SPEAKER_00: If you take the entirety of unicorn successful companies that have come out of the market over the last 15 years, 92% of those companies had a small fund like yours, Jason, early in, you know, the earliest days they were investors there. But then if you look at how much did they invest beyond the seed stage? Yes. Almost none. Almost none. Less than 5% of the time did they ever even participate beyond the seed stage, which is just, you know, I mean, with some of these companies, it's hard to imagine the value.

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SPEAKER_03: Welcome back to this week's liquidity podcast.

SPEAKER_04: With me today, I have Brian Rosenblatt of Kraft Ventures, a VC firm founded by Jason, your bestie, David Sachs, which now has over a 3 billion AUM.

SPEAKER_05: Next, we have Michael Downing of MDSV Capital, emerging manager focused fund of funds that also has a direct investment fund providing managers with follow-on capital. And, of course, we have Jason Galacanis from the Launch Fund. I'm your moderator, David Weisberg, co-founder of 10x Capital. Today, we have a busy episode. We have, first off, Reddit officially announced it's going public, how companies are using AI. There's a new corporate VC in town, and family offices are stepping in to fill the void left by many institutional LPs. And we'll close out with our special segment where we look at the panel's latest investments. Let's dive right in. Reddit officially announced that it's going public via their S1 filings on Thursday. In their filings, Reddit announced that it has over $804 million in revenue. Brian, you actually worked at Reddit for three and a half years between 2015 and 2019. What was your experience working at Reddit, and are you still bullish on the company?

SPEAKER_08: Yeah, I mean, I'm incredibly bullish. I was there in 2015, the time Alexis Ohanian had just come back to the company as a chairman. And Ellen Powell was interim CEO. So I joined. It was a small team. The business was tiny. They were doing less than $10 million in revenue. And it was a wild ride, obviously, the number cited today. But it's an incredible platform. Back then, advertisers did not know how to work with Reddit. It was sort of the wild, wild west. It was scary and dangerous. There were advertisers that would laugh us out of the room. And some of those advertisers are now spending millions of dollars. So incredibly bullish for kind of what's ahead for them.

SPEAKER_14: Brian, how did Reddit cross that chasm from being a small $10 million advertising platform to the behemoth that it's day?

SPEAKER_08: Yeah, I mean, there's a lot that went into it. First and foremost, it was education. There are so many passionate users on Reddit and communities, but there's a lot of people that it scared off. It was hard to use. And so it took a lot of education because the people that were buying the ads may not be the exact Reddit user. So there was a lot of education of why Reddit, how Reddit, how it compares to other platforms. There was a lot of hesitations around brand safety. We shipped a ton of features to kind of answer those concerns. And we changed the product a lot. We didn't have our own native mobile app. We shipped that. We did a complete redesign of Reddit to make it more user-friendly. And so a lot of work on the product side, but also in just kind of general education.

SPEAKER_17: You're one of these VCs that came from the product side. There's many different flavors of VCs.

SPEAKER_20: What advantages and disadvantages are there to going from company side, from startup experience?

SPEAKER_08: Yeah, I mean, I think there's a lot. I really came from the sales side. And as a salesperson at Reddit and Twitter, I would have to identify companies that were growing and that would be good targets to kind of spend time with and sell advertising to. And so early on, I was always picking companies that I thought would get bigger and have bigger ad budgets and then develop relationships with kind of those advertisers and marketers. And I think that crosses over really well into VC, which is also a big relationship business, spotting talented founders, building relationships, winning deals, negotiating, and then also just having empathy around the process of building. As an operator, there's just so much that goes on, good and bad, and there's a rollercoaster and the frustrations. And I think when talking to a founder and their team, being able to just understand what that

SPEAKER_26: actually means goes a long way versus someone who's only been on the investor side of things.

SPEAKER_04: And Jason, you've been around Reddit for quite a while. You guys started kind of in the alternative media space back in the 2000s. What have you seen and what are your views on Reddit's future?

SPEAKER_28: Well, it's incredible.

SPEAKER_29: I had Alexis Ohanian on This Week in Startups just a week or two ago talking about the IPO. It's just amazing that it survived this long, right? There's something about longevity on the internet. If you remember, there was Dig, which was a much fancier Silicon Valley-based product, as opposed to this Boston-based YC, quirky Reddit site. Both started at the same time. But Dig tried to change their interface. They had this big artificial intelligence machine learning concept early on that they were going to give everybody their own unique homepage. They tried to do what Facebook was doing. And Reddit didn't change. And Reddit just slowly built community. And now I think community has been very hard for people to monetize. It's one thing to have a social network and a feed like Twitter, X, TikTok, etc. But a dedicated forum and community, it was really hard to actually get one of those to scale. And the numbers are amazing. You know, like almost 100 million people use it every day. You have 500 million people using it every month. It's not throwing off as much advertising revenue as it probably should. 800 million, I think, was what they made last year. Because it is challenging. Advertisers in forums are going to contend with the good and the bad, right? And one of the things that's happened over this, uh, rotating set of, um, CEOs, they had, remember that Alan Powell for a minute, um, but of course you got the, the, the, the co-founder to come in and, and take over the CEO slot, which was great. You know, it, it's just amazing what you can do if you don't change the interface and you just let something be and you let it grow slowly. Um, now, if you were to look at the amount of advertising revenue, you know, they have less revenue than say Uber now has, I think Uber's at a billion right now. Is there a run rate? Um, and so it's very tiny, but it's very influential. So that's the thing to keep in mind. This is an influential audience. You can tell it's an influential audience because when people type in, you know, some product review or they want a piece of advice, they'll append to their Google search, the word Reddit. Uh, now users don't know, like how do you cite Reddit or they don't go search on Reddit. They just go to Google, they type it, they search it, it shows you how strong it is. And if you look at interfaces that have not changed and how big companies have become Craigslist, Amazon and Reddit are the top three that just did not change their interface and just let it grow organically. So there's a lot to be said for longevity there. Now the investors, this company was sold once for in a fire sale kind of situation to Condé Nast, then it was spun out famously. Uh, I think Sam Altman, um, he used his, uh, sharp elbows and great negotiating tactics that we've seen, uh, to kind of free it, um, and to get a new cap table gong. So kudos to him for helping the founders do that. I don't know what the company is worth right now as an advertising business, probably not very interesting as an advertising business. And it's very hard for somebody to buy it because to acquire it, you bring all of those challenging subreddits with you, adult content, spicy content. And remember they use pseudonyms over there so people can be anonymous basically. Um, but what's most interesting is the data and it was just revealed that they're making, I think $60 million from Google. And I believe that's a yearly deal. Now I wonder if there's 10 more deals like that to be had. And then the 800 million in revenue could be paired with 800 million in licensing data. Right. And I think eventually somebody might just buy this thing. Like they should buy stack overflow or other sites on the internet. Quora just to let them sit, let them grow, let them service their users, but to feed language models. So I'm kind of shocked that it didn't get bought and that it is IPO-ing, but sometimes companies would do an IPO in order to force the market's hand, right? They just clean up the cap table. Now it's public price is going to get price discovery. And then maybe somebody does want to buy it or somebody wants to buy 10 or 20% of

SPEAKER_36: it, so congratulations to the team over there. Congratulations to the community. I think it's a real testament to the community more than anything.

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SPEAKER_04: Brian, Jason referenced that there were some difficulties with the product in terms of some of the content, but also there's a very different audience.

