E207: Can AI Replace Your VC Analyst?

You recently vibe coded an AI VC tool.

We use AI, my girlfriend and I, to build this tool that allows you to upload a PDF.

The DI will do deep analysis, competitive research, web crawling, and generate an investment memo.

And you can also upload a forecast and Excel model, and it 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, back-end, chat interface, web search analysis, API calls, GitHub, GitHub Actions, Russell 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 analytics?

You get way more detailed analysis of the market, competitive trends, analysis.

You get forecasts built in.

So it just reduces the process and human biases to make it sort of much more transparent, fair, and efficient process.

Because going back again to Prince 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 I want to support you.

You founded super.com and you just had a milestone.

Tell me about where super.com is today.

Started that company in 2016, grew from zero to 200, 250 employees, over 200 million annual revenue, and profitable and 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 forward.

So since transitioning to the board at the end of last year, I've been spending a lot of time helping founders doing intro 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 dollars in AR and beyond.

And I thought there must be more than just these handful of companies like Cursor, Midjourney, et cetera.

So I decided to create this leaderboard to track all the super lean hyper-growth companies that post-AI that are growing extremely quickly with very small teams in an official place called the 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 a 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 there's a couple of reasons why you're seeing this new trend and it's a confluence of factors.

One is it's easier than ever to start a company with these AI tools, coding, co-palettes, customer service, marketing, et cetera.

You're seeing teams, instead of hiring people, they can just automate and augment themselves.

So a small, lean, crack team can stay nimble, move quickly, and 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 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, getting pressure from the markets.

So, there's a much higher willingness to pay from the customer side.

And oftentimes, you're seeing higher pricing because and higher AOVs because people are pricing based on outcome, not on necessarily software seats.

And for example, it's much harder to get to 10 million AR if you're selling a SaaS seat for five, $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 leading AI companies 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 a company called GrowthX.

So that's a sort of AI noble service company, but it's incredible because they have 70% margins and it's AI 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...

you know, tracking your growth analytics or something, right?

You couldn't charge that much and grow so quickly.

But because they're charging based on outcome, they're charging, I believe, five, ten thousand or more a month per client, but they're delivering end-to-end 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 lean ai company in today's digital world online privacy isn't optional it's essential that's why i use nordvpn it's one of the fastest and most reliable vpns on market it helps me protect my personal data block malware and keeps me secure when i'm connecting to public wi-fi networks whether i'm traveling at my local coffee shop or just browsing at home, NordVPN keeps my internet connection encrypted and my information safe from hackers.

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When you look at the history of venture capital,

Venture capital is actually the wrong product for most businesses, even those that do raise VC.

And it's gotten worse as the funds got got bigger and bigger and so I believe the status mega funds are over 500 million 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 deca coin and beyond.

But realistically, most companies are not decains.

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 attempts.

And that's actually just not the right vehicle for most companies and founders.

And for these Lean AI companies, if you can be five people doing 10, 20 million a year,

you're probably 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.

These are not lifestyle founders who are spending an hour, working an hour a day in Dubai or somewhere.

But they are hard-working founders who are driven, who are ambitious, who are motivated, but who recognize that there's a better way to start, build, and fund these companies.

So I've been paneling 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 royalty or something else, but it's much less, it's non-equity, it's non-dilutive, it's not a recourse, not a loan, and it gives the 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 recycle the capital right away.

So happy to dive more into it, but these are some of the things I've been piloting to explore new ways of funding and seed strapping companies.

So, you popularized this term called seed strapping.

What is seed strapping?

So, seed strapping is an interesting alternative way of building a scaling 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, seeds, cheers, A, B, C, D, etc.

And there's lots of benefits on why seed strapping, I think, is the ideal model for many lean AI hyper-growth scaling companies.

And we can go into the differences in terms of revenue, founder dilution, ownership control, founder liquidity, et cetera, et cetera.

But I think there's a lot of benefit now with Lean AI that you can seed strap companies and you're seeing a lot of founders do this.

Give me a sense for what kind of company should be using seed-strapping strategy.

I think almost all the lean AI companies should consider that because the good part about seed strapping is you don't need to dip into your own pockets, right?

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 native company, it's a great bet.

If you're in consumer PLG, I think that's also, you're seeing a lot of companies successfully do that.

