SPEAKER_00: Hello and welcome back to Twist. My name is Alex. It's Wednesday, which means it's time for yet another Venture Capital Roundtable. This time I do have to say we have an incredible panel. And as you can tell from the bags underneath my eyes, there's more than a little bit going on. So today we're going to be looking into strong second quarter exits, including a number of IPOs, the return of Anthropics Mythos and Fable models, rising demand for open-weight Chinese models, including GLM 5.2, what to make of $100 million Series A rounds and even larger seed rounds, and how our panelists are navigating investing in yet another boom. Now, today I have with me Aileen Lee from Cowboy VC. Aileen, how are you doing? SPEAKER_01: I'm great. I'm excited to be here. SPEAKER_00: Now, your firm raised $230 million Fund 4 and a $140 million opportunity fund back in 2023. You guys have backed Drata, Standard Kernel, and Binti, amongst others. How goes fundraising for Fund 5? SPEAKER_05: We're not raising for Fund 5 right now. We're still investing Fund 4. And it's a, I mean, we're going to talk about it. It's a wild time right now, but a lot of exciting things to look at right now. And some, I think, founder quality is incredible right now. SPEAKER_07: It's always good to hear. We also have Mike Maples from Floodgate. Mike, how are you doing? Can't complain. SPEAKER_00: Now, you filed with the SEC to raise a $130 million Fund 8 in May. Floodgate has backed Lost Energy, Hadrian, and Applied Intuition. Have you filled up that new fund? SPEAKER_08: Well, I'm not sure I'm allowed to say, but, you know, we're in pretty good shape. SPEAKER_00: Great. Good. And then finally, we have Ben Lair from Lair Hippo, which closed a $200 million Fund 9 last year. Lair Hippo is back to Zipline, which we've had on the show a number of times. SPEAKER_11: Palmetto ends in business, amongst others. Ben, how are you? I'm doing okay. I have more to complain about than Mike, I guess. SPEAKER_12: Oh, okay. Well, do you want to start? We can start with a therapy session and then get into the conversation. SPEAKER_11: Let's get into it. We got time. We have time. Actually, before we do anything serious, I want to point out there's two of us here who tweet all the time, Mike and myself. SPEAKER_14: And then there's these two people on the show today who apparently have lost access to their Twitter accounts, namely Aileen and Ben. So from Mike and I, how do you two manage to shut up when there's so much going on that both infuriates and delights us? SPEAKER_15: Like, how do you not just constantly go at it? SPEAKER_18: I mean, I definitely have become a little bit more of a lurker. I used to be a lot more of an active tweeter. SPEAKER_19: So I actually, I was an active tweeter back in the day and actually a pretty active social media user. SPEAKER_21: And I think it was probably during COVID that I sort of felt that the trade was no longer worth it. Like there was, I just sort of like hit a wall and went cold turkey one day. I went to a dinner with a friend. He told me that he had sort of pulled off all social media and was living his best life. And I sort of, you know, had like a second and third drink and was like, I can do it too. And deleted, like deleted the apps and, and really like didn't go back at all. I have become a little bit more of a lurker of late, like Aileen, but look, I just, I wasn't getting the joy out of it. I really do think that like in, in general, social media is like not great. I have young kids. I like feel the sort of FOMO that comes from it and the angst that comes from it. And I just like decided to pull out and I understand that like, there's probably some trade-offs in terms of like brand building and, you know, puffing out my chest that I lose as a result of it. But I try to put that sort of time and energy back into other productive things. SPEAKER_24: Yeah. Maybe Mike and I will eventually grow up and join you guys. But in the meantime, we're mad about everything. So I feel like, I mean, Mike, I'm super pissed too. SPEAKER_25: Don't get me wrong. I just like, you know, take it out on my children and colleagues. SPEAKER_14: Oh, that's much, that's much healthier. I'm sorry. SPEAKER_27: What have you guys ranted about recently? SPEAKER_14: Mike has ranted about, let's see, everything, California, mom, Dami, foreign policy, domestic policy, tax policy, immigration policy. SPEAKER_00: I mean, Mike, you've been, I went through all your tweets guys before the show and Mike's been on a bender. SPEAKER_31: Yeah. Maybe I've got a 4th of July on the brain. But I guess, I guess some of the, normally I just stay out of it all, but I guess lately I've been thinking that there are some things that if they happen would be very, very bad. SPEAKER_32: And, and I think I'd have regrets if I didn't say anything about it. SPEAKER_14: Yeah. Well, I bring this up, not just to be a brat, but to point out that there's so much going on that I feel like cycles of business have been compressed dramatically in the AI era. And we're seeing things become true in the Q1 and then not true in Q2. So it's a, it's a very kinetic time. I think it's a good time for us to chat and figure out where we are. And from that vein, I want to start with how much has recent venture liquidity helped you guys on the LP