[BidClub_]
20VC · · 79 min

OpenAI’s $6BN Jony Ive Deal & YC Is Both Chanel and Walmart, and Has Officially Won!

Harry StebbingsKyle Norton

YouTube
TL;DR
  • At large, later-stage funds, portfolio-level math matters more than requiring one company to return the entire fund. Builder.ai reportedly raised about $500 million, projected roughly $200 million of revenue but delivered nearer $45 million, and shut down after missing projections; the discussion treated Insight’s loss as more than $100 million against a roughly $12 billion fund. Hinge Health returned about $400 million, or 5x, to a $6.2 billion fund. The panel’s conclusion was that venture does not always need a single fund-returner—although at seed, one is close to necessary.

  • At scale, the extreme right tail matters more than loss rates or middling outcomes. Large funds may need several $10 billion exits even though the market produces too few, so equal-sized portfolios stop working. The math may require putting 20–30% of the fund into the best company. As Brian Singerman put it, “The enemy of great venture returns is capital concentration limits in an LPA.”

  • Speed to $100 million ARR is valuable as a proxy and a magnet for success, not as proof by itself. The panel called investors “traction junkies,” but stressed that lower dilution, stronger retention and a larger moat can outweigh raw speed; “$100 million with low churn” is the meaningful version. In AI, momentum compounds because the hottest companies attract scarce engineers and the capital needed to pursue hypergrowth.

  • The reopening IPO market is exposing how little protection some late-stage preferred investors possess. Hinge Health went public with roughly $200 million of preferred stranded until the common reaches about $77, versus an early-$40s trading price. Chime’s terms could instead force conversion above a $6 billion valuation and crystallize a loss against a $25 billion round. The emerging rule is blunt: “Anything you can get around, people are going to get around” to complete an exit.

  • Higher entry prices, longer holding periods and employee dilution are compressing venture ownership. A 2018 seed deal at a $7 million pre-money valuation now has analogues around $30 million, while seed investors without pro rata may lose more than two-thirds of their ownership before IPO. Foundation-model companies can issue 9–10% annually for employees because the scarce talent sets the terms; “the capital providers are along for the ride.”

  • OpenAI’s roughly $6.5 billion Jony Ive transaction is a hardware option and a financing narrative, not simply a full-time talent hire. The design studio was acquired, but Ive was not joining full-time. One panelist saw a subsidized third device expanding ChatGPT from roughly 20 minutes per user per day toward continuous presence; another saw the recurring “hardware paranoia” that has led software platforms into expensive, often unsuccessful devices. At roughly 2% dilution, even a one-in-five shot may be rational, and “20 minutes to 24 hours” is a compelling fundraising story.

  • Only perhaps 20–30% of 646 tech unicorns may still merit billion-dollar valuations under the current exit test. The observable bar is roughly $200–$300 million of revenue, about 30% growth and profitability or near-profitability; even two successful IPOs per week would take about six years to clear the inventory. Public-market capacity is not the ultimate constraint—2021 managed roughly one IPO per day—so the decisive question is how many companies can meet the new quality threshold.

Digest · the substance, structured for research

1. Large funds need not rely on a single fund-returner

  • Builder.ai reportedly raised about $500 million, projected approximately $200 million of revenue but delivered nearer $45 million, and shut down after missing projections. The discussion treated Insight’s exposure as a hole of more than $100 million, while preserving the uncertainty over exactly how the shutdown followed from the debt holder’s actions.

  • A roughly $100 million loss against a roughly $12 billion fund is approximately 1% of the vehicle. Nobody likes losing that amount, but the discussion placed it beside the partners’ other outcomes, including Jeff Horing’s involvement in Wiz, which was described with some uncertainty.

  • Hinge Health supplied the inverse example: about 5x the money, or $400 million, returned to a $6.2 billion fund. The panel’s conclusion was that large, later-stage venture funds should not be judged by whether one company returns the entire fund. That is not an absolute rule at every stage: at seed, a fund-returner was described as close to necessary.

2. The right tail—and the capital behind it—determines returns

  • The illustrative 20-company model assigns roughly 30% to losses, 50% to solid outcomes returning about 1x and 20%—four companies—to outcomes above 5x, averaging about 10x. The four large winners contribute roughly 2x, while the base hits add about 1.5x, producing approximately a 2.5x fund return.

  • Changing recovery from 0.2x to 0.8x among failures barely moves the fund, and middling deals are definitionally unable to transform it. What matters is whether an expected 10x or 15x winner unexpectedly becomes a 20x, 40x or 50x outcome—an upside event that cannot responsibly be assumed every vintage.

  • Insight’s 43% ownership of monday.com at IPO illustrated the older concentration model. At multibillion-dollar scale, however, a fund may need six $10 billion exits in a year when the market historically produces only about four. Equal-sized bets therefore become arithmetically fragile; the math may require one company to hold 20–30% of the fund and become the major winner.

  • Hence Brian Singerman’s line: “The enemy of great venture returns is capital concentration limits in an LPA.” That logic applies more strongly at later stages, where investors have more information and larger checks, than at seed, where certainty is much lower.

3. $100 million ARR is both signal and competitive weapon

  • Beyond seed, rapid revenue is one of the strongest available proxies for commercial success. But it is not dispositive: a slower, less dilutive company with stronger retention or a larger moat might still be the better bet. “$100 million with low churn” was described as the meaningful version.

  • Speed also becomes “a proxy for and a magnet for success.” It draws scarce engineers toward OpenAI, Windsurf, Cursor and other visibly ascendant companies, while concentrating venture capital among businesses with a plausible hypergrowth story.

  • A company outside that cohort can still thrive, but it needs its own ecosystem: a recruiting advantage, lower capital requirements and a deliberate strategy for operating outside the hottest talent-and-financing loop.

4. Public markets are routing around preferred-stock protections

  • Hinge Health and MNTN demonstrated that an IPO market exists for companies with roughly $200–$300 million of revenue, solid growth and profitability or near-profitability. Hinge’s growth was cited at about 48%; MNTN was less aggressive but still produced a multibillion-dollar outcome.

  • Hinge raised money at a $6 billion valuation in 2021. Coatue appears to have reached some kind of agreement involving selling shares back to the company, buying common and converting. Other preferred holders did not make that agreement and remained outstanding until the common reaches roughly $77; the IPO priced in the mid-$30s and traded in the early $40s.

  • Those investors retain a nominal 1x preference, but in a non-interest-bearing instrument whose market value is visibly underwater. The discussion’s takeaway was that the market can isolate an unwanted preferred block while founders and earlier investors access liquidity and continue building.

  • Chime presents the opposite structure: the last two rounds have no block and must automatically convert if the IPO is above roughly $6 billion. If an investor carrying a $25 billion round sees common worth $12 billion, it records about 0.5x; one automatic-conversion term separates a stranded nominal 1x from an immediately crystallized loss.

5. The unicorn backlog is a quality problem, not merely a liquidity problem

  • Hinge’s structure and an acquisition completed with only about 80.1% shareholder approval were treated as evidence that once-implicit protections are weakening. With roughly $2.7 trillion of privately held assets needing liquidity, buyers and public investors may accept complexity that previously would have required a clean balance sheet or near-unanimity.

  • Of 646 tech unicorns, the discussion estimated only 20–30% satisfy a plausible billion-dollar test: roughly $100 million or more of revenue, growth above 20% and profitability or near-profitability. The stricter observable IPO profile is nearer $200–$300 million, roughly 30% growth and profitability or near-profitability.

  • At two strong IPOs per week, clearing 646 companies would take roughly six years. The 2021 market managed about one IPO per day, showing that public-market capacity can return; the real culling comes from how few companies can meet the new quality profile.

6. YC has become both an enduring business and an aspirational brand

  • Accelerators and incubators represent roughly 24% of venture deals, and the panel’s default assumption was that YC has won the category. It has four batches, is bigger than ever, brought in Gary and tilted forcefully toward AI despite not initially leading that wave.

  • YC was distinguished from an ordinary fund whose relevance depends on its latest picks. It converts founders from London, Sweden, the Midwest and elsewhere into marketable companies within three months for roughly 7%; if it vanished, the market would need another organization to fill that product gap.

  • A rough comparison gave YC a structural 2x advantage over comparable seed investing: where a competent seed fund might earn 3x, YC’s published hit rates and structural access could produce about 6x. The discussion also pointed to its move toward post-money terms, increased ownership, anti-dilution and more follow-on investment.

  • YC remains more compelling for many first-time founders than for second- or third-time founders, for whom it can be a niche product. Project Europe received 8,000 applicants, with perhaps 300–400 described as excellent candidates.

  • The memorable formulation was “Walmart and Chanel”: YC combines industrial scale with an aspirational brand. Making company formation easier should create more attempts and a few outcomes large enough to cover the failures.

7. Series A is hardest precisely where the best companies are obvious

  • Seed was contrasted with Series A through a “Walt Disney” test—“Tell me the story”—and a “Jerry Maguire” demand: “Show me the money.” Many founders can narrate an opportunity; far fewer show revenue that is simultaneously real, durable and attractive to a Series A investor.

  • The discussion distinguished between the broad Series A market and its hottest pockets. In fashionable AI categories, the small set showing explosive traction receives intense competition. One firm described losing two such processes, being outpriced in one and “out-beauty-contested” in the other.

  • That bifurcation also makes the failure rate between an increasingly accessible seed round and an institutionally convincing Series A easy to underestimate.

  • RevenueCat was compared with a similar-risk YC company: a 2018 entry at a $7 million pre-money valuation versus roughly $30 million for the newer company. After allowing for GDP growth and inflation, the discussion judged the newer investment perhaps 2–2.5 times worse per dollar, requiring larger checks to preserve ownership.

8. Compounding dilution has rewritten otherwise successful venture outcomes

  • One investor described maintaining roughly 10–11% initial ownership across five or six funds back to 2009, while increasing check sizes to obtain roughly the same ownership. Later entry rarely offers enough expected return at prevailing prices, and claimed ownership targets often do not fit the fund-size math.

