September 1, 2025 • 34 mins
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.
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Episode Transcript
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(00:00):
You recently vibe coded an AI VC tool.
We use AI, my girlfriend and I, to build thistool that allows you to upload a PDF.
The DI will do deep analysis, competitiveresearch, web crawling, and generate investment
memo.
And can also upload a forecast and Excel model,and it can do all the situational analysis,
planning, forecasting, and generate a termsheet automatically.
(00:22):
It's incredible how someone with no engineeringexperience, never taken a CS class, doesn't
know what a terminal is, doesn't know what whata HTML is, is able to build this tool entirely
end to end, front end, back end, chatinterface, web search analysis, API calls,
GitHub, GitHub actions, Purcell deployed, andsend deployed all within a weekend.
(00:45):
And what's the use case that you're buildingaround?
Is it to completely replace VCAnalytics?
You got way more detailed analysis of marketmarket, competitive trends, analysis.
You get forecast built in.
So it just reduces process and human biases tomake 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,
(01:08):
hit your forecast, and be profitable or notdie, then I wanna fund you.
I wanna support you.
You founded super.com, and you just had amilestone.
Tell me about where super.com is today.
Started that company in 2016, grew from zero to200, 250 employees, over 200,000,000 annual
revenue, and profitable, and over 50,000,000users.
(01:28):
You also run a cool leaderboard.
It's called Lean AI Leaderboard.
Tell me more about this Lean AI movement.
After I ran the company for eight, nine years,after a point where we're hundreds of millions
of revenue, profitable, growing, I decided tostep 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 endof last year, I've been spending a lot of time
(01:51):
helping founders doing intro investing, sharingcontent, dabbling AI.
And it's been a great journey.
And in that process, I beginning of this year,2025, I saw a lot of people tweet on Twitter
and LinkedIn about how these companies with sofew people are getting to $10.20, $50,000,000
in AR and beyond.
And I thought there must be more than justthese handful of companies like Cursor,
(02:12):
Midjourney, etcetera.
So I decided to create this leaderboard totrack all the super lean hyper growth companies
that have post AI that are growing extremelyquickly with very small teams in an official
place called Lean AI Leaderboard.
So I bought this leaderboard, launched it, andit just took off, had millions of impressions
across social and the website, and now it'sthis sort of way to track these Lean AI
(02:35):
companies growing extremely quickly with veryfew people and a high revenue and oftentimes
profitably.
So it's incredible to see this new new trend.
Double click on why AI is allowing these crazyhigh growth companies that are grown on a very
lean basis.
Is there also a revenue and a cost side to theequation, or is it just simply less engineers?
(02:59):
That's a great question.
I think there's a couple of reasons why you'reseeing this new trend, and it's a confluence of
factors.
One is it's easier than ever to start a companywith these AI tools, coding, co palettes,
customer service, marketing, etcetera.
You're seeing companies, instead of hiringpeople, they can just automate and augment
themselves.
So a small, lean, crack team can stay nimble,move quickly, and get a lot more done.
(03:23):
So you're seeing that on the cost side, whereasbefore, you had to raise a lot of money to
build your product to go to market.
Now these teams can ship quickly and get tomarket extremely quickly.
On the demand side, you're seeing there's alsoa higher willingness to pay.
Everyone is sort of interested in AI,interested in trying AI, adopting AI.
They're getting pressure from the board andpressure from the markets.
(03:44):
So there's a much higher willingness to payfrom the customer side.
And oftentimes, you're seeing higher pricingbecause and higher AOVs because people are
pricing based on outcome, on necessarilysoftware receipts.
And for example, it's much harder to get to10,000,000 ARR if you're selling a SaaS seed
for $510 a month.
But if you're selling an outcome, can sell thesame thing for hundreds or thousands of
(04:05):
dollars.
So higher OV, higher demand, willingness topay, and lower cost basis, and you're seeing
this effect of leading AI companies scaling soquickly and oftentimes profitably.
Give me an example of one or two outcomes thatAI companies are pricing based on versus kind
of this traditional SaaS model.
So a good example is, I think, a company calledGrowthX.
(04:26):
So that's a sort of AI enabled service company,but it's incredible because they have 70%
margins, and it's AI powered growth.
They were able to scale from zero to, Ibelieve, 7,200,000 AR within a year and a half
and 13 people.
And that's an example where if you're gellingif you're just selling a SaaS tool for, you
(04:46):
know, tracking your growth analytics orsomething, right, you couldn't charge that much
and grow so quickly.
But because they're charging based on outcome,they're charging, I believe, $510,000 or more a
month per client, but they're delivering end toend out outcomes, and they're doing able to do
it efficiently and leanly with AI automationacross entire back office and keep 70% plus
(05:07):
margins.
Tell me about the ideal capital structure for avery lean AI company.
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When you look at the history of venturecapital, venture capital is actually the wrong
product for most businesses, even those thatthat do raise VC.
And it's gotten worse as the funds have gottenbigger and bigger.
(06:31):
So I believe the status of mega funds that areover 500,000,000,000 accounted for 77% of
capital raised in the 2022, and these billiondollar funds needs to own 15% of
$21,000,000,000 companies to just return threex, but there are only 22 public companies with
a 10,000,000,000 plus market cap.
So the question becomes, how do you returnthese mega funds?
(06:54):
Well, these investors have to chase more andmore extreme outlier outcomes.
But being a unicorn isn't enough.
You have to be a decker coin and beyond.
But realistically, most companies are notdecker coins.
So venture capital chasing these extremeoutliers makes it such that everyone is forced
to talk these large narratives, hire thesemassive teams, target these massive competitive
(07:16):
temps.
And that's actually just not the right vehiclefor most companies and founders.
For these lean AI companies, if you can be fivepeople doing $10.20 millionaire year, you're
probably doing bet you're probably better offthan most venture backed founders.
You have way more control, way more, way lessdilution, way more possible outcomes.
(07:37):
And by the way, these are not lifestylecompanies.
Right?
These are not lifestyle founders who arespending an hour working an hour a day in Dubai
or somewhere, but they are hardworking founderswho are driven, who are ambitious, who are
motivated, but who recognize that there's abetter way to start, build, and fund these
companies.
So I've been piloting a lot of different waysto try to support these founders where I think
(07:58):
the fundamental premise is if you can grow andyou 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, maybeit's rev share, royalty, or something else, but
it's much less it's it's not equity.
It's non dilutive.
It's not a recourse, not loan, and it gives afounder optionality while still giving
(08:20):
investors a good return, faster DPIs, and youdon't have to wait ten years for for an exit.
You can get can recycle the capital right away.
So happy to dive more into it, but these aresome of things I'm piloting to explore new ways
of funding and seed strapping companies.
So you popularized this term called seedstrapping.
What is seed strapping?
So seed strapping is a interesting alternativeway of building a selling company where you
(08:44):
raise a sizable, nice seed round, then and youget to escape velocity from there on.
So you no longer need to raise consecutiverounds of funding, like precede seed, series a,
b, c, d, etcetera.
And there's lots of benefits on why seedstrapping, I think, is the ideal model for many
Lean AI hyper growth scaling companies.
