This Week in Startups - Reddit’s IPO, Consumer vs. Enterprise AI, and Sam Altman’s New Fund and more! | E1903

Starting point is 00:00:00 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, 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 C stage, which is just, you know, I mean, with some of these companies, It's hard to imagine the value. This week in Startups is brought to you by Northwest Registered Agent will form your company fast, give you the documents you need to open a business bank account, and more.

Starting point is 00:00:44 Visit Northwest Registeredagent.com slash twist to get a 60% discount on your next LLC. Dev Squad. Most dev agencies only offer developers. Why? Because product management is hard. Get an entire product team for the cost of one U.S. developer plus 10% off at DevS.com slash twist. And Miro helps take ideas from in your head to out there in the world with its ability to democratize collaboration and input. Sign up for free at Mero.com slash startups. Welcome back to this week's liquidity podcasts. With me today, I have Brian Rosenblatt of Kraft Ventures, a VC firm founded by Jason Earvesty, David,

Starting point is 00:01:28 which now has over 3 billion AUM. 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 Gallaghanes from the launch fund. I'm your moderator, David Weisperd, co-founder of 10X Capital. Today, we have a busy episode. We have first off Reddit officially announced it's going public,

Starting point is 00:01:52 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 has over 804 million in revenue. Brian, you actually worked out Reddit for three and a half years between 2015-19.

Starting point is 00:02:25 What was your experience working at Reddit? in, are you still bullish on the company? Yeah, I mean, I'm incredibly bullish. I was there in 2015, the time Alexis O'Hannion 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.

Starting point is 00:02:45 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 didn't. 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 up the room.

Starting point is 00:03:05 And some of those advertisers are now spending millions of dollars. So incredibly bullish for kind of what's ahead for them. Brian, how did Reddit cross that chasm from being a small $10 million advertising platform to the behemoth that is today? Yeah. I mean, there's a lot that went into it. You know, first and foremost, it was education. There are so many passionate users on,

Starting point is 00:03:26 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.

Starting point is 00:03:54 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. You're one of these VCs that came from the product side. There's many different flavors of VCs. What advantages and disadvantages are there to going from company side, from startup experience?

Starting point is 00:04:17 Yeah, I mean, I think there's a lot. I really came from the sales side. And, you know, 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. I think that crosses over really well into VC, which is also a big relationship business,

Starting point is 00:04:48 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 is a roller coaster and the frustrations. And I think when talking to a founder and their team being able to just understand what that actually means goes a long way versus someone who's only been on the investor side of things. And Jason, you've been around Reddit for quite a while.

Starting point is 00:05:20 you guys started kind of in the alternative media space, you know, back in the 2000s. What have you seen? And what are your views on Reddit's future? Well, it's incredible. I had Alexis O'Hanney in on this week and startups just a week or two ago talking about the IPO. It's just amazing that it survived this long, right? There is 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.

Starting point is 00:05:59 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, you know, TikTok, etc. But a dedicated forum and community was really hard to actually get one of those to scale. And the numbers are amazing. You know, like they're almost 100 million people use it every day.

Starting point is 00:06:25 You're 500 million people using it every month. It's not throwing off as much advertising revenue as 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 rotating. set of CEOs. Remember, they had Alan Powell for a minute. But of course, you got the co-founder to come in and take over the CEO slot, which

Starting point is 00:06:53 was great. You know, 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. 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? And so it's very tiny, but it's very influential.

Starting point is 00:07:16 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. Now, users don't know, like, how to use site 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.

Starting point is 00:07:53 Now, the investors, this company was sold once in a fire sale kind of situation to Condé Ness. Then it was spun out. Famously, I think Sam Maltman used his sharp elbows and great negotiating tactics that we've seen. to kind of free it and to get a new cap table gung. 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.

Starting point is 00:08:23 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. 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.

Starting point is 00:08:45 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 Cora, 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 IPOing. 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 it.

Starting point is 00:09:22 So congratulations to the team over there. Congratulations to the community. I think it's a real testament to the community more than anything. Starting a business used to be a pain. You needed a lawyer. There were in fees. It was a mess. Now, with Northwest's registered agent, it only takes 10 clicks and 10 minutes.