If you're an AI nimble services company like GrowthX, I mean, you can raise money, but it's C-Stopping is 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 agents get better and better, I think we'll see the appeal of SeasTropping for more and more companies.

You recently vibe coded an AI VC 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 DI will do deep analysis, competitive research, web crawling, and generate an investment memo.

And you can also upload a forecast and Excel model, and it 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 an 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, back-end, chat interface, web search analysis, API calls, GitHub, GitHub Actions, Vercel deployed, end-to-end deployed, all within a weekend.

So truly using just clock code and clot.

And that's, I think, the best definition of vibe coding.

So you can see here all these interfaces, everything was built just within a weekend and entirely Vibe

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 seed strapping 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 early stage, was very

vibes-based.

Like, do I think this company is going to check all the boxes and become a technical?

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 the two companies in here that matter.

But the irony is that the sum of the revenue of the 999 they rejected is definitely higher than the one you're trying to pick.

So, my thought is: how do you analyze and approach and

systemically analyze the 999 founders who have been in 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 the market, competitive trends analysis.

You get forecasts built in.

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 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 and I want to support you.

It reminds me a little bit of Dan Groves, 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 Decricoin outcomes at the earliest 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 3.46 billion, right?

And some of the best, highest revenue companies have not raised transventure, like Telegram, you know, a billion revenue, not funding, mid-journey, 500 million plus,

zero dollars funding, surge AI, a billion dollars, zero funding.

So I think you're seeing a lot of these founders are realizing that's actually a better way to build incredibly massive successful businesses.

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Double-click a little bit on the founders of these seat-strapped businesses or these highly scalable non-VC-backed companies.

What are some characteristics that you see behind the founders themselves?

I don't know if you've seen the meme of the high IQ and low IQ and IQ.

A lot of times you see these incredibly successful repeat founders who built businesses before the traditional venture funded way, and they realize there's a better way.

So, for example, I had a founder who reached out to me.

His last company was 400 million AR, right?

400 million.

And he's starting a new company.

He's 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 YC Safe or equity funding.

What other methods are there?

Because these founders, they get it.

They've been through the journey.

They've gone through 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 know, sometimes the finance another side of the end, which is, you know, fortunately, they're maybe international, didn't go to Harvard or Stanford, didn't check the box, TAM's a little small, or something, whatever the reason venture isn't the right instrument.

Uh, 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 with 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 YC starting to play in this realm, or would you see kind of a new AI-native incubator that's focused on the seat strapping strategy?

That's a good question.

I don't know if traditional YC will get into this sort of realm 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 tried to 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 innovator's dilemma or alternative model where at first it looks different.

It's maybe

you know, 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.

I know 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 DecoCoins.

And hopefully that can translate to more founders, 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 DPIs right away, right, your IRs are extremely high.

You don't need to wait 10 years for an exit or a liquidity event.

You can get DPIs right away and then you can recycle that capital to invest in more and more more companies.

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Double-click on the seat strapping model on the investor side.

So clearly, this is a great model for a founder that's looking to maybe own 97, 98% of the founding team of a startup.

Tell me about the dollars and cents of investing on the investor side.

I've obviously tested various, experimented different mechanisms and models of this.

And sort of the latest thinking and iteration is basically it's a non-dilutive, 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 AI VC analysis tool to do a deep research on, generate the landscape market mapping memo, and then a 15-month forecast.

And what it would offer is based on the forecast,

basically the idea is like, if you can hit your forecast, which you said, by the way, right, the founder chooses.

If you can hit your forecast and generate growth and not die, then I want to give you the 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 it's up to the founder how much they want to draw.

So, let's just use round numbers.

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 tranches of 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 to be more disciplined about capital um and the the

structure is around five to ten percent revenue and it's capped over uh two to five years at two to three x right so it's not cheap like a bank loan but it's way faster and it's way cheaper than equity especially you know pre-seed funding which is you're giving up 20 of your company for oftentimes a million dollars right so it's cap 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

because sometimes what you see is you'll 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 dialed yourself 20 plus percent and you didn't need the money.

So why did you do that?

So the thinking here is help encourage founders to be disciplined with the funding, give investors a way to invest in these companies, whether they become unicorn or not, doesn't really matter.

If you can hit targets, grow, and and build a great business, I won't offend you.

And it's essentially a free option for the founder.

There's no cost.

If you don't want to use it, great.