  • Six percent annual dilution compounds severely over 10–15 years. Refresh grants, founder re-ups and option-pool governance in years seven through ten were described as low-joy, high-impact work, with an objective of containing annual dilution nearer 3–4% without losing essential talent.

  • An assumption of 40% total dilution from entry was judged too low for seed. The cited heuristic was more than two-thirds dilution by IPO without pro rata, versus roughly half historically. One investor also reported employee dilution of 9–10% annually in a foundation-model company.

  • The older economics show what has disappeared: Jim Andelman reportedly still owned roughly 9% of MNTN at IPO, about $180 million against a $20–30 million fund. Michael Kim at Cendana was said to have described Eric as 12x-DPI-ing the fund with HoneyBook, which returned $280 million to them; the discussion questioned whether comparable ownership would be possible today.

  • The broader conclusion was that vintage is an underrated determinant of venture returns. Older, less competitive vintages often preserved much more ownership, while today’s larger funds and heavier dilution can turn a similar company into a much smaller fund outcome.

9. The war a company chooses determines the dilution required to win

  • The governing rule was: “The wars that you choose to engage in dictate what it has to take to win.” MNTN and Hinge could create multibillion-dollar outcomes with $200 million-plus of revenue and 30–50% growth without competing for the same tiny pool of researchers as foundation-model companies.

  • Foundation-model economics reverse the hierarchy. The scarce people with the IQ, STEM knowledge and ability to generate the models matter more than capital providers, so companies issue whatever equity is required to retain them: “The capital providers are along for the ride.”

  • The OpenAI transaction illustrated the point starkly. Two people reportedly received about 2% of OpenAI in the relevant period: one party wrote a $6 billion check, while a roughly 55-person design studio was acquired under an arrangement that did not bring Jony Ive in full-time. Investors must accept those terms if they want exposure to that contest.

10. OpenAI’s hardware bet divides the panel on product, not rationality

  • One panelist interpreted the roughly $6.5 billion Jony Ive transaction as a bid for the “third device” after the laptop and phone. ChatGPT was said to have crossed roughly 20 minutes per average user per day; a cheap, stylish, always-present device could expand engagement toward 200 minutes or ultimately “20 minutes to 24 hours.”

  • The forecast was aggressive: launch within a year, subsidize the device to perhaps $20–$50, solve the form factor and possibly ship the 200 million units that the speaker thought Sam Altman had mentioned. Granola and Notion’s note-taking features were raised as examples that are useful as well as creepy because they can record or listen throughout the day.

  • The opposing view was historical: major software platforms develop “hardware paranoia.” Microsoft considered Nokia and built Surface, Meta pursued VR devices and Google built Pixel. Based on those precedents, the device could become a three-to-five-year fizzle, even if trying is rational.

  • At roughly 2% of market value, the bet can cover a one-in-five strategic risk. The hardware story may also support further fundraising: one speaker linked it to the roughly $50 billion OpenAI says it needs or expects to spend, while another framed “20 minutes to 24 hours” as the core pitch.

11. San Francisco’s advantage is density and systems, not superior humans

  • The Europe-side argument was that London can offer concentrated AI talent around ElevenLabs, Synthesia and Granola, while founders active in the right hackathons and networks can stay close to a local center of gravity. Paris and other European locations were also presented as possible advantages.

  • The Bay Area case was psychological and social: Dogpatch, YC founders and visible AI leaders create a “failure feeling” even among successful people. That density can push founders to compete harder because someone else is always doing better.

  • The counterargument separated people from infrastructure. Exceptional founders can emerge anywhere, and European founders who succeed despite weaker norms and systems may have unusual determination. But the US offers stronger systems for recovering from failure, raising capital and converting individual talent into a successful ecosystem.

  • The memorable formulation was that the US can take “mediocre people and make them damn successful.” The argument was not that Europe lacks genius or drive, but that its systems for turning those qualities into companies are weaker.

12. AI forecasts hinge on adoption speed, contracts and market structure

  • Duolingo was said to have produced 140 courses with humans over ten years, then 140 in one year with AI. Klarna and Duolingo’s public walkbacks were read as messaging concessions: companies with 500 employees or more reportedly tell people privately that they may not need 30–40% of their current teams, while publicly saying they are hiring.

  • One view was that mass layoffs could arrive within 24 months while net headcount remains broadly flat. The slower view was a steady grind of 2–3% less hiring annually, placing adoption nearer 60 months rather than 12–15 months. Both sides agreed that corporate messaging would settle into “AI makes us more efficient, and we’re hiring.”

  • On AGI, the discussion rejected a precise technical date. The term is ill-defined and may be declared when OpenAI or Microsoft gains leverage under their contract. One panelist took the under-2030 side, suggesting 2026 might feel like AGI while knowledgeable observers agree around 2028.

  • The corporate-tax view was that the current bill does not change the 21% corporate rate, which was made permanent in 2017, though it may contain minor international-tax changes. Separately, one California investor estimated paying roughly 7% more—not seven percentage points—after losing a pass-through deduction.

  • On a half-trillionaire, the near-term path was considered more plausible through Elon Musk’s private-company marks than through ordinary public-stock compounding. The caveat was that private-market marks have not yet been tested by the same public-market reality.

Speaker 1

The wars that you choose to engage in dictate what it takes to win. We have to let go of this vision that venture has to involve fund-returners. The only way the math works is if you stuff money into the very best company, and you don't end up with a balanced portfolio. You end up with one company having 20% or 30% of your fund in it, and that company turns out to be the big winner.

I think your absolute assumption has to be that YC has won. Look, it's one of the greatest equity businesses ever.

Speaker 2

Two Insight deals: a winner and a loser. It happens in this game. Insight had both Builder.ai, which raised $500 million, I think, across rounds and then shut down amid false projections. I read that they were projecting $200 million and actually had $45 million in revenue.

Let's start there. Losing $500 million is a lot. It's over a $100 million hole for Insight, I'm sure—maybe more. How did we analyze this one? This was a big hole.

Speaker 1

At first, I read it and was shocked. It almost seemed like fraud: losing $500 million on an AI website builder, right? But then, when I read it, SVB—or whoever held the debt—shut them down because they missed their projections. That's what I read happened.

Rory, when is that okay? Have you ever had a portfolio company or done an investment where the founders were more aggressive on their projections than the numbers they actually hit? Have you seen that in your storied career as a VC?

Totally. I'm shocked to discover that not every plan happens and not every company has 100% attainment of plan. But let's start with Insight's perspective: a $100 million loss, when I think the last fund is $12 billion, is approximately 1% of the fund. No one likes losing $100 million. Money is money. But in the context of the game they're playing, does it matter? Is anyone getting fired for this? Stepping back, does it matter?

Of course it matters, but whether you should get fired is the first question. If you do deals, as Jason said, you make investments. If your unit of account is $100 million—which is an impossibly large amount to any of us on this call, and still less to any of your listeners—it's just the nature of the checks you write.

If you have a plus-or-minus $10 billion fund, you write $100 million checks. Some of those $100 million checks don't work out. You lose the money. If you lose more than you win, you get fired, right? The good news is, I think Jeff Horing himself, the founder, was involved. He's made scads of money, and I think he was a big early investor in Wiz. I don't think Jeff is going to lose his job for dropping $100 million when he's returned a couple of billion dollars somewhere else. They'll all be just fine.

On the flip side, they had Hinge Health return 5x the money—$400 million. Great win. It's in a $6.2 billion fund. My take on that was: Is that just the nature of the game they're playing? Are they never going to have fund-returners by nature of it, or is that actually a pretty immaterial exit, as awful as it sounds?

Speaker 2

I think it's the former. I think they're playing a different game. We have to let go of this vision that venture has to involve fund-returners. As the fund size gets larger and the bets investors make are more later-stage, I think the probability of any one deal returning the fund goes way down.

It's not impossible at any level, but at seed it's almost a necessity. I defer to you guys on that; you have a better feel for it. Our model, for example, is that we do 20 deals. Roughly 30% are losses, 50% are solid and return 1x, and 20%—4 companies—return more than 5x, with an average of 10x. By definition, that means about a 2.5x return on the fund.

We've had fund-returners, but our mental model is that we have to get 4 of them right, each of them good enough to return half the fund. Therefore, you get 2x from your big winners, another 1.5x from your base hits, and there you are. That's a model at our stage.

Now, you go to a $6 billion or $8 billion fund—10x our size—and you're probably looking at some kind of model like that. If you're doing roughly equal-sized bets, it just gets harder and harder to assume that a single deal is going to transform the whole fund. You're left with this dynamic of having to make $500 million, have a happy day, and then say to yourself, “We're 10% of the way there.”

Rory, when you look at the historical data, where have your predictions of that dispersion of value been off? Have you had more losses and higher-upside returns? Where has it been off in the historical data?

Speaker 1

It's been pretty accurate overall. But what you'll internalize—and this is where all venture is the same—is that, if you think about the degrees of freedom there, you actually have 6 numbers. You have the percentage in each bucket and the value of each bucket.

The biggest single variable that can influence things is the return in the best deals. That's the thing that can save you on the upside. If you have 30% in losses and get 0.5x back in those deals, it doesn't matter much if it's 0.2x or 0.8x; it just doesn't move the needle enough. By definition, the number of deals in the middle bucket are middling, so the middling number can never change anything.

The only thing that counts is that you have to have 20% of them in the amazing-outcome category. Then the tail on that amazing outcome dictates the overall fund. I remember a venture guy I knew who had been in the business a long time. He basically said you have to have a model something like the one I just articulated, and then every 3 funds something utterly amazing happens that you can't really forecast.

Instead of that winner being a 10x or 15x, you get that one 20x, 40x, or 50x, and that fund is just amazing. Of course, it's a fatal error to assume you're going to do that every time because it's just not likely. That's how you think of the model.

Speaker 2

It's interesting, tying it back to the beginning of the conversation: Insight owned 43% of monday.com when it IPOed.

Speaker 1

Yes. Today, I hope they get more, right? It's harder today to collect 43% of the next Monday, right?

