SPEAKER_00: So important data here for entrepreneurs to consider the most important things here are, um, that if you get product market fit early, you're going to be in great shape because if you get product market fit early, then you need to raise less capital and you own more of the cap table and you spend less time fundraising people who don't have product market fit, have to convince people. Create arguments as opposed to just showing their data and saying, talk to my top three customers.

SPEAKER_01: If your top three customers are over the moon, it's all going to work out.

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David Friedberg: All right, everybody. Welcome back to This Week in Startups. I'm your host, Jason Calacanis. With me, my co-host, Alex Wilhelm. How are you, Alex? Happy Monday.

SPEAKER_10: I'm tremendous. I can't tell you how glad I am to be back at work. This was a busy weekend and nothing feels better than focus and time. Oh, very nice.

SPEAKER_11: Very nice.

SPEAKER_12: I guess it's been a slow news week, so we'll see if we have anything on the docket that we can get to. I'm sure people have a lot of questions for me.

SPEAKER_15: Yeah, but first though, Jason, you're in L.A., so we're coming here an hour later, but you wanted to talk a little bit about what you've been up to with the family, he said.

SPEAKER_19: Oh, well, no, I was just telling you, I went directly from Singapore to Los Angeles to do a quick Disney trip with the girls.

David Friedberg: Ah. That was quite nice. I got to do, I guess it's going to become a yearly tradition now to go there, and we had, like, you know, the in-laws and, you know, friends from L.A. when we lived here, so we had 10 people. Oh, man. But we did this VIP tour thing again, and oh, my Lord. So, did a little of that speaking gig money and put it towards the VIP tour.

SPEAKER_23: Oh, my speaking fees in Singapore go directly to my Disney, uh, adventure, but, uh, yeah, it was, it was quite nice to, uh, take a day off.

David Friedberg: And then of course my phone is blowing up because everybody's asking me, Hey, where's the, uh, episode of the other podcasts?

SPEAKER_00: And I was like, yeah, refer to my tweet. I'm taking a beat. So, we'll get to the news that we have in front of us here. Oh man.

David Friedberg: There's so much going on. It's almost hard to process it. I see we have a lot going on in the venture space. Yeah. Um, and then a lot of people talking about early stage startups and their valuations, which people listening to this week in startups are going to obviously really care about. I know we're going to do an office hours at the end here, but I had a great trip to Singapore. I don't know if we like recap the trip at all.

SPEAKER_15: Uh, we talked about the tokenization of venture funds last Friday, but we, uh, we had a short timeframe because of, uh, housekeeping, if I recall correctly.

SPEAKER_30: Oh yeah. Housekeeping kept knocking on my door, uh, at the hotel I was at when I first landed here.

David Friedberg: Well, my, my jet lag's good. Now I'm sleeping. Uh, I've been trying out this whoop. The founder of whoop sent me the whoop five, very interesting device, by the way. Now I got comped out on it. So it's not like I paid for this or take the review for what it's worth.

SPEAKER_00: Full disclosure, my, my old journalistic ethics, but it's actually kind of like an addicting device because it gives you like your stress, your energy, like your preparedness. It's much better than the Apple watches native software, obviously, but I kind of like my eight sleep, sleep data a little bit better, but overall a bit addicting.

SPEAKER_36: And I'm starting to see a double fisted friend when I was in Singapore, you know, people, there are pretty affluent, right? It's kind of like a Hong Kong, New York, London scene. So people are paying a decent amount for rent. And if you're there, you're probably making a pretty penny.

SPEAKER_39: Uh, and there's zero capital gains tax in Singapore, by the way. And so if you, if you were running a venture for real estate, I mean, whoa, they, they, they were talking about that. I was like, wait, I'm sorry. One more time. Is that what you said 0% capital gains is what I was told. I looked that up. It seems to be the case. Uh, I think that's why I like the, um, the, one of the Facebook co-founders, Eduardo.

David Friedberg: Yeah. Saverin. Saverin, uh, lives there. Supposedly, maybe he wanted to take a different route. He's been there for a long time, maybe 15 years. I don't know when the Facebook IPO was to pay an exit tax. So when you leave the United States, they make you settle up as it were. So if you had $10 million in Facebook shares and you went to Singapore, you, as I met somebody who was there, who had just given up their citizenship. Um, and so, you know, the other thing when I was in Singapore, the super interesting Alex is I was talking to a lot of parents.

Chamath Palihapitiya: Now these are, uh, people who are in typically, uh, mixed race or a multi ethnicity, multiple, um, what would be the way to say it? I mean, a lot of people in single motion, multiple nationalities, perfect, but also mixed race, whatever.

David Friedberg: So multiple nationality, um, couples. So, you know, one person's from America, but lived in Dubai, was educated in London and now lives in Singapore.

SPEAKER_00: Another person's from New Zealand, but grew up in Japan and China and now lives in Singapore. Like these are the 1% of the 1% of elites who travel the world, doing commerce, their children, unlimited money, resources, and ability to move around the planet, uh, and live where they want to.

David Friedberg: And, um, you know, multiple passport holder type people, right? Yep. Their kids, they were saying, don't want to come to America for school. They're concerned, one of them was concerned when their kids were in school and the talk in their class was, Hey, maybe we don't leave the country, America to go on spring break or go see our parents over Christmas. Because what if we can't get back in? Yep. Maybe the parents have to come see them, you know, in Boston at Harvard or something, because they're afraid they're not going to get back in. So it's like a real palatable frustration, fear, and even maybe on the margins, a little bit of anger or disappointment.

SPEAKER_00: And then on the trade basis, not understanding what's going to happen with trade, uh, for their businesses and that their businesses are looking at other options for trade partner.

David Friedberg: So I was, you know, sort of really taking pause on that because as a, somebody who travels the world on a regular basis, when I was in Dubai, Doha, Riyadh, Japan over the, you know, previous five years, it was always, Oh, you're American.

Chamath Palihapitiya: Like, Oh, that's amazing. My, my daughter's going to school, you know, in Berkeley, or, Oh, my son is going to go, is there on vacation and he wants to go be a ski instructor in Tahoe.

SPEAKER_00: Like these are the conversations that were happening just, you know, the last five years, not the last five months. So there's something definitely happening in that regard. But the reason this, you know, sort of applies to startups, I think is a lot of these startups are going to not come to the U S they're deciding to go to Dubai or Riyadh or Singapore, uh, or Australia, or stay in Europe or whatever.

David Friedberg: But generally going to really super friendly places to business that, uh, and, and, and still attacking the U S market, right.

