15 Hot Takes on VC and AI from the 2026 Allocate Beyond Summit

23:48And like to get the attention of like the top 10, 15 firms, like you need to be truly like obviously legible and special very early, which like that was not the case a few years ago. So then how does that change maybe the strategy you think that makes the most sense at kind of preceding seed stages? Totally. I mean, we're still investing in like, you know, people with just an idea, like free consensus. I would like put it like that way. And so like, I think one thing we've had a meaningful shift about and I'm like even thinking about like a specific portfolio company right now where like previously like building heads down and stealth and like all of that was like kind of cool or like fine.

24:22But I think now being legible to capital, if you're not like an obviously like known team is like important to like being on Twitter, like talking about like your research or like the breaks you're having. All this is like more important than it's ever been because like the classic like, oh, like seed investors is like introduced to the Series A funds and they're all excited to do Series A investment is like not necessarily true unless it's like a clearly known category. So like for our companies that are not obviously like, you know, X open AI or whatever, or like it's a category that people are like already excited about.

24:53If they're pre consensus, we have to do a better job of like making them legible to the capital markets. And some of that is like storytelling. It's, you know, for like making individual introductions those investors long before the series A. So they get to know the team over six to 12 months and they're like, oh, this person's really special. And I think that's like just a meaningful change in how we think about things. Yeah. We have the one shared investment that we can hype on the pod is Hanover Park, where I don't know, I think maybe a year or two ago, it might've fallen in that case of just like, what is this product even?

25:26We're not really sure, but the founder needs to prove it, get some customers, et cetera. He's done a really good job of being public, helping people understand the product, the company, the opportunity, also a really good founder. Yeah. And then also, I think the interesting thing is there's just kind of this whole like using AI to replace the services business. Yes. He's falling right into, again, the category that later stage investors are excited about, right? Services and software and like playing into those trends is like probably more important than it's ever been. And like, I think like there's obviously interesting implications.

25:58Like I think about like one thing is like, you know, right now, I think if you're a series A and B investor, Sure. There's like actually a lot of great companies out there that like the top firms are like not necessarily looking at or like just waiting. And like you could be that Series A investor or Series B investor before they go and do the$100 million or$200 million check of the C or the D. And like, I think there's like an opportunity for like contrarian, like Series B. Yeah, which is like crazy because like, you know, you think the Series A is like the most competitive space and it's like it is competitive for like the hot, obvious companies.

26:28Like if you're trying to get into like the company that everyone in the valley is chasing after that week like yeah as a new series a fund you're not going to do well but like if you're looking like a little bit beyond the like obvious known companies that have like three people came out from open ai last week like there actually is like a lot of opportunity yeah i mean i think i feel like the kind of canonical in this is like the podcast with the one big multi-stage firm that's just like we won't even take a call unless you do like one to 100 in the first year or whatever like we've all seen that that clip and you're just kind of like i don't know like that's a little bit extreme, but like some, that's the view that a lot of people have.

27:03And you went one to 50. That's still absolutely insane. You go to 50 million in revenue after a year? Yeah. And it's like, it's just, again, such a notable difference than before. Like five years ago, zero to one, you could get some venture fund in the Valley would give you a series eight. Now it's like, they're like, oh, I don't know about the space. Is the time really big? And everyone sees the growth rates of these other companies. They're like, okay, like it's not as good as Cognition. So like, I'm not going to invest. And Cognition is obviously a great company, but like Like there are going to be other great venture-backed companies that come out of this AI tailwind.

27:33And I think like there's real opportunity for sure in that stage of the market. Like these things are cyclical. Like I think eventually the multi-stage is some like some brave junior partner at like one of these firms will start doing some of these deals and like will make a name for themselves. And like, you know, just like it's always going to happen. Yeah. I mean, like some of the anthropic rounds were that. Totally. Like, yeah, totally. Like Yazzie from Spark, like she was doing like really non-consensus growth stage investments and like clearly cemented herself as like one of the five best of the last decade.

28:04And it's like because she was willing to do stuff that other people were like, oh, I can't take this kind of risk. I think someone's definitely going to be doing that for these AI companies that are doing really well, but are not in an obviously massive category like ITSM or ERP, or a team that's in a niche that's going to become obviously really big in a couple of years, but people aren't looking at it yet. Yeah, I think the interesting thing too as a seed fund is there's like less competition. So you can get way more ownership in the company. You can build way better relationship with the founder because other people aren't trying to wine and dine them all the time.

28:38And other people, you know, like selfishly, we're able to help them a little bit because no one else wants to help them. But again, like this is all, all these things we've talked about, like different pieces of it are good for different participants in the ecosystem. Totally. And yeah, it's like these things will always change. Like right now, I think there's a lot of alpha in A and B. And like, there's probably less than just like consensus seeds at like 30 to 50. But like, you know, there's just like stuff you can do to always, you kind of like want to shift with the market, I think, if you can.

29:07Yeah. Well, it's been a lot of fun. Thanks for coming on the show. Thanks. Matt Cohen of Ripple Ventures. Welcome to the show. Excited to be here, Turner. So you had a really interesting thing you brought up earlier was you think the second time founder premium is dead. Yeah. That's a little bit of a spicy. Yeah. So why do you think that? So I obviously think that founders that have gone through like Death Valley before and have experienced how hard it is to build a startup will never be able to take that away from them. I think that's really important. But I think the premium that we've given historically to founders that have gone through traditional B2B enterprise sales motions and those playbooks definitely do not have the same skill sets that can be applicable to an AI native founder who is a first time founder, let's say spinning out of Anthropic or Cursor or OpenAI.

29:52Because of the velocity and speed at which products are being released now, products need to be built and kept up with, is definitely something people should pay more attention to. You know, we have companies on both sides, second, third, fourth time founders who are not able to move as fast as first time founders. And that premium we are now showing first time founders is warranted because of the ways that they can deliver on product roadmaps, customer, you know, implementations faster and things like that. Because it's definitely one of those like, oh, you know, that, you know, I got this buddy who sold his last company.

30:24He's raising 5 million bucks. Like we're just going to kind of give him some money because he made us money last time. It's the whole second founder premium where it's like, we don't care what he does. We'll give him money. I'm not saying that experience is invalidated. I'm just saying the curve is inverted. And I think that those founders that are a little bit more in the weeds on how products are being built right now to keep up with that speed velocity have an advantage on that side. But they still need to find operational missionaries that can come and join them and build the company when they get to 5, 10, 15, 20 million of ARR.

30:58Because yeah, first time founder, that's a lot of pressure to go from five to 50. So you still need to hire a COO, a CRO, you know, CFO, things like that, which we do for our companies. But the speed to go from zero to 10 from first time founders is like nothing we've ever seen. I mean, think about how many companies are reaching 50 million of ARR with first time founders. It's the highest we've ever seen. Is it? Do you have any data around like what the percentage is? Yeah. So I don't have the data specifically, but anecdotally what we saw was that the first time founders getting to that speed of revenue velocity versus multi-time founders being able to do it at the same clip is the highest number of first time founders getting to that number.