What you're wrestling with here for these large funds—you’re absolutely right—is that you can run the math, and then you do what Josh Kopelman did and ask how likely it is that there are enough exits at that size and stage to allow you to achieve your objective. When you run that math, you realize, “I need 6 $10 billion exits in 2 years—in a year, let's just say—and on average there are only 4 a year.” The math doesn't work, especially if multiple people are doing it.

What you end up with is that the very tippy-top of the tail is the only thing that works. Instead of having 20 equal-sized bets where you're trying to spread the risk, the only way the math works is if you stuff money into the very best company and don't end up with a balanced portfolio. You end up with one company having 20% or 30% of your fund in it, and that company turns out to be the big winner.

That's why, as I said, you look at Founders Fund and stuff all the money you can into one company, because it's the only way to deploy that capital. Brian Singerman always told me, “The enemy of great venture returns is capital-concentration limits in an LPA.”

Speaker 2

Yes, I love that. I always remembered it. It's especially true at scale. It's not Jason's enemy. It's not your enemy because, at your stage, you probably don't know enough to have the certainty to put 30% of the fund in one deal. Let's be honest: at seed, you know jack, right?

This is why the game has changed. When companies stay private for longer, the correct way to play the later-stage game is very different from the correct way to play the earlier seed, A, and B game. That's why these mental rules of thumb—that one deal has to return the fund—are wrong and irrelevant for the game those guys are playing.

What they have to do is return that $8 billion in roughly $500 million chunks and make damn sure there's one deal where they have 20% of the fund invested in it, and that it gets them $2 billion or $3 billion back. That's the mission, right? It's a different business.

Can I ask about one number that everyone is so focused on, especially founders? They are fixated on the speed to $100 million. We have Mercor, Lovable, and Bolt, and they're all in the race to $100 million. It's this AI wave that's so focused on it.

As investors today, how much weight do you put on the speed of getting to $100 million ARR—or X number of ARR?

Speaker 1

You'd be an idiot not to weigh it at some level, right? We're all traction junkies, and once you move beyond seed, traction is the best proxy for overall commercial success.

But you'd also be an idiot to weigh it at 100%. It's an interesting qualifying proxy, but it's by no means dispositive—the kind of boring, nuanced answer that I specialize in.

My worry today is that it would be nice to say, “Those are all great examples, guys, but a company that grows at a great rate, is less dilutive, and has a bigger moat is a better bet—or just as good a bet.”

Speaker 0

I’d like to think that, right? And maybe it’s true, but what I worry about in today’s world are 2 things: access to talent and access to capital. Talent has always been a moth to the flame of the hottest startups, right? But AI has just amped it up.

Every smart engineer, every smart kid wants to work at the hottest AI company. They don’t even want to work at the best B2B company. They don’t even want to work at Rippling or Deel, okay? They want to work at OpenAI or Windsurf.

Kyle Norton

I’m just going to say something in their defense: yes, they’re right. Wouldn’t you? If I were starting out in my career, the best advice you could give someone is to join an amazing company that’s going to be at the forefront of things for the next 5 or 10 years, so you can be there at the start, build the connections, and build the knowledge.

Speaker 0

So, yeah, it’s not like the kids these days are bad. They’re entirely rational in planning their careers. They’re joining the wave because that wave is going to last them the next 30 years, much the same way you started out in SaaS in 2004 or 2005. Great call; it gives you a 20-year horizon.

Kyle Norton

Well, I think that’s some of it, but especially in engineering, the smartest people have always wanted to work on the most interesting problems, right? And the most interesting problems are just at these companies. So, the fact is, the problem with the plodding pace, which I would like, is that it’s hard enough to compete with Rippling and Deel for talent.

All the best sales talent I know wants to work at Rippling. Half of my old team works there. You’re already competing with Rippling, but poor Rippling’s competing with Windsurf, Cursor, Granola, and Chola[?]. Then there’s access to capital, which is—I don’t think 80% of the B2B VCs, like we’ve talked about, want to touch something that doesn’t have a chance at hypergrowth.

If you’re not in that category, the math looks great, but you better have your own little ecosystem where you can thrive, your own little world where you can recruit and you don’t need as much capital. You better be cognizant of it and have a strategy there, right?

Speaker 0

Thank you, Jason, for bringing us right back where we started, which was this: Is $100 million meaningful? I think the answer we’re both giving is yes, it’s meaningful, because it’s just a proxy for and a magnet for success. It’s not perfect, because there will be churn. $100 million with low churn—that’s very bloody meaningful.

Kyle Norton

Yeah, but maybe it’s better to be in London. Or Paris, or somewhere else—maybe better, right? Paris, because it still shocks me, the employee churn rate at OpenAI. I can’t believe how many people leave. You’re leaving so much money on the table to go to another AI startup.

It’s not like they have the highest employee retention on planet Earth. I don’t know who did it, but that was quite interesting information on the Anthropic retention rate being significantly higher than the OpenAI retention rate. That was just an interesting piece of data, and maybe it speaks to why those investors are taking that dilution.

Speaker 0

I mean, if you want to look at it, whenever I’m on a board or on a comp committee and we start talking about, “Oh, my God, the dilution is too high or too low,” what I always say is, “I want to see 2 other pieces of data.” I want to see attrition: are we losing people? And I want to see the close rate on offers: are we failing to hire people?

Because in the end, forget morality—it’s a marketplace out there. If you’re losing people a lot, especially for economic reasons, or if you’re not able to attract the talent, then maybe dilution isn’t high enough. Conversely, if you’re not losing people, maybe we can manage dilution a little better.

Kyle Norton

In the Anthropic–OpenAI wars, I think they’re doing what it takes to keep people. Clearly, as you say, astonishingly, people are willing to leave OpenAI despite all that.

Speaker 0

67% employee retention after 2 years.

Kyle Norton

67% versus 80% for Anthropic.

Speaker 0

Yeah, 80%. That’s a big difference. It’s brutal, man. So much cash on the table.

Kyle Norton

Not everyone is as greedy as you are, Harry. What can I tell you?

Speaker 0

Soft. I don’t know if I know greed’s complicated. They may think that they’re getting more. Some of the problem is, if you’ve been there 2 years at OpenAI and you made $8 million in tender offers, you might think another $8 million is easy, right? The mindset’s complicated, but money secondaries can come quickly.

You know this game. By the way, I do want to go back to the Hinge IPO, because there was some stuff I was tracking a week ago. We talked about it, and actually got a lot more clarity on them over the last week. I think it’s super interesting, and it goes a little bit to, yeah, Jason, some of the stuff you circulated about the state of the unicorns and where they are, right?

We’ve had 2 IPOs in the last week: Hinge Health and MNTN. One of them is a digital health company, Hinge Health, and one of them is a digital advertising company for cable TV, MNTN. Solid businesses, $200–$300 million in revenue, decent growth, wonderful outcomes for the VCs involved, right? You take that and you take Chime as well, which is on file, and it’s kind of a proxy for a couple of takeaways here.

One is there is an IPO market here right now, right? You don’t have to be $5 billion. Much of the stuff that people said—the comments about how you have to be at $500 million, which I think is a VC comment, and the comment that the window was going to shut a month ago—both of them are wrong. Deals are getting done right now, in the last week, that are wonderful outcomes for all concerned.

That’s the first point: $200–$300 million. It is no longer $100 million; it’s $200 or $300 million. It’s growth, it’s profitable or near-profitable, but that’s what it takes to get something done. These are facts on the ground.

Kyle Norton

But 48% growth, right? Still pretty high.

Speaker 0

Yeah, Hinge is growing nicely. MNTN’s growing as well, but not quite as aggressively. Still, solid growth—you’re exactly right. And to your point, Jason, it’s actually terrifying how few of the unicorns are close to that level. We’ll come back to that point.

The other point—and this is now down in the venture weeds, but it really matters—I was trying to figure out how all those super-high late-stage rounds get processed through the lens of the IPO. In other words, does the last round have a block and therefore can stop a down round? Does it not have a block? Or was the last round low enough that it doesn’t matter? We now have 1 of each in those 3 names.

MNTN, I don’t think, had a prior round that had a block, and I don’t think they had a prior round that made the IPO a down round. Perfectly normal, boring IPO.

Hinge is really interesting. They raised money at a $6 billion valuation in 2021. That money clearly had a block—not that they could stop an IPO, but they couldn’t make that preferred convert to common as part of the IPO. In my mindset, which turns out to be wrong, that meant they could, quote, block an IPO.

Well, what happened? If you look, there are a couple of investors, and if you read the detail of the S-1, it’s very dense. What you figure out is that Coatue, who clearly paid $6 billion for a company that’s now gone public at between $2 billion and $3 billion, did some kind of negotiation. They sold some shares back to the company. They bought some common. They basically agreed to convert in return for some kind of make-good.

Some of the other preferred investors in the last round didn’t come to such an agreement. I thought they could, quote, block the IPO, but it turns out they didn’t. The preferred simply stays in place. That preferred doesn’t convert to common until they hit $77 a share. But the IPO got done.

What this is is the public market saying, “Hey, you guys want to go public? You’ve got this preferred on the balance sheet. Normally, we’d say, ‘Clean up the whole balance sheet.’ But we’re not going to say that here. We’re going to get this deal done.” The deal priced in the mid-$30s and trades in the early $40s. You’ve still got this stranded $200 million block of preferred that doesn’t convert to common until $77 a share, but that’s their problem. We don’t give a shit.

What it does, to some extent—and this is really significant—is weaken the ability of those later rounds of preferred to block an IPO. The market is working. The public markets are saying, “We can deal with a bit of noise. We can price this. It’s just stuck up there in preferred, and it’s kind of a little isolated pile of capital that’s clearly underwater because the common price isn’t high enough.”

So, it’s a 1x instrument, and therefore, on a discounted mark-to-market basis, it’s worth less than 1x.

Also interesting: if you’re them, you’d rather it was bought for $2 billion by someone else.

Speaker 0

Absolutely. If you can get an M&A, you get your money back. But this is what I love about it. Maybe they couldn't sell for $2 billion, or maybe the other investors correctly wanted to go on and build a damn big company. The big news here is that maybe the other investors correctly wanted to go on and build a damn big company.