And we can go into the differences in terms ofrevenue, founder dilution, ownership control,
(09:09):
founder liquidity, etcetera, etcetera.
But I think there's a lot of benefit now withLean AI that you can seasrap companies, and
you're seeing a lot of founders do this.
So give me a sense for what kind of companyshould be using seed strapping strategy.
I think almost all of
the Lean AI companies should consider thatbecause the good part about seed strapping is
you don't need to dip into your own pockets.
(09:31):
Right?
So you can start the company without having todip into your own savings, but you don't have
to constantly dilute yourself and chaseinvestors and be on the VC treadmill.
You can own control, grow over time, get moreliquidity throughout the process, and maybe
even buy out some investors over time early on.
So it's a benefit for in many ways.
In terms of the companies, I think if you're alean AI native company, it's a great bet.
(09:55):
If you're a consumer PLG, I think that's alsoyou're seeing a lot of companies successfully
do that.
If you're an AI enabled services company likeGrowthX, I mean, you can raise money, but it's
C Sharp 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 AIsales agents aren't quite good enough yet.
(10:16):
But as the capabilities of AIs AI agents getbetter and better, I think we'll see, the
appeal of Seastrapping for more and morecompanies.
You recently vibe coded an AIVC tool.
So first of all, what's your definition of Vibecoding?
And then tell me a little bit about this tool.
Okay.
So, basically, we use AI, my girlfriend and I,to build this tool that allows you to upload a
(10:41):
PDF.
The DI will do deep analysis, competitiveresearch, web crawling, and generate an
investment memo.
And you can also upload a forecast and Excelmodel, and it can do all the situational
analysis, planning, forecasting, and generate aterm sheet automatically.
So that's sort of what we built, and it's anincredibly it's incredible how someone with no
engineering experience, never taken a CS class,doesn't know what a terminal is, doesn't know
(11:05):
what what a HTML is, is able to build this toolentirely end to end, front end, back end, chat
interface, web search analysis, API calls,GitHub, GitHub actions, Vercel deploy, end to
end deployed all within a weekend.
So truly using just clock code and clock, andthat's, I think, the best definition of of vibe
coding.
As you can see here, all these interface,everything was built, just within a weekend and
(11:28):
entirely vibe coded.
And what's the use case that you're buildingaround?
Is it to completely replace VC analysts?
Is it
As I'm exploring this new way of seed strappingand supporting founders, I'm getting a lot of
inbound and requests in companies.
And I've always felt that the traditionalventure investing, especially in early stage,
was very vibes based.
(11:51):
Like, do I think this company is going to checkall the boxes and become a tech coin?
And frankly, how am I supposed to know?
And the irony is the investors, they get 1,000pitches, they reject nine ninety nine of them.
They probably don't even look at half of them,and they're all trying to chase the two
companies near that matter.
Right?
But that is that the sum of the revenue of thenine ninety nine they rejected is definitely
(12:11):
higher than the one they're trying to pick.
So my thought is how do you analyze andapproach and systemically analyze the 999 on
founders who have been in good great companies,but in a way that's scalable, automated, and
unbiased and transparent, and you can do thismuch more effectively now with AI.
You get way more detailed analysis than marketmarket, competitive trends analysis.
(12:33):
You get forecast built in.
So it just reduces the process and human biasesto 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 notdie, then I wanna fund you.
I wanna support you.
It reminds me a little bit of Dan Gross, who'sobviously a prolific AI investor.
(12:57):
He had this project called Pioneer, which triedto find these founders all over the world that
maybe didn't fit the Stanford, Harvard, youknow, 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.
(13:18):
If they don't get VC funded, you know, theyessentially never actualize.
Exactly.
Right?
And so much of it is pattern matching and andsort of trying to predict DecreCorn outcomes at
the earliest stages.
And I'm just not sure that's I mean, maybe it'spossible if you're the top sort of ten, twenty
firms, but for everyone else, I think it's sohard.
(13:39):
There's so much sort of selection and selfselection and versus supporting the nine ninety
nine founders who collectively that that's aton of revenue, I think, the leaderboard you
see here.
Obviously, a of them have raised funding, but alot of them haven't.
And collectively, it's, you know,3,460,000,000.00.
Right?
And and some of the best highest revenuecompanies have not raised from this venture
(14:02):
like Telegram, you know, billion revenue, notfunded mid journey, 500,000,000 plus $0 from
the Surge AI, a billion dollars, zero funding.
And so I think you're seeing a lot of thesefounders are realizing that's actually a better
way to build incredibly massive successfulbusinesses.
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Double click a little bit on the founders ofthese seat strapped businesses or these highly
scalable non VC backed companies, what are somecharacteristics that you see behind the
founders themselves?
I don't know if you've seen the meme of thehigh IQ and low IQ and mid IQ.
(15:30):
A lot of times you see these incrediblysuccessful repeat founders who built businesses
before the traditional venture funded way, andthey realized there's a better way.
So for example, I had a founder who reached outto me.
His last company was 400,000,000 AR.
Right?
400,000,000.
Starting a new company, he's like, hey.
Hey, Henry.
I came across your seed strapping thing, andI'm starting a new company, but I don't wanna
(15:52):
do a traditional YC SAFE or equity funding.
What other methods are there?
Because these founders, they've 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 arepeat founder.
Or sometimes the finance is another side of theend, which is, fortunately, they're maybe
international, didn't go to Harvard orStanford, didn't check the box, TAM's a little
(16:15):
small or something.
Whatever reason, venture isn't the rightinstrument.
They're like, sure.
This is a great alternative.
And then you have folks in the middle, like thefirst time YC founder.
Right?
So who are like, hey.
This sounds interesting.
This is cool.
It's nondilutive.
It's, there's no recourse, but I don't know.
It's different, and I should just do a safebecause Gary Tan told me to do a safe.
Right?
So you're kinda seeing this distribution, butmy hope is over time as you highlight more of
(16:38):
these stories, when these incredible foundersbuild incredible business outcomes, that more
people are gonna shift to the right of the tailand 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 startingto play in this realm, or would you see kind of
a new AI native incubator that's focused onthese seat strapping strategy?
(17:01):
That's a good question.
I don't know if traditional YC will get intothis sort of realm because their whole model is
based on marking up and fundraising and sort ofhaving the prepping the companies for demo day
and getting marked higher valuations offundraising and traditional venture route.
And actually very good at it because if you'rean incumbent and you're the best at that type
(17:22):
of model, why should you change?
It's been very profitable for them, and they'reAnd in fact, it's 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 a good you know, sort of peopledon't get it.
But over time, as AI and the capabilitiesbecome better and better, I think we're gonna
see more and more founders opt into this newmodel.
(17:45):
And I'm not sure if it's an incubatoraccelerator or a funding model or something
else.
My hope is that there will be more people whoare doing this.
So it's not just me who's thinking aboutinvesting in different ways, but there we can
inspire other investors to think about fundingthe, you know, 999 companies who are not the
two a year that become Decka coins.
And hopefully, that can translate to morefounder, more diverse founders, more
(18:08):
transparent fund funding, and more much morefair efficient process.