31:36I mean, just go look at like the cursors of the world, right? You have those really young first time founders doing it, you know, and you have, you know, sometimes there are founders who had side projects before that just didn't work out, but they were never really venture funded founders. They were kind of like solo founders. And this time around, it feels different. Yeah, I guess anthropic technically, they were first time founders. to spin out some open AI. They're breaking the record. All seven of them still there. Crazy. Well, this is a lot of fun. Thanks for coming on the show. When you can build anything, Amplitude lets you know how to build the right thing.

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32:40Clark Chang, Miramak, welcome to the show. Thank you for having me. So we were talking earlier, you think that intelligence labor is gonna be one of the areas that gets completely crushed by AI. What do you mean by that? No, I completely agree. I think a lot of people don't understand what the capabilities of what AI are. I think they're still using it as a chatbot and asking questions and stuff. I know people can still vibe code and stuff, which is fairly easy on any of these apps and stuff. But when you start creating agentic agents and workflows, it is amazing what it can do. And it changes your whole mindset.

33:12But I think unless you're tinkering with it and playing with it, do you understand the power of AI? And I got to say, we invest in a lot of AI technologies. We invest in a lot of venture funds that do AI. even they don't understand AI. They get it from listening to podcasts like this. They get it from reading news and articles and stuff. But in reality, they themselves don't understand what the capabilities of this technology is. And it is going to change a lot in the next years. I wish I was 20 years younger to watch it or I wish I was retired. But right now it's going to be - You're like in the middle.

33:45I'm right in the middle. But I think, look, you have two chances in your career. Maybe one to make money in your life. and it's either a big risk-off scenario like a GFC or it's the next tech revolution. Like we had.com, we had mobile, we had cloud. And those are all big things that change. And it changes a little bit slower. This technology is bigger than the last three combined. It couldn't do it without computing, without mobile, without cloud. So now that we have them all, this technology has the infrastructure to build. But the innovation is happening so fast. If you're not on the edge playing with it every week, you miss a lot of things that happen.

34:21and stuff. But it's going to be amazing. It's going to hurt, I think, labor, intelligence labor in the near term. I don't think you'll see necessarily in the numbers because I think it's going to happen at that college level hiring phase. So if you imagine a company like a pyramid and the bottom layer, all the college graduates, say you have a hundred college graduates at a company, in the future, you only need 10. And those 10 will manage 10 sub agents, which will do regressions, downloading data, all the actual work work. But the tenant management have to understand agents, how they work, how to minimize hallucinations, how to make sure that security is there.

34:57And those 10 will basically move up to the next level, the senior people, which have relationships, understand the business and stuff. But I think it's going to get crushed. If you look at the labor numbers lately, I think one just came out recently and they were saying that government labor is still growing, nurses are still growing, hospitality is still growing. But those are actually areas that AI cannot disrupt as much. But when you start looking at finance and stuff, technology and stuff, I think that stuff will be impacted first. You're starting to see technology layoffs now. But unless you're playing with this, do you really realize what the future could look like?

35:30There will be new jobs being created. Everyone says there's new jobs being created. There's so many new jobs, I can't even explain them to you, which is always a great thing to say because you can't prove them wrong. But I think net-net, in terms of total jobs available, I think it will be less. and we're going to have to figure that out as a society, what that next is. So maybe you've talked a little bit about you need to play with the technology. What are some of your favorite things to do as an investor taking advantage of AI? What do you kind of do on a daily basis? I think the most powerful thing to do is to play with a platform like OpenClaw.

36:02Now, there's a bunch of Claws out there. There's NemoClaw, OpenClaw. There's HermesClaw. There's all these things. Open is like a broad platform that you can use any LLM to be the brain of it. So I think it's good to start with something like that that's broad. So no matter what happens, what changes and stuff, you have a platform that is open source that you can actually play with. If you start tinkering and playing with it, you start to kind of see the capabilities of it. I actually find OpenClaw more secure than it used to be because there's been an update literally every day, if not twice a day.

36:32And I find CloudCode to be more powerful in the sense that it can do anything and it's not limited. So I can use Cloud Code or Codex to code into OpenClaught and just build stuff. But it will actually build it all the way through with pipes and everything. It will actually tell it to email out to everybody if I want. OpenClaught won't even let me do that. I have to give it constant approvals and stuff. So nowadays, Cloud Code is actually more powerful and more dangerous if you don't do this right. The problem that people have with this stuff is they download it and they don't set up the foundation, which is your security, your hallucinations, and your memory.

37:06If you don't set up that foundation, it can be dangerous because it does have power. But if you set those things up well, and for us, we have a nightly audit on those things. So we ask it to audit itself based on the latest updates. Is there anything to optimize or improve? And then we just say approve it, and it will actually optimize all of your hallucinations to zero as much as it can. It'll do it for your security and everything else. It's funny. We had a conversation yesterday, and people were talking about those two issues, security. and privacy and hallucinations. And I told people, just tell your open claw, your agent or your LLM to not hallucinate.

37:46And everyone thought it was a joke that they laughed. But it works. But it really does work though because these are smart agents. You can literally talk to it in natural language and it will try to solve the problem for you. But I think at the most basic level, you really have to understand how LLMs work. They're a stochastic model that are predicting a token. And as a result, if it doesn't know the answer, it can't say, I don't know. It doesn't have permission to say, I don't know. So if it doesn't know the answer, it will actually give you the next likeliest answer, which is probably a hallucination.

38:16So just give it permission to say, I don't know the answer. There's something called temperature, where if you're doing math or tax or finance, you only have to tell it once. You tell it once, it goes into memory and it stores it. It will always do it from that point forward. But if you're doing math, just turn your temperature to zero. If you're writing me a research report, make it 0.3 or something. Give it a little creativity. And then you can also have the checks and balances in place where you can have Opus or you can have Codex be your brain for a platform like this. But then likewise, you can have the remaining models check the work of that.

38:49So if there was ever a hallucination and they don't hallucinate the same way, you have the other models to check it. And I think a lot of people are putting that stuff into place. If you talk to other tech guys who develop and code, they'll always use multiple models to actually build the same thing. And at the end, they just have to integrate all of it into one. Take the best ideas from Codex, from Quad, from whatever else, and just integrate it into one, and you'll have a much better system. But you really have to play with it. You have to have a fascination for this. You have to have this. It's a funny thing.

39:20It's like if you're a perfectionist, this is the perfect thing because it will never be perfect. It can always go on forever. but it's a competitive game to get it as perfect as possible. And it's kind of fun. It's a little bit addictive, but usually I'm doing this late into the night because during the day we still have our day jobs and meeting people. The thing that will not be disrupted is relationships and information. So as a result, like events such as this, Allocated, it's fantastic. You get to talk to people. You can have relationships. You can build this intimacy during the day. And then in the evening, you may have to do your emails and stuff.

39:53And at night is when you can actually build the stuff, the coding and stuff that that you can't replicate you know with with ai during in the day yeah i've been kind of getting addicted to just like slowly i feel like every day i just like slowly maybe like automate a little bit more of a thing like anytime i got a good two hours like sit down and really bang away at it i like kind of crack a new thing that i kind of slowly doing more and more things with it but like to your point it's like i got to do i can't just sit around and figure this out all day. I mean, if you set up your Discord channels, which has everything into different channels and threads, it's easier to manage because every time you have an idea, you can literally put it into that channel so that your AI does not get confused by what are you referring to and stuff.