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Starting point is 00:10:17 That's Northwest Registeredagent.com slash twist today. Brian, Jason referenced that there was some difficulties with the product in terms of some of some of content. But also there's a very different audience, very peculiar. It isocratic versus other communities. what did you come across when you were selling into advertisers? 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, techy computer programmers that live on Reddit.

Starting point is 00:10:47 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 Momit for moms and Dadid for Dadit. And so there are these communities. that are extremely wholesome. And 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

Starting point is 00:11:18 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. 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've started a company and then took it public. What should the Reddit, how will this transform Reddit as a company being a public company?

Starting point is 00:11:52 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 super impressive for where they've been and just the trials and tribulations that 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 tough right now. I mean, I think there was an article that just came out in the last three days. It 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 new kind of platform and, you know, different than traditional media. But I think, I think there's, you know, an advertising or purely advertising-based business, it's just a

Starting point is 00:12:38 tough time 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 creates a new layer of opportunity there. But just the overall environment in the ad market is pretty tough at the moment. And so it'll be interesting to see how they weather that. Advertising is a scale business these days is, you know, what it comes down to. So you just start thinking about the scale.

Starting point is 00:13:10 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 of Netflix has massive scale and they edit advertising, right? Now you look at the how close are you to the shopping cart, Amazon advertising, Uber advertising, inside the app.

Starting point is 00:13:38 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.

Starting point is 00:14:02 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 home shopping network or something and buy stuff there.

Starting point is 00:14:27 They just like advertising. and 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, 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?

Starting point is 00:14:48 It has to be, like, they're discerning users, right? They're not, like, Yahoo users or AOL users clicking on every ad. Yeah, it's definitely a platform where it's, it's, it's less of like a copy and paste your Google ad onto Reddit and you're successful, which was a challenge, especially early on because we have to convince, whereas not only to spend money on the platform, but to spend the time and energy to like develop content and ads that work for Reddit.

Starting point is 00:15:15 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, to get to this point. This company would be worth 10 times as much if they just set to the market. We have an ad business.

Starting point is 00:15:34 It 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 a great way for you to get answers, and they just 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

Starting point is 00:15:59 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 will be better. But Steve's been very clear that that data is proprietary and you cannot use it. And Elon's been very clear about that with X. 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 Microsoft did in collaboration with them and what Google's doing.

Starting point is 00:16:29 That open crawl dataset probably has a lot of Reddit data in it that is illegally unlicensed in people's models. So it's just something to definitely consider how much revenue they can make from that too. 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? The data is so key. I think there's very few companies that have truly, truly unique data at scale. And Reddit is one of those.

Starting point is 00:17:05 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? 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 not super unique. but I don't know, one in ten, something like that, there is a good answer for why they have

Starting point is 00:17:25 unique access through some sort of partnership or some sort of know-how or they know this, you know, antiquated industry and have access to this. And those are absolutely, you know, interesting strategies to invest against. And Michael, you're really, you're really bullish on AI and you invest in a lot of AI-only funds. What are you looking for, for early-stage funds in terms of AI investments. Yeah, I mean, for us, we think that this is going to develop much the same way in the mid-2000s. 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.

Starting point is 00:18:03 And, you know, they're 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

Starting point is 00:18:48 unique technical background. 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? 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. I think OpenAI 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 many opportunities in that category. We've stayed away from just simple kind of application concepts just because I think as you guys have discussed before on the pod,

Starting point is 00:19:40 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 any of the other kind of larger companies. And so we've really focused on that infrastructure layer. Brian, how are you playing the game on the field? What is Kraft looking at in the AI space? I mean, we're looking at everything. But it is a crazy game to be playing right now. I was saying this earlier today.

Starting point is 00:20:08 It literally feels like you're driving. driving in the storm and it's, you can't really see. It's really hard. And so, like, what I personally focus on 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

Starting point is 00:20:35 to go or should be or should be built. I kind of want to go and find the best people, best teams, and just trust them to kind of navigate what's happening. But I think that's what makes this so difficult right now. And so early stage, it's all about the team. And then like later stage, we need to see proof. There has to be more than just kind of hype around it. Whether you've got an idea or an MVP, the next step is to transform it into a fully-fledged, reliable business that can support a growing customer base. And that demands more resources on the product side, of course.

