deployed, all within a weekend.

So truly using just clot code and clot, and that's, I think, the best definition of vibe-coding. So you can see here, all of these interface, everything was built just within a weekend and entirely vibe-coded. And what's the use case that you're building around? Is it to completely replace VC analysts? As I'm exploring this new way of seedstrapping and supporting founders, I'm getting a lot of inbound and requests and companies. And I've always felt that the traditional venture investing, especially in the earlier

city, it was very vibes-based, right? Like, do I think this company is going to check all the boxes and become a Deckercoin? And frankly, how am I supposed to know? And the sort of the irony is the investors, they get a thousand pitches. They reject 999 of them. They probably don't even look at half of them. And they're all trying to chase this. the two companies in the area that matter, right?

But the irony is that the sum of the revenue of the 99 that rejected is definitely higher than the one to try to pick. So my thought is, how do you analyze an approach and systematically analyze a 999 on founders who have been good and great companies, but in a way that's scalable, automated, and unbiased, and transparent, and you can do this much more effectively now with AI. You get way more detailed analysis of the market competitive trends analysis. You get forecast built in. And so it just reduces the process and human biases to make it a sort of much more transparent, fair, and efficient process.

Because going back again, the first principles, now with AI, if you can be a lean team, grow, hit your forecast, and be profitable or not die, then I want to fund you and want to support you. It reminds me a little bit of Dan Gross, who's obviously a prolific AI investor. He had this project called Pioneer, which tried to find these founders all over the world that maybe didn't fit the. Stanford, Harvard, you know, MBA or computer science background, but had built something special. There's a lot more of these than people think. And the reason more people aren't aware of them is because it becomes reflexive. If they don't get VC funded, you know, they essentially never actualize. Exactly, right? And so much of it is pattern matching and sort of trying to predict Deckercoin outcomes at the earlier stages. And I'm just not sure that's, I mean, maybe it's

possible if you're the top sort of 10, 20 firms. But for everyone else, I think it's so hard. There's so much sort of selection and self-selection and versus supporting the 999 founders who collectively, that that's a ton of revenue. I think on the leaderboard you'll see here. Obviously, a lot of them have raised funding, but a lot of them haven't. And collectively, it's, you know, 3.460 billion, right? And some of the best, highest revenue companies have not raised as a venture, like Telegram, you know, billion revenue, not funded, mid-jury, $500 million plus, $0 funding, $1,000 to fund. Surge AI, a billion dollars, zero funding.

And so I think you're seeing a lot of these founders that are realizing that's actually a better way to build an incredibly massive, successful businesses. Have you ever Googled yourself and found your home address, phone number, or other sensitive information online? That's not an accident. Data brokers collect and sell your personal information, leading in spam, identity theft, and loss of control over your personal data. And with data breaches up over 70% recent years, the issue is only getting worse.

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guarantee. Once again, that's ingogny.com slash invest. I-N-C-O-G-N-I dot com slash invest. You can also find the link in the show notes for this episode. Your data belongs to you. Take it back with Incogny. Double-click a little bit on the founders of these seat-strapped businesses or these highly scalable non-V-C-backed companies. What are some characteristics that you see behind the founders themselves? I don't know if you see the meme of the high IQ and low-a-key. in a lot of times you see these incredibly successful repeat founders who built businesses before the traditional venture fund a way and they realized there's a better way um so for example at a founder who reached out to me uh his last company was 400 million a r right 400 million

and he's starting a new company like hey hey henry i came across your seed strapping thing and i'm starting a new company but i don't want to do a traditional ycc or equity funding what other methods are there because these founders they've get it they've been through the journey they've gone to the venture capital grind and they realize that actually there's better ways to build a company, especially if we're a repeat founder. Or you have sometimes the final found as another side of the end, which is, you know, fortunately, they're maybe international, then you go to Harvard, Stanford, didn't check the box, Tam's a little small or something, whatever reason venture isn't the right instrument. They're like, sure, this is a great

alternative. And then you have folks in the middle, like the first time YC founder, right? So who are like, hey, this sounds interesting. This is cool. It's non-dilutive. It's, there's no recourse. But I don't know, it's different and I should just do a safe because Gary Tan told me to do a safe. So you're kind of seeing this distribution. But my hope is over time, as you highlight more of these stories, one of these incredible founders building incredible business and outcomes that more people are going to shift to the right of the tail and realize that there's better ways and it's not just a single way to play the game. If you had to guess, would you see Y.C. starting to play in this realm?