So that's how my hope is more people can dothis and and sort of realize that it's also a
great economic opportunity as well.
Because if you can get DPIs right away, right,your IRR is extremely high.
You don't need to wait ten years for an exit ora liquidity event.
You can get DPIs right away, and then you canrecycle that capital to invest in more and more
(18:30):
companies.
So double click
on the seat strapping model on the investorside.
So, clearly, this is a great model for afounder that's looking to maybe own 97, 98%,
the founding team of a startup.
Tell me about the dollars and cents ofinvesting on the investor side.
I've obviously tested various experimenteddifferent mechanisms and models of this.
(18:53):
And so the latest thinking and iteration is,basically, it's a nondilutive, nonrecourse
capital.
So it's not equity.
There's no control.
There's no debt.
And all all Fantasy do is they give me a a deckof the company, which I use my AI VC analysis
tool to do a deep research on, generate thatlandscape market mapping memo, and then a
(19:15):
fifteen month forecast.
And what it would offer is based on a 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 generategrowth and not die, then I wanna give you the
opportunity to get funded.
So for example so right now, it's structured asa bit of a sort of a line of credit, which is
it's not debt, but it's it's up to the founderhow much they wanna draw.
(19:37):
So let's just do round numbers.
Suppose I do analysis on the forecast, and Isay, hey.
You know, I wanna give you a million dollarsthat you can draw in over four tranches, and
it's 250 k per quarter based on hitting yourquarterly forecast.
So, again, right, the founder sets theforecast, 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 wannadraw, if any.
(20:00):
So it's up to them if they wanna draw allmillion or maybe only 250 k or half of it.
It's up to them, and that actually encouragesfounders to to be more disciplined about
capital.
And and the the structure is around five to 10%of revenue, and it's capped over two to five
years at two to three x.
Right?
So it's not cheap like a bank loan, but it'sway faster, and it's way cheaper than equity,
(20:23):
especially, you know, pre seed funding, whichis you're giving up 20% of company for
oftentimes a million dollars.
Right?
So it's capped for the investor, but it's highDPS right away, and it's an option for founder
depending on if they wanna use it.
And because sometimes what you see is you seefounders say, oh, look.
I raised a massive seed round, you know,$5,000,000, and I didn't even have to touch any
of it.
Right?
(20:43):
Even though and they're they're flexing aboutit, but it's actually that's actually kinda
dumb because you just diluted yourself 20 pluspercent, and you didn't even need the money.
So why did you do that?
So the the thing here is help encouragefounders to be disciplined with the funding,
give investors a way to invest in thesecompanies whether they become unicorn or not.
Doesn't really matter.
If you can hit targets, grow, and build a greatbusiness, I wanna fund you.
(21:04):
And it's a it's essentially a free option forthe founder.
There's no cost.
If you don't wanna use it, great.
You know, if one is 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 financialdiscipline, encourages people to actually set
realistic targets.
And whether they use my money or not issomewhat irrelevant because I I would've still
(21:27):
helped you build a better company if you canhit your forecast and actually build a great
business.
And this is based on the idea that they'realready revenue generating and already you
could scale up from some revenue number.
Yeah.
Right now, I'm focusing on we'll mostly oncompanies with some form of revenue, but the
goal in the future is to have all types ofcompanies because, again, going back to the
(21:48):
first principles.
Right?
The reason why fundraising is hard and annoyingis because the there's a fundamental disconnect
between a founder's projections and investorsbelief in their projections.
Because if you think about it, if the investorsactually believe the founder's projections,
right, then you shouldn't invest in everysingle company because they're always up into
their right.
If you actually believe, you should invest inevery company.
But the reality is investors don't.
(22:10):
And the other the thing that things worse,founders are incentivized to of juice the
numbers because they're all taught, oh, youhave to talk about a Decacorn unicorn major
outcome, whereas investors aren't interested.
Well, that's going back because investors areof these mega funds are looking for these mega
exits and only 20 plus percent of deca coins.
Right?
So both sides, people are sort of incentivizedto sort of not align on financials or
(22:35):
projection.
So the thing here is if you can just get thefounder to set their own projection that they
that they believe in and align the capital totheir own projections, then they should
hopefully align to and end up with great sortof businesses that if you can hit projections,
are gonna be good investments.
So to answer your question, over time, I dohope to support companies' pre revenue as well
(22:56):
because so long as you can make a forecast andhit those forecasts, then I wanna fund you
because that's as simple as it should be.
If you can hit forecast and build a greatbusiness, then you should get funding.
Whether you need it not, separate, but youshould at least get the opportunity for that.
To play devil's advocate, historically, I thinksomething like three out of four startups did
not give back one x their money at the seriesa, not even at the seat, but at the series a.
(23:18):
How do you make that work with a two to three xreturn at that stage if you're capping
yourself?
That's a good question.
And so one is I think the probability ofsuccess will be much higher now with AI and
these leading AI methodologies because it'seasier and cheaper than ever to start a
company.
Before, you had to raise a lot of money, hire abunch people, spend a lot of time on r and d,
(23:38):
get the product to market.
By the time you have this large team, you have,you know, hired series a, for example, twenty,
thirty, 50 people.
In those cases, yeah, you might actually die.
You might actually run off a cliff because youhave this high burn, and you can't grow revenue
fast enough or or whatever.
You have all this fixed costs of people, labor,etcetera.
You might actually die.
But now with the Lean AI approach, you can getto that level of skill with a very small team
(24:02):
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 codesometimes.
And by keeping being lean, nimble, and scrappy,you have optionality and flexibility.
Right?
Like, you're not gonna fall off a cliff becauseyou have five people.
You can always adapt.
Like, you can always pull back here and spendless and more on marketing, but you're not you
don't have this fixed, large fixed cost basewhere suddenly you run out of money and you
(24:24):
fall off a cliff.
So one is the cost a lot lower.
You have more control and flexibility, andyou're more nimble.
You can adapt quicker and you can adjust.
So I think that's that's why I funfundamentally believe survival rates are gonna
go up.
And what I often look for in these founders is,as as you know, a lot of times, companies die
not because of competition, but because ofsuicide, because the founders give up, they get
(24:46):
bored, they do something else.
So, really, it's more about the resilience ofthe founder and their sort of persistence and
and sort of conviction versus, oh, we're gonnaoverspend, hire too many people and run out of
money.
It's more about them just maybe giving up as asa failure mode.
So that's one of the on the on the on the onthe, excuse me, on the cost and problem of
(25:07):
success.
And then on the return side, oftentimes you'llsee, right, these are because oftentimes you
see companies that are great companies who arenow zombie companies because they're not going
fast enough and they don't have an exitopportunity.
They've the prep stack is way too high.
The early investors get washed out.
So I think you also see a lot of reasons whyinvestors don't return capital.
(25:27):
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 zombiecompany, zombie unicorn company, right,
everybody's stuck and you're not getting yourmoney.
Whereas if you're doing it on a rev shareroyalty basis, it doesn't really matter if you
get stuck at twenty, thirty million AR, right?
Because I'm getting a revenue split of that.
(25:48):
So I can still get my return and my money, andI don't need to pray or depend on an, you know,
exit.