Chamath Palihapitiya: Still going after U S customers, but just from a different HQ, which means different investors, which means different employee bases, not being based in the U S.

David Friedberg: I just look at that and I was like, Hmm, I need to bring founder university or startup program to Singapore or Japan and the middle east. And, and maybe start capturing some of this energy. If we're going to balkanize the startup communities and, and people are not going to come to the U S the best and brightest talent. Maybe it's time to create funds with foreign LPs with foreign structures, foreign tax brackets, et cetera, and just domicile that.

SPEAKER_39: And then I just started thinking about that and I was like, wait a second, you know, I'm, uh, not going to pop myself up here, but I'm a modest player in the startup ecosystem. And I'm thinking, you know, I'd fund a hundred companies a year, 50 of them wind up, 60 of them wind up, 60 of them wind up going on to get more funding. So, you know, you know, some of these companies, two of the companies I think are in the S and P 500.

SPEAKER_09: I think Robin hood's about to be put in the S and P 500. So two of my first hundred news, it, it didn't get put in and its stock went down and everyone's very sad.

SPEAKER_28: Okay.

SPEAKER_36: So it was on the bubble, but anyway, you know, right there, right there. Right. So, I mean, I'll probably have two of my companies in my first hundred bets be in the S and P 500, Robin hood and Uber.

SPEAKER_39: That's kind of mind blowing. Maybe I'll do that again. You know, maybe in the next a hundred, I'll hit another two, who knows it's, it's possible.

SPEAKER_28: Well, Jason, we all know you do need more money. I think about you every day. And I think to myself, Jason Calacanis, he's just running out.

David Friedberg: Yeah, so anyway, what I just came to this conclusion of is there's a large number of deep pocketed individuals outside the world and future deep pocketed individuals who are just not interested in America anymore.

SPEAKER_19: And that made me sad.

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SPEAKER_36: And then I thought, well, wait a second. I'm talking about doing, spending whatever energy I have left as, you know, in the third act of my career and likely final, you know, see what happens with life extension. But, you know, if I'm in my third act here and it's going to be the last act of me, you know, in terms of professionally, I'm actually thinking like, maybe I spend half my time on things outside the U.S. This should be concerning to folks. And it was certainly concerning to me. So I'm just putting that out there. I'm going to write a blog post about it on my sub stack and just, but I think the opportunity means there's going to be a lot of opportunity for founders who, if you're not getting funded in the U.S.

Chamath Palihapitiya: I think you can get funded quickly in Dubai, Riyadh, Doha, Singapore, you know, Australia, like maybe there's other startup markets.

David Friedberg: If you, you could equally get funded as you might in San Francisco.

SPEAKER_15: I want to, I want to stay on this theme though, because this actually dovetails well with both the YC conversation we're going to have given its centrality in the San Francisco, therefore U.S. market, Jason. But just before we get into that, I want to point out that the discussion about people staying in their home markets and not coming to the United States to do business and so forth is not idle. It's, it's happening now to some degree. So Mistral is a French foundational AI model company. We've talked about them on the show a couple of times, part of the Twiz 500, and they've made a number of pretty cool agents and apps and so forth. But anyways, the reason why I have them on the docket today is that according to, I think it's the FT, Mistral has, quote, secured new contracts worth hundreds of millions of dollars. And that's going to help it raise probably about another billion dollars this year. What are these deals? Well, they're multi-year agreements with what I can tell is mostly European companies. So here we are seeing kind of the leading sovereign EU AI player absorb quite a lot of local business because, back to your point, I don't think the United States and U.S. companies and U.S. technologies have the same, uh, trustability, you might say, as they did, um, six, 12 months ago. Now, in this case, it's helping this company grow that we care about, but those contracts could have gone to probably an American company two years ago.

SPEAKER_00: Yeah. They're not a major player. Uh, there's some protectionism, I guess, in Europe and the people want to use the local homegrown product. I, it doesn't make sense to me that. You know, these customers would use what is probably an inferior product, not the most competitive product. So I wonder what's going on there. Right. Like, or maybe people are just testing it, but they only have a hundred million worth of revenue.

SPEAKER_36: Mistral. Yeah. Correct here.

SPEAKER_81: They're supposed to get to a hundred million this year. Yeah. Or it's supposed to get to a hundred.

SPEAKER_36: So looking at that, combining it with the breaking news about opening, I hitting a hundred times that.

SPEAKER_00: I think that kind of tells the story maybe, which is the people who are using Mistral and they secured all these new contracts worth hundreds of millions of dollars.

David Friedberg: It's probably people sampling it and they could cancel it.

SPEAKER_00: So, you know, when you see hundreds of millions of dollars in contracts, always as journalists or as an insider, former journalist, you would look at it and say, you know what?

David Friedberg: That might be a five-year deal that goes for five to 10 to 20 to 40 to 80, or maybe they made the estimates of what those contracts are worth.

SPEAKER_00: So you have to take it with a, I don't want to say a grain of salt, but in context to, this isn't, uh, going to the bottom line this year, perhaps if they said they have hundreds of millions, a hundred million is going to come in here.

SPEAKER_01: That might make sense.

SPEAKER_27: So the company though, really agrees with you.

SPEAKER_85: They said that quote, sovereignty is not our core business, but the company did say that in the last hundred days, it tripled and in particular in Europe and outside of the U S.

SPEAKER_15: So they're, they're trying to be not the EU is protectionist, like, uh, you know, welfare beneficiary. They're trying to be a global competitor with open source models and agents. Um, I just think that there's seen a lot of local demand because people have a little bit more faith and trust in them than perhaps a Microsoft or something similar. So I think they're playing it straight, but I do agree though. Jason, we need to be cautious about these long-term bookings because I don't know if a company came to you and said, we have a five-year contract. How many years of that are you going to give them credit for today? Two probably.

David Friedberg: I, I guess you'd have to look at the details in the contract and what the cancellation is. Most of these things have a three to six month out. So with three months notice or six months notice, you can cancel the contract. None of them would ever be like locked in. I, I wonder if even an NVIDIA contract for the most sought after product in the world right now, like H100s, would those even be guaranteed or not?

SPEAKER_00: Like maybe you have, you know, till three months out to cancel it. Like I said, when you order a car, you know, there's a point at which you can't return it, or you order a hotel room, there's a point at which you can't return it. Um, in business, I would say it's usually a yearly contract. You get a discount for just during the year you can cancel with three months notice or six months notice within that year.