Or would you see kind of a new AI native incubator that's focused on. on these seat strapping strategy. That's a question. I don't know if traditional YC will get into this sort of round because their whole model is based on marking up and fundraising and sort of having the prepping the companies for a demo day and getting marked higher valuations and fundraising and traditional venture route. And actually very good at it because if you're an incumbent

and you're the best at that type of model, you know, why should you change? It's been very profitable for them and they're great. And in fact, it's been awesome. Whereas here, I think it's a bit of like innovative dilemma or alternative model where at first it looks different. It's maybe sort of people don't get it. But over time, as AI and the capabilities become better and better, I think you're going to see more and more founders opt into this new model. And I'm not sure if it's an incubator, accelerator, or funding model or something else. My hope is that there will be more people who are doing this.

So it's not just me who's thinking about investing in different ways, but we can inspire other investors to think about funding. the 999 companies who are not the two a year that become Deckercoins and hopefully that can translate to more founder, more diverse founders, more transparent funding and more much more fair, efficient process. So that's how my hope is more people can do this and sort of realize that it's also a great economic opportunity as well, because if you can get DPI's right away, your IRAs are extremely high. You don't need to wait 10 years for an exit or a liquidity event. you can get DPI's right away, and then you can recycle that capital to invest in more and more companies. If you've been considering future straightings, now might be the time to take a closer look.

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And so the latest thinking and iteration is basically it's a non-daluing. of non-recourse capital, so it's not equity, there's no control, there's no debt. And all founders do is they give me a deck of the company, which I use my AIVC analysis tool to do a deep research on, generates their landscape market mapping memo, and then a 15-month forecast. And what I would offer is based on a forecast, basically the idea is like, if you can hit your forecast, which you said, by the way, the founder chooses, if you can hit your forecast and generate growth and not die, then I want to give you.

opportunity to get funded. So for example, so right now, it's structured as a bit of a sort of a line of credit, which is, it's not debt, but it's up to the founder how much they want to draw. So let's just use round numbers. I suppose I do analysis on the forecast and I say, hey, you know, I want to give you a million dollars that you can draw in over four tranches. And it's 250K per quarter based on hitting your quarterly forecast. So again, right, the founder sets the forecast. And so long as you can hit it, you can unlock more tranche of the capital. but it's up to the founder how much they want to draw, if any. So it's up to them.

If you want to draw all million or maybe only $250K or half of it, it's up to them. And that actually encourages founders to be more disciplined about capital. And the structure is around 5 to 10% of revenue and it's capped over 2 to 5 years at 2 to 3x. So it's not cheap like a bank loan, but it's way faster and it's way cheaper than equity, especially, you know, precede funding, which is you're giving up 20% of company for oftentimes a million dollars, right? So it's capital for the investor, but it's high DPIs right away. And it's an option for the founder depending on if they want to use it. And sometimes what you see is you see founders say, oh, look, I raised a massive seed round,

you know, five million dollars and I didn't even have to touch any of it, right? Even though they're flexing about it, but it's actually, that's actually kind of dumb because you just diluted yourself 20 plus percent and you didn't need the money. So why did you do that? So the thing here is help encourage founders to be disciplined with the funding. Give investors a way to invest in these companies, whether they become a unicorn or not. It doesn't really matter if you can hit targets, grow, and build a great business. I want to fund you. And it's essentially a free option for the founder.

There's no cost. If you don't want to use it, great. If you want to use it, that's awesome too. But my hope is that by giving founders a fair, transparent way to get capital as they hit their targets, it encourages great financial discipline, encourages people to actually set realistic targets. And whether they use my money or not is somewhat irrelevant, because I would have still helped you build a better company if you can hit your forecast and actually build a great business.

And this is based on the idea that they're already revenue generating and already you could scale up from some revenue number. Yeah, right now, I'm focusing on companies with some former revenue, but the goal in the future is to have all types of companies because, again, going to the first principles, right? The reason why fundraising is hard and annoying is because there's a fundamental disconnect between a founder's projections and investors belief in their projections. Because if you think about it, if the investors actually believe the founders' projections, then you should

invest in every single company because they're always up into the right. If you actually believe it, you should invest in every company. But the reality is investors don't. And the other the thing makes things worse, founders are incentivized to sort of juice the numbers because they're all taught, oh, you have to talk about a Deckercorn, unicorn major outcome where else investors aren't interested. Well, that's going back because investors are sort of these mega funds are looking for these mega exits and only 20 plus percent of Deco coins. Right. So both sides, people are sort of incentivized to sort of not allow on the financials or projections. So the thing here is if you can just get the founder to set their own projections that they believe in and align the capital

to their own projections, then you should hopefully align them to and end up with great sort of businesses that if you can hit projections are going to be good investments. So to answer question, over time, I do hope to support companies pre-revenue as well, because so long as you can make a forecast and hit those forecasts, then I want to fund you because that's as simple it should be. If you can hit forecast and build a great business, then you should get funding. Whether you need or not separate, but you should at least get the opportunity for that. To play devil's advocate, historically, I think something like three out of four startups did not give back one X their money at the series A, not even at the seat, but at the series A.