And oftentimes, as you know, these exits, thecompany has to be growing really fit quickly,
and the mark has to be right, and the sort ofmultiples have to line up.
So if you're investing at a high multiple andthe multiples don't catch up, yeah, you're
underwater.
But here, you're investing and they're growingoh, excuse me.
(26:09):
If you're investing and making money, even ifthey get stuck and the multiples are low, it
doesn't really matter because I can recycle thecapital through rupture royalty and then
reinvest in more companies.
I like a lot of parts of this concept.
I like the seat strapping.
I I like the term that he popularized.
I like the higher return of capital.
I worry about the misalignment where you'rebeing paid off of revenue and you're also
(26:32):
getting capped at the upside that in invariablymisaligns you with the founder, not in every
way, but in certain ways.
And I think if founders went about just raisingless money and not chasing the headlines, the
$5,000,000 seed round like you mentioned, therecould be more concentric circles that work
better for the founder and the GP.
(26:53):
Sure.
Right?
And and that's why after many iterations, I'vestructured it more like a line of credit.
So it's up to the founder how much they wannatake.
Right?
So they don't need to use all of it.
Whereas for a traditional equity, if you get afinal seat, all of it.
Right?
Even if you don't need it, that's all of it onyour capital, you can't give it back.
Whereas here, it's meant to be structured in away that's founder's option.
(27:15):
So, yeah, they want the headline and some bignumber 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 withtraditional equity funding.
As opposed they wanna raise a 2 mil round, theyraise a million equity and a million in this
new format.
And so that way, they don't need to overdevelopthemselves.
(27:35):
And instead of doing a two on 20, right, maybenow it's a one on 20 and another one on this
rupture 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 failto get to series a historically.
You believe there'll be much lower death ratesor much higher survival rates for startups.
(27:59):
What percentage of these lean AI startups doyou think will make it as defined by being
ongoing businesses in the future?
That's a question.
I think the metric you mentioned is fail toraise a series a.
Right?
But I think that is maybe no longer thedefinition of success or failure.
Whether you raise a series a or not, maybe itdoesn't matter.
Because you're seeing companies here on theleaderboard that are just blowing past series a
(28:21):
numbers.
Right?
So I I I don't know that raising consecutiverounds of funding is a true success metric.
In fact, that might actually be the wrongmetric because now you look at all these
companies who are raising all these successaround and getting marked up, but the DPI is
the last, you know, fund cycle has beenterrible.
Right?
So so is that truly the measure of success orit's truly measured as capital return and DPI?
(28:44):
So I think that's maybe a sort of discussionpoint about definition of success.
Two is in terms of survival rate, again, Ithink if you're a lean company, you're not
doing deep tech, you're not doing some crazyenterprise sales thing.
If you're doing standard tech consumer PLNGannual services, and again, the fund is
(29:06):
convicted, they're keeping lean, they'rekeeping the costs burn low, and they're nimble
and they're scrappy and they're hungry andthey're motivated, I think this survive
survival rate will be extremely high, muchhigher than fifty, even seventy percent because
most companies die because I'm assuming youdon't fall off a cliff because founders give
up.
Right?
And so long as they don't give up, they'refocused and committed and they're nimble and
(29:28):
scrappy and and can grow revenue head targets,yeah, I think it's gonna be much, much, much
higher.
And to your point, if
you double click even further, why foundersgive up?
Sometimes they have this capital stack, thisprep stack of $5,070,000,000, and there may be
a a $20,000,000 business today, and they justlook at it and they say, it's gonna take seven
years, and then I'm gonna get screwed by thepreference stack anyways.
(29:50):
I might as well close the company.
So this misalignment happens kind of the fromthe pref stack as well.
Yep.
Exactly.
Exactly right.
So that's why it's not worth it for them, to tocontinue a company that's like a zombie
unicorn.
I have many friends who are
in that situation.
Well, Hendrie, I wish I had people like youaround and and these types of funding when I
(30:11):
started my first company in 02/2004, myfreshman year in college.
So thanks for doing this for the community.
How should people keep up to date everythingthat you're working on, everything that you're
writing about?
Yeah.
You can find me, my content on my LinkedIn, mySubstack, Twitter as well.
Feel free to reach out.
Kinda like you, my company, we we raised a150,000,000 venture funding, grew to
(30:32):
200,000,000 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 100 investors for our seedround, got 98 nos, one maybe, one yes for our
series b.
We talked to a 144 investors, got a 143 nos.
And so every time it was a big distraction, itwas a whole song and dance, a whole process.
(30:57):
And it just never felt like the as, I don'tknow, just straightforward and enjoyable and
transparent as it is building a company andtalking to customers who are actually creating
value.
And same for the investor side.
You know?
I'm an LP at some of the top funds.
I'm also an angel investor, and I've met yourpartner in some funds.
And you see them on this table.
It's hard.
It's a it's a frustrating process for theinvestors as well.
(31:17):
So much noise, very little signal.
Everyone's trying to pattern match exact sameway.
So just there's gotta be a better way.
And, hopefully, by talking about this, bysharing these stories, these success case
studies, and putting my money where my mouthis, 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.
(31:39):
I think the second order effects of this couldbe enormous, maybe five, ten times more
startups if if you take it to its naturalprogression, and people are able to start
companies.
You don't have to work at large companies.
You could start companies with almost nocapital down, with no without knowing venture
capitalists, without going to Harvard andStanford.
The the TAM for potential founders is prettyenormous and probably easy to under
(32:05):
underestimate.
Absolutely.
That's kind of the future thesis is can youhave these AI enabled one person AI companies?
And Sam Altman talks about the one personbillion dollar company, right?
Which I think we're starting to see because oneperson just got acquired for 80,000,000 cash
more of 80,000,000 cash upfront and another 80plus million in earn out.
(32:27):
That's one person.
And I think we're gonna see more and more ofthat.
But I think what's even more exciting is notjust 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, are more fulfilled, who aremore driven, more motivated.
And what is the tooling?
What is the stack?
What is the sort of capital allocation tosupport these one person or one person AI
(32:50):
native entrepreneurs?
David Deutsch in his in his book, Beginning ofInfinity, basically philosophically thought
about this question, like, how much innovationcould there be?
And there's literally an infinite amount ofinnovation that could happen because it become
starts innovating on itself.
So people need not be worried that there willbe more more and more opportunities for
everybody.
Absolutely.
(33:10):
And and one of the most fun and fulfillingthings after putting out the Leading Eye Angel,
which I'll share here.
So let me just share my screen here.
Right.
So after I've I've coded this site where peoplecan upload their deck and financial, and we do
analysis and generate a term sheet.
Right?
The cool thing is one of the coolest things ishow many people and innovators and
(33:34):
entrepreneurs all over the world have theseincredible ideas that I never even thought
about or even existed, and it's fascinating tosee them build incredible business.
And, again, like, it may not be what VC'spattern match, but these people are building
real businesses, making real money, growingexcel excel growing, accelerating, and
succeeding in their fields and domains and justincredible to see.
(33:55):
So, hopefully, we'll see even more of that.
Awesome, Henry.
Well, I'll be in San Francisco soon, so we needto, 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 witha friend.