David Friedberg: So if you got to month six and you decided to cancel you early, she can get out as month nine or month 12, in which case you're just. Gonna use it for the rest of the year. But it is interesting that they're saying people are looking to them because they don't want a U S product. That's kind of what they're saying is they're getting an uptick in European folks who want it.

SPEAKER_93: Yeah, a nice tailwind, if you will, but they still want to compete and sell everywhere.

SPEAKER_00: I mean, this, I, if they're going after the foundational market space, it does seem like that is becoming quickly. Commoditized, uh, indistinguishable, you know, they're kind of all leapfrogging us when you look at the poly market for who's going to have the best model, uh, which we could pull up right now. I, I noticed it keeps changing. So, you know, open AI and I think, I think open AI and Google Gemini keep going back and forth as the most expected best model on the benchmarks.

SPEAKER_10: And, uh, yeah, this is the, which company has the best AI model at the end of 2025, Jason.

SPEAKER_15: I picked the furthest timeframe that I could see this market has about $900,000 in volume. So not the most, but not zero and wow, Google has a 51% chance right now. Open AI is in second place, XAI, 16%, Anthropic, 8%. And, uh, no, Mistral does not even make the betting, but Alibaba, MedEd, and DeepSeq all get a couple of points each.

SPEAKER_93: So there you go.

David Friedberg: So this is like very interesting to look at, because the people who would participate in that kind of a market are people with an ed.

SPEAKER_39: It's one of the things I love about poly market. Shout out to my friends at poly market. Um, they are capturing that 900,000 are people who are deep insiders on betting. People who really are either working on the models, work with the models, you know, some developer in Ukraine who's looking at it going, you know what?

David Friedberg: I think based on my firsthand knowledge, it's going to be either Gemini or open AI. I use this stuff every day and I know their release schedule. I mean, this is by the end of 25, somebody might even know the release schedules. Right. And so that's why this is so valuable to look at.

SPEAKER_00: It's either going to be one of those two companies, 85%. I think if you put the first two together, something like that, was it 84 or 85?

David Friedberg: Oh, 74 put together. So, you know, and then XAI right behind them in third place. So you put those three together. Now you're looking at 90, 90.

SPEAKER_00: So it's like, it's a three horse race right now. Yeah. Mistral is not in it currently. Even Meta is not in it. That's fascinating too, with all the, uh, open source.

SPEAKER_102: Mistral does a lot of open source work too. And so we're actually seeing Jason, Mistral and Meta, the two open source kind of what I would call leading lights, apart from anything coming out of China.

SPEAKER_15: It's really not perform as well as we might've expected, because if you think about what we were saying six months ago, we were saying, you know, maybe this open source stuff is going to be the winners and doesn't seem to be the case yet. At least I'm a little surprised.

SPEAKER_00: It would make sense that the closed products with lots of backing, those three have the most backing and the most hardware would do the best. The open source ones don't have as much iron. It's the exception of Meta, but even Meta, I think it's behind on iron.

David Friedberg: So, and they're open source, so they go slow to go fast and slow is smooth, smooth is fast.

SPEAKER_01: I think that's it. The Marines or something when they're cleaning their guns are, yeah, whacking Osama bin Laden.

SPEAKER_109: So interesting, uh, you know, I'm interested to see when people start betting on an open source model to win the day.

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SPEAKER_85: Yeah, we'll see. In the meantime, the corollary to the story, everybody, is that OpenAI, about 45 minutes ago, announced via CNBC that they have reached the 10 billion ARR threshold.

SPEAKER_15: Jason, I'm not going to lie, I did not think that OpenAI, best known, of course, for ChatGPT and the O-series of reasoning models, was going to be this big, this fast. I knew it was growing quickly, but I didn't expect this. Data point for everybody, 3.7 billion in revenue last year. Jason, of course, that would put them at a higher ARR number at the end of 2024, but did you expect to see 10 billion this soon? No? No.

SPEAKER_00: No. And I'm wondering how much of it is enterprise versus consumers. That's kind of the key here, is how much of it is people, just startups who are raising a bunch of money, big companies throwing jobs at it, or the second pillar of their stool, which is consumer subscriptions. Mm-hmm , we did have that information previously from last year. So do you have it handy by chance? Is it 50, 50? Is it 70, 30? I'm curious.

SPEAKER_93: I don't have that exact split, but I do have the most recent business announcement from them is that they went from 2 million paying business subscribers in February to 3 million. I think it was last week.

SPEAKER_133: 3 million and they, business people pay 40 bucks a month or something.

SPEAKER_09: It's 120 million a month. At a, at a minimum, so that will be 1.4, 1.4 billion.

SPEAKER_85: Yeah.

SPEAKER_15: Um, I will say though CNBC did add that the 10 billion ARR figure, according to open AI includes, uh, consumer chat GPT business products and its API, but does not include licensing revenue from Microsoft and large one-time deals, which makes sense as it's an ARR number. But I do like that they gave that clarification so we can mostly trust that this is a reasonable, annual recurring revenue figure versus just kind of a run rate statistic.

SPEAKER_78: I liked that.

SPEAKER_133: Yeah, it's pretty impressive. I do think we're going to see the consumer products are going to be free. Um, I think that the idea that consumers are going to pay for this, that could be a short-term thing people used to pay for the Netscape browser. Yep. They don't pay for their browser anymore.

SPEAKER_00: So I don't think subscription revenue will be a thing. I think subscription revenue is a thing right now because these are expensive products to run, to operate. But as they get cheaper to operate, there's no reason Apple, Google, or Facebook would ever charge for them. They'll just include them in their free product. So then what does the pro get you?

David Friedberg: Like it might be the pro is kind of like getting extra storage from iCloud. The pro could be, I don't know, having your badge on Twitter X.

SPEAKER_39: I don't, I'm not sure what the pro version of all this is, but I think you're going to get 99 of a hundred queries that'll be capable of being done by a free service that's advertising based, which could be the third leg of the stool.

David Friedberg: I wouldn't be surprised if in the next year or two, Sam Altman says, we now have an advertising product.

SPEAKER_00: You put in your URL, you put in what your product's about, and we present it to users and you pay us a dollar cost per click. And it's just integrated into the text. If you use the free product, you have to see an ad before you use it. You have to watch a video before you use it. Or, you know, on the sidebar, there's links or in between your answer, there's links. You have to click a link to see an interstitial and then you get your result. Yeah, actually that would work. I just figured out the new model. While you're waiting for your results, you have to wait 15 seconds or 10 seconds. You have to watch a video commercial while your results doing. And just like the five seconds skip, that would be the perfect model for a free version of ChatGPT.