How do you make that work with a two to three X return at that stage if you're capping yourself? That's a good question. And so one is I think the property of success will be much higher now with AI and these leading AI methodologies because it's easier and cheaper than ever to start a company. Before you had to raise a lot of money, hire a bunch of people, spend a lot of time on R&D, get the product to market. And by the time you have this large team, you have hired Series A, for example, 20, 30, 50 people. In those cases, yeah, you might actually.

die. You might actually run off a cliff because you have this high burn and you can't grow revenue fast enough or whatever. You have all this fixed costs of people, labor, etc. You might actually die. But now with the lean AI approach, you can get to that level of skill with a very small team and a bunch of AI tools. You don't need to hire a lot of engineers. You don't even need to know how to code sometimes. And by keeping being lean, nimble and scrappy, you have auctionality and flexibility. You're not going to fall off a cliff because you're for five people. you can always adapt. You can always pull back here, spend less or more in marketing,

but you don't have this large fixed cost base where suddenly you run out of money and you fall off a cliff. So one is the cost is a lot lower. You have more control and flexibility and you're more nimble. So you can adapt quicker and you can adjust. So I think that's why I fundamentally believe so rival rates are going to go up. And what I often look for in these founders is, as you know, a lot of times companies die not because of competition, but because.

of suicide because the founders give up, they get bored, they do something else. So really it's more about the resilience of the founder and their sort of persistence and and sort of conviction versus like, oh, we're going to overspend, hire too many people and run out money. It's more about them just maybe giving up as a failure mode. So that's one on the on the cost and problem of success. And then on the return side, oftentimes you'll see, right, these are because oftentimes you see companies that are great companies who are now zombie companies because they're not going fast enough and they don't have an exit opportunity.

The pref stack is way too high. The early investors get washed out. So I think you also see a lot of reasons why investors don't run into capital. It's not because these are not good companies. It's just it didn't fit the venture model. And when you're stuck as a sort of zombie company, zombie unicorn company, right, everybody's stuck and you're not getting your money. Whereas if you're doing it on a ruptured royalty basis, it doesn't really matter if you get stuck

at 20, 30 million AAR, right? Because I'm getting a revenue split of that. So I can still get my return and my money and I don't need to pray or depend on an exit. And oftentimes, as you know, these exits, the company has to be growing really fit quickly and the mark has to be right. And the sort of multiples have to line up. So if you're investing on a high multiple and the multiples don't catch up, yeah, you're underwater. But here, you're investing and they're growing. If you're investing in making money, even if they get stuck and the multiples are low, it doesn't really matter because I can recycle the capital through the rupture royalty and then reinvest in more companies. I like a lot of parts of these concepts. I like the seat strapping. I like the term they

popularized. I like the higher return of capital. I worry about the misalignment where you're being paid off of revenue and you're also getting capped at the upside. That invariably misaligns you with the founder, not in every way, but in certain ways. And I think if founders went about just raising less money and not chasing the headlines, the $5 million seed round, like you mentioned, there could be more co-centric circles that work better for the founder and the GP. For sure, right? And that's why after many iterations, I've structured it more like a line of credit. So it's up to the founder how much they want to take. Right. So they don't need to use all of it. Whereas for a traditional equity, if you get a final seat, that's all of it. Even if you don't

need it, that's all of it on your capital. You can't give it back. Whereas here, It's meant to be structured in a way that's founder's option. So, yeah, if they want the headline and some big number because they feel psychologically better, that's cool. But you don't actually need to use all of it. And oftentimes, I've actually paired this with traditional equity funding. I suppose they want to raise a two mill round. They raise a million equity and a million in this new format.

And so that way, they don't need to over doubt themselves. And instead of doing a two on 20, right? Maybe now it's a one on 20 and another one on this revsure model. and that's only 5% dilution, right? So that's oftentimes good to pair it as well. I just looked up the numbers, roughly 50 to 70% of seed stage companies fail to get to Series A historically. You believe there will be much lower death rates or much higher survival rates for startups.