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Starting point is 00:21:55 Visit devsquod.com slash twist and get 10% off your engagement. That's devsquod.com slash twist. 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 if you use your United app now or your Bonvoy app, it feels pretty great. But 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. You would buy

Starting point is 00:22:32 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 2. And you would buy it again. And it had three new features. It wasn't like versions. And there wasn't subscriptions.

Starting point is 00:22:45 And with a company likecom. 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.

Starting point is 00:23:12 And so a lot of what we said, 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 Chatchip, T, 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,

Starting point is 00:23:41 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 Robin Hood 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. It took maybe four or five generations to have something really good on mobile. I think we're in the first generation around out of these AI companies. Now, we're investing in a ton of them. I'd say more than half the companies we

Starting point is 00:24:16 invest in are specifically AI related, 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 Schmach will do well with Grock, 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. I think it's a really good point.

Starting point is 00:24:47 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 of 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 one million, to 20 million in like six months. And, you know, those kinds of numbers are just really unique and not something that we've

Starting point is 00:25:37 seen before. Typically, you've scaled out and hired a ton of salespeople and, you know, created a big 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 on using AI tools themselves internally. it's definitely the trend I'm seeing and so the question is if that is what's happening what a 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 dollars a year and if they're making 20 they're making four million of profits a year I mean the the case that 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.

Starting point is 00:26:36 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 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 much venture capital at that point if they're doing over 200 million. I wouldn't assume, but it'll be interesting to watch.

Starting point is 00:27:08 The contrarian view on that would be that all the resources will go towards the scarcity. 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 the cost going down for everything? How does that change how you invest? You know, I'm very lucky to be pre-seed and seed, and then I get to work with funds like crap. And, you know, we have 70 companies or super 70 that we've identified 70 downstream investment. and we focus on sending our companies to, there's about four of them that are like fantastic

Starting point is 00:27:59 four who are LPs in our fund and who we give very unique access to our companies and then the rest of 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 and pre-seed because, you know, you need your first five hundred. K, you need your first $3 million. And then why wouldn't you take, 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,

Starting point is 00:28:38 Brian, and I'm curious your position as a Series A, a primary investor, but I know you have a C 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-jurney 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, you know, a direct listing IPO kind of SpaceX secondary thing. I don't know. What are you seeing on the field run? I am definitely seeing that more and more at this kind of like growth stage series B and later. So definitely more funds leading tender offers. The companies just, they don't. need to raise more cash, but they want to get their employees some liquidity. And so that, that works. It's a bit, 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,

Starting point is 00:29:37 we have partaked in things like that outside of your just typical straight equity round. I think we're going to continue seeing it. I also think, like, you know, if rounds do get smaller, that's okay. The round size has got crazy the last two years. There's so much money, so many investors. Everyone's raising too much money. Founders have too much money and it becomes an issue. So I think it's just the best of the ecosystem. I think it's actually okay to raise less and to need less capital. It's not only okay. 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. you've experienced this as well. Like, it Fs with your head. Oh, yeah. Totally. I mean,

Starting point is 00:30:25 look at that deposit and then you see five percent, you see $10 million in interest a year, you know, 800,000 a month at interest coming in. And you're like, oh, wow, I can do crazy things with large piles of cash on natural things. Yes. You feel like you have to. The crazy, the crazy off-sites and offices and hiring. 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. This is back when we had offices. I always knew when a startup was in trouble when the,

Starting point is 00:31:06 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. We're going to have this room and that room. I was kind of like, hmm, this seems like an awful lot of cognitive load. And you know what? I see it 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 what 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

Starting point is 00:31:45 and back to my family. So prioritization and focus is so key. Yeah, absolutely. And we just went through so much of that as well, just too much money in the system and so much questionable judgment. I mean, it's, you know, 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 kind of ugliness of that. So it's definitely a challenge. Ryan, you've seen companies kind of get bloated. Have you seen any companies recover or is that kind of just, you know,

Starting point is 00:32:25 psychologically they're addicted to the money and they can no longer recover? I've totally seen recoveries. And 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 do it. I do think, though, there are some teams and some founders where the money kind of hid the issues, and they weren't able 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 where maybe we didn't invest, but they were, they were growing like crazy.