SPEAKER_15: Just enough friction to make you pay if you want, or just enough friction to monetize with an advertisement. But not so much that it ruins the experience. I dig it. And backing up your thought there, Jason, don't forget they hired Fiji, the former CEO of Instacart. She is previously not only of Instacart, but also of Meta, which makes its money off advertising. And under her tenure, Instacart made a lot of money off advertising inside of its application. So quite a lot of bona fides there on that front.

SPEAKER_85: I found the number, by the way, 75% of OpenAI's revenue last year was thought to be consumer. That's an extrapolated stat, not a hard one from the company.

SPEAKER_15: But even if it's directionally accurate, I think it's fair to say that the company is still a majority consumer business, which I think makes the revenue seem a little bit less solid, given what you're saying about the potential for disruption there. But at least for now, it's working.

SPEAKER_06: I could see, you know, like I was thinking the other day, like how many of these things am I actually paying for?

SPEAKER_36: Maybe I need to cut a couple. Like if I'm paying 30 bucks a month for five of them, I think I'm paying probably 1,800 a year. Sure, a business person is not a lot if you're, and for somebody who covers it as an investor, it's not a lot. But even I was thinking like, yeah, maybe I'll cut the bottom two.

David Friedberg: Do I need to have that? Or maybe I'll get a backup account that I share with the entire team on one common email address, you know, so we can sample it once in a while.

SPEAKER_00: What's going on with the venture funds slowing their pace? Because I think this is also kind of an interesting trend if we're going to get into it. And I think Wednesday, we're going to have our first VC roundtable on the show. Is that right?

SPEAKER_15: We are. I'm starting to work on that actually right after this show. We're going to get the outline pulled together. So everyone expect a fun episode on Wednesday.

SPEAKER_149: Okay. So venture fund investing pace.

SPEAKER_15: Here we are talking about a chart shared by Megan Reynolds, regular viewers of the show. Jason will recall that she came to the 2024 liquidity summit. We shared her talk in episode 2008. If you want to go hear how she discusses the LP side of relationships in the venture game. And that's because she leads both talent and capital formation over at Altimeter.

SPEAKER_149: All right. All that said, she shared a very interesting chart showing the time between funds.

SPEAKER_15: And you're going to pull up this chart here, Jason, and just give everyone a quick overview if they're on the audio. It's a time series chart tracking data from 2005 to 2024. And it shows how many months between funds from the same firm. And it gives a middle 50% interval and then also a median number. And it breaks this data into three categories, the kind of like olden days from 2005 to 2013, then the acceleration through COVID, which was 2014 through 2022. And then the last couple of years. And just to kick you off here, Jason, I ran all these numbers into a sheet and the average for the first era was a 45 month gap between funds. Then that fell to a 29 month gap in the accelerated COVID era ZERP period. And then most recently, it's come back up to 31.5. I'm curious what you see in this data.

SPEAKER_00: It's fascinating. I think people used to raise a fund and they were methodical deploying it over three or four years from 2005 all the way to, it looks like, sorry, the chart just went off the screen.

SPEAKER_156: Oh, I'm sorry.

SPEAKER_00: I was, don't worry about it. I have the chart on my notes here. So just looking at it in my notes here, if you look at, or maybe leave it up so the audience can see as I, as I sort of sportscast it. But if you look from 2005 all the way to 2014, that goes through the great financial crisis, right? And, uh, and, uh, right up until things started to boom and you have the average, I'm looking at the average dots, which were in the middle. And it starts in 2005 with 49 months to deploy a fund, right? That's after the.com bust. And then we see 52, 36, 42, 41, 46, 47, 45, 48. And then all of a sudden a sudden drop to 36. Months to deploy a fund in 2014. So that's an interesting 10 year cycle there of where people were taking, you know, 40 some odd months, three and a half, four years. I've always thought three years of primary investing was the right timing between funds, maybe four. Then we get into sort of ZERP. It's getting really hot in here kind of era.

SPEAKER_70: And oh my Lord, you know, here at this week in startups, we try to keep founders just

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Chamath Palihapitiya: In 2022, there was a 20 month. And in, yeah, 20, if you look at 2020, 2021, 2022, that kind of tells the story. 23, 24, and 20 months between raising funds, you've got numbered sequential funds.

SPEAKER_00: That's wild. That's wild. That means in, you were going back to your LPs every, you know, two and a half, three years. It's, it's just crazy.

SPEAKER_133: Um, and now we're back up to 34, it looks like, um, so reversion to the meme, mean, um, or the meme version, um, but yeah, Zerp was not thoughtful.

SPEAKER_00: And then what happens is there's a very practical thing that happens here, Alex. If you concentrate all your bets in a two year period versus a three or even better four

Chamath Palihapitiya: year period, if you take four years, then if there was a boom or a bus that happened, you might have two years of boom, like peak Zerp, and then two years in the trial, you

SPEAKER_00: know, or you might have just rid the last four years of the boom up, but at least the first two years might not be what would have been as unreasonable, right? Or you could have gotten lucky. All four years are deployed at the bottom of the market. Like we are, I think over the last year or two, and then boom, it all comes back. And you're a hero or, or the 2009, 10, 11, 12, 13, 14 vintages that were just Airbnbs,

SPEAKER_156: Coinbases, Ubers, et cetera, lots of juicy stuff in there.

SPEAKER_85: The, the, the compressed timeframe then just really makes your venture funds bets incredibly

SPEAKER_15: concentrated on a time basis, which is worrying to me, but I want to go back to the 2014 points. We saw a pretty rapid shift from a 48 month median deployment time to 36. That's a 25% decline in one year. And honestly, 2014 kind of to me is the start of the unicorn era companies staying private, longer raising more money. And so I wonder if some of the decline in time between funds was simply the ability of firms to write larger checks that were growing faster than their proximate funds were. So let's say you can write a hundred billion dollar check instead of 50 that's two X, but if your funnel, it goes up by 30%, you know, incrementally from one, fund two, fund three, you could end up burning through your fund faster. And that can work well if it's all going into Coinbase or it can go pretty poorly if it's all going into WeWork. So I I'm curious to see what the new normal will be. I don't think we're going back to 52 months like we saw in 2006 though. So for founders though, Jason, we are seeing funds take a little bit longer to invest. I'm curious, what does this mean for on the ground folks?

SPEAKER_78: If you're out there raising a pre-seed seed or series A, how should this change or just impact your thinking about how you approach the capital markets?