You know, 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 you 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 focused mostly on companies with some form of revenue, but the goal in the future is to have all types of companies because again, going back 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 that makes things worse, founders are incentivized to sort of juice the numbers because they're all taught, oh, you have to talk about a decor coin, unicorn, major outcome, whereas investors aren't interested.

Well, that's going back because investors are sort of these mega funds and looking for these mega exits and only 20 plus percent of decor coins, right?

So both sides, people are sort of incentivized to sort of not align on the financials or projections.

So, the thing here is if you can just get the founder to set their own projection that they believe in and align the capital to their own projections, then you should hopefully align the two and end up with great sort of businesses that, if you can hit projections, are going to be good investments.

So, to answer your 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 as it should be.

If you can hit hit forecasts and build a great business, then you should get funding.

Whether you need it or not, it's 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 seed, 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.

So one is, I think the probability 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, and et cetera.

You might actually die.

But now, with the lean AI approach, you can get to that level of scale with a very small team and a bunch of AI tools, right?

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 optionality and flexibility, right?

Like you're not going to fall off a cliff because you provide people.

You can always adapt.

You can always pull back here, spend less or more on marketing, but you don't have this fixed, 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 that's why I fundamentally believe survival rates are gonna 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 gonna overspend hire too many people and ran out of money it's more about them just maybe giving up as as a failure mode um so that's one on the on

excuse me, on the

cost and problem and 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 prep stack is way too high and the early investors get washed out.

So I think you also see a lot of reasons why investors don't return 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 rev sure royalty basis,

it doesn't really matter if you get stuck at 20, 30 million AR, 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 quickly and the market has to be right and the sort of multiples have to line up.

So, if you're investing at a high multiple and the multiples don't catch up, yeah, you're underwater.

But here, if you're investing and they're growing, excuse me, if you're investing and making money, even if they get stuck and the multiples are low, it doesn't really matter because I can recycle the capital through rupture royalty and then reinvest in more companies.

I like a lot of parts of this concept.

I like the seat strapping, I like the term that you 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 cocentric 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.

So they don't need to use all of it.

Whereas for a traditional equity, if you get a final seed, that's all of it, right?

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.

So, suppose they want to raise a two-mil round, they raise a million equity and a million in this new format.

And so that way they don't need to over-dilute themselves.

And instead of doing a two-on-20, right, maybe now it's a one-on-one and another one on this rub share model.

And that's only 5% dilution.

So that's oftentimes good to pair it as well.

I just looked up the numbers, roughly 50 to 70% of seed stage companies failed 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 good question.

I think the metric you mentioned is fail to raise a series A, right?

But I think that is maybe no longer the definition of success or failure, whether you use it to raise a series 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 DPIs for the last fund cycle has been terrible.

So, is that truly the measure of success, or it's truly measured 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 founders

convicted, they're keeping lean, keeping the costs burn low, and they're nimble and they're scrappy and they're hungry and they're motivated, I think the 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 focus and they're committed and they're nimble and scrappy and can grow revenue and hit 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 pref 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 pref stack as well.

Yeah, exactly.

Exactly, Rice.

And 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?

Yeah.

You can find me, my content on my LinkedIn, my Substack, Twitter as well.

Feel free 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 a hundred investors for our seed round got 98 no's one maybe one yes for our series b we talked to 144 investors got 143 no's and so every time it was a big distraction it was um

a whole song and dance, a whole process.

And it just never felt like as, I don't know, just straightforward and enjoyable and transparent as it is building a company and talking to customers actually creating value and same for the investors I you know I'm an LP and some of the top funds I'm also an angel investor and I venture partners some funds and you see on this 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 investing 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 under underestimate.

Absolutely, right?

And that's kind of the future thesis is can you have these AI-enabled one-person

AI companies?

And Sam Altman talks about the one-person billion-dollar company, right?

Which I think we're starting to see because one person just got acquired for 80 mil cash and more of more 80 mil 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 not just the 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?

What is 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 becomes starts in a innovating on itself so people need not be worried that there will be more more and more opportunities for everybody absolutely and one of the most fun fulfilling things after putting out the leaning eye angel which uh i'll share here so

um let me just share my screen here uh

right so after i vibe coded this site where people can upload their deck and financial and we do the 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 over 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, making real money, growing,

growing, accelerating, and succeeding in their fields and domains.

And just incredible to see.

So 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.

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