Starting point is 00:33:05 And then the market turns, and not only are they not growing, like 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. How do you have that conversation, Jason, 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. How do you have that conversation with companies around, you know, facing reality? Yeah, you know, people who select me as an investor and a partner, you know, they know that they're getting J-Cow, not to talk to myself in the third person,

Starting point is 00:33:44 but they know my brand is like candid, kid from Brooklyn, I'm going to give it to you straight. And so I tell them like, I've seen this movie before. And if you start blowing money this quickly and you take that $100 million and you divide it by 18 months,

Starting point is 00:33:58 we're going to be sitting here a 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 you. your mind. And it was the same conversation I had 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

Starting point is 00:34:20 give you the perfect example. Every founder of a company without product market fit wanted to add one to five million dollars 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 editing boards we were on together? why are we doing this before we have product mortgage fit? We got cash in the bank. What is the seventh million dollars do? We have six million in the bank. We're going to add one or two million in venture debt.

Starting point is 00:34:49 Why? Why are we doing this? Because somebody called us up and offered it to us. I saw a venture debt go really wrong during the great financial crisis, and I started to go wrong during the dot-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 whole life becomes trying to negotiate with a bank.

Starting point is 00:35:12 And yeah, you know, I think it took two years in some cases to convince people. And in many cases, we were not successful. 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.

Starting point is 00:35:35 You raised your Series B, and you're racing towards a cliff like Thelma and Louise. Is this wise? It's not wise. You know, take your time. You know, you're, what's the rush year? And, man, I don't know about you, Brian, but it's the ultimate frustration the last couple of years is watching people blow through cash piles. And they're like, what did I do?

Starting point is 00:35:56 I wish I just had, I wish I had the incremental $5 million I blew on nonsense. Yeah. And especially with venture debt when, when teams and founders confused. 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 we we are very we advise founders to be very cautious with with it and you know there are some businesses in times where it may make sense but for the most part um you know founders need to know their bank account their burn uh they need to manage it really really carefully and i think founders who

Starting point is 00:36:35 grew up in the Zerberra, like they didn't realize that until they kind of got smack in the base with reality. Yeah. If you have a CFO, like a legit CFO, and the CFO tells you, yeah, you know, we should have a little bit of venture debt. I've worked with these folks before. I negotiated it. This is standard.

Starting point is 00:36:50 That's non-standard. But when a, you know, 15-person company adds three or four million dollars in venture debt because they think, well, I'm spending $500 a month. That's an extra six, eight months a 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 punchups while I have some great news.

Starting point is 00:37:13 We worked with the team at Miro, that awesome whiteboarding software, to create an amazing pitch deck template for founders, which you can see if you're watching the video. This will help bring your pitch from zero to VC ready, and our Founder University participants love this template. They use it all the time. So head to Miro.com slash Miroverse and search for it. pitch deck to check it out. If your team is hybrid or fully remote, Mero is incredibly useful. It's like an old school in-person whiteboarding session, but distributed and asynchronous. Miro lets you brainstorm ideas and collaborate on projects from anywhere in the world. When you think Mero, think zero to one, but faster. And Mero is so much more than a simple

Starting point is 00:37:52 digital whiteboard. Your team can collaborate on planning, research, design, and feedback cycles. And remember, faster inputs equals faster outcomes and product velocity is how startups win. So here's your call to action. To access our new Miroverse template and thousands of others, sign up today for a free Mero account at Miro.com. slash startups. That's Miro.com slash startups, MIRO.com slash startups to sign up for free. Moving on, there's a new corporate venture capital fund in town.

Starting point is 00:38:20 We've been talking about AI. The fund is none other than Sam Altman's OpenAI Fund. Axis 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. Noteworthy is that Open AIS fund has outside LPs, which include none other than Microsoft. Brian, what do you think about Open AIs corporate fund?