SPEAKER_20: Very peculiar. It is Socratic versus other communities. What did you come across when you were selling into advertisers?

SPEAKER_08: I think it's actually, there's a lot of surprises. So I think, you know, you talk about some of the adult content and maybe people assume like that very nerdy, techie computer programmers that live on Reddit. And that definitely is true. But some of the biggest communities are around like makeup, makeup addiction. And so L'Oreal and beauty brands are all over that. There's a community called Mommet for moms and Daded for Daded. And so there are these communities that are extremely wholesome. And, you know, speaking on like the anonymous point, people, unlike, you know, these other platforms, like people can have really authentic, real conversations when they're not concerned about their neighbor or friend, you know, hearing everything that they're thinking. And so there's a lot of really deep conversations that happen on Reddit that aren't going to happen elsewhere. There's so many subreddits that I think advertisers continuously get really become surprised by how relevant there are, you know, these communities are to their brand. And they get really excited once they get educated about that.

SPEAKER_04: And Michael, you've been around, I'm not going to say how long, but you've been around through several market cycles. You've taken a company, you started a company and then took it public.

SPEAKER_15: What should the Reddit, how will this transform Reddit as a company being a public company?

SPEAKER_00: Well, I mean, first, to be honest with you, it's like, I'm amazed they're doing 800 a million a year. I mean, that's, that's, that's super impressive for, um, where they've been and, and just the trials and tribulations that a company's gone through with acquisitions and so on. I think that the bigger challenge here is the backdrop of media and digital media is so, um, tough right now. I mean, uh, I think there was an article that just came out in the last three days that talked about how the publicly traded large media companies are on average down by about 50% over the last two years. And obviously this is, you know, a, a new kind of platform and, and, you know, different than traditional media, but I think there's, you know, an advertising or purely advertising based business. It's just a tough time to be, um, to be fighting that fight. And hopefully this training acquisition fee that apparently was 60 million or so from Google, you know, maybe that is a new source of revenue that, that, that creates a new layer of opportunity there. But, um, just the overall environment in the ad market is, is pretty tough at the moment.

SPEAKER_47: And so, uh, it'll be interesting to see how they, how they weather that.

SPEAKER_28: Advertising is a scale business these days is, you know, what it comes down to.

SPEAKER_29: So you just started thinking about the scale. Those are the two major trends in, you know, maybe there's three, there's scale, there's data, and then there's, how close are you to the checkout box? And if you look at those three trends, Meta and Google have massive scale. Now TikTok has massive scale. And then you look at the cohorts, uh, and Netflix has massive scale and they added advertising, right? Now you look at the, how close are you to the shopping cart? Amazon advertising, Uber advertising inside the app. You're really, and DoorDash does this as well. Instacart is an advertising business. Essentially. It seems like Instacart doesn't make money or profits, at least from delivering groceries. It seems like, you know, the end cap advertising when you're in the Instacart app is where they're generating a lot of revenue. And so, you know, Reddit doesn't have any of those things. It doesn't have scale. It doesn't have the end cap. What it does have is influential users. And so, you know, I think when they sell that advertising, you know, to get a passionate group of people, but those people are also cynical and they're not the dopey ad clickers. One of the secrets of the ad business is there's kind of like dopey, like less sophisticated users in the advertising industry. They have kind of terms for them. I don't remember it, but there are people who are just have a tendency to click a lot of ads. You know, same people might watch a home shopping network or something and buy stuff there. They just like advertising. They like shopping. So like, maybe we all don't click on a lot of Google ads or ads in our social media feeds, but those people do. The sophisticated Reddit people. I mean, it's hard to get them to click on ads.

SPEAKER_49: I think it has to be really well-crafted, creative, et cetera. And I think it has to be like really targeted. I think you would agree, Brian, right? It has to be like, they're discerning users, right?

SPEAKER_32: They're not like Yahoo users or AOL users clicking on every ad.

SPEAKER_07: And yeah, it's definitely a platform where it's less of like a copy and paste your Google

SPEAKER_08: ad onto Reddit and you're successful, which was a challenge, especially early on. Because we have to convince brands not only to spend money on the platform, but to spend the time and energy to develop content and ads that work for Reddit. I do think they've convinced the market to do that now, which has been great. So I think you are starting to see really interesting, different ads and people taking it seriously. But it took a long time, you know, to get to this point.

SPEAKER_29: This company would be worth 10 times as much if they just said to the market, we have an ad business that keeps the lights on. We're building a large language model exclusive to our language model and you can ask Reddit questions and nobody else is allowed to have access to this data, period, full stop. And we're not going to license to anybody. And our LLM is going to be, you know, a great way for you to get answers. And they just, you know, put that answer engine when you search there. And then I think the market street would be really like that story. And maybe they put a billion dollars into the IPO for them to buy NVIDIA servers and GPUs and get to work on it. Seems like maybe they didn't do that. Steve maybe just thinks the licensing deal would be better. But Steve's been very clear that that data is proprietary and you cannot use it.

SPEAKER_49: And Elon's been very clear about that with X.

SPEAKER_29: And I think a lot of these people are looking at open crawl. They're looking at what open AI did. They're looking at what, you know, Microsoft did in collaboration with them and what Google's doing. That open crawl data set probably has a lot of Reddit data in it that is illegally unlicensed

SPEAKER_56: in people's models. So it's just something to definitely consider is how much revenue they can make from that too.

SPEAKER_14: We saw the New York Times open AI lawsuit. How much of a lens do you look at that, Brian, when looking at AI companies? How much is proprietary data driving indicator of value?

SPEAKER_60: The data is so key.

SPEAKER_13: You know, I think there's very few companies that have truly, truly unique data at scale and Reddit is one of those. So that's huge. But I mean, when I'm looking at a startup investment, it's a key question. It's like, well, what's the moat?

SPEAKER_08: What's the data moat? Why do you have this that someone else can't get? And most of the time, there's not a good answer. Like it's, you know, not super unique. But I don't know, one in 10, something like that, there is a good answer for why they have unique access through some sort of partnership or some sort of know-how, or they know this antiquated industry and have access to this. And those are absolutely, you know, interesting strategies to invest against.

SPEAKER_12: And Michael, you're really, you're really bullish on AI and you invest in a lot of AI only funds.

SPEAKER_64: What are you looking for, for early stage funds in terms of AI investments?

SPEAKER_45: Yeah, I mean, for us, we think that this is going to develop much the same way in the

SPEAKER_00: mid 2000s, you know, when it was mobile and cloud, you had some mobile specific funds, cloud-focused funds, and then it became clear that that's in everything. And, you know, there kind of ceased to exist, those focused kind of thematic funds. We think the same thing's going to happen here. But, you know, for the moment, we do think there's certain folks who have a technical advantage when it comes to AI investments. And what we've seen is they're typically individuals who were on like ML ops teams for the last five or seven years, and they've got a level of technical expertise that's pretty unique that not only gets them into interesting deals, but also kind of creates a network around them of people who have been doing this for a long time. And so the managers that we've backed that are focusing on AI look like that, a pretty unique technical background.

SPEAKER_14: And do you see it like stages, like in crypto, everybody was investing in infrastructure and they have this whole thesis of like three different stages of development. Do you see the same thing in AI or is it completely different?

SPEAKER_00: No, we do. There's kind of the foundational concepts, the infrastructure concepts, and then the many, many apps that are going to, you know, get created, which has already started.