40:35But there's things that excite me about this are something like Mirrorfish, which is using swarm technology to run a simulation of like 500 ,000 agents. You couldn't do this like a few years ago. You couldn't do this without AI. And now you can actually do this. You can I could create 500 ,000 agents and run a simulation on a Reddit or Twitter to figure out what could happen if Taiwan gets invaded or if we start a war with someone else or something like that. You can actually run this. This is tech that has never been available before that you could do now. You just have to program it. A lot of it's on GitHub if you just wanted to do it.

41:08There's something like Paperclip, which you just hire a CEO, give it a goal, and it will actually build out your entire company, hire all the agents, the CIO, the analysts, the portfolio manager, everything, like over a week. And it will actually build your entire firm for you. So that's at the basic level. If you get deep into it, not only do you give it a goal, but you give it a goal, you give it costs, and you can actually have a target, a specific number, like give me the highest number you can have performance relative to token costs, relative to a hallucination, relative to anything. And that's the power of this AI step.

41:40You really have to play with it every day to really understand it. And I'd tell you, even the AI venture investors aren't into it enough to really truly understand. There's a few that I've talked to that we invest with that are phenomenal. Some of them are here, like even Theria Tomas. He's fantastic and he's playing with it. He's on the edge. And it's because of people like him and other friends of mine that we tinker with the stuff that we truly understand. And you can see the future if you do this. Because we actually just came on the podcast. If you go to the back catalog, it'll be the first one right there.

42:14Okay, great. So, well, thanks for coming on the show. It's been a lot of fun. Sunil Nagaraj, Ubiquity Ventures. Thanks for coming on the show. Of course. Happy to be here. As you were saying earlier, we're about 12 months away from a lot of certain category of investors losing their shirts. Something interesting is happening right now, Turner. I think AI has shown up on the scene. It's been around for five or six years, but the last six months has brought it into focus in a way that has convinced a lot of SaaS investors that a lot of SaaS companies may not be as durable. So there's been a flight over this other category.

42:44And at the moment, that other category is physical AI. So as someone who's been looking at physical AI, what I call software beyond the screen for the last 10 years, very actively, it's been bittersweet to see so many folks rush in. I enjoy having more partners, more capital upstream, downstream. What I don't enjoy are non-technical investors rushing into a pretty technical space. And this is where I believe that in the next 12 months, we're going to see a major reckoning that a lot of folks who dumped a lot of money in chasing a few proxy signals about what might make for a good company, they are very likely to lose their shirt.

43:14There are companies now in the physical AI sector where the tail is wagging the dog. Something that really bothers me is if you think you need$400 million to launch your physical AI company, then your valuation has to be$2 billion. That's literally putting the cart before the horse. Yeah, you need to sell 20%. Right, exactly. And that's a little funny. What's worse than that, though, is when the technical premise of the company is just fundamentally not sound. And so you're seeing a lot of folks rush into a few hot sub areas of physical AI and they'll use signals like they were the third author on the paper or they were ex this company, you know, SpaceX is a common one, for example.

43:48Yeah, this is a pretty common, pretty common thesis that people have. Yeah. Yeah. And I will often talk to these investors as a technical nerd. I call Ubiquiti Ventures a nerdy and early firm. And I'll ask a couple kind of high level but nerdy questions and there won't be any answers. I don't know, Sunil, they're ex SpaceX. I think they got to figure it out. Don't figure it out. Yeah, that's a common response. Or they have 300 million, they'll figure it out. It turns out there's a whole long list, and I won't name them all now, but dozens of companies where they've raised all this money and it goes to zero.

44:14And so I think PhysicallyEye demands a certain level of thoughtfulness, technical depth. And at the moment, capital rushing in is not reflecting that. So what do you do? How's Ubiquiti kind of responded to what's going on? It's a good question. We're sticking to our knitting. You know, Ubiquiti write one, two,$3 million checks often in brand new companies, but we're not rushing in to the$100 million rounds at 500 pre when it's a new world model or new foundation model. It's rarely, I actually hate this word moonshots, right? So I'm not doing anything that's a moonshot, which either sounds unambitious or it sounds like we have just a tremendous amount of discipline.

44:54So I actually think about Ubiquiti as a disciplined deep tech firm looking for that sliver of deep tech that can be capex light that can have quick time to revenue. Usually my one to three million dollar round will turn on a company's product in customer's hands. That flies in the face of most deep tech and most physical AI. So I think there's a way to look at this where you're chasing opportunity, not chasing headlines or chasing large financing rounds. So why do you need the hundred million dollars then? Like what's the rationale on raising a hundred million to get this thing in market when you could maybe do it for less?

45:22Yeah, that's a very good question. I mean, you end up with some perverse incentives. I mean, if you raise a hundred, then your company happens to be worth 400 million just by the 20 % rule, which, you know, benefits, technically benefits everyone on the table because they all feel like they're worth a lot more on paper. Now the issue is, and we saw this with SoftBank and WAG and a few other things like that, giving companies too much money inevitably causes a failure. And I think you might say with a hundred million, we can just spend as if we have 5 million, impossible. So it just doesn't play out that way.

45:53And at the moment, you have folks, maybe SpaceX going public, if it happens at$2 trillion. It's created this wake of uninformed enthusiasm. Like, oh, my God, SpaceX could do that. I bet these other companies could, too. And some thoughtful entrepreneurs are raising capital. Some less thoughtful entrepreneurs are taking advantage of the situation to pull in as much capital as possible, short-sightedly, and folks are piling into those rounds. And so in the last month, there have been five or seven rounds of$500 million,$400 million, $800 million for pre-launch companies. You know, they haven't in the space sector, for example, haven't made it to space once.

46:25And their company is predicated on space. And to me, that seems really, really crazy. Well, it's been a lot of fun. Thanks for coming on the show. Of course. Thanks, Turner. I appreciate it. Sung Joon Cho, Fortitude Ventures. Welcome to the show. Thanks for having me. So you were telling me earlier, you feel like there's going to be a reckoning coming for kind of the general purpose robotics investment space. What's kind of been going on and what do you think is going to happen? But to preface everything, I've been investing in robotics or going deep in this space for 10 years. The bottleneck or the hurdle for a long time was there wasn't enough capital.

47:02So I'm rooting for robotics companies. I'm super excited that there's enough capital for a lot of these companies to get over the hump. I'm just a little bit concerned that there's too much capital going into kind of the proverbial chat GPT moment for robots. And I think that's 15 years away. You think it's 15 years away. Okay. What has happened to make people think that we're getting this chat GPT for robotics moment? Is it just chat GPT and it's like same thing going to happen? I think so. I think there are a lot of investors who missed OpenAI or missed Anthropic at the seed round or traditional Series A.

47:47I agree that the upside of a general purpose humanoid robot is absolutely huge. And so I think the technology has come really far for sure. But if you look at companies like Waymo or just the self-driving space in general, Waymo first demonstrated self-driving with supervised learning in 2012, I think. Yes, this is like 13 years before the broad adoption. Exactly, right. And then it was on the road in 2015 in Arizona. And it took 10 years. All right. And self-driving cars is a much easier technological problem than a general purpose robot. Right. So why is the general purpose robot so hard? Because I see these people are posting videos that the robots are doing things.