Starting point is 00:38:46 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. They know the space probably better than anyone. You know, and, you know, unlike a lot of corporate BCs. 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

Starting point is 00:39:19 they're building and what they're not building. And they're going to use that knowledge to decide, but 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, you know, going to build this, you know, is, is Sam and is Open AI going to build this? But open AI 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. Michael, corporate VC's date back to the early 90s.

Starting point is 00:39:59 Intel Capital, famously is one of the most active investors in Silicon Valley. And then corporate VC really evolved with GV, originally called Google Ventures. What's the pros and cons of taking corporate VC for your startup? Yeah, I mean, from the LP position, but also 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 this 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,

Starting point is 00:40:40 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

Starting point is 00:41:27 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. A lot of VCs get afraid that having a strategic scares away other potential requires. What are the pros, though, of taking corporate VC money? I mean, does it provide validation early on? It absolutely can. And I think that's why a lot of entrepreneurs, a lot of founders,

Starting point is 00:41:57 you know, love to have that big name on their cap table. So I think there are certainly positives. 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. Yeah, if you want to have a large, sustainable business, you want the best venture partner in the world.

Starting point is 00:42:24 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 to give you your Series A, Series B? Would you rather have Sequoia do it? You'd rather have Sequoia. 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 Open AI.

Starting point is 00:42:52 When Open AI 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 Open AI Fund, which is Open AIs, not Sam's. I think Axios was kind of playing a little gotcha, that it was under Sam's name and not, you know, officially open AIs. You know, like journalists will do. It's fine.

Starting point is 00:43:17 You know, I think this, 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 Waltman and Open AI had invested in.

Starting point is 00:43:49 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're giving them equity, as we say in the industry, no conflict, no interest. This is 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?

Starting point is 00:44:14 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 ced them on this email. You know, and I have a Descript competitor in my portfolio. I don't, but I'm just saying, what if I did?

Starting point is 00:44:40 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? Why wouldn't Google do this with their Android 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.

Starting point is 00:45:10 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 title. We're going to invest in Uber, but not Lyft. We'd invest in DoorDash, but not Instacart, right? And they started picking winners and they owned 10% of them. AOL did that back in the day as well. And Nvidia is doing that now. So conflicts exist in our business.

Starting point is 00:45:33 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. So be careful. Brian, you mentioned you would be an LP and OpenAI if there's an opportunity. Would you counsel your companies to take money from OpenAI? Why or why not? Some of the reasons Michael mentioned, like, why corporate BCs could be bad.

Starting point is 00:45:55 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, 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 ceded 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

Starting point is 00:46:27 shareholder. They're just a part of the cap table. I'll tell you like if we're, you know, if you're investing in a 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 Open AI is going to invest in one of them. Like what I want open AI to invest in my company or the competitive company. I'd probably want them on my side. They are, you know, they're a special, a special company. And I think this is a unique, this is unique. This is different than if it was like Visa and MasterCard sort of thing. Open AI, 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

Starting point is 00:47:12 more from a defensive standpoint. You look at the ecosystem. You have Open AI, you have GROC, you have Anthropic, you have Google. What's your view on the overall ecosystem and who will be the winner in your eyes? Well, I mean, Open AI clearly looks like they have the lead. But I think, you know, the players you just mentioned, it seems to be like those are kind of going to be the players and there's wild cards. Obviously, what Elon's doing with XAI be a wild card, you know, I think with Anthropic, it's Amazon is a huge investor in that. So time will tell, but this kind of goes back to what I was saying before. It's really hard to predict the future.

Starting point is 00:47:55 But Open AI right now has a huge head start. They're releasing so much product so quickly and I have such a talented team that it'd be hard to bet against them. What do you think, Jason? I am long open source, especially because of the controls that these players are putting on some of these models. 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-InPod. And then I said, I asked Chat Chibi, give me a list. And Gemini was like, you know, elections are complex, presidential kinds, blah, blah, blah, you should use Google search.

Starting point is 00:48:35 And then, you know, Chachy-Ptie was like, here are the six cases where anyone, here's a link to a story about each one with citations. 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, I'm 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.

Starting point is 00:49:04 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, open source Maggie, I think it's called. So Apple just released it. It's terrible. But I opened my Apple photos just the other day.