SPEAKER_70: I think open AI said something like there's 70,000 GPT apps or something that have been created, but we're focused in on that infrastructure layer right now, because there's, there's many

SPEAKER_00: opportunities in that category. We've stayed away from just simple kind of application concepts, just because I think as, as you guys have discussed before on the pod, there's these extinction events that occur, if it's any kind of business, it's adjacent to what open AI is interested in or, or any of the other kind

SPEAKER_70: of larger companies. And so we've really focused on that, that infrastructure layer.

SPEAKER_04: Brian, how are you, how are you playing the game on the field? What is graph looking at in the AI space?

SPEAKER_74: I mean, we're, we're, we're looking at everything, but it is a, it is a crazy game to be playing

SPEAKER_08: right now. Um, I was saying this earlier today, like it, it literally feels like you're, you're driving in the storm and it's, you can't really see, um, it's really hard. Um, and so like what I personally focus on is, is kind of picking the driver, like focusing on the individual. There's just every single day, every single hour, something changes, completely changes the game. And so I don't really want to go out and say, this is exactly how I think things are going to go or should be, or should be built. I kind of want to go and find like the best people, best teams, and just trust them to kind of navigate what's happening. Um, but I think that's what makes this so difficult right, right now. And so early stage, it's, it's all about the team.

SPEAKER_76: And then like later stage, we need to see proof there has to be more than just kind of hype around it.

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SPEAKER_29: That's devsquad.com slash twist. I think Michael's point is really good. I use the analogy as well, Michael, of mobile, and what we all witnessed where when mobile apps came out, that was a chance to displace some incumbents, maybe who didn't build a mobile app quickly enough or didn't understand it, eventually they all caught up. And, you know, if you use your United app now or your Bonvoy app, it feels pretty great. But, you know, it wasn't very good, you know, when mobile apps were first coming out. And then what mobile apps would be and how they would monetize change like five times. It used to be you would buy an app, like a flashlight app for a dollar or $2 in the app store. It was a one-time purchase. The app wasn't updated. And then they would come out with flashlight two. And you would buy it again. And it had three new features. It wasn't like versions. And there wasn't subscriptions. And with a company like calm.com, which we were the first investors in, we had put $378,000 into the company. They were charging $10 for the app, just like everybody else. And then they got early access to subscriptions. And they changed their model to $10 a month. And consumption went up. And when subscriptions came out, you know, things got, you know, really, really popping. And in fact, the app store didn't exist in the first iPhone, nor did GPS. And so a lot of what we said, and payments certainly didn't. And so it took a while, as Brian is sort of saying, I think that's what's happening. Brian's right. In, you know, AI startups, the products like ChatGPT, Gemini, as we saw, you know, this week with all kinds of weird, woke, you know, funny stuff happening on X that trended, the answers are not good. And, you know, verticalized apps can give good answers. If you ask it to do something very verticalized, you know, very narrow with a great prompt. Yeah, maybe you can get close to an actionable, reliable answer. But a lot of these things feel like toys and proof of concepts. So I think we've got three, four, five years of work to do to make these functional apps. So that's something like Robinhood or Uber, you know, those apps, Instacart, DoorDash, et cetera, it took a while for the sophistication level of the mobile phones to be able to do those kind of apps. Like it took maybe four or five generations to have something really good on mobile. I think we're in the first generation right now of these AI companies. Now we're investing in a ton of them. I'd say more than half the companies we invest in are specifically AI related.

SPEAKER_49: And 100% of them are using AI to build their companies. So this is the trend. That much is clear. And if you try to do hardware, you missed it. Sorry. NVIDIA is going to run the table. You know, maybe Chamath will do well with Grok. I suppose he will because he got in seven years ago. But, you know, I don't know how much hardware opportunity there is right now or language model opportunity for that matter. I think open source wins that too. So I think it's back to the application layer.

SPEAKER_00: I think it's a really good point. I mean, the one thing we've seen that we feel like has been net new and just very unique to observe out there has been, you know, because we offer up an opportunity fund to these small emerging managers. They bring to us some of their fast growing companies. And so we've been able to see just how fast some of these AI companies are growing. And to Jason's point earlier about the companies themselves are using AI products. I mean, what we've seen is like very small teams. I mean, in one case right now, like a 16-person company that's doing over 20 million in ARR, which, you know, and they got, they went from 1 million to 20 million in like six months.

SPEAKER_70: And, you know, those kinds of numbers are just really unique and not something that we've seen before. Typically, you've scaled out and hired a ton of salespeople and, you know, created a big

SPEAKER_00: organization. And, you know, I just wonder if that's going to become more of the norm, smaller teams, fewer people, but they can actually scale these businesses really quickly, largely based

SPEAKER_70: on using AI tools themselves internally.

SPEAKER_49: It's definitely the trend I'm seeing. And so the question is, if that is what's happening, what do cap tables look like over the next five years, right? Like, yeah, exactly. And when do founders take money? If they have 16 people, like how much revenue, how much investment do they need? If they're paying everybody, if they just say they paid everybody a million dollars a year, which I'm sure isn't the case. Right. Maybe $16 million a year. And if they're making 20, they're making 4 million in profits a year.

SPEAKER_00: I mean, the case that everybody references a lot out there right now is mid-journey, which I think has 11 full-time employees and is doing over 200 million a year. So you just think about that for a second. It's like, that's an entirely different reality, you know, for how a startup can scale. So, I mean, it's exciting. It's also a little bit, you know, terrifying as far as, you know, do they need VCs anymore

SPEAKER_90: at that point? I mean, are they going to need to raise money? What's the answer? I mean, I think they're not going to need, you know, much venture capital at that point if they're doing over 200 million. I wouldn't assume, but it'll be interesting to watch.

SPEAKER_20: The contrarian view on that would be that all the resources will go towards the scarcity.

SPEAKER_14: So you see, the paradox is that all these AI companies are raising tens of billions of dollars because they're all focusing on compute. So it really depends where the bottleneck and where the next scarce resource comes through. Jason, what do you see as a second order effect in terms of, you know, the cost, cost going down for everything? How does that change how you invest?

SPEAKER_33: You know, I'm very lucky to be pre-seed and seed, and then I get to work with funds like

SPEAKER_29: CRAFT and, you know, we have 70 companies, um, or super 70 that we've identified 70 downstream investors and, um, um, we focus on sending our companies to, there's about four of them that are, are like fantastic four who are LPs in our fund and who we give very unique access to our companies. And then the rest of the, the, you know, super 70, we try to put them in touch with them. I don't think it's going to have too big of an effect on series a, it's certainly not going to affect seed, um, and pre-seed because, you know, you need your first 500 K, you need your first 3 million. And then why wouldn't you take a, you know, a great sequoia, $10 million round or a great craft, you know, $5 million round, whatever it is. But series B and C, you know, could become, my prediction might be, we might see an industry, Brian, um, and I'm curious your position as a series a, a primary investor, but I know you have a seed group too, you know, I wonder if series B and C will become buying secondary more than buying primary. And so, you know, if you're a mid journey and you had this amazing outcome, like, well, maybe you just sell 10% of the company. Maybe you sell 5% of the company and just give liquidity to your employees and founders. And that's how you liquidate. It's kind of like, um, you know, a direct listing IPO kind of space X secondary thing.