48:36Is it not solved yet? I definitely don't think it's solved. So I think like Tesla will have humanoid robots doing productive things, but it's in a very controlled environment within their factories. right and maybe same with figure um and i'm not you know i'm not deep i don't know exactly what they're doing and how far they are so i'm not trying to say i'm not trying at all trying to discount um what they've built so far and what they will build um in the you know near future even the you know midterm future i think just having you know if you think about it like what would you want a robot to do what would you pay thirty thousand dollars for a robot to do inside your home right like if it's just does your dishes and bowls your laundry probably not worth it right you kind of need it to do it depends how much money you have yeah oh that's fair that's fair 30 30k for some people is not as much as it is for other people that's fair that's fair and is this 30k and kind of a you know upside scenario where we get to scale and you can finance it too sure so you can get a loan for your humanoid robot yeah yeah but then if you look on the industrial side um i don't know if you've been to like uh you know you're from michigan right so like automotive factory or fulfillment center like the industrial automation moves super fast in In factories, it needs to be really accurate.

49:51If you think about it, if a robot is 99 % accurate, there's a thousand cycles, then there's enough errors in a day to have to stop the factory, right? And that's unacceptable. And so I just think that if you take the industrial side, the need for accuracy and the need for speed just makes kind of special purpose robots or just traditional industrial automation more effective and efficient. In homes, I just think that it's hard to imagine that robots will get to the level of efficacy to justify the ROI. And then if you think about ChatGPT, when we first started using it in late 2022 it was like mind-blowing but there was like hallucinations it also kind of sucked yeah like mind-blowing but yeah yeah it was like it was cool but it's also like 70 effective exactly but but we used it and so it got better it was just some text exactly versus like building something yeah but would you you know throw a robot in your home to like kind of try it and get 70 you know accuracy unloading a dishwasher 70 of them make it put away in the shelf and 30 % are broken on the floor.

51:08Broken, exactly. Yeah. Or it takes, and it takes much longer to do. So you think that the moment of these actually truly working in like true commercial fashion is probably like a little bit further away? I think so. I think so. I think the technology will get there. Definitely less than 15 years. But it's just like a timeline. We're probably shortening the timelines more than we should be. I think so, right? You and I, we need to exit our positions in hopefully 10 years. Let's call it 15 years. But if the upside starts to happen, then I think there's going to be pressures. And there's a lot of investors who have shorter timeframes than we do.

51:49Yep. Makes sense. Well, it's been a lot of fun. Thanks for coming on the show. Yeah. No, I appreciate it. Josh Christensen, Mercado Partners. Welcome to the show. Thank you. Thanks for having me. You're actually based in Utah. I am. We're in Utah right now. Am I the only one from Utah? Honestly, I don't know. I'll have to go back and look. Maybe. But anyways, you were telling me that you think that there's going to be a little bit of a reckoning for some of these AI application kind of like paper marks. Can you just kind of explain what you're thinking and what you think is going to happen? Yeah.

52:17And I'm not talking necessarily about like the big model providers. They may have their own reckoning at some point. I think what happened is in 22, 23, 24, there was this broad consensus that, hey, we should avoid investing in GPT wrappers. And everyone kind of defined that in their own way. But a lot of the investing that I've seen over the last probably just 24 months has been in companies that have amazing traction. They go from a million to 10 million very quickly. The problem is there's 15 or 20 clones that look just like them that also went from 1 million to 10 million that also got funded.

52:52And I think what happened is as we were sorting through what is a moat and what's not a moat, there's very obvious moats out there, you know, where there's a data moat, there's a regulatory moat, there's something structural that the company does that nobody else does. But when there's 15 clones, that means the moat's probably weaker. And I think that many investors have fallen for, oh, there's a unique ontology that we have, or there's a fine tune that we've done to the model. And the reckoning is not because those companies are necessarily bad. It's just a very competitive space. And the second is that much of the revenue, if you rewind it 20 years ago or even 10 years ago, you could go look at a two or three year contract and say, that's real ARR.

53:34We understand where that's at. We know when the renewal cycle is. We can talk to the customer, understand the value. we understand the switching cost. I don't think we understand all of those things today. And much of that revenue is experimental. It's just as likely that they go from one to 10 to a hundred as it is they go from one to 10 back to one. And because of that, it's very difficult to understand if those marks are durable or not when the revenue itself is experimental. I mean, another person on the podcast was talking about with Anthropik, you go one to 43 billion and, you know, be a public company CTOs coming out and saying, we used our entire annual budget in Q1.

54:11So it's like, do they refresh the budget and it continues to grow 10x? Or do they just say like, hey guys, we can't spend this much money on this stuff anymore? I think it will also require shifting of budgets. You know, you had people budgets, maybe some of those people get replaced so that you have more to spend on those credits. But if you're getting the value out of the models that I've seen is capable, you know, that Claude is capable of doing, you'd be foolish not to increase your budgets. There's so much efficiency. There's so many more products. There's so much more development cycles that are occurring.

54:42If you can get that return on invested capital that quickly, you should put more money behind it. It's just, where's the budget going to come from? And I think you, you kind of have a belief that in terms of mortality rates are a little different. So traditionally in venture, when you're kind of like creating your portfolio, you just assume like 90 % of the companies will just go to zero and fail. You think it's a little bit different now. How do you kind of square that up and think about that? Yeah. I mean, I think what we're seeing is there's been so much hype around when are we going to see the solopreneur get to a billion dollar or trillion dollar outcome.

55:14But the reality is, is it's so easy now to create an application and the application layer is hard to navigate. There's many different types of modes. They're different than the old types of modes. The signal is hard to separate from the noise because of this experimental ARR. And so I think growth, I'm biased, I'm a growth investor. I think growth could become more interesting. I hope it does. Just as an asset class? As an asset class. Category, kind of a slice of the market? And the reason I think that is that if you could start, if it was difficult to start a company before, you had an idea, you wanted to start it, it's now easier by default.

55:46You should be able to vibe code or get somebody to help you vibe code to a spot that you have a product to sell. And you couldn't do that before. So now we potentially get to a spot where there's, again, these 15 companies that are all doing close to identical things. Hopefully they're building in a spot where they understand, hey, if we're first mover, we can actually build a moat. We'll get some data. The data becomes more valuable. The more customers use it, makes the model more valuable, or there's a regulatory moat we're going to go tackle first before anybody gets there. But if now that the mortality rate isn't quite so high because those companies all got to a million or two or five without taking much money, then what do they need next?

56:23They need to go to market capital to be able to out compete their peers. So maybe where there was three or four companies in a category that survived and all of them got funded, now you got 15 that need funding. And the one that raises the most, if there's truly a durable moat they're trying to build, the one who raises the most is the one that will win. And so that makes a large growth round potentially more attractive. Interesting. And so that's why you think it's an interesting category because there's a lot of these, as an investor, there's a lot of opportunities. I think there will be more of them.

56:56I think founders are starting to understand what is a wrapper, what is not. I look at kind of three different tiers of moats. The first are things like regulatory moats, vertical data moats, where there's already something in place. The second is a little bit softer, which is something you have to build towards. You don't necessarily have it on day one, but it could be the idea that eventually we'll have enough data that as consumers start to use the app more, as companies start to use that more, it starts to create a flywheel of data or a flywheel moat. There's the brand building moat. You know, you talk about the sales organizations that are being built around Anthropic and on OpenAI.