Kyle Norton

So, do they lose money, then?

Speaker 0

Yes. They haven’t, quote, lost money because they still have their theoretical value. They don’t have to convert from preferred to common until the stock is at $77 a share. They don’t, quote, lose money, but they’re sitting there in a non-interest-bearing instrument that’s way out of the money.

The mark-to-market on that is now clear for all to see. Congratulations: you have preferred stock that’s a 1x, and you don’t make any return until the stock gets to $77 a share. It’s now trading at $40.

What this does is remove the ability of that late-stage, high-priced round to get in the way of everything. You can't make them convert. They still have their 1x. Good for them. But you, as the founding CEO, and you, as the early investors, can go into the public markets, get your liquidity, get your 10x if you were the first one, get your 4x if it's Insight, whatever it takes, and get on with your lives. That late-stage money is stuck at a 1x, 0% IRR, for the next 3 years. Knock yourself out. It's a really big deal.

Speaker 1

Some of these implicit protections we thought we had in venture are kind of breaking down.

Kyle Norton

Yeah, right. One of the worst investments I did was only able to get 80.1% of the shareholders to agree to an exit. The acquirer didn't care at all. Whatever the statutory minimum was, that was fine. The acquirer didn't care. It didn't care 1%; it didn't even attempt to get the votes from the other 19.9%. It didn't care.

I think what all these things have in common is that the capitalist universe is recognizing that there's $2.7 trillion of privately held assets that are going to have to go public, find a home, and involve a little more complexity than normal. But the great thing about capitalism is that people find a way. In the case of Hinge, they found a way to get it public with preferred stock. In the case of your deal, they found a way to just close the deal and accept the risk. I think we're going to see a lot of that because that's what it's going to take to deal with these 600 unicorns.

Speaker 1

All the rules—anything you can get around, people are going to get around it to go public or make a dollar, right?

Kyle Norton

In fact, I mentioned a thread on them. I didn't know the answer a week ago on Chime. Is there a block? But I got interested, as one does, and pulled the pre-IPO articles of incorporation. What are the terms right now?

The last 2 rounds do not have a block. They can be auto-converted, provided the IPO is above $6 billion. All the preferred converts to common. There's no way for that preferred to remain outstanding; it just converts to common at any price above $6 billion.

So, in answer to your question, Harry, in that case those investors will record an immediate mark-to-market loss. I had a 1x at $25 billion. Right now I have a 0.5x at $12 billion. I've taken a loss. It all boils down to one little term deep in the bowels of the liquidation preference auto-convert terms, which is what Hinge didn't have and what these guys did.

Speaker 1

Whoa. So they're going to crystallize the loss?

Kyle Norton

They're going to crystallize the loss. Exactly. In the case of Hinge, the preferred investors are just going to sit there at a 1x in an illiquid instrument inside a liquid common stock. In the case of Chime, they're going to get auto-converted, provided it clears $6 billion. If you were still carrying that at $25 billion, you're going to record a significant loss. If you've written it down already, you're fine.

So, this is not the great game that we thought it was, which is that you get your money back and then, when it pops, you get the premium on top.

Speaker 1

Absolutely.

Kyle Norton

No, no, there's a whole bunch. That's why I said, if you zoom out a million miles, this is all about what happens to those 600 unicorns. These are the best unicorns—the ones that can go public. What you're seeing is that some of the late-stage money has protection, keeps its 1x, and has a miserable IRR. Some of the late-stage money cuts a deal and says, “I'll roll the dice on converting to common as part of the IPO.” Then some of the late-stage money has no damn choice and just gets converted to common and takes a loss. There's a lot going on here.

Speaker 1

Oh, God. No, no. I'm not loving “seed is for suckers” anymore. This late-stage shit is fucking hard.

Kyle Norton

That is hard. Oh, God. That's not nice. If you're in Chime, you're going to crystallize those losses. You're going to lose 50%.

Speaker 1

Well, maybe not. Maybe it trades at $12 or $15 billion. I don't know where it trades, to be clear. I think it could trade much closer to that.

Kyle Norton

All I can say for sure is that they have a mandatory conversion. The later-stage rounds don't have a block, and if that conversion is exercised, they will be converted to common at whatever the prevailing price is.

Speaker 1

My only takeaway from this is that I want to be Jim Andelman with Mountain. We're just circling back and forth. As I said, we hated seed a week ago. Now we're like, “Oh, my God, only seed.” No shit. I just want to be at seed in 2013 or 2010. That's when I want to be.

Kyle Norton

Exactly. It turns out vintage is the single most important and underrated part of venture capital. Just being there for the good years.

Speaker 1

Listen, you mentioned the brilliant report that Jason shared. I thought one really interesting element was that accelerators and incubators are 24% of all VC deals. Twenty-four percent—accelerators and incubators. Does that mean YC has just won this game? How did you guys read that?

Kyle Norton

That was my point. I think, for the first time recently, there's more competition at the accelerator-incubator phase. There's more, right? But YC is four batches and bigger than ever. I do think they've won.

They also made 2 of the greatest strategic tilts. It's not the same YC as it used to be. First of all, bringing in Gary was a huge, massive change—obviously an uplift, right? For sure, a level-up, but also just a massive change on all levels. Second, I mean, it's obvious, but massively tilting into AI when they weren't ahead of the curve, right, and being a center to attract the best talent. Huge, huge.

It's very fluid, but, right or wrong, and I'm not into the brands, people want to go to Harvard, Stanford, and MIT, and the kids want to go to YC, right? They're doing this massive event for hundreds of the best kids in college, with the best people. I don't know what you think.

Speaker 1

When I look back, it seems new, but when I look back, all of my first investments were in some sort of accelerator. Five out of 5, right? So, it's not brand new. It's just bigger than ever.

Kyle Norton

I think your absolute assumption has to be that YC has won. Look, it's one of the greatest equity businesses ever, and I deliberately use the word “business” as distinct from just a fund.

The thing about being a fund, an investor like any of us, is that you're only as good as—I’ve said it many times—you're only as good as your last game. Every day, you have to get up and make good new picks. If you blink, and if you get the picks wrong, you're done. You're out. The world doesn't need you. There are 600 or 700 funds like you, right?

The beauty of YC is that they've got a business. The definition of a business is that if the owner of that business, Paul Graham, can be sitting back in England, walking around the cute little bookstores, and the machine keeps humming, that's a damn great business.

Why is it so great? Because the world needs one. The Valley needs at least one big accelerator like that. As you say, they'll take in anyone, provided they have the smarts and the know-how, and they can convert 2 people from London, 1 person from Sweden, or 2 people from the Midwest into highly marketable properties in the space of 3 short months, in return for a mere 7%.

The world needs that product, and it needs it on an industrial basis. Give them credit. Give Paul Graham credit. The original stated intent was to make it easier for startups. That was the mission, and they've succeeded. Because they've succeeded, they've built, as I say, a compelling business.

You can say sometimes it's better run than others. Some CEOs of that business are better than others. The current CEO seems to be doing a pretty amazing job, but overall it's just a great business.

I did the math once, trying to figure out—seed is not what we do—but how much better is the YC locked-in return than a seed fund at the same stage? They basically have roughly a 2x advantage. If you look at the deals they do, and then extrapolate based on the published hit rates and success rates, if a seed fund investing at that stage with decent picking gets a 3x, they get a 6x.

It's a structural economic advantage that's very compelling. It's a great business, and it should be a great business because, at the risk of sounding like a defender of free-market capitalism, it met a market need at scale. It met it brilliantly, and therefore they deserve the return. Go team. Wish I thought of it.

Speaker 1

I just think, for 2nd-time and 3rd-time founders, it's still a niche product. In my ecosystem, for folks that have been around, for every Parker Conrad who wants to do it again at a much better deal, other founders don't get it, right? But for 1st-time founders, it's absolutely YC and Project Europe are the beacons.

Absolutely. I mean, if I have to be honest, this is what gives me hope for Europe. We have 8,000 applicants to Project Europe. You know what? 300 or 400 of them are pretty fucking awesome.

Speaker 0

Totally. And we’re getting there—it’s amazing. Could not agree more. It’s that kind of thing that just wasn’t there. Again, going back to the mission, I give Paul Graham credit for being one of the clearest thinkers. I’ve never met the man, but I’ve read a lot of his work. He’s just such a clear thinker.

The objective was to make it easier for founders to start companies. That’s the kind of thing Europe needs. If you make it easier for founders to start companies, more companies will be founded. Most of them will be mediocre. That’s life. But some of them can be freaking amazing and cover a multitude of sins. That’s the way it’s meant to work. So, go Project Europe.

I think the thing that’s so amazing about it is I always say the future of venture is won by Walmart and it’s won by Chanel. Chanel is the incredible brand with a very specific customer base. Walmart is, whatever product you want, they’ve got it.

What I think is so special about YC is that it’s Walmart and Chanel. They have scale and they’ve retained brand. That’s very good. It’s still an aspirational brand that has managed to do scale. That’s hard. Let me repeat: I believe it to be one of the great enduring equity businesses. There are lots of funds, but there are very few enduring brands that occupy a clear niche.

The test you run is, if they went away, would someone else rise to fill the gap? Absolutely, because the world needs that product. If the 600th venture firm went away, we might just stop at 599 and say, “We’re good. Thank you.” That’s the difference.

I like to start with a comment that is completely unsubstantiated with data, but I feel like Series A is the hardest place to be investing today. When you hear me say that, do you agree with me? What’s your take?

Kyle Norton

I guess my question then is, if seed is so easy, that combination is really troubling, isn’t it? It means we’re underestimating the failure rate to Series A, right?

Speaker 0

Seed is easy because it’s Walt Disney versus Jerry Maguire. Walt Disney is, “Tell me the story.” There are lots of people who tell a good story and come from great companies. Then Jerry Maguire is, “Show me the money.” There are actually very few people who are showing the money in a way that’s true quality, sustainable, and attractive for a Series A investor. That’s why seed is good and Series A is hard.