SPEAKER_36: I don't know. What are you seeing on the field, Brian?

SPEAKER_93: I am definitely seeing that more, more and more at this kind of like growth, growth stage series B and later.

SPEAKER_08: So definitely more funds, leading tender offers, the companies just, they don't need to raise more cash, um, but they want to get their employees some liquidity. Um, and so that, that works. Um, it's, it's a, it's different, it's unorthodox, but for us, like we, you know, as a firm, we don't have kind of super hard and fast rules and we try to be opportunistic. So we, we have partaked in, in things like that outside of your just typical, uh, straight equity round. Um, and I think we're going to continue, continue seeing it. I also think like, you know, if rounds do get smaller, that's okay. You know, the round size has got crazy the last few years. There's so much money, so many investors. They rate, we rate everyone's raising too much money. Founders have too much money and it becomes an issue. Um, so I think it's just the best of the ecosystem. I think it's actually okay. Um, you know, to raise less and to need less capital.

SPEAKER_13: It's, it's not only okay.

SPEAKER_96: It's preferable because man, when a founder is sitting on a hundred million or 200 million in cash in their bank account, Michael, you're shaking your head. Like, I think you've experienced this as well. Like if it F's with your head.

SPEAKER_29: Oh yeah.

SPEAKER_96: I mean, look at that deposit and then you see 5%, you see $10 million in interest a year, you know, 800,000 a month in interest coming in. And you're like, oh wow, I can do crazy things with large piles of cash on natural.

SPEAKER_08: You feel like you have to the, the, the, the crazy, the crazy off sites and offices and hiring. And then, and then, and then it's, you know, time to get fit and it's like, wait, we just cut all these, you know, cut all these things out and we're actually, not only are we okay, we're actually better, we're moving faster. So it's, it is, it does feel like a drug raising, you know, raising too much money can, can be a real negative.

SPEAKER_29: This is back when we had offices. I always knew when a startup was in trouble, when the, um, founders were meeting with architects and, you know, designing the lobby or like the open office areas and stuff like that. I'm like, what does this have to do with the business? Like just find an office space and no, no, we're creating a culture. We need to have these like pods and we're going to have this area. We have a ping pong table area. I'm going to have this room. And that was kind of like, this seems like an awful lot of cognitive load. And you know what I see with VC friends, they make some big win. And now they're meeting with architects to build their dream home. And I'm always like, you know, it'd be really good is to just build a home. That's already finished. And it may not be my dream home, but close enough. And I can get back to work and back to my family.

SPEAKER_78: So prioritization and focus is so key. Yeah, absolutely.

SPEAKER_70: And, and we just went through so much of that, uh, as well. Just, just too much money in the system and, and so much questionable judgment. I mean, it's, um, you know, we, we feel like we're going to be kind of living through that for at least another quarter or two here. And we certainly see from LPs and institutional LPs. They're still living through, you know, the, the kind of ugliness of that.

SPEAKER_73: Um, so it's definitely a challenge.

SPEAKER_102: Ryan, you've seen, you've seen companies kind of get bloated.

SPEAKER_20: Have you seen any companies recover or is that kind of just, you know, psychologically, they're, they're, they're addicted to the money and they can no longer recover.

SPEAKER_08: I've totally seen coveries. Um, and it's, it's, it's amazing, but it's also frustrating that, you know, that it kind of took, you know, a forcing function of the markets to, to do it. I do think though, there, there are some teams and some founders where the, the money, um, kind of hid the issues and they weren't able to, to kind of build an efficient business. Like there just wasn't true product market fit, you know, you have to keep in mind during this, this like Zerp era, it was just easier to sell. And so, you know, I've definitely, there are startups, um, where maybe we didn't invest, but they were, they were growing like crazy. And then the market turns and not only are they not growing, like they're, they're shrinking, but certainly there are companies that had to get more efficient that did, and they're better for it. And they're growing into evaluation. That was high, but won't be that high in another year or so.

SPEAKER_04: How do you have that conversation, Jason? Uh, because a lot of these companies are very hot and you want to get into the next round. You want to get your pro rata.

SPEAKER_14: How do you have that conversation with companies around, around, you know, uh, facing reality?

SPEAKER_29: Yeah. You know, people who select me as an investor and a partner, you know, they know that they're

SPEAKER_49: getting J Cal, not to talk to myself in the third person, but they know my brand is like candid kid from Brooklyn. I'm going to give it to you straight.

SPEAKER_29: And so I tell them like, I've seen this movie before. And if you start blowing money this quickly and you take that a hundred million and you divide it by 18 months, we're going to be sitting here in month 12 or 14. And you're going to be regretting this decision. Instead of saying, this is what I need over the next 18 months to accomplish these tasks. And then putting the money out of your mind. And it was the same conversation to have with people about venture debt. Now, sometimes I'm successful. And during this, I would say two out of three times I was not. And so I'll give you the perfect example. Every founder of a company without product market fit. Wanted to add one to $5 million worth of venture debt on their round. And I, I, David Sachs and I had long talks about this on all in and previously. I'm just like, what is it? Editing boards we were on together. Why are we doing this before we have product market fit? We got cash in the bank. Well, what is the $7 million do? We have 6 million in the bank. We're going to add one or 2 million in venture debt. Why? Why are we doing this? Because somebody called us up and offered it to us. I saw venture debt go, go really wrong during the great financial crisis. And I started to go wrong during the.com era. And when the covenants start getting broken, even if you have a no covenant thing, you can't pay back the bills, man, your, your whole life becomes trying to negotiate with a bank.

SPEAKER_96: Uh, and yeah, you, you know, I think it took two years in some cases to convince people. Uh, and in many cases we were not successful. They ran, uh, they ran the car off the cliff. We told them that's a cliff, not a bridge. If you keep going that fast, you're going over the cliff. There's not going to be another round of funding for you. We certainly can't do it. We're seed investors. You're, you're, you raised your series B and you're racing towards a cliff like them and Louise. Like, is this wise? It's not wise, you know, take your time. You know, you're, you're, you're, what's the rush here. And I mean, I don't know about you, Brian, but it's the ultimate frustration of the last couple of years is watching people blow through cash piles.

SPEAKER_110: And they're like, what did I do? I wish I just had, I wish I had the, you know, incremental 5 million. I blew on nonsense.

SPEAKER_13: Yeah. And especially with, with venture debt, when, when teams and founders confuse the venture debt as like, it's more runway, you know, um, that, that's, that always, uh, it's again, it's another, another drug. So yeah, for all the reasons you and David talked about on, on all in, um, we, we are very, we advise founders to be very cautious with, with it. And, you know, there are some businesses and times where it may make sense, but for the most

SPEAKER_08: part, um, you know, founders need to know their bank account, their burn, uh, they need to manage it really, really, really carefully. And I think founders who grew up in the Zerb era, like they didn't realize that until they

SPEAKER_42: kind of got smacked in the face with reality.

SPEAKER_112: Yeah. If you have a CFO, like a legit CFO and the CFO tells you, yeah, you know, we should have

SPEAKER_29: a little bit of venture debt. I've worked with these folks before. I negotiated it. This is standard. That's non-standard. But when, uh, you know, 15 person company adds three or $4 million in venture debt, because they think, well, I'm spending 500 a month. That's an extra six, eight months of runway. That's not what venture debt is for. You know, you have to have profits or, you know, the ability to pay back that debt. That's why you would do it. Founders always ask me for pitch deck punch-ups.