Starting point is 00:49:26 And I had a picture of my Bulldogs. And there was that little AI stars. And I pressed it and it was like, Bulldog, click here. Click Bulldog. It takes me in 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.

Starting point is 00:49:47 Now, if you're going to build your next app, you're going to use that or are you going to use, you know, Dolly? I think you're going to go open source. I'm just a big proponent of open source in this case. And I also licensing of data is very much an active discussion between the lawsuit with 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 won't. Michael, what do you think about that?

Starting point is 00:50:12 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? Yeah, it's interesting way to get together a couple of weeks ago with some of the managers who were investing in AI. And we actually had Blake Samick from Open AI, who's the head of product operations, come and talk. And some of the kind of interesting things that came up that I wasn't aware of.

Starting point is 00:50:39 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. One thing that I wasn't aware of and I think is driving a lot of the investment activity for our managers is of the $1.7 billion in revenue or so that's happening in and around open an AI right now. The majority of that is consumer-driven, which was a little surprising to us. us. We just figured it was enterprise business, people starting to build tools, etc. And so I think

Starting point is 00:51:18 that's a filter that a lot of our managers are applying and thinking about, you know, is this first wave 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, in fact, their broader organization or business. But that data was pretty surprising to us, and we think it likely is going to be important in just how things develop in the market. What does that say about the space?

Starting point is 00:51:51 Is the opportunity in consumer or is it still an enterprise? Well, in this case, I think it's not so much it's consumer because all these are productivity tools or 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 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 for them and start using them first as a kind of life hack. And then they make their way into the enterprise.

Starting point is 00:52:31 Brian, your partner, David, obviously founded Yammer. sold it for a billion dollars to Microsoft, and another actor in this player. What percentage of your opportunities are you seeing in consumer versus enterprise when it comes to AI? I mean, we're really focused on enterprise B&B, so it's definitely more in that world. So it may be a little skewed because that's really what we're doing.

Starting point is 00:52:55 But, you know, I have been a bit surprised by how few interesting opportunities I've seen in consumer. I do think that's going to change. Elod Gill had a good article, I think it was him today, but he made the point like chat GPT. It's still fairly new 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 put their job and go all in on AI and start building things. So I think like the next year is going to be really interesting to see what types of companies get built. I think we're still super early there.

Starting point is 00:53:30 Jason, 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 in consumer or in Enterprise? Yes. I mean, it's, you know, you have second and third time founders really like to go enterprise because they probably did something in consumer

Starting point is 00:53:52 and they realized 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.

Starting point is 00:54:12 You'd have 20 different people going up for some narrow SaaS vertical. And, you know, but I love consumer. And we are a power law investor. We do 100 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.

Starting point is 00:54:40 And so we can deal with consumer. Whereas most VC is because they're placing 30 bets. I don't know if 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 $400 million, $600 million fund, I think you probably have 40 names in it most typically. Michael, you might know, actually, what the number of,

Starting point is 00:55:03 are now, but thinking like, you know, Mark Suster at Upfront or Fred Wilson at Flatiron. No, no, I'm sorry, Union Square now. And so, you know, what are the chances of hitting a one in a hundred, hitting a Twitter? You know, listen, Fred hit it. So a lot of people will just go for the enterprise ones because 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.

Starting point is 00:55:30 and consumer is the three-point shot. And you get paid a much bigger premium. If you look at my biggest hits, Uber, Robin Hood, Com, those are all consumer, thumbtack consumer. And then if you go, thanks for no, my portfolio. But then I have data stacks and, you know, grin and density, all unicorns. And those are in B2B. So, you know, you can play either game.

Starting point is 00:55:59 I let the founders tell us where the world is going. 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. Brian, Jason called you out on portfolio construction. So let's talk about craft's portfolio construction.

Starting point is 00:56:18 How do you look at that and how flexible is your portfolio construction? It's flexible. And it changes based on the market. There are times where it, It makes more sense to be more focused on series A or series B. And sometimes 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, personally, I'm probably more excited at the earliest stage, seed stage for growth when there's like a lot of a more proven metrics.