Kyle Norton

Weirdly enough, I agree with you despite the data. On the other hand, I think what you’re saying is correct: for the stuff that’s working and in the chosen hot markets, there is mass competition because everyone wants to get the early traction in those AI companies that are just starting to explode.

So you are correct: if you are in the chosen sweet spots, almost every venture person is looking at those deals, right? Those are the very few deals that are widely competitive. We competed in a couple of deals in a broadly recognized emerging AI space. Brutally competitive. Didn’t win. I think we got outpriced on one and out-beauty-contested on the other.

Speaker 0

It is hard. It’s funny, going to Rory’s point of whatever you look at looks harder. I was thinking the other day about RevenueCat, where Harry and I are both investors. It announced that it raised its last round at a $500 million valuation, which actually was lowish. They just did a deal in 1 hour at a $500 million valuation, and I invested—I was the first investor in 2018 at $7 million pre-money.

That was right before YC, and I thought about a deal I did in the last batch that was probably the same risk profile at $30 million. Obviously, deals are done higher or lower at YC, but I’m saying there are some similarities between these 2 companies, RevenueCat and this new one. So, $7 million versus $30 million: how does that math work?

If the fund size is the same, do I need a 3- or 4-times-bigger fund? Am I taking 4 times the risk? Help me think about this, because I’m roughly thinking now. Granted, upside has gone up, right? That’s the meta point. But they’re still, I would say, the same at 4 times the price versus 2018. So do you adjust check size or adjust ownership on entry?

Kyle Norton

I feel like I have no choice. You write a larger check for the same ownership. If the round is bigger, you write a bigger check. If the round is smaller because it’s a YC deal and they don’t need as much money, you write a smaller check. I honestly feel like I have no choice.

Speaker 0

That’s not new. When I invested in RevenueCat as the first investor, I wanted to put twice as much money in. I just wasn’t allowed to. I could only buy 10%. But that is a question, right? Either way, where do I get the 4 times—the 4 times the fund or the 4 times the risk?

Kyle Norton

In mild consolation, Jason, I’d probably say it’s only around 2.5 times worse off, in the sense that you do have to give some credence to the fact that, as I’ve mentioned earlier, we just had huge GDP inflation over the last 5 or 7 years.

A buck today was probably 50 or 60 cents 10 years ago on a GDP basis—not just inflation, but inflation plus growth, which is what you have to look at. So it’s probably not 4 times worse, but you are correct: it is probably at least 2 times and maybe 2.5 times as risky per dollar as it was.

The second thing is, you’re exactly right: you do have to expand the check size because the truth is, you have to play the game on the field. We’ve seen that at our stage, which I think was typically at least a stage later than you, right? We’ve had roughly the same ownership targets for 15+ years and the same typical core deal size, but the check size has gone up to get roughly the same ownership. That’s just the nature of the beast.

I have a slide in our deck where we point it out to the LPs and just say, “Look, this is the dynamic of the marketplace we’re in now. This is the scary part of the game.” Do you guys honestly get 15%?

Speaker 0

We typically get around 10% or 11% ownership, and that’s been pretty consistent across 5 or 6 funds, all the way back to 2009. It’s a pretty typical median.

We don’t navigate off ownership targets because, as I tell people, I would happily go later and take less ownership if I could get our target return. But in the pricing environment for the last decade, frankly, it’s been almost impossible to have clarity on average that a later-stage round would give you your target return.

Obviously, some later-stage rounds give an amazing return, and we can come back to that discussion some other time, but on average, probably not. So it’s typically been those early-revenue companies at $2–3 million, growing hyper-quickly, where you’re glad to get 10%, and 20% is not on the table for sure.

Everyone gets less ownership than they claim on Twitter, right? Every seed manager is like, “We’ve raised a new $30 million fund. Our target ownership is 15%. We’re going to do 25 of those in the fund,” and the math just doesn’t make sense on planet Earth, right?

The bigger learning for me—and it really kind of snuck up on me—is that companies now hold for so long, and you hold these investments for so long. I did not fully understand the compounding nature of dilution.

If you model 6% dilution per year for a portfolio company for hiring, and you hold that investment for 15 years, what is 6% compounded over 15 years? Is it 9% ownership, isn’t it?

Kyle Norton

Totally. I mean, it’s obviously not 9%, but you’re exactly right because it’s a descending scale. The impact of dilution over time is huge. On the other hand, you can’t avoid it, because you do want to hire.

It’s an interesting discussion. Honestly, the least enjoyable, least rewarded, but most necessary part of my job as a board member is that I’m often on committees where you’re trying to set up policies for companies not in their first 4 years of life, but in years 7, 8, or 10, where you’ve got to grant new shares and re-up founders.

Sometimes I think that’s a very legitimate thing to do because you want them incentivized, but at the same time, you’ve got to manage overall dilution. Trying to keep it down—not to the 5–6% level, but to the 3–4% level—and manage that over time is really important.

You’re exactly right: 6% a year for 6 or 7 years, or even 10 years, is a huge impact on everyone, including the founders and the initial equity investors. Spending a lot of time on refresh policies for mid-stage tech companies is, as I say, the combination of low-value, low-joy, high-impact work.

Speaker 0

It’s so funny you say that. I was with an investor this morning who said that the challenge with LLM investments—and we have one of the best—is that the employee stock is 9% a year. It’s not 6%; it’s 9% to 10%.

So, actually, the level of dilution on the employee stock grants is so much higher than traditional investments that it makes it an even harder venture category to invest in, which I thought was interesting.

Speaker 1

Yeah, I’ve heard that. Sorry, Jason from Google.

Speaker 2

No, no, I think it’s gone up. My view, when I look at the exits I had in 2021, when everyone had a lot of exits, is that I haven’t had a billion-dollar exit since 2021. It may be quite a while until I have one.

The dilution—I made up a term, “dilution profile,” which probably makes no sense, but that was a term I made up on SaaS a while ago—was much lower in 2021 than it is today. I look at those exits and I’m like, “Man, I owned that. It was pretty good.” If I looked at the companies today, I’d say, “I’m not going to own that much at those exits.”

They’d better be much bigger exits, because otherwise I’m going to own so much less. So, when I go into a deal, I assume 40% dilution from my entry. Is that a reasonable heuristic, or am I over- or underestimating?

Speaker 1

It’s too low for seed. No, it’s way too low. I think you’ve got to assume over two-thirds dilution from seed if you don’t do pro rata to IPO. Two-thirds.

Speaker 2

Well, I think there are two types of dilution. Obviously, there’s the following-round dilution and then purely the option dilution. I’m not sure which one you guys are talking about, but I’m combining them all to two-thirds. I think it used to be half if you didn’t do pro rata. Now, I think two-thirds is absolutely right.

There’s a very pure test to this, with lots of data associated with it: you just look at Y Combinator, because they have fixed ownership every time. They have 5,000 data points. If you felt strongly about calculating the answer here, you’d just look at their ownership at IPO and have a statistically valid sample. Go do the work.

That’s why they’ve dramatically increased their ownership. There are no dummies there at YC. Moving to post-money instead of pre-money is supposedly for the benefit of the founders, but then they raise their ownership, have anti-dilution, and invest more. They’re the only ones that have caught up, I think, which is why I see more power.

Speaker 1

I want to go back to the foundation-model comment, because I think it’s something that we should internalize and get humble about. We, the capital providers, are not the most important people in the equation, and you’d better just internalize that. That’s the way it is.

The important people in the equation are the people with the IQ, the STEM knowledge, and the ability to generate these models. Anyone running those companies is going to pay those people what it takes to keep them. Frankly, tough shit on the dilution from the capital-provider side. That’s the nature of competing in a huge talent war for small numbers of people who can do amazing things.

So, yes, you can bitch about it and say, “Oh my God, that’s awful,” but it’s a cost of doing business. I think it segues because we just had the largest single instance of dilution in a foundation model in terms of an acquisition this week, which is obviously, at some level, an acquihire.

Speaker 2

What you can see is that it takes 2% dilution, or $6 billion, to hire 1 really great VP of hardware engineering and a solid team under him. The capital providers are along for the ride. You’d better like the terms of trade and internalize them. You don’t have to like them, but you have to accept them if you want to play.

The terms of trade are being set by the leaders of these companies and the need to attract that amazing talent in a very competitive world.

Speaker 1

It was funny. I was looking at MNTN, which IPO’d. How do you say it? MNTN? They call it Mountain, by the way. I funded it, I think, in 2009, and immediately Jim Andelman, who’s at Bonfire and who I’ve known as an OG SaaS investor, flipped the prospectus and said, “How much does he own after all these years?”

I think it was probably Bonfire I. It was probably a very small fund—we could look it up, $20–30 million—and he still owned 9-something percent at IPO. I’m like, “That’s old school. This is going to be a good deal for him.” The market cap is only—and I’m putting this in quotes—“only” $2 billion, but if he owns $180 million on a $20–30 million fund, that’s a great outcome.

Today, in a company just like MNTN, you’d own half that at IPO or less. The fund size might be 5 times bigger for seed. So instead of a 5x or 6x performer, it might be a 1x. Sign of the times.

Speaker 2

You actually had this with Michael Kim at Cendana, who said that Eric 12x DPI’d the fund with HoneyBook. HoneyBook returned $280 million to them. I thought it was incredible. But would that happen with HoneyBook today? Probably not.

Speaker 1

The thing is, when you look at these old deals, they’re great because they were all modeled on much smaller exits and much less competition, so you could get the ownership. These old-school founders often don’t have the same dilution. I read through the prospectus. I didn’t say it, but I bet the MNTN guys were very conservative on management. There’s no way Jim could own 10% over all those years if the founders were giving away 10–12% of the company a year.

Speaker 2

But I also think, as they say, horses for courses. We’re playing a different game, and even today there are different versions of the game. I think MNTN was trying to build a profitable company in a defined space where you’re not competing against a gazillion companies. Even at the time, you weren’t competing against the largest-value, highest-market-cap companies on the planet.