side of things for the last couple of years? SPEAKER_00: VCs were raising less money than before. People were raging about a lack of exits. Things have gotten better lately. So I'm curious how that's manifesting in your future fundraising plans and how you're thinking about allocating capital. And Ben, I thought we'd start with you. Chamath Palihapitiya: Sure. Yeah. I mean, you know, like Aileen, we are not raising right now. We, we raised our last fund last year. We're in the sort of, you know, generally early innings of deploying that. SPEAKER_21: Uh, you know, I think probably like a lot of folks, we had a few years of slower liquidity following sort of like a bunch in 21 and early 22. Um, things have picked up, uh, but I don't, you know, I, I never feel like I am, our liquidity is, is what is really important to our LPs. Most of our LPs are large institutions that have a bunch of exposure to multi-stage and sort of, you know, gigantic funds that they have huge checks with. And I think like they need the, you know, SpaceX's and stripes and open AIs and anthropics to go public, to sort of feed money back into their system in a large scale versus, you know, me returning five or 10 or $15 million to LPs on a, you know, 150 or $130 million fund or whatever it is. And so, uh, you know, I don't get a ton of grief from LPs. I think also I'm very early stage, like people who are signing up with us and probably with Mike and Aileen understand that this is like the best companies take a long time to mature. I understand we have this like weird, very short-term view on companies are worth a trillion dollars in 15 minutes, but I still think probably over time, we get back to some general sanity around the idea that building great companies takes time. And, um, I've, you know, I think we're lucky that we have LPs that are sort of signed up for that. SPEAKER_24: Aileen, I'm really curious about this because Jason has been complaining for several years about a lot of liquidity. SPEAKER_00: He said, you know, the venture industry was under just so much pressure, um, seems that Ben saying that maybe some LPs are just less concerned. So how does that manifest over on the cowboy side? SPEAKER_47: Oh, I do. I think it's going to be interesting because obviously a lot of folks are locked up still, right? SPEAKER_49: But there's a lot of money that's going to get distributed with SpaceX. We have one LP that had a target venture exposure of 25%, but because there's been so much appreciation from some of the larger fund holdings, they're at 45% venture exposure. And so what will happen, uh, when they get the money back, you know, will like the percentage of it's probably, you know, they want to have diverse portfolios, but I think it will help because they, I think some of them have been a little, um, hesitant to commit more to venture when they weren't getting money out. So I think it's good news for the venture business that they're going to get money back and hopefully they'll put it back into a diversity of funds, both large and small. SPEAKER_51: This is like back to the denominator effect, right? SPEAKER_21: I mean, we're back to sort of like the 21 denominator effect, paper gains that hopefully turn into not paper gains and hopefully have more staying power than the 21 paper gains did. SPEAKER_08: Mike, do you think they're going to, well, I, I, we try really hard, uh, to have liquidity, uh, you know, regardless of the environment. SPEAKER_31: So we've, um, uh, you know, we, we've returned a little over 350 million in the last two years. Uh, but, but like our, you know, that's nothing compared to what founders fund will get from SpaceX, but our fund is tiny compared to founders fund. Right. Our, our fund is like 150 million. And so we're trying to, um, I think one of the things that seed funds can do is, um, they, they have more exit optionality. Uh, and, and there are, there are times when, uh, I think that, uh, the seed funds can proactively take advantage of that in ways that the big guys can't. SPEAKER_57: And that's why I actually, I, I think we're going to talk about this, but I'm encouraged by the bending spoons IPO. Yep. SPEAKER_59: Uh, because that's a vehicle that's been kind of gobbling up older companies and not necessarily AI native companies. And that's the thing we need. Cause a lot of, I mean, obviously everybody for the past two years has generally been investing in AI native companies, right? But you've got a bunch of portfolio companies that were kind of pre AI. SPEAKER_60: And so a lot of us are also working with them to actually make this transition to become much more AI native. In some cases, burn the boats and like build a whole new product suite or figure out what the exit's going to be. But while like, you know, traditional SaaS companies are trading at such crappy multiples, uh, they haven't been very acquisitive. SPEAKER_59: So I think it's like, it's exciting that MNA is coming back. And I assume that 27 will be maybe even more active. And, and so we'll, there'll be more exit opportunities for what we call like pre AI companies. SPEAKER_63: Yeah. SPEAKER_00: So just to put some, some notes behind that, the bending spoons IPO, uh, price last night went out today, price to $29 per share up from its range of 26 to 28, worth about 18.5 billion non-diluted last