This helps us grow.
Also provides the very best feedback when wereview the episode's analytics.
Thank you for your support.
You recently vibe coded an AI VC tool.
We use AI, my girlfriend and I, to build thistool that allows you to upload a PDF.
The DI will do deep analysis, competitiveresearch, web crawling, and generate investment
memo.
And can also upload a forecast and Excel model,and it can do all the situational analysis,
planning, forecasting, and generate a termsheet automatically.
(00:22):
It's incredible how someone with no engineeringexperience, never taken a CS class, doesn't
know what a terminal is, doesn't know what whata HTML is, is able to build this tool entirely
end to end, front end, back end, chatinterface, web search analysis, API calls,
GitHub, GitHub actions, Purcell deployed, andsend deployed all within a weekend.
(00:45):
And what's the use case that you're buildingaround?
Is it to completely replace VCAnalytics?
You got way more detailed analysis of marketmarket, competitive trends, analysis.
You get forecast built in.
So it just reduces process and human biases tomake 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,
(01:08):
hit your forecast, and be profitable or notdie, then I wanna fund you.
I wanna support you.
You founded super.com, and you just had amilestone.
Tell me about where super.com is today.
Started that company in 2016, grew from zero to200, 250 employees, over 200,000,000 annual
revenue, and profitable, and over 50,000,000users.
(01:28):
You also run a cool leaderboard.
It's called Lean AI Leaderboard.
Tell me more about this Lean AI movement.
After I ran the company for eight, nine years,after a point where we're hundreds of millions
of revenue, profitable, growing, I decided tostep 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 endof last year, I've been spending a lot of time
(01:51):
helping founders doing intro investing, sharingcontent, dabbling AI.
And it's been a great journey.
And in that process, I beginning of this year,2025, I saw a lot of people tweet on Twitter
and LinkedIn about how these companies with sofew people are getting to $10.20, $50,000,000
in AR and beyond.
And I thought there must be more than justthese handful of companies like Cursor,
(02:12):
Midjourney, etcetera.
So I decided to create this leaderboard totrack all the super lean hyper growth companies
that have post AI that are growing extremelyquickly with very small teams in an official
place called Lean AI Leaderboard.
So I bought this leaderboard, launched it, andit just took off, had millions of impressions
across social and the website, and now it'sthis sort of way to track these Lean AI
(02:35):
companies growing extremely quickly with veryfew people and a high revenue and oftentimes
profitably.
So it's incredible to see this new new trend.
Double click on why AI is allowing these crazyhigh growth companies that are grown on a very
lean basis.
Is there also a revenue and a cost side to theequation, or is it just simply less engineers?
(02:59):
That's a great question.
I think there's a couple of reasons why you'reseeing this new trend, and it's a confluence of
factors.
One is it's easier than ever to start a companywith these AI tools, coding, co palettes,
customer service, marketing, etcetera.
You're seeing companies, instead of hiringpeople, they can just automate and augment
themselves.
So a small, lean, crack team can stay nimble,move quickly, and get a lot more done.
(03:23):
So you're seeing that on the cost side, whereasbefore, you had to raise a lot of money to
build your product to go to market.
Now these teams can ship quickly and get tomarket extremely quickly.
On the demand side, you're seeing there's alsoa higher willingness to pay.
Everyone is sort of interested in AI,interested in trying AI, adopting AI.
They're getting pressure from the board andpressure from the markets.
(03:44):
So there's a much higher willingness to payfrom the customer side.
And oftentimes, you're seeing higher pricingbecause and higher AOVs because people are
pricing based on outcome, on necessarilysoftware receipts.
And for example, it's much harder to get to10,000,000 ARR if you're selling a SaaS seed
for $510 a month.
But if you're selling an outcome, can sell thesame thing for hundreds or thousands of
(04:05):
dollars.
So higher OV, higher demand, willingness topay, and lower cost basis, and you're seeing
this effect of leading AI companies scaling soquickly and oftentimes profitably.
Give me an example of one or two outcomes thatAI companies are pricing based on versus kind
of this traditional SaaS model.
So a good example is, I think, a company calledGrowthX.
(04:26):
So that's a sort of AI enabled service company,but it's incredible because they have 70%
margins, and it's AI powered growth.
They were able to scale from zero to, Ibelieve, 7,200,000 AR within a year and a half
and 13 people.
And that's an example where if you're gellingif you're just selling a SaaS tool for, you
(04:46):
know, tracking your growth analytics orsomething, right, you couldn't charge that much
and grow so quickly.
But because they're charging based on outcome,they're charging, I believe, $510,000 or more a
month per client, but they're delivering end toend out outcomes, and they're doing able to do
it efficiently and leanly with AI automationacross entire back office and keep 70% plus
(05:07):
margins.
Tell me about the ideal capital structure for avery lean AI company.
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When you look at the history of venturecapital, venture capital is actually the wrong
product for most businesses, even those thatthat do raise VC.
And it's gotten worse as the funds have gottenbigger and bigger.
(06:31):
So I believe the status of mega funds that areover 500,000,000,000 accounted for 77% of
capital raised in the 2022, and these billiondollar funds needs to own 15% of
$21,000,000,000 companies to just return threex, but there are only 22 public companies with
a 10,000,000,000 plus market cap.
So the question becomes, how do you returnthese mega funds?
(06:54):
Well, these investors have to chase more andmore extreme outlier outcomes.
But being a unicorn isn't enough.
You have to be a decker coin and beyond.
But realistically, most companies are notdecker coins.
So venture capital chasing these extremeoutliers makes it such that everyone is forced
to talk these large narratives, hire thesemassive teams, target these massive competitive
(07:16):
temps.
And that's actually just not the right vehiclefor most companies and founders.
For these lean AI companies, if you can be fivepeople doing $10.20 millionaire year, you're
probably doing bet you're probably better offthan most venture backed founders.
You have way more control, way more, way lessdilution, way more possible outcomes.
(07:37):
And by the way, these are not lifestylecompanies.
Right?
These are not lifestyle founders who arespending an hour working an hour a day in Dubai
or somewhere, but they are hardworking founderswho are driven, who are ambitious, who are
motivated, but who recognize that there's abetter way to start, build, and fund these
companies.
So I've been piloting a lot of different waysto try to support these founders where I think
(07:58):
the fundamental premise is if you can grow andyou 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, maybeit's rev share, royalty, or something else, but
it's much less it's it's not equity.
It's non dilutive.
It's not a recourse, not loan, and it gives afounder optionality while still giving
(08:20):
investors a good return, faster DPIs, and youdon't have to wait ten years for for an exit.
You can get can recycle the capital right away.
So happy to dive more into it, but these aresome of things I'm piloting to explore new ways
of funding and seed strapping companies.
So you popularized this term called seedstrapping.
What is seed strapping?
So seed strapping is a interesting alternativeway of building a selling company where you
(08:44):
raise a sizable, nice seed round, then and youget to escape velocity from there on.
So you no longer need to raise consecutiverounds of funding, like precede seed, series a,
b, c, d, etcetera.
And there's lots of benefits on why seedstrapping, I think, is the ideal model for many
Lean AI hyper growth scaling companies.