SPEAKER_00: It's, you know, a lot of times founders I find get too obsessive with the market conditions and what's going on in VC land. And they tend to start blaming the VCs as opposed to looking at what they're doing. And, um, that is reasonable. If you're not having people throw money at you, you're probably like, well, the VCs just don't understand. It's like somebody who writes a great screenplay and is a director and you're quitting Tarantino

David Friedberg: and nobody will make your movie. And then you're like, you know what? I'm going to put Pulp Fiction and True Romance aside. I'm going to work on this little more narrow thing, Reservoir Dogs, and I'll prove it.

SPEAKER_00: You got to do your Reservoir Dog. It's up to you as a founder to get that prototype built in today's market. In the vibe coding 25, the roaring vibe coding 20s, you kind of got to get your product to market. You kind of got to get to 5k a month in revenue. You kind of got to get to 10 customers giving you 500 bucks a month or a hundred giving you a hundred, whatever it is. And, uh, have two or three people, you know, grinding on it, uh, based on sweat equity. There's very few J-Cals and Y-Combinators out there taking flyers on teams. I'll just be totally honest about it.

SPEAKER_103: Everybody's waiting to see who hits a million, two or three million in revenue.

SPEAKER_00: Nobody wants to do the hard work of, you know, I write, I think our firm is writing 60, 25k checks this year and maybe 30, 125k checks. And we'll do 10, you know, 250k C checks, something in that range. And so you start doing the math on that. Like most people don't want to bother running an accelerator or a pre-accelerator that gives you your first friends and family check because it's hard, really hard. Uh, and it creates a lot of work. Well, if you are, if you have a pool of capital, what's a better life if you're trying to do

David Friedberg: lifestyle and maybe you just ask your friends, what are you investing in? And can I put 250, 500k into what you're investing in?

SPEAKER_00: And so for founders, just know where you're at. If you got the first 500k check from a seed fund, the other two 250k checks are going to quickly follow because you got that person as an anchor and they're, they've got conviction. And you've got, in that case, 250k in revenue, 500k in revenue, and they're just going to, you know, zip, zip, zip. If you're before that and you're trying to pitch the same group of people, you're probably not going to get them unless you're a second time entrepreneur. So then you have to get the customer. So focus relentlessly on customer product market fit. It'll all work out. And if it doesn't work out on this startup and you run out of cash and you don't get

Chamath Palihapitiya: product market fit, well, then you're going to be better the second time around.

SPEAKER_156: And you'll, you'll, you'll be able to get product market fit faster, um, with less

SPEAKER_00: resources and that's the key, can you get product market fit how fast and for how little

Chamath Palihapitiya: money and overhead can you get to product market fit?

SPEAKER_146: Okay. We're going to, we're doing this a little out of, uh, out of the order I had in mind,

SPEAKER_85: but I, that's too good of a corollary to bring up the, uh, data from Andreessen's. We just can't pass it up. So Andreessen Horowitz dropped some data, uh, looking at companies, both in their portfolio

SPEAKER_15: and companies that they had seen and got enough information from to include inside of their kind of bucket of data. If you will, this is all anonymized, but we're talking about the path to series a Jason. And we're trying to figure out the revenue benchmarks for high quality, if you will, for both enterprise and consumer AI startups. Now this is under the umbrella of our startup growing faster today than ever before. And I think also to your point about why a lot of investors want to see some traction because companies are growing so quickly. Why not wait for some? So here's a bit of data from Andreessen about revenue benchmarks for enterprise gen AI startups and just sports casting folks out there. This shows three different quintiles, quartiles, the bottom, the median, and then the top. And it shows revenue growth at six months after monetization and 12 months. So if you're a median enterprise gen AI startup after six months, Jason of selling your product, you have about 700,000 worth of ARR and at month 12, 2.1 at the top quartile, it's 2 million ARR at six months and 5.3 million, uh, at the 12 month point. And if you are in that top quartile, you raise your series a just seven months after your seed round.

SPEAKER_09: Okay.

SPEAKER_00: So let's pause there before we get to the amount they raised afterwards. So getting to 500, 700, or 2 million in revenue in just six months is absolutely fantastic. So anybody who does that is a winner. So this data is a subset already. These are people who got to revenue. Remember, probably 80% of startups never get to revenue. And I would say 90% of startups never get to 500K in revenue. So this is like literally the top 10% or 5% of startups, you know, coming out of Y Combinator, Launch Accelerator, Techstars, et cetera, Antler.

David Friedberg: So the bottom quartile here is in fact, like the 90th quartile, the 90th percentile in startup land.

SPEAKER_36: So just so we don't neg them. So, uh, yes. Good point, Jason. Yeah, because this is, uh, and, and as you can see, um, one, the bottom group goes two and a half to just over, yeah, two and a quarter or two and a half, two and a half times in from six to 12 months. So they're growing at a nice pace. Uh, the 0.7 triples to 2.1 and the 2 million, you know, two and a half to 5.3. In other words, they, um, they grow their revenue pretty briskly between that six and 12 month period, which is indicative of product market fit that we just talked about. The first six months you get product market fit, but it's, it's light, it's loose. And then something happens between months six and 12 F and that's, that's not, that's not month six or 12 of the startup. That's month six after launching. So let's assume they spent a year in the lab with unpaid trials going through an incubator. So this would be month 18 and month 24 is probably from the incorporation date or when they started writing code and doing customer research is probably what we're looking at here.

SPEAKER_63: It might even be like 18 months in the lab with free customers, et cetera.

SPEAKER_36: So it might even be 24 and 30 months, something in that range is what we're talking about here.

Chamath Palihapitiya: But these things are growing quickly. And Andreessen has made a bucket of people who are in the top 10%.

SPEAKER_00: What's very interesting here is the time to series a, I think you would agree is that if you're a fast growing startup, a top quartile raises their series a in seven months after launching revenue. So about seven months and they launched in month 18 or 12, you know, they're getting that series a, you know, by year, end of year two, very impressive. And then 13 months from the bottom and nine months.

SPEAKER_01: And it's very interesting. Yeah.

SPEAKER_184: The thing that I, that really struck me though, Jason, if you look at this chart and I'll take

SPEAKER_15: it down in a second, but it shows how much money they raised these companies before their series a, and there's an inverse correlation between pace of growth and time to series a and capital raised. So the companies that grew the fastest and raised the most quickly, reaching that series a milestone raised in this data set, 2.3 million, 4 million for the median and 5.5 million for the bottom quartile. So essentially the companies that are raising the least are growing the fastest, which surprised me because frankly, there's. Doesn't surprise me. Money is useful. Okay. Tell me why.