value at 11 billion. SPEAKER_14: And if you want to go read the S1, actually it shows a company in pretty rude health, frankly, doubled revenue year over year. And I think it had positive operating and, uh, net income on a gap basis in Q1 of this year. So doing quite well now alien, it bought, uh, AOL, it bought, uh, Evernote and Vimeo and I don't know, probably like caveman Inc. These companies are so old. Do you think that's a vehicle that actually can provide real liquidity to the old unicorns from the 2000 era that are just seemingly drying out on the vine? SPEAKER_65: We love an exclusive here on the pod and I have an amazing deal to announce. That's just for twist listeners. SPEAKER_67: Go right now to agree.com sign up for their easy to use all in one contract to cash stack. And if you tell them Jason sent you, you're going to get 50% off for life. That's right. 50% off for life. It's really important to have a tight system to get paid agree is the number one fastest way to go from contract to cash. That means gathering e-signatures, invoicing, billing, payments, and revenue recovery. If it comes to that, no more jumping between four or five different platforms, just to write out a contract, get it signed, set up billing and start sending invoices. Check out these numbers. The average time from contracts that to signature is under seven hours using agree.com. And the median time from invoice sent to invoice paid is just 36 hours. So if you want to stop chasing invoices, go right now to agree.com. If you tell them Jason sent you, you'll get 50% off for life. SPEAKER_68: Well, they're not all drying out on the vine. SPEAKER_70: I apologize. What percentage are? But I mean, I think Bending Spoons and others, right? SPEAKER_59: Like maybe Bending Spoons, there's a lot of PE firms, right? Who are going to do this, I think, more actively as well. SPEAKER_60: But I did notice, like I am still an Evernote user, which people give me shit for, but they just jacked up their price a ton year over year. So it'll be interesting to see how they balance being public and needing to grow revenue and keeping user bases. SPEAKER_72: Are you going to turn? I don't know. I haven't decided yet. SPEAKER_14: Okay. Well, I have to say that you probably are a little bit less price sensitive than the average Evernote user. SPEAKER_00: So I think that if you're on the fence, then that's not really good news for them. Now, I was going to save this for later, but we're talking about it now. So, Mike, Floodgate backed Ignite back in the day, yeah? Oh, that's a good one. Yeah. Shout out Vanity Jane, one of the nicest guys in technology. Vanity, yes. Period. Love that guy. Yep. They sold to private equity early last year, February 25, for I think $1.5 billion. SPEAKER_14: And at the time, I was a little bit disappointed by it because I had known Vanity for a while, and I really liked the company, how he ran it. It's focused on frugality and profitability and all that. But looking back, it actually seems kind of pressured, given what we've seen, as Aileen mentioned, with SaaS multiples. How common are deals like that going to be? SPEAKER_76: Or are we going to see more like the roll-up strategy we're seeing from Bending Spoons in the next couple quarters? SPEAKER_08: Well, I think they were a lot more common when it happened. So, it was interesting, right? And I remember, actually, you were at a dinner we had with Ignite one time. That's the one time we met. Way back when. Yeah, yeah, yeah. Yeah, like maybe more than 10 years ago, right? It was a while ago. SPEAKER_82: It was before I quit drinking. So, yes, it was more than 10 years ago. SPEAKER_08: So, I've been on the board of Ignite since 2008, and then we exited, you know, last year. SPEAKER_31: And I think that Vanity really wanted to go public. SPEAKER_08: But I think that the challenge for him was, you know, he's been doing this company for almost 20 years. And you miss one quarter, and it's like you just get eviscerated. SPEAKER_31: And so, you know, there was a lot of interest in his company. And, you know, there was just, he put so much time and effort into it that I think that he thought that he could create more value being part of this private equity concern. And I don't think we had any idea of what was going to happen to SAS multiples. I think that's just, you know, us getting lucky. But I think in hindsight, he probably made the right call. SPEAKER_87: Yeah, I think so. Ben, I know you don't care about liquidity because your timelines are infinite. SPEAKER_14: Oh, my God. SPEAKER_89: Let's have that be the thing that comes out of today, please. SPEAKER_14: I've never heard a VC say, my LPs are so patient, I've literally taken the net. That was really not what I said. SPEAKER_93: Oh, forget it. SPEAKER_94: I'm so glad we're all here today. SPEAKER_93: This is why I don't leave my house or participate in any of these things. SPEAKER_94: You're on Zoom. You didn't even have to leave your house to come here today. SPEAKER_00: No, given that you're not under, let's say, undue duress on the liquidity front, I'm curious how you think about private equity or non-IPO exits for your portfolio companies today. Are you encouraging companies to look for them if they're not going as quickly? SPEAKER_76: Or do you think that multiples will rise