57:34They're doing that. They're advertising. We're talking about it yesterday, advertising the Super Bowl to build that moat. Those are real moats that they can build. You have to build it. You have to make it difficult for there to be ability to switch to another application. Those moats still exist today, but those are softer. You have to build towards those. The third are things I think are red flags. I think the last 10 companies I talked to all told me they have a unique ontology layer. When I press them on that, some of them do, some of them don't. Many tell me that the reason that nobody else can compete with them is that you need to fine tune a model to be able to produce what they accomplished.

58:09But when you really go look at the research, most fine tune models underperform compared to the generalized models. And so those are kind of red flags to say, if we invest behind those, there has to be some other sort of mount. Well, it's been a lot of fun. Thanks for coming on the show. No, thank you. MyScarity, QED, welcome to the show. Thank you. So we were talking a little bit before this. You were telling me that the AI bubble is closer to popping than people think and that you think you know what's going to cause it. So what's going on? So when public company CTOs are telling you that they blew their entire token budget in six weeks in Q1, they can't increase spending at the rate of growth that we've seen.

58:50And everybody knows that as a company goes public, the old rules still apply, whether it's an AI company or not, whether it's the hottest company or not. To go public, you need to create a beat and raise cadence. And if you've pulled forward 100 % of your largest client spend into Q1, where's the money coming from for Q2 and Q3 and Q4? So CFOs of the clients, the users of AI are going to have a reckoning because their AI usage is not increasing their revenue at the rate that the AI company's revenue is increasing. And when that happens, which could be as soon as Q2 or Q3 of this year, those companies that are going to try to go public, they're not going to have that beat and raise cadence that has allowed them to become become such amazing juggernauts this quickly.

59:38So the only way to get around that is make sure that the AI products are actually adding a ton of value and the companies will continue to increase spend. Yes. But again, they have to add value in a way that hits the bottom line of the company. They continue to spend five times more than they thought. Right. There's no budget in any company. There's no budget line item that can grow 5x in a year and the CFO is happy. Other than revenue. Like revenue is the one. Sorry, you're right. The only line item that can grow 5x in a year and make the CFO happy is revenue or profit. Yeah, gross profit, free cash flow.

1:00:17That's right. There's no cost line item that can grow 5x in a year and 5x over a budget that was already 5x. Yeah. Right. So the reason I think this is important, we've just seen this movie in the very recent past. We lived it. Every VC lived it. we saw an amazing bump of digital transformation, digital usage go up at the start of COVID. And we all thought it was a new trend. It was not a new trend. It was a one-time step function change. So the change was real, but the trend was not extrapolated because eventually people, you know, there was only so much money in the budget for Netflix. So once everyone signed up for Netflix in order to get through COVID, there wasn't another group of people who could spend another double on their Netflix.

1:01:06And I think what we're seeing as the AI usage has gone from awesome experiments to real production functions, the ROI calculations for everyone who's spending, they no longer have the headroom. And that's why I think it could come faster than we think. Yeah. I think maybe the other way to get around that is just 5x the number of customers. Like you had the one customer, the boost of the budget, can you just quit get a bunch more customers? Which, I mean, that could happen. Absolutely. It totally could happen. And I think one of the most impressive things that Anthropic disclosed was they've got, I think, more than a thousand customers spending more than a million dollars.

1:01:49Now, at some level, that's really impressive. It shows real breadth of adoption. And another, just a thousand times a million, that's only a billion. If they're doing$30 billion of revenue, Isn't it like 45 now? I mean, it's incredible. You know, I'm telling you the bubble may become faster than it thinks that I'm going to look like an idiot. But I will tell you, there is some limit to how much spending AI can absorb. And it is simultaneously so early in the age of AI, right? But there is, as we get into real numbers, right? These companies have more revenue than Salesforce. source. Like Databricks is one of the most impressive private companies in the world.

1:02:30It is anywhere between a sixth and a ninth of Anthropic. So how much revenue can you really pull out of the economy? Because ultimately the economy is not growing at 10 % a year. There is not that much excess spend. So you're pulling the budget from somewhere. And eventually when you're, you know, there's a, there's a great law in economics. It's called Stein's Law says anything that cannot continue won't. It's just that simple. You can't grow 10x a quarter forever. Yeah. And that's a function of how all these companies are valued. It's basically just the revenue growth rate. That is like really like 100 % of the way people are valuing these businesses.

1:03:14And by the way, relative to previous generations of technology change, we should give these companies a huge amount of credit for that. Yeah. They are valued off real revenue and they're valued off real revenue growth rate. This is more revenue than narrative relative to some of the things we've seen before. And yet. A hundred billion dollars of revenue? Maybe. Two hundred? Three hundred? I don't think so. We start to get in meaningful percentages of US GDP. And you can only pull meaningful percentage of US GDP into this space if you're taking it away from something else. And also if it's truly actually useful and doing things.

1:03:57Yeah. So again, it's just, you know, people show those charts of like how good the models are and do they continue to just get better on that exponential line? Here's what I think happens. I think the CFOs will bring a hammer down. Q1 was the quarter of token maxing. It was really fun. But token maxing does not have ROI. By Q2, Q3, Q4, the CFOs will bring a hammer down. Token maxing will be dead. People will have done the token maxing in order to learn how to use these tools. And by the way, even for my companies, I recommend token maxing. You've got to token max in order to learn, but then you've got to have an ROI case.

1:04:37And actually one of the reasons why we're so bullish at the application layer is those application layer companies have mostly gone through the gauntlet of a business case with real ROI. Now they still have to deliver on that, but they've gone through the business case. Whereas the broad enterprise adoption of every single person in our enterprise gets a open AI, a Gemini, a Claude, a co-pilot. That doesn't have an ROI case. That is a we must do AI case. And that's the case that's harder to build on after you do it the once. Yeah. I think you also mentioned something. We haven't talked about this at all.

1:05:14A lot of people say we're at the pace of like, we're in an era of like the fastest pace of technological improvement, adoption, et cetera, ever. How do you feel about that? I think it's wrong. I think the history is written in increments of human lifetimes and anything that happens within a human lifetime will be compressed. So when you think about the computer era, our grandchildren will never think of computers as not having had AI. So the whole idea of a computer that is not connected to the internet The whole idea of a computer before the internet will be some historical anomaly that like people write PhD thesis.

1:05:53Do you know there was 20 years where the computers were not connected to the internet? Do you know there was 20 years where the computers did not have AI? So I think what will happen is what people will realize is that this entire era is the computer, internet, AI era. And everything that we think of as extremely rapid change right now will be one change. And the society that we live in will react to that change as one unit of cultural, social, and economic change. And if you compare that to, let's take it 1890 to 1950, cars. Cars were not the same as nuclear. Cars were not the same as planes.

1:06:36Planes were not the same as the age of fertilizer, which completely transformed our ability. Or like the age of like boats. Indoor plumbing. Yeah. Right. So those are actually more technological change across more sectors of the economy than we're experiencing now. Even though it feels like the pace of change is so fast, we're very myopically focused on the pace of change, which then one sector, which will be when history books are written, viewed as one lump of change. How do you think they'll write the history books? Like, what do you think it will read like? So here's one of my favorite things.