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SPEAKER_05: Moving on. There's a new corporate venture capital fund in town. We've been talking about AI. The fund is none other than Sam Altman's OpenAI fund. Axios reported that the OpenAI fund, which was set up in 2021, has already invested $175 million in commitments. Which includes startups like Descript and Harvey.

SPEAKER_04: Noteworthy is that OpenAI's fund has outside LPs, which include none other than Microsoft. Brian, what do you think about OpenAI's corporate fund?

SPEAKER_13: Well, I mean, for them, it's a no brainer. You know, I mean, they have maybe the best access to developers and founders building within AI.

SPEAKER_08: They know the space probably better than anyone. And, you know, unlike a lot of corporate VCs, I mean, they have a leader and CEO and Sam who, you know, has a proven track record of being a really good investor and picker of people. So I think it's huge. I mean, they also obviously like they know their product roadmap. So they have this unique insight into what they're building and what they're not building. And they're going to use that knowledge to decide what to what to invest in or what not to. I mean, every AI investment decision, I think every, you know, at every firm people are going to talk about is, are they going to build this? You know, is is Sam and is OpenAI going to build this? But OpenAI knows that answer gets to invest based on that. So I think it's a no brainer for them. You know, I'm sure we would, you know, as a firm will be co-investing with them. And I think, as you said, like they're, I don't think they're really raising outside capital, but I'm sure if they were, there would be a line out the door of a ton of demand.

SPEAKER_04: Michael, corporate VCs date back to the early 90s until Capital famously was one of the most active investors in Silicon Valley.

SPEAKER_14: And then corporate VC really evolved with with GV, originally called Google Ventures. What's the pros and cons of taking corporate VC for your startup?

SPEAKER_00: Yeah, I mean, from from the LP position, but also just just from being a former operator, I think too often you see founders at too early a stage say, gosh, wouldn't it be great to get validation by having the strategic investor come in this corporate and be part of the cap table? And I think what people forget all too often is, you know, the problem with strategics is they're not going to lead around, they'll probably require a blue chip, you know, lead to be in the round. They're only going to come in once. They're rarely going to follow on in any rounds. And, you know, for the most part, except for perhaps Google Ventures and others, you know, they're very seasonal, meaning when the market is pumping, you see a lot of corporate VCs. When the market is going into a tough macro cycle, you see a lot of those corporate VCs just, you know, lock the door and shut down as we're seeing right now. And so, you know, there can be some challenging and awkward moments in board meetings when you have a big strategic. If I was right now in this AI space, I mean, me personally, and looking at the funds we invest in, I'd rather have founders, you know, who are pirates, not people pleasers, meaning go out and scare the hell out of the open AIs. Don't go partner and take money from them, especially in a market where they're going to eat up a lot of little application companies along the way. So that's how I look at it.

SPEAKER_14: A lot of VCs get afraid that having a strategic scares away other potential acquirers. What are the pros, though, of taking corporate VC money?

SPEAKER_00: I mean, does it provide validation early on? It absolutely can. So, and I think that's why a lot of entrepreneurs, a lot of founders, you know, love to have that big name on their cap table. So I think there's certainly positives.

SPEAKER_70: In my experience, the negatives outweigh the positives generally, especially in such a hyper-competitive market like AI, and it's the biggest AI company, you know, in the market who's going to likely be very acquisitive going forward.

SPEAKER_53: Yeah, if you want to have a large, sustainable business, you want the best venture partner in the world.

SPEAKER_29: So if you could have your choice, if you think that, I don't know, Microsoft's the greatest partner in the world, would you rather have Microsoft give you your Series A, Series B? Would you rather have Sequoia do it? You'd rather have Sequoia.

SPEAKER_96: Sequoia is aligned with building a large, legendary company that goes public and is sustainable and becomes the next Microsoft and competes with Microsoft. And, you know, with strategics, and we saw this with OpenAI, when OpenAI had problems, what did Microsoft do? Microsoft went in and said, we'll take the entire team. We'll gut it. So there is the perfect example. We're talking about, you know, Sam's OpenAI Fund, which is OpenAI, it's not Sam's.

SPEAKER_29: I think Axios was kind of playing a little gotcha that it was under Sam's name and not, you know, officially OpenAI's, you know, like journalists will do. It's fine. You know, I think they probably just didn't finish paperworking it properly. In the case of Sam Altman, I will say no conflict, no interest. If I could put money into that fund, I would do it immediately for the reasons Brian states and more. Number one, they have access to proprietary data. They know which apps are getting traction. They also have the ability to give you access to software before they give it to anyone else. And there was an instance with one of the companies we had invested in, and they were like, hey, we can't compete against this company that Sam Altman and OpenAI had invested in. And they're giving them early access so they can get early access. Now you'd be like, oh, that's unfair. You know what? Life's unfair. If that startup got that deal, and part of that deal is to get early access, and they were giving them equity. As we say in the industry, no conflict, no interest. This has conflicted 18 ways to Sunday, which is why it's awesome. You know, now, and who's going to complain about it? You know, who's getting hurt here? I mean, I guess arguably some startups that compete, and maybe it doesn't feel fair, and somebody might call that out at some point. The Descript competitor, right? And let's say Descript, you know, can call Sam Altman up and say, hey, you know, we have this problem with tokens or whatever. Can I talk to an engineer? So, yeah, talk to Joe. Talk to Susan. I CC'd them on this email. You know, and I have a Descript competitor in my portfolio. I don't, but I'm just saying, well, what if I did? That company, you know, can't even get access to anybody over there. And then the folks there might be like, you know what? Yeah, we don't own shares in your company. We're not obligated to give you, you know, some competitive edge against the one we have equity in. Now, if you were to think about this, well, why wouldn't Apple do this with their ecosystem? Well, the reason is they don't want to have this kind of problem. So OpenAI and ChatGPT are too small to have this unfair playing field issue. But as it grows, you know, maybe it will become pronounced. And people will be like, imagine Apple was like, yeah, we're going to invest in Spotify, but not Tidal. We're going to invest in Uber, but not Lyft. We're going to invest in DoorDash, but not Instacart, right? And they started picking winners and they own 10% of them. AOL did that back in the day as well. And NVIDIA is doing that now. So conflicts exist in our business. They can lead to great returns. They can also lead to, you know, developers and people feel, they can lead to a lot of bad feelings.

SPEAKER_124: So be careful.

SPEAKER_20: Brian, you mentioned you would be an LP in OpenAI if there's an opportunity. Would you counsel your companies to take money from OpenAI? Why or why not?

SPEAKER_106: Some of the reasons Michael mentioned, like why corporate VCs could be bad.

SPEAKER_13: I mean, what comes to mind to me is if they're asking for these weird special rights, they want a row for an acquisition, you know, potential M&A, or they say you have to use us as, you know, your preferred vendor. But if they're coming in with no special rights and not, they're not going to control the company,

SPEAKER_08: they're a minority investor. I think it could be interesting. And I think, you know, I think the companies that they've invested in, like Harvey, I think they may have seeded it. But Sequoia led the A, and I think another big firm did the Series B. So I think the way I'm thinking about them is not as like they are the largest shareholder. They're just a part of the cap table. I'll tell you, like, if you're investing in a company in the legal tech, doing something with like a co-pilot for legal, and, you know, that, that company is raising money and raising a Series A and you have a competitor, and OpenAI is going to invest in one of them, like what I want OpenAI to invest in my company or the competitive company, I'd probably want them on my side. They are, you know, they're, they're a special, a special company. I mean, I think this is a unique, this is unique. This is different than if it was like Visa, MasterCard sort of thing. OpenAI, I think just has such a lead and could be such a kingmaker that it's really strategic to have their involvement. Even if it's more from a defensive standpoint.