in the future and therefore holding on a bit longer before trying to find a landing place that makes more sense? SPEAKER_21: To what Mike said earlier, we are also obviously always trying to figure out ways to create liquidity, regardless of whether or not we have people screaming at us about it. That's the job. That's why we're here. And my philosophy is that companies get bought, not sold. I think it's really hard to go out and decide that it's time to go like ship off your slightly broken company and have somebody pay you not even a good multiple for it, but like maybe anything for it. And so, you know, maybe, and now to reference what Aileen said, like we're spending time with companies from past generations that we think are good companies with still motivated, serious founders, hopefully like unfair data advantages and lots of customers, but maybe that were built for a different time. That's why we're going to be able to re-imagine what their company needs to be, sometimes it's building some new products, sometimes it's changing some talent, but I think this is a moment where if you just sit around passively and look at your old companies and say, well, I hope these, I hope they figure out AI, we're going to be very disappointed. And actually, this is, there is something that I'm experiencing, I'm not sure if Mike and Aileen would agree, but we're, we are finding that as a, even as a seed investor, we need to go re-engage with companies from, you know, 8, 10, 12 years ago in ways that I would not have expected because the later stage investors are not stepping up. And I think a lot of it is because they're at funds that have raised enormous, enormous, enormous, enormous, newer funds, they are very focused on the sort of, you know, investing in the next trillion dollar company today, they've had a lot more turnover because that's what happens at big funds, the people who made the investments aren't there. And we have some sort of pretty dysfunctional boards with real companies, but a bunch of people asleep at the wheel. Chamath Palihapitiya: And so we're coming in maybe as quite small owners and not even active board members and like shaking the thing and being like, everybody, you know, there's a real company here. But if we just think we're going to hang out and grow, you know, 10%, 20% and make a little money or lose a little money, this company might be worth nothing. It's time to get serious. And so we're spending the time doing that. SPEAKER_21: And then maybe just a little other sort of thought on liquidity. We have, and maybe this touches on Mike's company that sold last year. I tend to think that if you have an outsider come and make a real serious approach, you should take that very, very, very, very seriously. That, you know, Eric Kippo, my partner, has this philosophy, which is sort of your first offer is probably your best offer. And if somebody really wants you, yes, you should, of course, go run a process and see what else is out there. But there are not all that many moments for companies that are not extraordinary companies to create liquidity. And when opportunities present themselves, don't be dismissive and greedy. SPEAKER_14: All right, we're going to get to Aileen and her response to shaking the old startup cage. But first, we have to do a quick little segment about our dear friends over at Plod. SPEAKER_00: Jason and I are big fans of Plod. They are beautiful little AI note takers that I wear on my wrist. He wears on his lapel. We run tons of notes here at Twist. And to not forget everything, we record it all. If you work here, you're always being recorded. And that means we never forget a darn thing. If you want to be cool like us, you can get a Plod note pen S at plot.ai slash twist. Use the code twist to save 10%. And if you think AI hardware doesn't work, well, bad news. It actually does. Aileen, back to you. SPEAKER_14: I want you on going to startups that are maybe with dysfunctional boards shaking the cage and getting them back on track. SPEAKER_60: I mean, I totally agree with Ben. There are definitely a lot of board members that are kind of MIA or just, I mean, there's been a lot of turnover at firms. And it's hard. SPEAKER_49: You've got orphan companies where, in some cases, CEOs optimize more for valuation in years past than kind of active board members or experienced investors. And a lot of the folks who were newer and had a new checkbook aren't there anymore, which is really disappointing. SPEAKER_59: But, I mean, I think that's hopefully how you also build your reputation as an investor is, like, being there through thick and thin and being there in hard times. You know, that's what it's interesting, actually. After kind of like ZERP and post-ZERP, I definitely feel in competitive situations when we're talking to founders, when they ask to do references, they will ask founders, like, how did they handle a downturn? How did they handle things when things weren't good? Because they know that that's, you know, obviously there's a lot of talk right now about data center financing and whether it's going to fall over and this kind of somewhat circular economy and, like, what's going to trigger something to fall over. And we kind of saw this with .com. And so I think people got a little bit of the jitters. Like, I'm going to try and