Starting point is 00:56:51 That's the series A and series B, we're going to do, we're going to do them, but they're harder. So it is. Because they're overpriced and without traction. very little traction, overpriced, lots of hype. Everyone has an AI fund. Everyone's investing in AI. It's, you know, it's the craziness again. And it's hard.

Starting point is 00:57:11 Like, it's really, it's really hard. Like, you know, I think the more we learn about AI every day, I think there's like more and more questions that come up. It's very different than a lot of other, you know, areas and sexes where we're getting smarter and smarter every day. I feel like we're literally, there's more questions every day. So it makes it really hard to pick that series A stage especially right now. But when you look at your portfolio construction, are you still kind of general as a

Starting point is 00:57:40 billion dollar fund? Are you still looking for one company to return the fund? Do those metrics change with fund size? Yeah, yeah, definitely. Because there are companies that sometimes I will see where I like the founder. I think they're going to have a good outcome, but it's not going to be big enough to return the fund. We don't invest in a company unless we think it has the potential to return the fund. So we will pass on things that could be good outcomes for the founder or for smaller funds,

Starting point is 00:58:11 but they're not deals that we will do. Our sweet spot, we will lead C deals series A, series B, and anything beyond that will go into the growth fund. Michael, 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? Well, we have a pretty specific approach and 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.

Starting point is 00:58:48 Many of them are 20 million, 30 million. 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 of managers as well, which is basically a direct investment fund for the follow-ons into the outliers that come out of those portfolios. 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 3.5x return on the emerging manager funds and what we kind of underwrite at a 4 to 6x return on the direct investments that go into the outliers from those portfolios. I'm curious. What is the name for that your type of fund, Michael? Because I know a fund of fund is and we know what a GPS is.

Starting point is 00:59:44 and we what do you call these funds specifically designed to be a yeah we kind of changed it up a little bit because the fund of fund part of it meaning the capital that goes into the small emerging manager funds we charge no fees off 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.

Starting point is 01:00:16 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 seeing them stack since the managers themselves charge fees. And so it is a little bit of a different approach. I'd like to say that we invented this, but actually there's

Starting point is 01:00:32 a handful of single family offices in Silicon Valley. We've 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. Yeah. Yeah, exactly.

Starting point is 01:00:53 And they do SPVs for these typically, or you do SPVs for these and then pass the hat, or you have the funds dedicated. So we have dedicated funds for the directs, but 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 $100 million fund or be able to invest further into the life cycle of the company. And so a big part of that

Starting point is 01:01:31 is, you know, how do you help the small fund managers punch above their weight and get more value out of those companies that they identified early on. 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%. Yeah. It's like two per fund generally.

Starting point is 01:01:54 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 kind of high trajectory company. So you have to stay in touch with those fund managers pretty tightly to not miss opportunities. We do. I mean, 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.

Starting point is 01:02:27 And oftentimes we're approaching the manager and saying, hey, looks like this company's doing really well. Should we talk about, you know, a direct, you know, larger investment into the upcoming round. And that's how we'll get that entry point. Jason, I'm going to put you on the spot. You were early in Robin Hood, Uber, Thumbtack. What was your pro rata if Michael was around? How much could you have deployed over before that? Large amounts, because 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.

Starting point is 01:03:05 And, you know, now I have the dry powder to do it. And we could always fire up an SPV if we need to, to capture that with our LP pool if there was a huge opportunity. Yeah, I mean, we hear that all the time. Yeah, you've done some, you've done some paracol analysis on this. What's the opportunity so like? Well, so 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,

Starting point is 01:03:45 early in 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 C stage, which is just, you know, I mean, with some of these companies, It's hard to imagine. In our first fund, it was 4.9x on paper right now, 5X or something.

Starting point is 01:04:12 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 bats, not a crazy bet, it's like an extra half million or extra million. They would have been 1520x fund. So, yeah, I think the way you get those outlier funds is the second third. But Brian, how do you look at second and third bets? It's hard to find these big winners. And when you do, you pile in.