1:07:12when you were learning about computers, there would be a picture in your textbook and it said, do you know that computers used to be as big as warehouses? Oh, yeah. Like a massive, huge machine. Well, where are computers today? They're in your pocket. No, they're not. They're in warehouses. Fair. They technically are still in warehouses. They're still in warehouses. So I think that's a good example of a historical blip. The thing that a computer did went from a warehouse to your desktop. That felt like a really important historical change. But now the value of compute, the idea of a decentralized, of a network puts most of the compute back into the warehouse.

1:07:52And so when the history books are written, they'll just be like, yeah, computers are in warehouses. Of course, they got more powerful, but they started in warehouses, they ended in warehouses. Yeah, that's fair. I have not thought about it that way, but that's interesting. Interesting framing. Well, this is a lot of fun. Thanks for coming on the show. Absolutely. Thank you, Turner. John Oberheide. What's up, Turner? One of the founders of Duo Security. Regular listeners of the show will actually be familiar with you. Yeah. What did they say? Second time caller, long time listener. Yeah. Well, yeah.

1:08:19Thanks for being here. So we were talking a little bit before. You feel like a lot of people, especially individuals, when they first get into doing venture investing, they make a lot of mistakes. What do you think people do wrong? Yeah. In my journeys, you know, as a founder, head of exit, now mostly kind of investing off my own balance sheet. And due to my role in the company and raising from some great funds, I kind of had privileged access to a lot of top tier venture funds. But then in my journeys, I run into a lot of folks that maybe they're new to venture, maybe they're interested in the asset class, maybe they're not experienced in technology, but they're very smart individuals.

1:08:58But I see so many cases of high net worth individuals just doing venture wrong. And it's not necessarily a hot take. It's kind of maybe uncommon common sense. It's maybe just not vocalized enough? I think it's a lack of understanding of the asset class. And it's an area where maybe it's not a hot take, but I'm really passionate about it because I want to see people make good investments and have good returns and back good firms at back good companies. So what are some of the biggest mistakes you see people make? I think that the anti-pattern is when people get excited about the innovation economy, they get excited about AI, and they say, hey, listen, my cousin's dog walker's college roommate is starting an AI fund.

1:09:50And I made a commitment, AI is really hot. And I'm like, what are you doing? So that's not good. You shouldn't do that? I mean, I don't have any tattoos, but if I did, I would get, you know, adverse selection is real tattooed on my forehead. Because, you know, the number one thing when you see a deal, you have to ask the number one question. It's not like, who's in it, or what's the terms, or what's the founder? It's, why am I seeing this deal? Why is it coming to me? And, you know, top tier, top quartile venture fund managers are not coming to the wealth channel generally. They're not coming to high net worth individuals.

1:10:28They've already filled up their allocation and have a long waiting list. So if someone's coming to you, it's probably not top tier unless you truly have some edge or some privilege access. So when I talk to folks like that, I try to give them the rundown of one, why participate in venture? Yeah, because it sounds like it's something you do want to participate in. So then how do you do it? Well, you might want to. So there's like the qualitative part of like, yo, you're backing the companies in the future. Innovation economy is important. The quantitative side is like, you know, there's trillions of dollars now being created in the private markets.

1:11:04Whereas, you know, I think NVIDIA went public at 400 billion market cap and like Microsoft went out like, I think it was sub 1 billion. All that value was created in the public markets. That's shifting now with, you know, SpaceX, Anthropic, OpenAI. So you want to be part of that value creation, kind of get your share. But most people say, I want to invest in venture because of the returns. In reality, when you look at the data, whether it's from Cambridge or wherever else, whatever benchmark or timeframe you look at, the median venture returns suck. Median venture underperforms... Every other asset class.

1:11:42S &P 500 underperforms NASDAQ depending on what vintages and what time periods you're looking at. But median is bad. And ventures has the highest return dispersion of any asset class. The difference between 25th percentile and 75th is crazy. Or the difference between median and top quartile, maybe 10 points. Well even top quartile, top decile, 1%. Yeah. I mean, it's not 10 basis points. It's like 10 points of return. Yeah. I mean, I think if you look throughout history in bad vintages, 1x DPI is top quartile, which is not good. I guess not a good return. Yeah. So you can say, like, I'm a top quartile fund.

1:12:26Like, not necessarily great. Yeah. And I think like in the 2021 vintage, I think 1.5x is top decile. That's a rough one. And prior guest to the show, Ali Partovi at NIO, they had like a 10x 2021 fund. Yeah. Oh, they had some good ones. So like talk about top decile, like it's probably in the top 1 % 2021 fund. So like being even in a top decile venture fund in 2021 is not really that great. And venture is unique too because it has persistence that like if your fund X is top quartile, your fund X plus one is not guaranteed to be top quartile, but it's more likely to be top quartile than a fund Y that was second or third quartile suddenly jumping to fund one.

1:13:15And it's intuitive, like the best founders want to work with the best firms, therefore they get the best returns, therefore it's that sort of compounding cycle. And so the obvious answer is like, oh, okay, well, if I want to participate in venture, I just need to invest in the top quartile funds, right that's easy like yeah well you also don't know necessarily which ones specifically like you know there might be a firm that has a good fund and a bad fund a good fund and a bad yeah so yeah it could just late a little bit or it just might be like a bad year yeah like because of the way public markets like the economic cycle works because like who knew that llms were going to do what they did in 2022 and like if you weren't allocated i think 2022 and 23 vintage funds are going to do really well.

1:14:01And if you skip that and now you're deciding in 2026, you're going to come in a lot different environment. You could probably argue 22 is set up to perform better than 26 will be. Yeah. Yeah. The only true all weather fund, of course, is banana capital. But that's true. Yeah. You know, it's like the it's easy enough to say, like, oh, you should just invest in, you know, Sequoia, Benchmarked and index and so on. But that's where the real challenge is that, you know, venture capital is an access class, not an asset class, and you can't get access to those top tier managers. And we were here at the Allocate Summit.

1:14:37This isn't meant to be a commercial for Allocate, but that is the value they provide. It's access to, hopefully, your top quartile managers, a much higher probability of accessing your top quartile managers with low fees, low commitments, where you're high net worth individual, you can write a couple hundred K check into a top fund or into a fund of fund vehicles, as opposed to either having to be some like super founder with specialized access or being a$20 billion endowment that can write$100 million checks. It is a way of kind of democratizing access to the private markets. Yeah. Well, this is a lot of fun.

1:15:16Thanks for coming on the show. No problem. Thanks, everybody. Dan, Dan Fader at the University of Michigan. Thanks for coming on the show. So I wanted to ask you, there's a headline recently that the University of Michigan invested in OpenAI. Can you talk about that? Well, we're going to talk about how it takes on this little conversation. So I feel pretty far out of my depth on this, Turner, because you have one of the best Twitter games or X games. Not their X games. I guess they're Twitter games, right? Yep. Out there. And I have basically none. So I'm going to give you some advice in general.

1:15:48Oh, thank you. It's very general advice. Yeah, thank you. take it for what you can it's worth no more than what you paid for it um which is you know with respect to twitter or x you know you shouldn't always believe everything you read on twitter and you probably shouldn't always not believe everything you read so um with that maybe we'll move on that's fair yeah i think one of the things you want to talk about was you think that asset allocators should be thinking about doing venture a little bit differently I know you came on the podcast for regular shows on the show. They maybe heard this feel a little bit.