And we can go into the differences in terms ofrevenue, founder dilution, ownership control,
(09:09):
founder liquidity, etcetera, etcetera.
But I think there's a lot of benefit now withLean AI that you can seasrap companies, and
you're seeing a lot of founders do this.
So give me a sense for what kind of companyshould be using seed strapping strategy.
I think almost all of
the Lean AI companies should consider thatbecause the good part about seed strapping is
you don't need to dip into your own pockets.
(09:31):
Right?
So you can start the company without having todip into your own savings, but you don't have
to constantly dilute yourself and chaseinvestors and be on the VC treadmill.
You can own control, grow over time, get moreliquidity throughout the process, and maybe
even buy out some investors over time early on.
So it's a benefit for in many ways.
In terms of the companies, I think if you're alean AI native company, it's a great bet.
(09:55):
If you're a consumer PLG, I think that's alsoyou're seeing a lot of companies successfully
do that.
If you're an AI enabled services company likeGrowthX, I mean, you can raise money, but it's
C Sharp 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 AIsales agents aren't quite good enough yet.
(10:16):
But as the capabilities of AIs AI agents getbetter and better, I think we'll see, the
appeal of Seastrapping for more and morecompanies.
You recently vibe coded an AIVC tool.
So first of all, what's your definition of Vibecoding?
And then tell me a little bit about this tool.
Okay.
So, basically, we use AI, my girlfriend and I,to build this tool that allows you to upload a
(10:41):
PDF.
The DI will do deep analysis, competitiveresearch, web crawling, and generate an
investment memo.
And you can also upload a forecast and Excelmodel, and it can do all the situational
analysis, planning, forecasting, and generate aterm sheet automatically.
So that's sort of what we built, and it's anincredibly it's incredible how someone with no
engineering experience, never taken a CS class,doesn't know what a terminal is, doesn't know
(11:05):
what what a HTML is, is able to build this toolentirely end to end, front end, back end, chat
interface, web search analysis, API calls,GitHub, GitHub actions, Vercel deploy, end to
end deployed all within a weekend.
So truly using just clock code and clock, andthat's, I think, the best definition of of vibe
coding.
As you can see here, all these interface,everything was built, just within a weekend and
(11:28):
entirely vibe coded.
And what's the use case that you're buildingaround?
Is it to completely replace VC analysts?
Is it
As I'm exploring this new way of seed strappingand supporting founders, I'm getting a lot of
inbound and requests in companies.
And I've always felt that the traditionalventure investing, especially in early stage,
was very vibes based.
(11:51):
Like, do I think this company is going to checkall the boxes and become a tech coin?
And frankly, how am I supposed to know?
And the irony is the investors, they get 1,000pitches, they reject nine ninety nine of them.
They probably don't even look at half of them,and they're all trying to chase the two
companies near that matter.
Right?
But that is that the sum of the revenue of thenine ninety nine they rejected is definitely
(12:11):
higher than the one they're trying to pick.
So my thought is how do you analyze andapproach and systemically analyze the 999 on
founders who have been in good great companies,but in a way that's scalable, automated, and
unbiased and transparent, and you can do thismuch more effectively now with AI.
You get way more detailed analysis than marketmarket, competitive trends analysis.
(12:33):
You get forecast built in.
So it just reduces the process and human biasesto 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 notdie, then I wanna fund you.
I wanna support you.
It reminds me a little bit of Dan Gross, who'sobviously a prolific AI investor.
(12:57):
He had this project called Pioneer, which triedto find these founders all over the world that
maybe didn't fit the Stanford, Harvard, youknow, 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.
(13:18):
If they don't get VC funded, you know, theyessentially never actualize.
Exactly.
Right?
And so much of it is pattern matching and andsort of trying to predict DecreCorn outcomes at
the earliest stages.
And I'm just not sure that's I mean, maybe it'spossible if you're the top sort of ten, twenty
firms, but for everyone else, I think it's sohard.
(13:39):
There's so much sort of selection and selfselection and versus supporting the nine ninety
nine founders who collectively that that's aton of revenue, I think, the leaderboard you
see here.
Obviously, a of them have raised funding, but alot of them haven't.
And collectively, it's, you know,3,460,000,000.00.
Right?
And and some of the best highest revenuecompanies have not raised from this venture
(14:02):
like Telegram, you know, billion revenue, notfunded mid journey, 500,000,000 plus $0 from
the Surge AI, a billion dollars, zero funding.
And so I think you're seeing a lot of thesefounders are realizing that's actually a better
way to build incredibly massive successfulbusinesses.
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Double click a little bit on the founders ofthese seat strapped businesses or these highly
scalable non VC backed companies, what are somecharacteristics that you see behind the
founders themselves?
I don't know if you've seen the meme of thehigh IQ and low IQ and mid IQ.
(15:30):
A lot of times you see these incrediblysuccessful repeat founders who built businesses
before the traditional venture funded way, andthey realized there's a better way.
So for example, I had a founder who reached outto me.
His last company was 400,000,000 AR.
Right?
400,000,000.
Starting a new company, he's like, hey.
Hey, Henry.
I came across your seed strapping thing, andI'm starting a new company, but I don't wanna
(15:52):
do a traditional YC SAFE or equity funding.
What other methods are there?
Because these founders, they've 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 arepeat founder.
Or sometimes the finance is another side of theend, which is, fortunately, they're maybe
international, didn't go to Harvard orStanford, didn't check the box, TAM's a little
(16:15):
small or something.
Whatever reason, venture isn't the rightinstrument.
They're like, sure.
This is a great alternative.
And then you have folks in the middle, like thefirst time YC founder.
Right?
So who are like, hey.
This sounds interesting.
This is cool.
It's nondilutive.
It's, there's no recourse, but I don't know.
It's different, and I should just do a safebecause Gary Tan told me to do a safe.
Right?
So you're kinda seeing this distribution, butmy hope is over time as you highlight more of
(16:38):
these stories, when these incredible foundersbuild incredible business outcomes, that more
people are gonna shift to the right of the tailand 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 startingto play in this realm, or would you see kind of
a new AI native incubator that's focused onthese seat strapping strategy?
(17:01):
That's a good question.
I don't know if traditional YC will get intothis sort of realm because their whole model is
based on marking up and fundraising and sort ofhaving the prepping the companies for demo day
and getting marked higher valuations offundraising and traditional venture route.
And actually very good at it because if you'rean incumbent and you're the best at that type
(17:22):
of model, why should you change?
It's been very profitable for them, and they'reAnd in fact, it's 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 a good you know, sort of peopledon't get it.
But over time, as AI and the capabilitiesbecome better and better, I think we're gonna
see more and more founders opt into this newmodel.
(17:45):
And I'm not sure if it's an incubatoraccelerator or a funding model or something
else.
My hope is that there will be more people whoare doing this.
So it's not just me who's thinking aboutinvesting in different ways, but there we can
inspire other investors to think about fundingthe, you know, 999 companies who are not the
two a year that become Decka coins.
And hopefully, that can translate to morefounder, more diverse founders, more
(18:08):
transparent fund funding, and more much morefair efficient process.