It’s very different from building an LLM today, where you’re competing against Microsoft, Google, and OpenAI. The wars you choose to engage in dictate what it takes to win.

Speaker 1

I think the big aha from this, Jason—and you’re right—is that you can create meaningful economic value for yourself, your investors, your fund, and yourself as a founder in markets that are significant but by no means have the hugeness of the AI foundation-model bet. MNTN is a great example of that, as is Hinge, the other IPO in the last week.

Those are 2 really solid companies, with $200 million-plus in revenue and growing 30–50%, depending on the 2 deals. They’re solid outcomes—multibillion-dollar outcomes. Everyone involved made money, but we’ll come back to some nuances on that.

Speaker 2

Yeah, great classic venture outcomes. It’s just a very different game when you’re trying to compete with someone who has publicly stated it’s going to take another approximately $50 billion to get to cash-flow break-even.

Speaker 1

I do just want to take this a bit in turn, because there are so many elements.

Speaker 2

Too much?

Speaker 1

No, no, it’s fantastic. We mentioned Jony Ive. Obviously, we saw the acquisition for $6.5 billion of his design studio and company by OpenAI. Is it a simple acquihire? And when I say simple, I don’t mean cheap, but is it a simple acquihire bringing Jony in to do a hardware play for OpenAI? How did you guys read it?

Speaker 2

Well, look, first of all, it was really interesting that he’s not joining full-time. He’s still managing his design firm, which was an important point. I’m sure it’s been worked out, but it’s super interesting. It was clear he’s not joining full-time. They’re just buying the startup that he’s a founder of.

So, for all of the $6 billion, they’re not even getting him full-time. They might be getting most of his time. I’m sure they’re his top client, but he’s not joining full-time. Of all the things, I thought that was a sign of the times: you had to pay $6 billion, but you could get away with not getting the guy full-time as part of the deal.

Speaker 1

Sam’s so smart, right? He was clear in that video. He was like, “I want the third device. The laptop, the phone, and the third device.” At first I laughed. I thought, “Of course, that’s what every tech dude in San Francisco wants.”

But then they said, “Listen, ChatGPT has crossed 20 minutes per day for the average user.” Going from 20 to 200 minutes with a device for a small percentage of your market cap—you could have 10x the coverage, 20x the coverage of a life. If this is the right guy and the right team, that might be the best investment they could make: to go from 20 minutes to 200 minutes.

I think we’re going to live in a world where our AI listens to us 24 hours a day, one way or the other, whether it’s on our watch, this device, our screen, or in the background like Granola or Notion. It’s always going to be listening. I think it might be a war he has to win to always be listening. “Might” is, of course, the word here.

Speaker 2

I mean, stepping back, every single significant software-platform company develops hardware paranoia at some point in its life—the feeling that somehow the hardware guys are going to screw them, and the only way they can stop themselves is by spending a whole ton of money attempting to build a hardware platform.

They almost invariably fail, but you’re kind of like, “That’s the cost.” Making sure that doesn’t happen to you and scratching that terrified itch is just part of doing business. If you look at Microsoft—“Oh my God, Nokia is going to get us. We should buy Nokia.”

Speaker 1

Oh my god, we should build the Surface. If you look at Facebook, it's, “Oh my god, we should build these VR devices because otherwise we're going to lose in the multiverse.” If you look at Google, it's, “We need to own the phone.” So they crank out Pixels at absolutely no margin.

Everyone does it. Who is Sam to break this time-honored tradition of spending a lot of money on a hardware device? My guess is that, statistically, the likely outcome, based on the priors of the other companies in the space, is that 3–5 years later it turns into a fizzle. It wasn't a product; it didn't pan out, but it's okay to try.

Speaker 2

No way. This is going to be huge. It will launch in a year. It will be massively subsidized, so it'll be $20 for this device.

They will figure out the form factor. I don't know what the right combination is, whether it's embedded in your ear, like the baristas—the cool coffee guys—wear, or whether it's that lid you wear backwards. Within a year, we will be living all day long with AI, and the timing will be perfect.

Speaker 1

This is great because we now actually have something that we can track and disagree about. I'm not saying it's dumb. I'm simply saying it's an itch that every platform vendor has to scratch.

Speaker 2

What you're saying is you believe that we will look back 2 or 3 years later and go, “Wow, they shipped a meaningful device with meaningful hardware revenues as part of the overall OpenAI business model.” I think he said he's going to ship 200 million, and I don't think that was a throwaway comment.

Speaker 3

Okay, here's the difference between us. One difference, though, is I spend almost 2 hours a day in AI already. This was 4 months ago. I spent 2 hours a day in AI between our AI tools and everything. I don't do anything without AI anymore.

So I can already see it. I can already see that. Listen, I'm scared about it. I'm scared that ChatGPT will now rewrite itself not to shut down. I don't think that's a joke. I don't think it's a joke that Anthropic's Claude Opus 4 is threatening researchers with blackmail for affairs. I don't think it's a joke. But I'm already in AI for 2 hours a day, all day long.

I mean, literally, at SaaStr Annual this year, one of the folks who helped put us on—he rewrote the best summary of the day, that day, of his day. He led an entire day. He hosted our chief customer officer summit, John Gleason, and then that day he wrote the best summary of the entire day.

How did he do it? He just had Granola running on his phone 24/7. We could have Granola—I could have Granola. I'm not running Granola now, but I might next week so that I don't have to do anything. Granola just runs.

Speaker 4

Granola and the new feature from Notion are pretty cool and pretty creepy. They run at the hardware level. You don't know it's a note-taker. You can't see anything. It's recording every minute of the day.

And again, I agreed with all that, Jason. But actually, the key sentence for the market, for the 200 million consumers, is that it ran on the phone, right? How many people are going to be willing to spend $200, $300, or $400 for another device and then make it part of their daily lives?

Speaker 2

It'll be $20. It'll be $50, and it'll be cool. The thing is, Jony Ive will make it cool.

Don't get me wrong. I didn't get it at first. It took me a beat to think about it. If it's cool, and it's the elusive next device, I think all Sam needs is for it to be cool and to work, right?

Just think about the connected Ray-Bans that everybody has. They're wildly successful. They're wildly successful.

Speaker 1

But going back, my first comment is that I think it's okay to try that, right? Because when you're at the stage OpenAI is, you should make those bets. And it gets right back to the comment on dilution, even. It's very sobering.

Just think about it: 2 people got 2% of OpenAI in the last 3 months. One of them wrote a $6 billion check. Have any of us ever seen $6 billion? Have any of us ever had it in our account? No.

The other one signed a part-time working deal, sold his 55-person design studio, and got the same amount of money. If that doesn't show where the capital providers stand in the hierarchy in the great AI race, nothing does.

I'm sitting there as SoftBank or someone like that. I just wired you $6 billion, and you effectively took that $6 billion and gave exactly the same ownership to a 55-person startup.

Speaker 4

Can you also just—I think we need to remember that Sam will need to go out and raise more money. He says he needs to spend $50 billion. What this enables him to do in terms of a storytelling narrative is unbelievable.

Now he's got a hardware play done by the guy who did Apple. The Saudis will give him more money than he needs with this new chapter, this new challenge that needs funding. It's a great story.

Speaker 2

Absolutely. “20 minutes to 24 hours” is a great argument. That would be my slide. We're going from 20 minutes a day to 24 hours a day.

Think about if ChatGPT could be monetized per minute and then per human. That's a lot more revenue. Twenty minutes to 24 hours a day—that might be the strongest PowerPoint argument that ChatGPT is underrated, right?

Speaker 3

But I think without this, getting another $20 billion for the next model is hard. It's starting to exhaust the insight that I probably missed.

Speaker 4

Yeah, totally agree in terms of storytelling. This is the kind of thing you do. And as I say, even if you look back—and that's the thing in these hypergrowth markets where almost nothing is certain—you would far prefer to take the dilution and cover the base than be wrong and get sideswiped, right?

Once things settle down and the paths are more obvious, maybe several years from now, when some view of the world will emerge as it did with the iPhone—where you put it all in this single device—it'll become much clearer. Then you probably wouldn't spend $6 billion on a one-in-five shot. But right now, making that kind of bet totally makes sense, right? It's also 2% of market cap, so it's not a Hail Mary.

Speaker 5

And Harry, I can say you're sitting back there in England, and you must look at Jony Ive and go, “Oh my god, if every STEM and design graduate from every high-quality London college isn't figuring out how to get on a plane and go to San Francisco, I don't know what they're thinking.” Six billion dollars.

Speaker 6

You know what I'm thinking, Roy? I'm thinking Americans still have to buy Europeans to get some taste. You know, the other thing I did kind of like about Harry—you’re exactly right, Harry. That's why Europe has 1 very rich entrepreneur who does taste, Bernard Arnault, and we have the other 9 who do tech and have all the money.

So knock yourself out with your taste. Taste you can buy. Cold, hard tech lasts forever. So, yeah, you can feel good about that.

Speaker 5

You know what I love? I love the American banking sector. Years of trying, you guys create all this enterprise value. We have a Russian in London who creates a $100 billion behemoth that makes Chime and everyone else look like child's play.

Speaker 3

I want to go back on that. I didn't realize you were going off on that tangent. I'll tell you very directly: that's partly because you have a mediocre incumbent banking sector there, and thus there's a huge amount of surplus value to be extracted.

It's just like—what are the guys in Brazil? I'm sorry, Nubank, right? The crappier the existing banks, the bigger the opportunity for fintech. Broadly speaking, in the United States, with a few exceptions, some of these existing companies are pretty efficient. So you're right: there wasn't the same idiocy to attack there, and the opportunity for fintech was a tougher business to get to scale.

You had the countervailing fact that you have Visa and interchange revenues, which are pretty exciting in the US. So that's been an advantage to the US over Europe, where they're more capped. But I don't think attributing success in fintech in London to the greater entrepreneurial qualities of Russians living in the UK is perhaps the most logical analysis.

Speaker 6

Harry, I agree. We should instead look at a Swede who created Spotify, changed the music industry, and created a $100 billion company.