1:16:24So what exactly do you mean by that? Well, there is a distinction and I guess a difference as well between being an allocator and being an investor. And the way that the industry has evolved over at least my observation, which has been over the past 25 or so years has been that the the allocator aspect of the way endowments foundations and multi-asset class investors behave has has really taken an increasingly dominant role so it's less investing more allocated and by investing what i mean is less about what the underlying exposures are much more about managing portfolios on a risk basis so looking to optimize based on benchmarks or benchmark exposures and not taking full account of where you are as an investor so where are you are you at an endowment are you at a foundation pension are you an individual and if you're at any of those places what are the characteristics of that place and that to me is what the whole portfolio means which is where are you in the case of where we are at the university of michigan we are at the university that has world-class research and innovation areas and the breadth of which is just absolutely stunning we have an endowment that's fairly substantial and we have an ability to execute in ways that other people don't so there are drawbacks to each one of those characteristics there are things that we wouldn't do well as a result but there are also things that are just inherent advantages and the shortcoming that i see is that as people have come up through the allocator roles where there's much more of a career path the allocator piece of the equation just naturally tends to dominate how people go about their jobs she did something interesting when you were at wash you what was one of the big um one one of the more interesting investments you made when you were there well it really goes to like the the beginning stages of taking this approach of looking at the whole portfolio where we have advantages and one of the advantages that we had there and that we have at michigan is we have networks and information flows that other people don't and we we started leveraging that into some directs and co-investments that were pretty impactful.

1:18:56So there's one in a company that may or may not go public this year that we started out investing in. May or may not be a American rocket, aerospace, data computing, cloud computing, AI company. But it helped to demonstrate, for me, the power of how you can apply these networks and where you are to making investments that are either available to you only or available because you're taking more of an entire portfolio approach of what are the things that I have as tools to invest and where can I apply them? So it's kind of the same thing that an allocator is looking at a GP. It's like, what is your unique advantage?

1:19:40It's almost like you step back and look at yourself. What is my unique advantage as an allocator that I can do a little bit differently? Yep. And a big part of what I think everyone has to remind themselves of, if you have a couple things that go well, you should take the right lessons from those successes. It's much easier to take lessons from failures, but the lessons that one should take in my seat or seats like it is that we shouldn't pretend to be something we're not. So we are not world-class venture capital investors. We're not the best pickers in the world with some sort of magical picking ability.

1:20:22What we are, or what I think I am, is that we're pretty good at creating trusted relationships and listening carefully to people who know what they're doing and hopefully being in business with some of the best people in the world at doing those things. And that's where we can play our hand and play it well. Well, this is awesome. Super interesting. Thanks for coming on the show. Well, my pleasure. Ben Ivey at Marshall Street Capital, welcome to the show. Appreciate it. Thanks for having me. So we were talking earlier, you were saying that you think that a lot of allocators need to start looking beyond just returns.

1:21:00What did you mean by that? Yeah. So I think when allocators are looking at the venture asset class, it's so unique because you're at such an early stage and an inflection point for basically any technology. You think about AI, biotech, you name it. And so I think there needs to be more of a premium and more of a value put on the information that you actually get from the GPs that you work with as a source of just intelligence that you can use throughout the rest of your portfolio. And I think just focusing on, oh, I'm going to get the top quartile manager and expect them to repeat for fund two and three and four and beyond is just a little bit of an overly narrow way of looking at the value that the asset class can bring to a portfolio.

1:21:46So what would be an example of a way to maybe get like extra information you can apply elsewhere? Yeah. So I feel fortunate at Marshall Street to be a generalist investor. And so I think that's very rewarding and it certainly informs my perspective. So I'll have to caveat with that. But you think about emerging technology like Amito said, Anthropic, right? Where this model basically coded its way out of its own box. And you think, okay, well, let's think about other applications that that can solve, right? And I think, okay, well, let me think about what are the implications for other asset classes?

1:22:26So lots been made about private credit. But can AI think through a strategy to do a liability management exercise? I did actually see a company. There's a company that you input a 100 page credit agreement and it gives you a lot of information that you would not have. It's going to give you the outs, right? I mean, I'm just an investment guy, certainly far from in the weeds on every PPM that I see. I'll be the first to admit that. But you just have to think about how some of these technologies are going to impact the rest of the portfolio. And we were chatting earlier about kind of generalist versus specialist.

1:23:04I think increasingly teams that just rely on specialists to do that low level due diligence, those type of tasks are going to be taken away by AI. And so what we need to lean in on the human side of things is putting two and two together. And I don't mean, oh, let's look at X portfolio company and AI that could be purchased by a larger one. I mean, what are the implications cross asset class and not just talk to your buddies across the desk about venture A firm versus venture B firm. You need to think about the implications for the total portfolio because at a family office, I'm not belated into what the venture returns are in my portfolio.

1:23:48I'm belated into what the return is that I deliver to the family that I serve. Yeah, makes a lot of sense. Well, thanks for doing this. It was a lot of fun. Absolutely. No, thanks for having me. It's a great event that Allocate hosts and certainly appreciate getting involved and always come away with excellent connections here. So thank you. Astro Shadiki with Song United. Welcome to the show. Hey, great to be here. You had an interesting blog post that you wrote a couple months ago, kind of relevant now, the Russian dolls of SPBs. What was the blog post and what's kind of going on? So it was a series of five blog posts, actually.

1:24:22So Matryoshka dolls, which are, you know, Russian dolls, where, you know, like you open up a doll and there's another doll and then you open up that doll. And the reason why that image sort of came into my mind was because there was this fever around, you know, 600 million in SPVs into Anthropic. It was like several billion dollars worth of demand for SPVs into Anthropic. and part of it was like I live in the Bay Area and I've got friends all over the world and they're calling me, they're like, hey man, do you have any access to, you know, any of the five, six top names? And I don't do SPVs. So I was talking to all these people and after a while I'd like follow up with them, you know, what happened, did you do anything?

1:25:11In some cases I introduced them to VCs, fund managers that were on the cap table and they could get allocation. But the response was, we don't pay carry. We don't pay carry. And so that's what led to me writing the blog post or a series of blog posts because I don't think people really understood what was going on. And what's going on with these SPVs was, you're subscribing to an SPV. They were willing to pay 8%, 12 % upfront one time, management fees on an SPV just so that they could avoid a 10 20 percent carry and I did the math for them it's like if it's a 1 % and 10 percent which I was able to get them it's the same but the risk that they're taking is like here is a VC that's giving you a 1 in 10 or 2 in 20 and they're on the cap table you know they have ownership or they can get access and then here on the other side you've got this SPV and that SPV and you're paying 12 % and no carry.

1:26:17You make money just on the transaction. On the transaction. Not on any kind of economic value created beyond the initial transaction. And we're talking 10,$20 million checks that people are writing. So this is not like 100K checks, you know? You can make a million dollars in a day from writing an email. And then I found out that some of these SPVs were actually in another SPV that my friend was running. And that SPV was actually an SPV into an angel-less syndicate. So this is a four-layer SPV. Yep. And this is rampant. And so what I was talking about was, you know, like, look, I don't like to pay carry either.