So that's how my hope is more people can dothis and and sort of realize that it's also a
great economic opportunity as well.
Because if you can get DPIs right away, right,your IRR is extremely high.
You don't need to wait ten years for an exit ora liquidity event.
You can get DPIs right away, and then you canrecycle that capital to invest in more and more
(18:30):
companies.
So double click
on the seat strapping model on the investorside.
So, clearly, this is a great model for afounder that's looking to maybe own 97, 98%,
the founding team of a startup.
Tell me about the dollars and cents ofinvesting on the investor side.
I've obviously tested various experimenteddifferent mechanisms and models of this.
(18:53):
And so the latest thinking and iteration is,basically, it's a nondilutive, nonrecourse
capital.
So it's not equity.
There's no control.
There's no debt.
And all all Fantasy do is they give me a a deckof the company, which I use my AI VC analysis
tool to do a deep research on, generate thatlandscape market mapping memo, and then a
(19:15):
fifteen month forecast.
And what it would offer is based on a 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 generategrowth and not die, then I wanna give you the
opportunity to get funded.
So for example so right now, it's structured asa bit of a sort of a line of credit, which is
it's not debt, but it's it's up to the founderhow much they wanna draw.
(19:37):
So let's just do round numbers.
Suppose I do analysis on the forecast, and Isay, hey.
You know, I wanna give you a million dollarsthat you can draw in over four tranches, and
it's 250 k per quarter based on hitting yourquarterly forecast.
So, again, right, the founder sets theforecast, 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 wannadraw, if any.
(20:00):
So it's up to them if they wanna draw allmillion or maybe only 250 k or half of it.
It's up to them, and that actually encouragesfounders to to be more disciplined about
capital.
And and the the structure is around five to 10%of revenue, and it's capped over two to five
years at two to three x.
Right?
So it's not cheap like a bank loan, but it'sway faster, and it's way cheaper than equity,
(20:23):
especially, you know, pre seed funding, whichis you're giving up 20% of company for
oftentimes a million dollars.
Right?
So it's capped for the investor, but it's highDPS right away, and it's an option for founder
depending on if they wanna use it.
And because sometimes what you see is you seefounders say, oh, look.
I raised a massive seed round, you know,$5,000,000, and I didn't even have to touch any
of it.
Right?
(20:43):
Even though and they're they're flexing aboutit, but it's actually that's actually kinda
dumb because you just diluted yourself 20 pluspercent, and you didn't even need the money.
So why did you do that?
So the the thing here is help encouragefounders to be disciplined with the funding,
give investors a way to invest in thesecompanies whether they become unicorn or not.
Doesn't really matter.
If you can hit targets, grow, and build a greatbusiness, I wanna fund you.
(21:04):
And it's a it's essentially a free option forthe founder.
There's no cost.
If you don't wanna use it, great.
You know, if one is 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 financialdiscipline, encourages people to actually set
realistic targets.
And whether they use my money or not issomewhat irrelevant because I I would've still
(21:27):
helped you build a better company if you canhit your forecast and actually build a great
business.
And this is based on the idea that they'realready revenue generating and already you
could scale up from some revenue number.
Yeah.
Right now, I'm focusing on we'll mostly oncompanies with some form of revenue, but the
goal in the future is to have all types ofcompanies because, again, going back to the
(21:48):
first principles.
Right?
The reason why fundraising is hard and annoyingis because the there's a fundamental disconnect
between a founder's projections and investorsbelief in their projections.
Because if you think about it, if the investorsactually believe the founder's projections,
right, then you shouldn't invest in everysingle company because they're always up into
their right.
If you actually believe, you should invest inevery company.
But the reality is investors don't.
(22:10):
And the other the thing that things worse,founders are incentivized to of juice the
numbers because they're all taught, oh, youhave to talk about a Decacorn unicorn major
outcome, whereas investors aren't interested.
Well, that's going back because investors areof these mega funds are looking for these mega
exits and only 20 plus percent of deca coins.
Right?
So both sides, people are sort of incentivizedto sort of not align on financials or
(22:35):
projection.
So the thing here is if you can just get thefounder to set their own projection that they
that they believe in and align the capital totheir own projections, then they should
hopefully align to and end up with great sortof businesses that if you can hit projections,
are gonna be good investments.
So to answer your question, over time, I dohope to support companies' pre revenue as well
(22:56):
because so long as you can make a forecast andhit those forecasts, then I wanna fund you
because that's as simple as it should be.
If you can hit forecast and build a greatbusiness, then you should get funding.
Whether you need it not, separate, but youshould at least get the opportunity for that.
To play devil's advocate, historically, I thinksomething like three out of four startups did
not give back one x their money at the seriesa, not even at the seat, but at the series a.
(23:18):
How do you make that work with a two to three xreturn at that stage if you're capping
yourself?
That's a good question.
And so one is I think the probability ofsuccess will be much higher now with AI and
these leading AI methodologies because it'seasier and cheaper than ever to start a
company.
Before, you had to raise a lot of money, hire abunch people, spend a lot of time on r and d,
(23:38):
get the product to market.
By the time you have this large team, you have,you know, hired series a, for example, twenty,
thirty, 50 people.
In those cases, yeah, you might actually die.
You might actually run off a cliff because youhave this high burn, and you can't grow revenue
fast enough or or whatever.
You have all this fixed costs of people, labor,etcetera.
You might actually die.
But now with the Lean AI approach, you can getto that level of skill with a very small team
(24:02):
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 codesometimes.
And by keeping being lean, nimble, and scrappy,you have optionality and flexibility.
Right?
Like, you're not gonna fall off a cliff becauseyou have five people.
You can always adapt.
Like, you can always pull back here and spendless and more on marketing, but you're not you
don't have this fixed, large fixed cost basewhere suddenly you run out of money and you
(24:24):
fall off a cliff.
So one is the cost a lot lower.
You have more control and flexibility, andyou're more nimble.
You can adapt quicker and you can adjust.
So I think that's that's why I funfundamentally believe survival rates are gonna
go up.
And what I often look for in these founders is,as as you know, a lot of times, companies die
not because of competition, but because ofsuicide, because the founders give up, they get
(24:46):
bored, they do something else.
So, really, it's more about the resilience ofthe founder and their sort of persistence and
and sort of conviction versus, oh, we're gonnaoverspend, hire too many people and run out of
money.
It's more about them just maybe giving up as asa failure mode.
So that's one of the on the on the on the onthe, excuse me, on the cost and problem of
(25:07):
success.
And then on the return side, oftentimes you'llsee, right, these are because oftentimes you
see companies that are great companies who arenow zombie companies because they're not going
fast enough and they don't have an exitopportunity.
They've the prep stack is way too high.
The early investors get washed out.
So I think you also see a lot of reasons whyinvestors don't return capital.
(25:27):
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 zombiecompany, zombie unicorn company, right,
everybody's stuck and you're not getting yourmoney.
Whereas if you're doing it on a rev shareroyalty basis, it doesn't really matter if you
get stuck at twenty, thirty million AR, right?
Because I'm getting a revenue split of that.
(25:48):
So I can still get my return and my money, andI don't need to pray or depend on an, you know,
exit.