SPEAKER_12: You look at the ecosystem, you have OpenAI, you have GROC, you have Anthropic, you have

SPEAKER_127: Google. What's your view on the overall ecosystem and who will be the winner in your eyes?

SPEAKER_08: Well, I mean, OpenAI clearly looks like they have, they have the lead, but I think, you know, the, the players you just mentioned, it seems to be like those, those are kind of going to be the players and there's wild cards. Obviously what, what Elon's doing with XAI be a wild card. Um, you know, I think with Anthropic, it's, it's, uh, Amazon is a huge investor in that. Um, so time will tell, but this is kind of goes back to what I was saying before. Like it's really hard to predict the future, but OpenAI right now has a huge headstart.

SPEAKER_13: Um, they're releasing so much product so quickly and have such a talented team that it'd be hard to bet against them.

SPEAKER_30: What do you think, Jason?

SPEAKER_96: I am long open source, um, especially because of the controls.

SPEAKER_29: That, you know, these players are putting on, um, some of these models. Um, so, you know, if you want to, I was asking Gemini today, like, just give me a list of Trump's legal cases. I kind of did this in a trolling way on the all in pod. And then I said, I asked chat to me, give me a list. And Gemini was like, uh, you know, elections are complex presidential, blah, blah, blah. You should use Google search. And then, you know, chat to PT was like, here are the six cases where anyone, here's a link to a story about each one with citations. Um, I think people are going to want to know how these things work. And in order to make really elegant applications in verticals, you're going to need to understand how these models work. So I believe if you're going to build something in accounting and tax, you're probably not going to use chat GPT. I think you're going to wind up using some open source model with some proprietary data, and that's going to be a better solution for that verticalized app. Um, and then I think they'll just be just like, there is a long tail of open source projects that do really interesting things. I think there'll be an open source of these models and they'll be faster and better. And I think that's why Apple, you may have seen Apple has an image, uh, open source, uh, Maggie, I think it's called. So Apple just released it. It's terrible. But I opened my Apple, uh, photos just the other day and I had a picture of my bulldogs and there was that, that little AI, you know, stars and I pressed it and it was like, bulldog click here, click bulldog. It takes me to the Wikipedia page for bulldog or the definition. So even Apple moving slowly, they have an open source image project and it's basically to edit, manipulate, understand what's in images and they're going open source.

SPEAKER_96: Now, if you were going to build your next app, you're going to use that. Are you going to use, you know, Dolly, I think you're going to go open source. So I, I'm just a big proponent of open source in this case.

SPEAKER_29: Um, and I also licensing of data is very much an active discussion between the lawsuit with

SPEAKER_49: New York times and open AI, Reddit licensing to Google. So I think a lot of the paid models will have issues that they open source ones.

SPEAKER_14: Michael, what do you, what do you think about that? You're, you're talking to all the early stage GPs that are investing in AI. What are the models for the future? How is AI going to monetize itself?

SPEAKER_00: Yeah, it's, it's interesting way to a little get together a couple of weeks ago, um, with some of the managers who are investing in AI. And we actually had, um, Blake Samick from, uh, opening AI, who's the, um, head of product operations, come and talk. And some of the kind of interesting things that came up that I wasn't aware of. I mean, if we think about it for a second, chat GPT just launched in November of 22. So it's only been out there for what is that 14, 15 months total. Um, one thing that, that I wasn't aware of, and I think is driving a lot of the investment activity, uh, for our managers is of the 1.7 billion in revenue or so that's happening in and around, uh, open and AI right now. Um, the majority of that is, is consumer driven, uh, which was a little surprising to us. Uh, we just figured it was enterprise business, people starting to build tools, et cetera. And so I, I think that's a filter that a lot of our managers are applying and thinking about, you know, is this first wave, um, going to be more a kind of consumerization of the enterprise type cycle where individuals are going to perhaps adopt tools, start to use them. And then eventually those tools will, you know, infect their broader, uh, organization or, or, or, or, or business. Um, but that data was pretty surprising to us and, and we think it likely is going to

SPEAKER_70: be important in just how things develop in the market.

SPEAKER_14: What does that say about the space? Is the opportunity consumer or is it still an enterprise?

SPEAKER_00: Well, in this case, I think it's not so much it's consumer because all these are productivity tools or, you know, ways to kind of manage multiple applications or create a single pane of glass to, you know, various, various applications that you use in your life. And so, um, the way it got filtered in this discussion and we're talking about it is that, you know, more and more of these applications may have a kind of Yammer-esque approach to the market where they get individuals to sign up, um, for them and start using them first as a kind of life hack. And then they make their way into the enterprise.

SPEAKER_04: Brian, your, your, your partner, David, uh, obviously founded Yammer, sold it for a billion dollars to Microsoft and another, uh, actor in this player.

SPEAKER_14: What percentage of your opportunities are you seeing in consumer versus enterprise when

SPEAKER_15: it comes to AI?

SPEAKER_13: I mean, we're, we're really focused on enterprise B2B. So it's definitely more, more in that, in that world. Um, so it may be a little skewed because that's really what we're doing, but, you know, I have been a bit surprised by how few, um, interesting opportunities I've seen in consumer.

SPEAKER_08: I do, I do think that's going to change. Um, Elad Gill had a good article. I think it was him today, but he made the point like chat GPT, it's still fairly new. Um, and it's changed a lot of things and it takes, oftentimes it takes six to 12 months for an employee at Google or wherever to decide, like they're going to quit their job and go all in on AI and start building things.

SPEAKER_13: So I think like the next year is going to be really interesting to see what types of companies get built. Um, I think we're still super early there.

SPEAKER_14: Jason, you're, you're looking at startups at the very infancy. Sometimes it's just a couple of people and an LLC. Are you seeing more opportunities today, 2024 and consumer and enterprise?

SPEAKER_143: Yes.

SPEAKER_110: I mean, it's, uh, you know, you, you have, um, second and third time founders really

SPEAKER_29: like to go enterprise because they probably did something in consumer and they realize consumers, lightning in a bottle, one in a hundred figure something out and it becomes really big and then enterprise, you know, probably, you know, I don't know, one in four or five have a great outcome. So I think that's why a lot of people rushed into it. It got a little bit too crowded. That's why there were too many project management. You know, you'd have 20 different people going out for some narrow SAS, uh, vertical. And, um, you know, but I, I love consumer and we are a power law investor. We do a hundred new investments a year. We'll do two, 300 names in our fourth fund. And then we'll reserve capital, half the capital for the top 5%, which will be 10 to 15 names. So we'll be super concentrated in those names when they break out. And so we can deal with consumer. Whereas most VCs because they're placing 30 bets on a craft. You have 40 bets in a fund. I'm guessing you have a billion dollar fund now and they also have multiple vehicles, but you know, if you were a classic. Uh, $400 million, $600 million fund. I think you probably have 40 names in it most typically, uh, Michael, you might know actually, um, what the, the, the numbers are now, but thinking like, um, you know, Mark Schuster at upfront or Fred Wilson at, um, flat iron, uh, no, no, no. I'm sorry. Union square now. Um, and so, you know, what are the chances of hitting a one in a hundred hitting a Twitter, uh, you know, listen, Fred hit it. So a lot, a lot of people will just go for, for that, for the enterprise ones. Cause the hit rates are so much better, but you're not hitting half court shots. You're not hitting threes. So if you think about this, you know, maybe enterprise is the layup of venture and a consumer is the three point shot and you get paid a much bigger premium. If you look at my biggest hits, Uber, Robin hood, calm. Um, those are all consumer, thumbtack consumer. And then if you go, uh, thanks for knowing my portfolio, no, but then I have data stacks and, you know, grin and a density, all unicorns like, and those are in B2B. So, you know, you, you can play either game. I, I let the founders tell us where the world is going.