Speaker 3

You're right. Yes. Look, I'm delighted to see you guys have some wins. I'm a European too, you know.

But the truth—genuine comment—yes, it's wonderful to see Europe have some wins. Unfortunately, the data just shows that the vast majority of market cap in venture and technology is being created first of all in the United States, second of all in China, and then Europe is a far distant third.

You'd love to change that because, broadly speaking, despite recent events, Europe is broadly on our side. It would be good for the United States if Europe would get its act together and have amazing technology companies. But for some reason, you just don't seem to be capable of doing it. Sorry, that was harsh.

Speaker 6

This wasn't even on the agenda, Harry. This wasn't even on the agenda.

Speaker 3

Actually, Harry, let me ask you a question about a vibe check, because I'm curious. I've been going to London for years and have done a lot of Europe-to-US, but, objectively, the pull of San Francisco for AI is so powerful. We can argue over France, but it is powerful to founders.

Is it powerful in the entrepreneurs that you meet across Europe? I mean, EF is hybrid now, isn't it?

Speaker 6

I'm going to get in trouble for this: EF sold itself out by going to San Francisco. It's a complete sellout.

To your question, we have a huge number of people who say you can only build companies in Silicon Valley, so people—and I'm not one of them, especially young people—are very aware within the founder communities that it is incredibly hard to retain great talent in San Francisco. It's incredibly expensive, and you're competing against OpenAI and Anthropic.

So, yes, it has the allure of Hollywood for our industry, but I think when you dig beneath the surface, the smart ones are going, “Actually, I can get better people, often for cheaper, in London, where DeepMind is, where there is unbelievable AI talent.”

Speaker 1

Absolutely. The reason I asked about the vibe is that you can’t afford anybody in the Bay Area as a startup. Inflation is so high, to our point. But here’s the thing: it took me a little while to realize that the San Francisco Bay Area is not what it was pre-2020. In some ways, it’s smaller.

But if you’re a solo founder, if you don’t know anybody, or if you’re an outsider, the sense of community in AI that you get in the Bay Area is so powerful. In 2019, I would tell founders to come to the Bay Area because if you’re in B2B, you walk down the street and you’re going to see everybody, because we’re all working in an office, right? But it’s more this community.

I underestimated the power of sitting in Dogpatch, seeing every YC founder, seeing Sam Altman on the street, seeing everybody. The density is actually higher than 2019 for AI founders—only for founders, not for SDRs, marketing managers, or everybody else. But for founders, it’s nuts.

The density is a smaller community, for sure, but that actually makes my life easier because we have 3 companies that are crushing it and have created an ecosystem just in themselves: ElevenLabs, Synthesia, and Granola. All 3 of them have created a mentality that you can build amazing AI businesses in London, so it’s actually easier for me because it’s a much more concentrated supply of great AI talent that’s not as distributed as the Bay Area.

As long as you’re in the hackathons, hanging around ElevenLabs, and hanging with Mati, you’re kind of near greatness. It’s easy. But do you feel, as a founder—and this is going to sound facetious, but it’s not—like you’re failing every day as a founder? Because that’s the special part of being in San Francisco: you feel like you’re failing every day compared to everybody around you.

Kyle Norton

It took me a while to internalize what you’re actually saying. I thought you were saying, “Are you failing in London?” What you’re basically saying is that the core San Francisco value proposition is a feeling that, no matter how well you’re doing, someone else is doing better and you just have to compete more. Is that what you’re saying?

Speaker 1

Listen, right now, I feel like a failure. The instant I get off a plane in the Bay Area, I’m not joking—even I feel like a failure every day in the Bay Area. Sitting here at the beach for 1 week, I’m feeling like I’m a success story right here, right now. I’m not kidding.

I haven’t been full-time in the Bay Area other than this last year, and I felt like a failure every day. The YC company I invested in hasn’t announced it yet, right? The one I compared it to. The founder is a pretty good AI guy; he’s, like, 26. I feel like a failure. I had 1 small exit. I’m falling behind everybody, right? He literally works 7½ days a week, and it’s just that failure feeling.

I think it’s bigger than ever, and I yell at some of my founders to feel like they’re failing sometimes. I yell at them. I’m like, “You should feel that way.”

Kyle Norton

My mother would argue that I have too high an opinion of myself, but I have a high opinion of myself. I’m a fucking machine, and I’m not motivated by an external person. I’m motivated by the internal fire in me, and the greatest founders that I know are motivated by that internal fire.

Being in London, I push myself every day to be better. Everyone around me is relatively mediocre, generally speaking, so I don’t need them to make me feel like a failure. I will push myself, and the best founders push themselves.

I don’t think the London-versus-San Francisco thing is a function of that, to be honest. I think anyone who’s built a successful company, like the 3 you mentioned, has shown that the drive it takes to do that in a country where it’s not the norm speaks to something even more powerful in those entrepreneurs. Over here, it’s almost like you go to Stanford, you drop out, and you go to Y Combinator. It’s almost the preset path.

Whereas, for someone who has been an entrepreneur, frankly failed in London in the UK, and gone bust, it’s incredibly hard in Europe to be entrepreneurial. Therefore, the people who do it have something really determined and awesome about them. At a human level, I’m not worried that those guys aren’t competitive enough. I don’t think that’s the issue.

I generally find people are roughly the same the world over. I think what is true is that the systems to become successful are way more powerful in the Bay Area than in Europe. You’d like those systems in Europe to be better, but, just as an objective statement of fact, your ability to bounce back from failure, your ability to get capital, and all the other things make it a lot easier in the US to be successful.

To make this very concrete, I always used to say to people, talking about Europe, “Exceptional people rise to the top anywhere in the world.” The strength of the United States economic system is that we can take mediocre people and make them damn successful. That is the secret superpower of the US free-market economy.

The truth is, mediocre people in Europe can often drift off into government jobs or whatever safe sinecures. In the United States, the free-market system keeps the whip on everybody’s back, and as such, a lot more people have to strive and become successful.

I don’t think there’s any lack of genius in the UK or Europe, just as there isn’t here. I don’t think there’s any lack of drive in people. It’s just that the systems to transform that individual talent and drive into a successful ecosystem are so much stronger here.

Speaker 1

We mentioned Duolingo, so let’s go further on this. You’re always proclaiming that AI is going to replace all of our jobs, and then we’ve had Klarna backtrack on it, and now Duolingo is backtracking on its AI stance. Are leaders getting way ahead of their skis and then walking it back? Is this going to be a continuing trend?

Kyle Norton

Fundamentally, when I read that, it sounded to me like every backstage conversation I had at SaaStr Annual this year with public-company CEOs. They’re trying to guide folks to a truth. Not everyone can say what Fiverr said, right? Fiverr got there really fast: “We’re going to go AI-first, and we’re not going to hire anybody. We don’t need to. AI can do better than our contractors, and we’re only going to hire people when we have to.”

I think public companies are trying to prepare their teams for it, but the backlash was too strong. He had to walk it back to 70% of the truth when he said, “We still need the same number of employees.” In fact, they all say, “We’re hiring.” That’s what public companies always say: “In fact, we’re hiring,” because that seems to take the edge off.

But I think they’re just walking back the fact that everybody knows they don’t need 30–40% of the team they have today. Everybody says this—not if you’re 50 people like Granola, but everyone with 500 employees and up that I talk to off the record, including public companies, says, “I don’t know what I’m going to do. I don’t need 30–40% of my team.”

Now, I think we’re going to see mass layoffs in the next 24 months, but I don’t think the net headcount is going to change. I think the net headcount is going to stay flat. I think he walked it back because it’s too hard for people to hear. It’s too hard, and there’s only so much honesty you can get from a CEO.

Speaker 1

Just for some statistics, in 10 years they made 140 courses with humans, and in 1 year they made 140 courses. So, 10 years of work took them 1 year with AI.

Kyle Norton

I think, actually, on this one, you’re 100% right. You see every one of the CEOs oscillating between 2 extremes on AI. One extreme is, “Oh my God, it’s going to make us wildly efficient,” because I’m sucking up to Wall Street and I probably overpromised on that side. You saw Klarna do that and have to walk it back.

On the other side, when you say, “AI is going to change everything. I’m going to save a whole bunch of people,” your other constituents—your internal constituents, which are your employees—kind of lose their shit, and you have to walk that back too.

You’re constantly evolving toward what I think people are going to settle on, as you said: the very bland statement, “We’re going to adopt AI. It’s going to make everything better. I’m not going to threaten mass layoffs. I’ll come back to that in a second. It’ll just make things better. Oh, and by the way, we’re hiring.”

You nailed it exactly. We have evolved to standard corporate speak for how you talk about AI: it’s going to make us more efficient—wink, wink, Wall Street people—and no one’s going to get fired. You’re just going to do more interesting things. That’s the current state of the lie.

The good news, as a separate comment, is that I think it’ll be just fine. Yes, I do think there will be gradual efficiencies, and there will be jobs that would have existed in the absence of this product that won’t exist now, so there will be tension. But I don’t think it translates to mass layoffs.

We’ve had this discussion iteratively. I think it’ll take a lot more time to adopt. I think some companies, especially tech companies at the very forefront of this, will see significantly reduced hiring.

Speaker 0

And I saw that LinkedIn executive who posted that graduate hiring is pretty screwed up right now, in part because people aren't sure how many graduates they're going to need in computer science and all these things. So, I do definitely think there's going to be an impact here. I don't think it'll be, quote, mass layoffs. I think it'll be more of a steady grind of 2% or 3% less hiring per year, a tweak at the margin on the organization. You're going to keep trying to move it forward. It's just going to take time.

Klarna was just what everybody wants to do. They went first. They went to the extreme. But all it is is the future pulled forward a certain amount of months. I think it's 12 to 14 months. You think it's 60.

The thing we're in consensus on is Jason's decision, on Jason's kind of articulation of how to manage the messaging here. The messaging from Corporate America will be bland, with a slight hint of upside on the stock, but not being so direct that it alienates all your employees. That is going to be corporate speak for the next 2 years.