David Friedberg: Doesn't surprise me.

SPEAKER_00: Um, you're having less resources makes you scrappier and they needed less resources. So they spent less time raising money because they were making more from customers. So that's the best part of the data. That last column is the best part of the data. Everything, you know, is like as expected for me. The last row is super confirming of a trend that I was monitoring and talking about for the past year or two, which is the breakout companies now that really figure out revenue are raising much less and they don't need to raise as much. And this confirms that. Now, I don't know if this is based on 10 companies or a hundred. It would be really nice to know the denominator here.

SPEAKER_09: And I think they're trying to be a little bit aloof, aloof from the data so they can share it.

SPEAKER_00: So important data here for entrepreneurs to consider the most important things here are, um, that if you get product market fit early, you're going to be in great shape because if you get product market fit early, then you need to raise less capital and you own more of the cap table and you spend less time fundraising. People who don't have product market fit have to convince people, create arguments as opposed to just showing their data and saying, talk to my top three customers.

SPEAKER_191: If your top three customers are over the moon, it's all going to work out. Uh, before we go to the customer, let's just do the YC thing real quick. Uh, yes, let's do that. Cause that's the kind of button on all of this.

SPEAKER_146: Yes. We actually had a really great kind of a coordinated link of, uh, data points today.

SPEAKER_149: All right. So, uh, Nicole Wiskoff from Wiskoff Ventures, uh, posted some very interesting data over on

SPEAKER_15: the Twitters and Gary Tan did respond. So we have quite a lot to discuss here, Jason, but here is the data she put out. She grabbed some data from the Y Combinator spring 2025 batch. And then she looked at a number of non YC pre-agency companies from around the same era. And she found that from the YC cohort, the average round size, 3 million average cap on their safe notes was about 25 million and their average AR just over a hundred K for non YC precedency companies at around the same time, average round size, 2.4 million smaller average valuation cap on their safe 15 million, much lower. And their average ARR was 290,000 much more.

SPEAKER_149: Uh, there's a lot of nuance to this data, Jason, but did any of that surprise you when you saw it?

David Friedberg: No, not at all. Uh, what Y Combinator has done is what Harvard has done. They've created incredible brands that people are willing to, um, pay for value or proceed value. You can make a big debate there.

SPEAKER_36: Um, this data of course is, uh, probably friends. It follows the absolute trend I see, which is non YC companies with traction versus YC companies with traction. You're going to get essentially here, half the price for triple the performance, which is six X leverage, but let's just call five X leverage on every dollar invested. This is why a lot of folks have opted out of the YC game because there are a lot of dentists and a lot of folks coming to Y Combinator demo day who are, you know, maybe not as entry price discerning. And the majority of unicorns in Silicon Valley did not go to Y Combinator. They didn't get backed by Sequoia and they didn't get backed by me. That's just the nature of how big our market is.

SPEAKER_00: So going, and I would say a percentage of Y Combinator companies I know historically don't clear market. So they try for 25 million on the valuation cap, but Nicole might never meet them because they give up trying to raise money or they raise a small amount at a smaller valuation. And, you know, they don't make their way to the seed funds.

David Friedberg: In, in other words, this data is kind of skimming the cream of two different groups, I think. So let's put that in there.

SPEAKER_10: Yeah. Just like the Andreessen data we were just discussing, we're talking about companies that

SPEAKER_85: Andreessen cared about or invested in. So we're already looking at a pretty rare circle. Yeah.

SPEAKER_00: So I think, and if Y Combinator accepts 1% of startups and companies that get to 25K a month

David Friedberg: in revenue, I would say, you know, in the non YC pre-seed and seed co's that would equal 1% of startups that were formed, you know, in the United States. So this data is about the 1% of startups in the seed ecosystem. And it is correct. You will pay 5X net net on the valuation to the ARR performance.

SPEAKER_00: Now, but, you know, listen, there's a Airbnb who went to Y Combinator. So people are hoping of the 500 companies or I'm not sure how many they're doing a year now.

SPEAKER_204: Maybe their cohorts have gotten smaller again. So, okay.

SPEAKER_36: So there's three cohorts now instead of two, I think. And I think they're doing 250 per or 200 per. So if they're doing 250 per and they're doing three, that's 750. So it was at 500. It would be good to know that number.

SPEAKER_00: Because for Y Combinator or Techstars or us, we're doing a large amount of bets,

David Friedberg: knowing that our pull through rate is going to be 50%, 60%, 70%. I bet, you know, of YC companies, maybe 60%, 70% actually wind up raising a round.

SPEAKER_00: That statistic is the one you really need to look at. What this means is if you get accepted to Y Combinator, go. If you get accepted to Launch, go. If you get accepted to Found University, go. Antler, Techstars. I don't know the other top accelerators out there. I suppose it's probably a steep drop off from there. But if you can get into one of these programs, they act as a filtering mechanism for people like Nicole. People like Nicole do not have a big enough staff to sort through the 20,000 applications we get, the 50,000 that Y Combinator gets, the 40,000 that Techstar gets. Antler probably gets 40,000 or 30,000. It's just too much work to get through all those. So what you're looking for as a seed manager or a pre-seed fund is for somebody to just weed out people who can't show up for 12 weeks in a row to an accelerator and have three co-founders,

David Friedberg: one of which is a developer submitting code who owns over 10% of the equity on the cap table.

SPEAKER_00: That's what we do at our accelerator or at Found University or YC or Techstars. That's what we all do. We curate a group of apples, you know, picked from the same orchard that aren't brews, that are shiny and new and don't have worms in them. And we put them out, you know, and say, hey, look, we worked with these apples. These are some good apples. How about these apples?

SPEAKER_36: But if you were a venture capitalist, the best thing to do is to go to Demo Day, collect all the information, do all the meetings, and then wait one year to then go and meet with your favorite companies. I guarantee you, if you're raising a $25 million valuation caps, if this data is directionally correct, and I believe it to be, with 100 in ARR, it's 250 times revenue. So if you wait one year, that company will have spent that $3 million or much of it,

SPEAKER_00: they'll have gotten to 300K in revenue. And if they do a $25 million round, now they're still at 100 times or 90 times revenue, which is still extraordinary. And you can make the same bet with three or four times the revenue. So stay in touch with the company, et cetera. I would, and these companies will get funded. So just pause and then do the funding after is my best bet.

SPEAKER_211: I think that's the best advice.