And oftentimes, as you know, these exits, thecompany has to be growing really fit quickly,
and the mark has to be right, and the sort ofmultiples have to line up.
So if you're investing at a high multiple andthe multiples don't catch up, yeah, you're
underwater.
But here, you're investing and they're growingoh, excuse me.
(26:09):
If you're investing and making money, even ifthey get stuck and the multiples are low, it
doesn't really matter because I can recycle thecapital through rupture royalty and then
reinvest in more companies.
I like a lot of parts of this concept.
I like the seat strapping.
I I like the term that he popularized.
I like the higher return of capital.
I worry about the misalignment where you'rebeing paid off of revenue and you're also
(26:32):
getting capped at the upside that in invariablymisaligns you with the founder, not in every
way, but in certain ways.
And I think if founders went about just raisingless money and not chasing the headlines, the
$5,000,000 seed round like you mentioned, therecould be more concentric circles that work
better for the founder and the GP.
(26:53):
Sure.
Right?
And and that's why after many iterations, I'vestructured it more like a line of credit.
So it's up to the founder how much they wannatake.
Right?
So they don't need to use all of it.
Whereas for a traditional equity, if you get afinal seat, all of it.
Right?
Even if you don't need it, that's all of it onyour capital, you can't give it back.
Whereas here, it's meant to be structured in away that's founder's option.
(27:15):
So, yeah, they want the headline and some bignumber 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 withtraditional equity funding.
As opposed they wanna raise a 2 mil round, theyraise a million equity and a million in this
new format.
And so that way, they don't need to overdevelopthemselves.
(27:35):
And instead of doing a two on 20, right, maybenow it's a one on 20 and another one on this
rupture 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 failto get to series a historically.
You believe there'll be much lower death ratesor much higher survival rates for startups.
(27:59):
What percentage of these lean AI startups doyou think will make it as defined by being
ongoing businesses in the future?
That's a question.
I think the metric you mentioned is fail toraise a series a.
Right?
But I think that is maybe no longer thedefinition of success or failure.
Whether you raise a series a or not, maybe itdoesn't matter.
Because you're seeing companies here on theleaderboard that are just blowing past series a
(28:21):
numbers.
Right?
So I I I don't know that raising consecutiverounds of funding is a true success metric.
In fact, that might actually be the wrongmetric because now you look at all these
companies who are raising all these successaround and getting marked up, but the DPI is
the last, you know, fund cycle has beenterrible.
Right?
So so is that truly the measure of success orit's truly measured as capital return and DPI?
(28:44):
So I think that's maybe a sort of discussionpoint about definition of success.
Two is in terms of survival rate, again, Ithink if you're a lean company, you're not
doing deep tech, you're not doing some crazyenterprise sales thing.
If you're doing standard tech consumer PLNGannual services, and again, the fund is
(29:06):
convicted, they're keeping lean, they'rekeeping the costs burn low, and they're nimble
and they're scrappy and they're hungry andthey're motivated, I think this survive
survival rate will be extremely high, muchhigher than fifty, even seventy percent because
most companies die because I'm assuming youdon't fall off a cliff because founders give
up.
Right?
And so long as they don't give up, they'refocused and committed and they're nimble and
(29:28):
scrappy and and can grow revenue head targets,yeah, I think it's gonna be much, much, much
higher.
And to your point, if
you double click even further, why foundersgive up?
Sometimes they have this capital stack, thisprep stack of $5,070,000,000, and there may be
a a $20,000,000 business today, and they justlook at it and they say, it's gonna take seven
years, and then I'm gonna get screwed by thepreference stack anyways.
(29:50):
I might as well close the company.
So this misalignment happens kind of the fromthe pref stack as well.
Yep.
Exactly.
Exactly right.
So that's why it's not worth it for them, to tocontinue a company that's like a zombie
unicorn.
I have many friends who are
in that situation.
Well, Hendrie, I wish I had people like youaround and and these types of funding when I
(30:11):
started my first company in 02/2004, myfreshman year in college.
So thanks for doing this for the community.
How should people keep up to date everythingthat you're working on, everything that you're
writing about?
Yeah.
You can find me, my content on my LinkedIn, mySubstack, Twitter as well.
Feel free to reach out.
Kinda like you, my company, we we raised a150,000,000 venture funding, grew to
(30:32):
200,000,000 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 100 investors for our seedround, got 98 nos, one maybe, one yes for our
series b.
We talked to a 144 investors, got a 143 nos.
And so every time it was a big distraction, itwas a whole song and dance, a whole process.
(30:57):
And it just never felt like the as, I don'tknow, just straightforward and enjoyable and
transparent as it is building a company andtalking to customers who are actually creating
value.
And same for the investor side.
You know?
I'm an LP at some of the top funds.
I'm also an angel investor, and I've met yourpartner in some funds.
And you see them on this table.
It's hard.
It's a it's a frustrating process for theinvestors as well.
(31:17):
So much noise, very little signal.
Everyone's trying to pattern match exact sameway.
So just there's gotta be a better way.
And, hopefully, by talking about this, bysharing these stories, these success case
studies, and putting my money where my mouthis, 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.
(31:39):
I think the second order effects of this couldbe enormous, maybe five, ten times more
startups if if you take it to its naturalprogression, and people are able to start
companies.
You don't have to work at large companies.
You could start companies with almost nocapital down, with no without knowing venture
capitalists, without going to Harvard andStanford.
The the TAM for potential founders is prettyenormous and probably easy to under
(32:05):
underestimate.
Absolutely.
That's kind of the future thesis is can youhave these AI enabled one person AI companies?
And Sam Altman talks about the one personbillion dollar company, right?
Which I think we're starting to see because oneperson just got acquired for 80,000,000 cash
more of 80,000,000 cash upfront and another 80plus million in earn out.
(32:27):
That's one person.
And I think we're gonna see more and more ofthat.
But I think what's even more exciting is notjust 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, are more fulfilled, who aremore driven, more motivated.
And what is the tooling?
What is the stack?
What is the sort of capital allocation tosupport these one person or one person AI
(32:50):
native entrepreneurs?
David Deutsch in his in his book, Beginning ofInfinity, basically philosophically thought
about this question, like, how much innovationcould there be?
And there's literally an infinite amount ofinnovation that could happen because it become
starts innovating on itself.
So people need not be worried that there willbe more more and more opportunities for
everybody.
Absolutely.
(33:10):
And and one of the most fun and fulfillingthings after putting out the Leading Eye Angel,
which I'll share here.
So let me just share my screen here.
Right.
So after I've I've coded this site where peoplecan upload their deck and financial, and we do
analysis and generate a term sheet.
Right?
The cool thing is one of the coolest things ishow many people and innovators and
(33:34):
entrepreneurs all over the world have theseincredible ideas that I never even thought
about or even existed, and it's fascinating tosee them build incredible business.
And, again, like, it may not be what VC'spattern match, but these people are building
real businesses, making real money, growingexcel excel growing, accelerating, and
succeeding in their fields and domains and justincredible to see.
(33:55):
So, hopefully, we'll see even more of that.
Awesome, Henry.
Well, I'll be in San Francisco soon, so we needto, 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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