Speaker 1

I totally agree. What we don't agree on—you’re exactly right, Jason—is whether it’s 12 to 15 months, in which case it could be a significant change in terms of employment, or whether it’s my theory, 60 months, 5 years, in which case it’ll be more gradual.

Speaker 0

When will OpenAI achieve AGI: before 2030 or after 2030?

Speaker 1

That's easy. It'll achieve AGI whenever it suits Sam Altman in his negotiations with Microsoft over the OpenAI AGI term in that contract, to declare it to be AGI, because it's a meaningless, ill-defined term that will be used for economic leverage.

Speaker 0

Go team. That's it. There are 2 separate discussions. Maybe you listeners don't know: there's the whole big-ass AGI discussion—when will it happen, and what does it mean? No one can quite define what it is, and no one can quite define what happened. Then, oddly enough, there's a term in the Microsoft-OpenAI relationship that now appears to be quite contentious. It says—I think; I'm trying to remember—when AGI is achieved, I can't remember which way the leverage moves.

I'm willing to predict that that term will be exploited by one of the 2 parties to get leverage. Someone now finally has an economic reason to give a shit what OpenAI thinks AGI is and when it can be activated. So, my guess is the determination of what it is will be driven by that contract rather than any theoretical B.S., kind of fear-of-the-world stuff.

Speaker 1

Listen, I think Elon Musk calls the ball, but he's just always optimistic about exactly when it's going to launch across all his companies. He always calls the ball, right? I mean, he founded OpenAI, too. The guy's pretty good. All the trillion-dollar-ish ones he founded, right? Most of them.

He said 2026. So, what I think—and again, I'm not an expert—is that it will feel like AGI in 2026, and the really smart guys will agree we're there around 2028. This is just me. I think he's right. He's so good, right? So, I'm betting on 2026: it feels like it in 2028, we agree. Unfortunately, we're there, right?

Speaker 0

It's a nice one. It's an over-under. So, I'm like under 2030.

Speaker 1

I'm with Jason on that one.

Speaker 0

Will Trump cut corporate tax this year?

Speaker 1

No. Easy bet if you read the docs. Basically, if you look at the One Big Beautiful Bill—I can't believe I said that without laughing—the corporate tax rate was changed permanently in 2017. So, there's no reason to touch it now. It's 21%. It's not going to be changed. I think the current version of the bill doesn't include another change in the corporate tax rate.

There are some minor second-order changes to corporate tax around international taxation, but all that stuff makes your head hurt when you even try and understand it. In my understanding, in the current version of the bill, there's no change to the taxation rate, and there's no need to because, unlike the personal income tax changes in 2017, the corporate tax was a permanent change.

Speaker 0

Yeah, certainly. Rory's and my taxes are going way up, though. Venture capitalists' taxes are going way up under the Trump bill because we can't deduct California taxes from federal taxes anymore. So, our taxes are going way up, just like they did under the first Trump administration. Under the first Trump administration, they got rid of SALT, so our taxes went up. Right now, our taxes are going up again because, as partnerships, we're not going to be able to deduct our California taxes against our federal taxes anymore.

Speaker 1

You'll be fine, Jason.

Speaker 0

No, no, but it is interesting. Listen, I'm not into politics, but it is interesting that under both Trump regimes, my taxes have gone way up, right?

Speaker 1

Absolutely. Way up. Way up because Trump doesn't care about California, which is the main thing. You run the demographics as wealthy inhabitants of New York and California and look at their voting propensity. I'm sure there was some guy in the House Ways and Means Committee when they realized, “Oh, this really sticks it to those rich guys on the coast.” It was like, “This is the only damn tax cut we're ever going to support. Let's push it through.”

So, yeah, I hear you, man. But oh well.

Speaker 0

How much are they going up? Just for me to know.

Speaker 1

A lot. You'll be fine, Jason.

Speaker 0

No, no, but it just is interesting. Rory is better than me at this. 6%. But that's personal. I don't have a sense of the personal impact because of the pass-through entity. You'll no longer get a pass-through entity tax deduction in California.

I think our taxes will go up another 7%, not 7% out of 100%—not 7% higher, which I'd be cool with. It's another 7% we're going to be paying this coming year. Hooray. No one's going to cry for us, and California is still a great place to live, so we'll figure it out. Nor probably should he, right? Nor probably should he.

When will there be a half-trillionaire—someone worth $500 billion? Will it be before 2026 or after 2026?

Speaker 1

I'll take after easily. Isn't it just tied to how the stock market essentially performs over the next year? If you think the stock market is really bullish, then there's a chance that it happens next year, right? We need to see double-digit growth in several stocks, but overall in the Nasdaq over the next couple of years. We need to see a return to that double-digit growth rate.

I think this poll is actually pretty good. The 38%—that's my gut. What are the odds that we return to the great growth rates overall in the Nasdaq that we saw before this instability? Thirty-eight percent sounds about right. That's my gut.

But I'm making a bet. I'm actually making the bet that it's higher. I'm all in on the market, so I'm betting your 2026 number, even though it's not really consistent with reversion to the mean for gains of public equities. We can't have this growth rate forever, can we?

Speaker 0

Wow. With one caveat, I thought this was bullshit when we started it a week ago, but now I'm thinking of making a bet on Kalshi, which just shows how easily it works. My bet is that it's well after 2027, for exactly the reasons you articulated, Jason. I just think it's hard to assume—from 2010 to this year, it's been an amazing stock market for 15 years now—that you can extrapolate continued, medium-term growth at the same level.

One of the things you learn in the data is that it's almost impossible to predict the stock market over 1 month, 6 months, or 12 months, but over 5 or 10 years, the correlation between entry valuation and ultimate return is pretty high. Entry valuations are high, so statistically, and Vanguard published great work on this, over the next 10 years your default assumption on the equity return from United States stocks should be much lower than it’s been for the last decade.

If you take that into account, then you're right: none of these guys are going to get to a half-trillionaire by 2027. The only caveat to that entire sentence is that the only person who can sprint his way through to a half-trillionaire in the next couple of years is obviously Elon, because he has private stocks. The ability of the private market to mark up investments is as yet untried by any form of reality.

When you own a slug of SpaceX, a slug of X, and a slug of Twitter, it is entirely plausible that someone gives you such a big step-up that you have a paper net worth north of $500 billion in the next 2 or 3 years. I don't think Microsoft or any of the public stocks are going to compound their way to the same level.

Speaker 1

646 U.S. tech unicorns: how many are actually unicorns in reality?

Speaker 0

That was—I thought that was a really good one. Again, it was from Jason's paper. Let's give him credit: from the Silicon Valley Bank work on unicorns. I think the data there says 20% to 30% max.

In other words, if you say you have to be roughly $100 million, roughly growing more than 20%, and vaguely at or near profitability, what they were saying is that percentage is in the mid-to-high 20s, early 30s.

Speaker 1

Right. I think that's exactly correct. What it means is that 70% of those unicorns aren't worth $1 billion-plus. They're worth something, but they're sub-$1 billion, subscale, sub-growth, and sub-profitability. So, they're probably not worth $1 billion.

The overall return from the entire $2.7 trillion of equity will be driven by 5 or 6—not just decacorns, but I can't remember what a hectocorn is, whatever it is.

Kyle Norton

Because if they don't compound their way out, the average unicorn isn't going to get you there.

Speaker 1

I would certainly agree. So what's the question? The exact question here is: of those 646, how many are actually unicorns—worth $1 billion in hard cash today? Here's what I'm worried about. 20% was kind of what the SVB data said, right, which sounds about right to us. It's an unfortunate number.

It's smaller than we'd hope. It's smaller than the markdowns that GPs have taken, right? The only thing I would say is—and I know we've talked about this, and I hope we do one of these and it changes—I'm just worried there aren't as many exits for these folks as there should be. And so I'm worried the number is, whatever we calculate it to, in practice half of that, when in 2021 it was twice that, right? Because there was so much liquidity for PE and others, right, Jason?

Speaker 2

You're exactly right, which is why it's this quantity, 646, and then you circle back to 2 good IPOs. Let's say we had 2 good IPOs a week for the next year. That's 100 good exits, right? If they were all going to make it, that would take 6 years to clear the total balance of unicorns.

It just brings it home. There will be some value from this, but the bar on exit that's now knowable and achievable is $230 million plus 30% growth. It's a relatively small number of the 646 in the herd that's going to make that.

Kyle Norton

The only fun thing I would say is, in 2021, at the peak, we had an IPO a day.

Speaker 1

Yep. So clearly the markets can absorb it, right? If these companies all reflated to growth, we've already done this, right? 2021—it sounds crazy today—was an IPO a day. You couldn't even keep up, right?

Speaker 2

It's a great point. TechCrunch said in 2021, “We won't even cover companies at $1 billion. It has to be $2 billion and up to write a post,” right? It was so crazy.

Speaker 1

Yeah, you're exactly right. That's actually an excellent point. I shouldn't have throttled it at 2 a week.

Kyle Norton

No, I think that 2 a week would be great. If the appetite comes, which is why it's really good that both of these companies are performing, more of them can go public. It isn't a question of whether the liquidity is there. It isn't a question of whether the ability of bankers to get transactions done is there. To your point, Jason, the real question is how many of that 646 meet the new profile: $200 million plus, 30% growth, and profitability. And that's where the culling of the herd will take place.

Speaker 1

Boys, I've so enjoyed doing this. I always love this. You have been fantastic. Thank you so much for joining me. It's slightly earlier, also. God, I love you Californians doing early mornings.

Kyle Norton

This gets back to Jason's point. We work over here, dude.

Speaker 1

Sorry, that was mean. You're a traitor. You're Irish. How could you do this?

Kyle Norton

You mean leave England?

Speaker 1

Let me explain. I could give you 800 years of history and explain why, but let's not.

Kyle Norton

We don't have time for that, Harry. I can do it just fine.

Speaker 1

Oh, we miss you in the UK. We miss you.

Kyle Norton

That's a longer subject.

Speaker 1

I know you don't. Boys, you're amazing. Thank you so much. Take care.

Kyle Norton

All right. Rock on.

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