SPEAKER_85: Yeah, I, I agree with that from the, the venture perspective. I do want to say that Gary Tan, I want to give him his, uh, his words here. Response. He had a couple of different notes, but one, he says that the, the vast majority of YC startups start with just an idea or with no revenue, meaning that they are younger at Demo Day age and the other startups raising similar rounds. So he thinks that the ARR comparisons that Nicole put up are a little bit specious, but we're always talking about in private markets, incomplete data. And so we're always doing our best. I don't think she's being at all malicious. I think Gary has a reasonable point, but no matter how you slice it, you're still paying quite a lot for not a lot of revenue.

SPEAKER_15: Um, and just, if you want to hear more from Nicole Wiskoff episode 2061 from last December, we had her on the show. She's a great interview.

SPEAKER_133: I would say his response about don't worry about YC 7% equity take is a good comment. I tell people this about our accelerator or YC.

SPEAKER_00: And now if it was 10% or 15%, I would be a little bit worried. Cause those are, that's a large number. But any of these programs that 7% gets made up for in the valuation you get, if you go raise money after, whether it's our program or his program or any program and the AR comparison, um, you know, that, you know, the vast majority of YC startups are just an idea with no revenue, just an idea with no revenue. 25 million is a pretty crazy valuation to ask for, for just an idea with no revenue. So I, I think that doesn't make a lot of sense. These, uh, results on the, uh, best in class for the companies that's TV PI.

SPEAKER_216: So I would ignore this because that's paper gains, not DPI.

SPEAKER_218: I'm pulling this up for you right now, Jason. I just had to make it, make it big. Yeah.

SPEAKER_216: Yeah. Uh, so here we go.

SPEAKER_133: I'm not sure who made this chart, but, uh, maybe it's Carta, it's Carta data maybe. Yeah. This is not a good chart to go on because this is just paper gains.

SPEAKER_00: And we just established that YC gets you a higher evaluation that is outside to Garrett's own admission. Like, don't worry about the 7% because we're going to get you a higher evaluation. Then that means the valuations are inflated because of the white combinator reputation and justly. So because they have a great reputation and they run a great program, what that means is the paper gains are not what you should be looking at when making a decision and evaluating them. You should be looking at the DPI and the distributions that actually got generated. Paper gains are inflated here by Gary Tan's own admission.

SPEAKER_36: He's saying, come to YC because we're going to get you a, a much higher valuation, five times more than a non-YC startup. If that actually is true, then these numbers based on TVPI would need to be divided by five or divided by three or something. And then you would be looking at much different numbers. And actually I think if you did that, the top 10% being 3X, that might actually be the actual correct number. 3X is great for a fund. Okay.

SPEAKER_221: 3X is great for a fund.

SPEAKER_85: All right. Now, Jason, I do want to get to our office hours today. We're getting back into this now that you're no longer over in Singapore.

SPEAKER_149: And so today we have Sean Stegerwald from CustomerIQ. They were in Founder University cohort eight. They are in Launch Accelerator cohort 34. Please welcome Sean to the show. Sean, hey. Oh my gosh. Hey, hey. You've got too much hair.

SPEAKER_28: Just for starters. How dare you, sir?

SPEAKER_187: You look great. All right. So tell everybody what CustomerIQ does and how it's going.

SPEAKER_224: Yeah, definitely.

SPEAKER_225: So we work with revenue teams to expand their capacity by automating email and CRM data entry. And it's going well. Most people hate both of those things. So they love when we solve them.

SPEAKER_103: Who would be the ideal customer for your startup? The ICP, as we say in the business, ideal customer profile.

SPEAKER_227: Yeah. Ideally it's teams with large sales teams and they send a lot of quotes.

SPEAKER_225: So they have a ton of just action going on in their inbox. It's really important for them to get them out quickly, respond to people quickly, and then follow up. And those are three things that our agent helps a ton with.

SPEAKER_216: Are people, if I'm, you know, explaining the product correctly, are people cool with

SPEAKER_133: automated communications with customers or do they like to have the AI kind of queue up the

SPEAKER_00: communications and tell you like, Hey, this might be a good thing to send to that customer you signed six months ago and haven't spoken to since.

SPEAKER_225: Yeah. Great question. So we never send without the user reviewing. It's all drafts. So what they love is that it's in the inbox and that's one of the unique things that we do. So we integrate directly with Gmail and Outlook. And for example, like my favorite part, every morning, you get an email from Quinn is the name of the agent and says, Hey, you sent 14 emails over the last few days where we expected a response and we didn't get one. So I left these drafts in the drafts folder and they just flip over to the drafts and they go through and they review them. And as they send them out, it gets better, but it's never sending, uh, as they make edits, it gets better, but it's never sending on their behalf.

SPEAKER_133: So I pay for superhuman, superhuman is doing drafts for me. Why would I use customer IQ if superhuman is doing that already?

SPEAKER_57: What's the difference between the two products? Now I know the answer to this, but I'm, I'm giving you a softball.

SPEAKER_225: Yeah, sure. Superhuman, phenomenal. If you're an email power user and it's a, you know, just like such a thoughtful interface over the email, we build an agent that lives in the inbox. So all of our users, they're either committed to, or just still using like Gmail or Outlook, the actual interface, nothing about that changes. They keep using it the same way. And then we're focused on revenue teams, which is sales and customer success. So what we build might not end up making as much sense to maybe support or product management or some of these other roles in the companies that we work with. Got it. Um, and you kind of see that reflected in a bunch of different features that we show.

SPEAKER_238: You also have access to some unique data when you're drafting your emails, correct?

SPEAKER_225: Exactly. Yeah. So the, the two pronged approach of integrating with the CRM and automating all that data in there means we have just amazing context of what should be written here, like what good looks like data that performs well in deals. And that kind of keeps expanding. And as the models get better, the context is the most important thing. So we help them, uh, you know, automate a bunch of the busy work and what data gets put into that system, but in actual, like the actionable bits that the agent does in drafting, uh, we, we can use that to, to do it even better.

David Friedberg: So if I have somebody in my Salesforce or my HubSpot, you're using that as part of the drafts. Yeah.

SPEAKER_225: Yeah. And just imagine like in Salesforce or HubSpot, a contact or an account record. Ultimately, those are like profiles of people that you're speaking to. And when you go to write emails or reach out or follow up, or you work some sales process that, that profile really informs everything. And the, the models have this incredible intelligence and ability to write just like you and, and solve that blank page problem. But those profiles give it all the context. And, and so, yeah, that's what we use.

SPEAKER_240: Sean, I want to ask about the contextual AI engine that kind of underpins Quinn.