SPEAKER_56: That's I have that humility in the second decade of being a capital allocator. It's not about what I think it's about what these founders think they want to build, how passionate they are about and how well they know the customer base.

SPEAKER_20: Brian, uh, Jason, Jason called you out, uh, on portfolio construction. So let's talk about craft portfolio construction. How do you look at that and how flexible is your portfolio construction?

David Friedberg: It's flexible. Um, you know, and it, and it, it, it changes based on the market.

SPEAKER_08: There's, there are times where it makes more sense to, to be more focused on series A or series B. And sometimes it, it doesn't like we are always looking at the risk report based on the market, based on the space right now. So if, you know, for example, with AI, um, personally, I'm probably more excited at the earliest stage, seed stage or growth when there's like a lot of, a lot of more proven metrics that series, the series A and series B, um, I'm, we're going to do, we're going to do them, but they're harder. So it is overpriced and without traction, very little traction, um, overpriced, lots of hype, everyone has an AI fund. Everyone's investing in AI. It's, you know, it's, it's the craziness again. Um, and it's hard, like, it's really, it's really hard. Like, you know, I think the, the more we learn about AI every day, I think I create, there's like more and more questions, um, that, that come up. It's very different than a lot of other, you know, areas and sectors where we are, we're getting smarter and smarter every day. I feel like we're literally, there's more questions every day. Um, so it makes it really hard to pick that series A stage, especially right now.

SPEAKER_05: But when you look at your portfolio construction, are you still kind of general as a billion dollar fund? Are you still looking for one company to return the fund?

SPEAKER_150: Do those, do those metrics change from, do it with fund size?

SPEAKER_08: Yeah, yeah, definitely. Cause there, there are, there are companies that sometimes I will see where I like the founder. I think they're going to have, they're going to have a good outcome, but it's not going to be big enough to return the fund. If you know, we, we don't invest in a company unless we think it has the potential to, to return the fund. So we will pass on things that could be, you know, good outcomes for the founder, um, or for smaller funds, but they're, they're not deals that, that we, we will do, um, you know, our sweet spot, um, you know, we will lead C deals, series A, series B, and anything

SPEAKER_76: beyond that will go into, to the growth fund.

SPEAKER_14: Michael, you're, you're working with much smaller managers. Some of your managers are 20, 30, $40 million. How does that change your portfolio math on your managers?

SPEAKER_00: Well, we, we have a pretty specific, um, approach in a specific strategy that we apply here. You know, we're going into approximately 24, 25 of these small funds. They're all 60 million or less. Many of them are 20 million, 30 million. Um, they average right around 30 million in size. And, you know, there is the allocation to those fund managers. And then, you know, specifically we have the kind of opportunity fund for the broader community

SPEAKER_70: of managers as well, which is basically a direct investment fund for the follow-ons into the outliers that come out of those portfolios.

SPEAKER_00: And so, for us and for our LPs, it's the combination of these two things that create the opportunity, a really steady, predictable, call it three and a half X return on the emerging manager funds.

SPEAKER_70: And what we kind of underwrite at a four to six X return on the direct investments that go into the outliers from those portfolios.

SPEAKER_85: I'm curious, what, what, what is the name for that?

SPEAKER_157: Your type of fund, Michael, because I know what a fund to fund is, and we know what a, you know, a GPS, and what do you call these funds specifically designed to be a, you know,

SPEAKER_00: help a prorata? Yeah, we kind of changed it up a little bit because the, the fund to fund part of it, meaning the capital that goes into the small emerging major funds, we charge no fees on, no management fee, no carry. And so when LPs come in, part of their capital is going to that. And part of their capital is in this, this kind of direct allocation. That's just going into the outliers that come out of the portfolio. We're only charging fees on the direct investment part of it. And, and the reason why we did that is we had feedback from LPs from the beginning. It's nobody likes doubling up of fees or, or seeing them stack, uh, since the managers themselves charge fees. And so it is a little bit of a, a different approach. I'd let, I'd like to say that we invented this, but actually there's a handful of. Single family offices in Silicon Valley have been doing a form of this for a number of years where they basically equip an army of small specialist fund managers out there, you know, to go find great deals and invest in companies. And then they will selectively invest more capital. Go invest. Yeah. Yeah, exactly.

SPEAKER_85: And they do SPVs for these typically, or you do SPVs for these and then pass the hat, or you have the funds dedicated.

SPEAKER_00: So we have dedicated funds for the, for the directs, but the, the one thing that we do, that's kind of unique here to try to create a little bit of a network effect is when we, when a manager comes to us and says, Hey, I've got this company, it's doing a series a or series B now, and it's growing fast. And we give them $5 million to do that deal. We actually split the carry with the manager. And so we're helping that $20 million fund manager act like he's a hundred million dollar fund or be able to invest further into the life cycle of the company. And so a big part of that is, is, you know, how do you, how do you help the small fund managers punch above their weight and, and get more value out of those companies that they identified early on?

SPEAKER_110: So they vet the companies early on, they get you a foundation of bets, and then you have to then re underwrite them the best of those and it's the top 1%, top 10%.

SPEAKER_00: Yeah. It's like two per fund generally, you know, they come out and these small funds, you know, they're making 10 or 12 investments a year. So maybe there's 30 in total in that fund. And so there's probably two or three that are going to be the real, you know, significant

SPEAKER_165: kind of high trajectory company.

SPEAKER_164: So you have to stay in touch with those fund managers pretty tightly to not miss opportunities.

SPEAKER_00: We do. Speaking of AI, we kind of built out an analytics system to track those underlying portfolios. So we don't just wait for the manager to tell us how the company's doing. We also try to collect external signal and track the company. Um, and oftentimes we're approaching the manager and saying, Hey, looks like this company is doing really well. Should we talk about, you know, a direct, you know, larger investment into the upcoming round? And, and, and that's how we'll get that entry point.

SPEAKER_05: Jason, I'm going to put you on the spot. You were early in Robin hood, Uber thumbtack.

SPEAKER_20: What was your pro rata? If Michael was around, how much could you have deployed over before that? Yeah.

SPEAKER_110: Large amounts. Cause I was also friendly with each of those teams and they would have probably let me go super pro rata as well. So yeah, painful, it was a painful discussion. I mean, that's why after doing a $10 million fund, $11 million fund, I did a 44 and then I'll have this one, which would be 50 or so.

SPEAKER_49: Um, and you know, now I have the dry powder to do it. Um, and we can always fire up an SPV if we need to, to capture that with our LP pool. Um, if there was a huge opportunity.