Starting point is 01:04:34 But I do think it could be a trap too, especially for emerging managers. You think like you just have to pile into any prorata round. So I do think you want to look at it, you know, 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. And so the bar is really high for when we pile in. But we, you know, often will do prorata and, you know, more than that. Speaking of pro rata, we're going to go from the from the theoretical to the

Starting point is 01:05:08 specific. Let's look at everybody's last three announced investments. Brian, let's start with you. Sure. So I'll share a company Solis that we invested in. Solis, Health, it's a marketplace connecting individuals with health care advocates to better their own or their loved ones' health care outcomes. So the idea is pretty simple. Navigating the medical hospital landscape as a patient is a show for everyone, especially if you're helping an aging parent or loved one who lives in another city. So these advocates are individuals who have a background in health care. They know how to play the game and navigate the system of getting the right referrals to the correct type of doctor, the right treatment, and they match you. So we led their seed that was recently announced,

Starting point is 01:05:57 really excited about what they're seeing demand-wise from consumers, advocates, and health systems. The other one, a GENTO, 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 buy and purchase ads on Facebook, Google, Twitter, Reddit, but for creator-led marketing. You know, 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 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. This CTO worked on Spotify's ad platform.

Starting point is 01:06:49 And then the third one, I'll do a wild card, is personal investment into a VC fund, which is Jack Alton's new fund that he recently announced called Alt Capital. Jack was the founder, CEO of Gladys, Unicorn in the SaaS, HR SaaS space. I love backing operator-turn investors and really excited to invest in his fund one and excited to see where this goes. Michael, you're up. Okay, great. Yeah, last three investments we made into funds. The first one is recursive ventures manager named Edmarnovic.

Starting point is 01:07:30 Awesome, small fund. His fund number one was all of $1 million. Out of that fund, he wrote a 50K check into a company that is now doing over $100 million in ARR and just crushing it. Yeah. And so, I'm 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 Morgenthallar ventures and just an incredibly smart and scrappy guy who 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 amazing track record and kind of a unique skill set. I'm glad it popped up Avin on the screen because that's one of their unique investments that's done really well.

Starting point is 01:08:21 But Sumit, Gajri, and Ryan Snow are the main partners there, both of whom spent time at Carter, Sumit, Chief Strategy Officer over there. He was also a chief strategy officer at a company called Instabase. 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 financing process, which I know for so many portfolio companies, is just a massive time-sucking challenge. And so they're an awesome fun. And then lastly,

Starting point is 01:09:14 Silent Ventures, which is one of our, who notably doesn't have a whole lot on their website, but this is a really unique manager, Jackson, Moses, who has been, aside from having a biblical name, has been investing in the aerospace and defense tech area for eight years. So as we like to say, 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 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 three that we've done, all pretty different.

Starting point is 01:09:58 Jay Cowell, what do you have cooking? All right. Recall is a toolbar that allows you to take the various web pages, podcasts, YouTube videos, etc., that you visit and then put them into your own language model 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, Evernote-ish, if you think about that. So we think this is, and it's a paid product, and people love it already.

Starting point is 01:10:27 there's a lot of nerds out there who like to organize stuff so I can see this really helping people figure things out. Micro One is one of the fastest growing startups we've invested in recently. They use AI to vet developers around the world so they can skim the cream of the top 1 or 2% and then package them up and handle, you know, pairing them with companies that need projects done. And because they use AI, they can figure out really who's really good and who's not. And it's growing very quickly, micro one. And then Melango came out of our last accelerator and got a massive amount of interest from investors and is very successful right now.

Starting point is 01:11:10 What they do is they've taken the entire process of designing a hoodie, for example, and they will let you source, develop with, you know, AI, what you want your hoodie to look like. I want a hoodie with bulldogs on and blah, blah, blah, blah. It makes the hoodie. And then they will help you pick the fabric. etc. because 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,

Starting point is 01:11:35 manufacture it, and get it to your distribution center. So anybody who wants to create products and merch or even a whole business, they're going to be like your soup to nuts platform for doing that powered by AI. Those are my

Starting point is 01:11:51 top three for this week. Excellent. Well, it's been another great episode of the liquidity podcast, AI, has truly taken over everything. For Brian Rosenblatt, Michael Downing, Jason Kalakana, to see our host, David Weisberg. Thanks for listening.

This Week in Startups - Reddit’s IPO, Consumer vs. Enterprise AI, and Sam Altman’s New Fund and more! | E1903

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