SPEAKER_15: Is this a model you guys change yourself? Is it a model you've built on top of? Curious about that. And then also just data privacy, because if you're inside of my email, you're inside of the absolute most critical information in my business. So how do you guys handle bringing in context to do this work without sacrificing some privacy

SPEAKER_93: for the user?

SPEAKER_225: Yeah, the, the context is, is really everything. And the, that engine we described is really like a really intricate, uh, rag format. They are just the system that we've created. It's a retrieval augmented generation. It's when we know we have a task to do and we need the LLM to go do it. What information can we pull in from the CRM profiles or past conversations? I like little nuggets that have been saved along the way to make that really, really good. And, uh, so yeah, we, we, that's that contextual that, that we talk about. And it's what differentiates customer IQ from just out of the box using Gemini, for example, like in Gmail, if you ask it to write an email, most people have experienced this. It does definitely write an email for you, but it's not usually in your tone and style. It has no knowledge of like this process or this deal.

SPEAKER_85: So do you guys, uh, host a, a, a models internally on kind of on your own metal,

SPEAKER_184: or are these the models that you're accessing via commercial APIs?

SPEAKER_225: Right now it's commercial APIs as we, yeah, we're early stage. As we start bringing on more and more larger customers, I, I definitely see a world where we are hosting open source models using that. And especially as those get better, the magic is really in the context. Then that can be, yeah, that's we, to answer your security question, like that's the same software practices we've always used in software development. Yeah. We use AWS as our manage main backend follow all encrypted database practices. Uh, you know, go through talk to compliance audits, all of that. Right. Yeah. All right.

SPEAKER_249: So you went through found university. You're in the accelerator now, um, or you're in the next flash.

SPEAKER_00: You're in the accelerator now. Yeah.

SPEAKER_250: We're in right now. Yep.

SPEAKER_00: So that's great. We just had a whole conversation about, you know, year one startups and getting revenue. You've got customers, you've got revenue. That's amazing. Uh, and, uh, you have questions for me.

Chamath Palihapitiya: What's challenging, any blockers, any frustrations, anything you need advice on?

SPEAKER_224: Yeah, definitely. There's a couple of things. One interesting, maybe even conversation to be had is we, this is my third company,

SPEAKER_225: third software company, first time ever in, obviously in AI as most of what's usable today. It's pretty new. Yeah. Yeah. Pretty new. And, uh, one, like investor question we get, and also just thing we think about every day is usage and like, think about monthly active users. It's kind of a whole different world now where the vast majority of our users don't actually log in to customer IQ. They sign up, they get set up initially, but then Quinn lives in their inbox and they kind of work alongside it every day. So I don't know if you have any advice around just managing that or. Yeah.

SPEAKER_133: So there's, there is a big question now, if companies are going to have less employees,

Chamath Palihapitiya: then selling a per seat basis that requires them to have less employees means you're empowering them to spend less money with you. Right.

SPEAKER_00: So let's let that sink in. Yeah. If you do your job, then tells 10 salespeople could come down to six because they're selling or five, because you're selling twice as much because your product's so damn good. So you probably want to get some sort of a consumption or the amount of sales and how you improve it metric. Hard to do. I might be selling ads on a podcast and my book of business might be low millions of dollars. Alex might be selling, you know, HVAC solutions for, you know, campuses and the average sales might be a $10 million contract per year. And it's a three year contract for 30 million. So how do you reconcile that? Right. It's three, two different groups, same type of person, but different ticket sizes, et cetera. So, you know, you have to find something that is going to like Salesforce. There's a third of people who will never use Salesforce because what is Salesforce course now? Like 3000 a person per year.

SPEAKER_225: I know there's a $500 a month per seat plan. So yeah, it's, it's, it's up there. Yeah.

David Friedberg: Well, I mean, that's $6,000 a year per salesperson. That's why we don't use it.

SPEAKER_00: Um, and so like, doesn't make any sense and it's also cumbersome and whatever.

SPEAKER_36: So you're gonna, you'll find who your ideal customer profile is, who wants to embrace this. You come up with a price maybe for their activity and the number of users, the number of records in their CRM, maybe the number of active engaged customers.

SPEAKER_00: So the more they engage customers and the more the customers respond, the more you get paid. So if you are, in fact, helping somebody engage in more customers,

SPEAKER_36: maybe it's $500 a month plus, you know, uh, you know, $10 for every record in the CRM or every customer engaged, or, you know, charging less than the value you provide is like one of the

SPEAKER_00: things startups do really well. So if Salesforce is $6,000, maybe we're charging, you know, $1,000 a year or 2000 a year and maybe making it not necessary for them to have Salesforce. So I would get audacious here and think if this is how the future of sales is this really thoughtful, you know, agent working with you, maybe the agent is, you know, $50,000 a year. And either you want that agent in your 10 salespeople's email box, or you don't. And you just go for the people who are selling those $30 million contracts, $10 million contracts, seven figure deals only, or six or seven figure deals only. And anybody who's not selling six or seven figure deals, like you should not use this product. And you just go straight for the high end and you help customize it for them. And you give them a lot of attention. Or the other approach is you do what HubSpot did, which is it's very affordable. It's almost too affordable. It makes no sense how cheap HubSpot is. So congratulations on the success. If people want to get in touch with you, what's your email? In case investors, angels, seed funds, employee, potential team members, or most importantly,

SPEAKER_191: customers want to get a direct line to the CEO. What's his email?

SPEAKER_266: It's Sean at getcustomerIQ.com. So the get part important, but Sean, S-E-A.

SPEAKER_191: Yeah. Okay. Sean, I guess, getcustomerIQ.com. Continued success.

SPEAKER_00: And, uh, really sky's the limit. I'm so excited that you went to Foundry University and the accelerator. I think it's like, um. Oh yeah. Becoming a big pattern that we see people, Alex, over 12 weeks in the Foundry University, and we see people who are taking it seriously and watching people work. This is like a great lesson for me in my life is when you watch people work, kind of hard to fake it.

Chamath Palihapitiya: You can, kind of hard. So if you can like make a great steak and I watch you make it, and then I take a bite. Hmm.

SPEAKER_191: You know, like that, it's kind of hard to fake. I mean, you could have gotten lucky and made the perfect steak, but I doubt it.

SPEAKER_00: Okay. We'll see you all, uh, next time on. Oh, you know what? Alex, everybody had a question for me. Where's the all in episode? We'll see you all next time on this week. We'll see you in charge. Bye-bye.