SPEAKER_78: Yeah. I mean, we, we hear that all the time.

SPEAKER_20: Yeah. You've done some, you've done some empirical analysis on this. What, what's, what's the opportunity sell like?

SPEAKER_00: Uh, well, so if you, if you look. If you look at this universe of small emerging manager funds and you look at the last 15 years, I mean, the really interesting data is if you take the entirety of unicorn successful companies that have come out of the market over the last 15 years, 92% of those companies had a small fund like yours, Jason, early in, you know, the earliest days they were investors there. But then if you look at how much did they invest beyond the seed stage? Yes, it is less than almost none less than 5% of the time. Did they ever even participate beyond the seed stage, which is just, you know, I mean, with some of these companies, it's, it's hard to imagine.

SPEAKER_133: In our first fund, it was 4 point it's 4.9 X on paper right now, 5 X or something.

SPEAKER_29: And we did an analysis of the four unicorns that came out of it. If we had just hit one or two of them with one more bet, not two bets, not a crazy bet. It's like an extra half million or extra million. Um, they would have been 15, 20 X fund.

SPEAKER_49: So yeah, you, I think the way you get those outlier funds is a second there, but Brian, how do you look at second and third bets?

SPEAKER_106: It's hard to find these big winners. And when you, when you do, you, you pile in.

SPEAKER_08: Um, but I do think it's could be a trap to, um, especially for, for emerging managers who think like you just have to pile into any, any prorata round. Um, so I do think you want to look at it, you know, you, you, you do want to look at it as a net new deal and make sure the excitement level matches like what's actually happening at the company. You know, there's very few companies that are, that are special.

SPEAKER_76: And so the bar is really high for when we pile in, but we, you know, often we'll do prorata and, and, you know, more than that.

SPEAKER_20: Uh, speaking of prorata, we're going to go from the, from the theoretical to the specific, uh, let's look at everybody's last three announced investments.

SPEAKER_05: Brian, let's start with you.

SPEAKER_08: Sure. Um, so I'll share, um, a company solace that we invested in solace health. It's a marketplace connecting individuals with healthcare advocates to better their own or their loved ones, healthcare outcomes. So the, the idea is pretty simple navigating the medical hospital landscape as a patient is, is a show for everyone, especially if you know, you're, you're helping an aging parent or loved one who lives in another city. So these advocates are individuals who have a background in healthcare. Um, they know how to play the game and navigate the system of getting the right referrals to the correct type of doctor, um, the right treatment. Um, and they, they, they match you. So we led their seed that was recently announced. Um, really excited about what they're seeing demand wise from consumers, advocates and health systems. Um, the other one, a Gentio, um, it's an ad platform connecting brands with YouTubers to create sponsored content. The idea being to make it as easy as it is to, to buy and purchase ads on Facebook, Google, Twitter, Reddit. Um, but for creator led marketing, you know, I, I used to work in radio and the best performing ads in radio was when the radio host who had a following would actually do a host read ad and it was authentic. And it, it, it worked. So that's what these guys are trying to do. And there's been a bunch of these in the past, but this one got really, got us really excited because the founder built cameos business and understands how to work with an onboard talent. The CTO worked on Spotify's ad platform. Um, and then the third one I'll do a wild card, um, is personal investment into a VC fund, which is, uh, Jack Altman's new fund that he recently announced called Alt Capital. Uh, Jack was the founder CEO of Lattice, uh, unicorn in the, the SAS, um, HR SAS space. We love, you know, I love backing, uh, operator turn investors and really excited to, to invest in his fund one and excited to see where this goes.

SPEAKER_178: Uh, Michael, you're up. Okay, great.

SPEAKER_00: Yeah. Last three investments we made into funds. Uh, the first one is recursive ventures, uh, manager named it Marnovic. Um, awesome, small fund. His fund number one was all of $1 million. Uh, how did that fund? He wrote a 50 K check into a company that is now doing over a hundred million in ARR and just. Wow. Yeah. And so it, Mark's got a really unique background in that he's been an operator who took a company public, but he's also been in the venture world and was briefly with Morgenthaler ventures and just an incredibly smart and scrappy guy who, uh, continually finds great deals. The other funds that we've announced original capital, which is actually a generalist fund, but a team with a super interesting background and, uh, amazing track record and, and kind of a unique skill set. I'm glad it popped up even on the screen. Cause that's one of their unique investments. That's, uh, it's done really well. Um, but Sumit Ghajri and Ryan snow are the main partners there. Um, both of whom spent time at Carta. Um, Sumit, uh, chief strategy officer over there. He was also, uh, uh, chief strategy officer at a company called insta base. You guys might be familiar with, which speaking of AI tools and fast growing companies. And one of the reasons why I love these guys is the special kind of value add that they bring to their portfolio companies is they roll up their sleeves and basically run the financing process for their companies. Meaning when it's time to do a series a when it's time to do another round, they will step in like investment bankers and run that, uh, financing process, which I know for so many portfolio companies is just a massive time sucking challenge. And so, um, they're an awesome fund. And then lastly, silent ventures, which is one of our, uh, who, who notably doesn't have a whole lot on their website, but, um, this is a, a really unique manager. Jackson Moses, who has been, uh, aside from having a biblical name is, uh, has been investing in the aerospace and defense tech area for eight years. So as we like to say, he was, he was country before country was cool and has developed very under the radar. One of the most amazing defense tech portfolios out there. And, uh, in the process is established a really unique point of view on what's happening in that market. And so these were, these were the last, uh, last three that we've done all, all pretty different.

SPEAKER_182: Jake, how what do you have cooking? All right.

SPEAKER_29: Recall is, um, a toolbar that allows you to take the various web pages, podcasts, YouTube videos, et cetera, that you visit and then put them into your own language model. Uh, so that you can use it in the future and search it. So you can think of this. It reminded me of delicious back in the day or Yahoo bookmarks, a lot of cool web 2.0 products. Uh, Evernote ish. Uh, if you think about that. Uh, if you think about that. So we think this is, and it's a paid product and people love it already. There's a lot of nerds out there who like to organize stuff. So I could see this really helping people, uh, figure things out. Micro one is one of the fastest growing, uh, startups we've invested in recently. They use AI to vet developers around the world. So they can skim the cream of the top one or 2% and then package them up and handle, um, uh, you know, pairing them with companies that need projects done. And because they use AI, they can figure out really who who's really good and who's not. And, um, it's growing very quickly. Micro one. Um, and then, uh, Malengo came out of our last accelerator and got a massive amount of interest from investors and is very successful right now. What they do is they've taken the entire process of designing a hoodie, for example, and they will let you source, um, develop with, you know, AI, what you want your hoodie to look like. I want a hoodie with bulldogs on it, blah, blah, blah. It makes the hoodie. And then they will help you pick the fabrics, et cetera, cause they have all of that stuff abstracted in the data from the factories. They'll help you finance it. And then they'll actually pair you manufacture it and get it to your, uh, distribution center. So anybody who wants to create products and merch, uh, or even a whole business, they're going to be like your soup to nuts, uh, platform for doing that powered by AI.

SPEAKER_185: Those are my top three for this week. Excellent.

SPEAKER_04: Well, it's been another great episode of the liquidity podcast. AI has truly taken over everything, uh, for Brian Rosenblatt, Michael Downing, Jason Calacanis, this is your host, David Weisberg. Thanks for listening. Thanks for listening.