What percentage of these lean AI startups do you think will make it as defined by being ongoing businesses in the future? That's a question. I think the metric you mentioned is failed to raise a series A. Right. But I think that is maybe no longer the definition of success or failure, whether you raise a serious A or not. Maybe it doesn't matter because you're seeing companies here on the leaderboard that are just blowing past series A numbers. Right. So I don't know that raising consecutive rounds of funding is a true success metric. In fact, that might actually be the wrong metric because now you look at all these companies who are raising all these success around and getting marked up. But the DPI is the last, you know, fund cycle has been terrible. Right. So is that truly the measure of success? or as truly much as capital, return, and DPI. So I think that's maybe a sort of discussion point about definition of success. And two is in terms of survival rate, again, I think if you're a lean company doing,

like you're not doing deep tech, you're not doing some crazy like enterprise sales thing, right? If you're doing like standard tech consumer, PLG, animal services, and again, the fund is convicted, they're keeping lean, keeping the cost, burn low and they're nimble and they're scrappy and you're hungry and they're motivated. I think this will survive survival rate will be extremely high, much higher than 50, even 70%, because most companies die because assuming you don't fall off a cliff because founders give up. And so long as they don't give up, they're focused and they're committed

and they're nimble and scrappy and can grow revenue and head targets. Yeah, I think it's going to be much, much, much higher. And to your point, if you double click even further, why founders give up, Sometimes they have this capital stack, this rough stack of 50, 70 million, and there may be a $20 million business today and they just look at it and they say, it's going to take seven years and then I'm going to get screwed by the preference stack anyways, I might as well close the company. So this misalignment happens kind of from the preft stack as well.

Yeah, exactly, exactly right. So that's why it's not worth it for them to continue a company that's like a zombie unicorn. I have many friends who are in that situation. Well, Henry, I wish I had people like you around and these types of funding when I started my first company in 2004, my freshman year in college. So thanks for doing this for the community. How should people keep up to date everything that you're working on, everything that you're writing about? You can find me, my content on my LinkedIn, my substack, Twitter as well, for you for me to reach out.

Kind of like you, my company, we raised 150 million venture funding, grew to 200 million revenue a year. Overall, we were very lucky, very successful, and our investors have been very supportive, but the journey was super painful. We talked to 100 investors for our seed round, got 98 nose, one maybe one yes for our series B. We talked to 144 investors, got 143 nose. Every time it was a big distraction. It was a whole song and dance, a whole process.

And it just never felt like that as, I don't know, just straightforward and enjoyable and transparent as it is building a company and talking to customers, you're actually creating value. And same for the investors I know. I'm an LP and some of the top funds. I'm also an angel investor and I venture partner in some funds. And you see them on the table, it's hard. It's a, it's a frustrating process for the investors as well.

So much noise, very little signal. Everyone's trying to pattern match the exact same way. So just there's got to be a better way. And hopefully by talking about this, by sharing these stories, these success case studies, and putting my money where my mouth is, invest in my own money in this new model, hopefully we can help inspire more founders, especially now with AI and lean AI methods to build

amazing companies in a new way. I think the second order effects of this could be enormous, maybe five, ten times more startups if you take it to its natural progression. And people are able to start companies. You don't have to work at large companies. You could start companies with almost no capital down without knowing venture capitalists, without going to Harvard and Stanford, the TAM for potential founders is pretty enormous. and probably easy to underestimate.

Absolutely, right? And that's kind of a future thesis is can you have these AI-enabled one-person, you know, AI company and Sam Altman talks about the one-person billion-dollar company, right? Which I think we're starting to see because one-one person just got, you know, acquired for 80-mill cash and more of more, even more, even more cash up front and another 80-plus million in earn-out, that's one person. And I think we're going to see more and more of that. But I think what's even more exciting is not the one.

not just a one-person billion-dollar company, but the billions of one-person AI companies, right, entrepreneurs who are building, who are chasing their own dreams, who are more fulfilled, more driven, more motivated, and what is the tooling, when it's the stack,

what is the sort of capital allocation to support these one-person, or one-person AI-native entrepreneurs. David Deutsch, in his book, beginning of infinity, basically philosophically thought about this question, like how much innovation could there be?

And there's literally an infinite amount of innovation that could happen because it starts innovating on itself. So people need not be worried that there will be more and more opportunities for everybody. Absolutely. And one of the most fun fulfilling things after putting out the Lean AI Angel, which I'll share here. So let me just share the ice screen here. Right. So after I live code at this site where people can upload their deck and financial and we do

analysis and generate a term sheet, right? the cool thing is, one of the coolest things is how many people and innovators and entrepreneurs all in the world have these incredible ideas that I never even thought about or even existed. And it's fascinating to see them build incredible business. And again, like it may not be what VC's pattern match, but these people are building real businesses, being real money, growing, excel, growing, accelerating, and succeeding in their fields and domains and just incredible cities.

Hopefully we'll see even more of that. Awesome. Henry. Well, I'll be in San Francisco soon, so we need to get together and sit down soon. Yeah, awesome. Yeah, great to catch up and thanks for having me. Thanks, Henry. Thanks for listening to my conversation. If you enjoyed this episode, please share with a friend. This helps us grow. Also provides the very best feedback when we review the episode's analytics. Thank you for your support.