1:27:01I hate paying carry on SPVs. You know, like I'm a fund. I invest in funds. I pay the fee and the carry. That's okay. But on SPVs, I don't like to. But in one of these hot names, you're taking on a lot of risk. And so, you know, in this case, either pay or don't do it. But taking on the risk. And so one of the things that I worry about is like, that was five, a series of five blog posts that I did. The thing that I did not say because it's like, you know, LinkedIn or whatever, the amount of litigation, the amount of lawsuits that we're going to see over the next three, two, four, five, six years is going to be crazy.

1:27:39because a lot of these things haven't really unraveled. Because none of them have really had to yet. There's no exit, right? Yeah. But we're coming up to a point where the companies where this was the most common in were kind of reaching a point where they will all list, become public. These things need to settle. Everyone finds out, you know, the Russian dolls are fully opened and they see what's in the, you know, the bottom of the doll, the final layer. And it may not be, it might just be a Russian doll. It won't be the asset that you thought. The anthropic shares, yeah. Yeah, it might just be, when you're buying an SPV, if you don't have access, I get it.

1:28:19The best way to get access is to invest in the access class. And the access class, you know, invest in LPs. This is why we invest as an LP into venture funds. We invest into venture funds because we want access, we want information. And when opportunities come, we then co-invest alongside. That is the right way. There is no shortcut. So when I meet family offices in different parts of the world who say, I don't need to do this because I have direct access, more likely than not, they don't. They think they do, but they'll find out in a year or two or three. So how do you know that you actually do have the direct access versus not having it?

1:28:58I mean, so there's obvious ways to confirm it, right? You can do proper diligence. Let me ask you, do you know anybody that's subscribed to an SPV that has done any diligence on what they're buying? I don't think I've had a single SPV that I've raised where they've asked to meet the founder. Yeah. But it's usually they're all a portfolio company that's in the fund. And it's all I write a memo, put quite a bit of work into it. And there are most people are LPs in my fund, multiple funds. And they trust me that what I'm presenting is real. Yeah. And if it's not real, what are they going to do to you?

1:29:34I mean, it's on me. My reputation is immediately destroyed for not actually investing in this asset that I thought I was giving them. Now, imagine you're not a VC. You're just a broker and you're doing the SPVs. And you used to do real estate. And you kind of saw you can make a million dollars by sending email. And you sell these in the arts club in Dubai or London or... Yeah, you got to be careful with this stuff. Yeah. Well, this is a lot of fun. Thanks for coming on the show. Thanks for having me. I had a lot of fun too. Sarah Pinto at Robinhood Ventures, welcome to the show. Thanks for having me.

1:30:08So I know maybe people are kind of familiar with Robinhood, maybe they're not. So what is Robinhood Ventures? Like mechanically, how this kind of works for people who have never heard of this before. Of course. So Robinhood's mission is to democratize finance for all. And we're the logical next step of that. So if you think about it, companies are staying private a lot longer. and most Americans are not accredited. And even if they are, they don't have access to the best private companies. And so that's the problem that we're solving with Robinhood Ventures. And so Robinhood is quite unique in that we already have a number, about 27 million retail investors on our platform, and we know how to work with the SEC, and we are a Silicon Valley insider.

1:30:50And so we think we can uniquely build portfolios of excellent private companies for for anyone to invest in in a way that the SEC approves. And trying to help people visualize how this works. If I have the Robinhood app on my phone, is there really a button like invest in startups? And you click it and you can buy it in your portfolio in the Robinhood app? Are we allowed to talk about this? Or how does that actually work? Yeah, of course, of course. So you can actually, so right now it's a publicly traded fund. Our first fund is called Robinhood Ventures One. The ticker is RVI. So anyone can? Anyone can buy it on any platform.

1:31:26So when we IPO'd the fund in March, the retail access was exclusive to Robinhood. And so you would just, like any IPO, put in an order. But right now you can buy it and sell it on any platform. Interesting. Okay. And I think there will be a lot of people that argue retail should not be investing in the private markets. I mean, maybe what you have is like a hot take. Maybe it's not a hot take. But so why do you think retail should have access to this stuff? I think, first of all, there's so much innovation and wealth creation happening in the private markets that I think it's really an issue that we're locking so many people out of it.

1:32:07The second thing is, I think what we've found at Robinhood is that when you give people information and when you give them products that are safe and regulated by the SEC, it's a great way for them to learn by doing. And essentially, our customers behave like adults. They know the amount of risk they're able and willing to take. And because we allow people to buy really small quantities, you can just kind of try it for yourself with a very small amount of dollars. And so that's essentially how I think about access, is if you do it the right way, it is much more just and much better than no access.

1:32:44And frankly, in this world where there is just so much wealth creation that happens on the private markets, it's just frankly a huge issue. And then the last thing I would say is if we as a society want our citizens to root for tech and innovation, and particularly in this AI cycle, they have to feel a sense of ownership. They have to feel like it's theirs too. And if it's just making institutions and high net worth individuals wealthier, that's a more challenging proposition. Yeah. And I'm assuming maybe a lot of people are saying, I've kind of seen this whole debate about like all these different like double, triple layer SPVs and like, you're trying to get access to some of these companies and you may not even own the shares in the business that you think you're buying.

1:33:32So the SEC regulated, you're able to buy this publicly traded fund in the sense you could argue you're actually helping people avoid some of that mess, some of this mess that's going on out there. Absolutely. So importantly, we have for every investment that we make in the fund, we go directly to the companies, we get their approval. They're excited to have retail investors through our fund on their cap table. And we've invested directly for the 10 companies we've invested in, we've invested directly on the cap table. And so, yes, we provide an alternative. It's not single stock, which again, to to to protect retail, the SEC doesn't allow for now.

1:34:11It is a basket of companies, but it is a very curated basket. It's 10 companies today and probably a few more in the future. But it is direct to cap table. There's no extra fees and there's no legal risk. I think the most exciting thing to me, other than to give access, is also that we found that a lot of entrepreneurs are actually excited about this because they see, they know that they're going to create a lot of wealth and a lot of success. and they find it really exciting to democratize that. And particularly for the companies that have a consumer or a consumer product or maybe a marketplace product where there's participants on the marketplace, the idea that the people who make you successful can also benefit in your success, not just your employees and your investors, that actually really appeals to founders and they resonate with that.

1:35:02That was super interesting conversation. Thanks for coming on the show. Of course, thanks for having me. And thank you for listening. And thanks again to this episode's sponsors. Upgrade your business to Flex with the link in the description. Put your sale tax and autopilot at numeral.com. And for AI analytics, just ask Amplitude. If you enjoyed this conversation, please like, comment, subscribe, and share this episode with a friend. Make sure to check out the back catalog of over 100 episodes with the founders of companies like Robinhood, Sweetgreen, and Mercury, and investors like Gary Tan at YC, and Chathan and Eric at Benchmark.

1:35:32Tune in for the next few weeks for conversation with Sam Blonde at Monaco, Dan Taron at Gutter Capital, Will at Exa, Charles Hudson at Precursor, and Hans, whose secondaries firm, Industry Ventures, was just acquired by Goldman Sachs. If you don't want to miss any of these, subscribe to my newsletter, The Split, linked in the description. Get each episode plus a transcript, email directly to your inbox every week. Thanks again for listening. See you next time.

1:36:07Thank you.