raise as much as I can right now, which can be, you know, is a double-edged sword. It gives you a big war chest to be able to hire great people and to be able to go for a long time. But going for a long time without actually a feedback loop from the market can also be a negative. SPEAKER_49: We've definitely worked with, and, like, in one case, we have a portfolio called Mutiny that's been in the news quite a bit because they burn the boats. SPEAKER_59: You know, Jelly had a really nice growing product, but it wasn't completely AI native. And they were like, you know, we could continue to milk this and try and tweak it, but it doesn't feel like we're really capturing the moment for customers to really give them an AI native product. And so they basically, like, unfortunately had to cut a lot of the people, went back to the drawing board, built a whole new product suite, and are selling it now. And it's incredible. But I think they feel strongly that they would not have gotten there if they hadn't burned the boats. 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And the links are in the show notes. SPEAKER_112: Now, on the burning the boats front. SPEAKER_73: That was quick. SPEAKER_14: Oh, I know how to type. On the burning boats front, we saw Intercom become FIN and then sell for a pretty quick number. And that was very much a, we are going to start over. We're going to become AI first. Working on, I think their own models as well, if memory serves. Owen said about that. But that was a success. Aileen, how many companies do you think that are pre-AI companies can execute a pivot like that and actually land a plane? SPEAKER_76: Because to me, that sounds incredibly challenging. But I also, I don't want to be a hater and underestimate, you know, founder potential. SPEAKER_115: A lot of it depends on who the customer is and what the problem is that you're solving. So there's some customers where they don't want, like, a completely AI-native product, right? SPEAKER_59: They're not in that trust zone yet where they want everything. And you've got, especially it depends on, like, the customer base and how big it is. SPEAKER_60: But in Mutiny's case, I think it just felt like there's so much opportunity to support sellers in how they prep for, like, you know, whether it's getting a lead and then building the relationship to close that could leverage AI, that they really wanted to take the time to figure out how to make it work. SPEAKER_08: One factor in some of this that I think is interesting, many years ago, I was involved with a company called KeepSafe. And we were doing well, but not set the world on fire well. And one day we all get in a room and we said, you know, maybe we should stop thinking about being growth first and become profit first. And, like, what if we operate this company in the rule of 70s? So if we're at breakeven, we've got to grow 70% a year. If we're growing 40% a year, we've got to have 30% margins. But that's just going to be our immutable rule. And so then what we would do is every month we would say whatever our profit target was, we'd put that much money in the bank. And whatever we had left was what we could run the business on. And it's funny because a couple of weeks ago, I was having lunch at Philip Berner's ranch in Petaluma, who's one of the founders of KeepSafe. And, you know, he's probably made somewhere between $10 and $20 million, maybe more, just dividending out the profits, you know, over the last decade. And so I like to say that growth is a combination of ambition and acceptance. And it's like, you know, you're entitled to burn venture capital money if on the other side of it you create enough growth and category dominance to justify that burn. But if you have no path to doing that, I think a lot of times you're better off accepting the reality that you need to be a profit first company and, you know, make as much profits as you can. And that company, had they not done that, probably wouldn't exist anymore. SPEAKER_31: But now they're, you know, every quarter, you know, we get another dividend check. So I think Floodgate put in like a million and a half bucks, and I think we've gotten more than $10 million of dividends from them. SPEAKER_120: That's a hell of a return. Slow IRR, but lovely dollar amount. SPEAKER_08: And to some degree, that's really what Bending Spoons is doing, right? They're kind of, you know, I like to say that a startup starts at zero to one, and they have to have proof they have an insight about the future. SPEAKER_31: Then it's get product market fit, then it's one to X, then it's grow at a rate that's predictable, that justifies your burn. Then there's profitable growth, and then there's profitable decline. SPEAKER_08: And I think part of my job as a VC is to help the founder locate where they are in that sequence. And where you are in that sequence has a set of laws of gravity and space time, right? If you're in one to X rapid growth mode, for every dollar of burn that you burn, you have to achieve a certain amount of growth to justify that burn, or you can't credibly claim that you're a growth-first company. SPEAKER_121: And so I think that a lot of people are growing not fast enough relative to their burn. SPEAKER_49: Yeah, you know, one thing I think that's important for founders who are listening or watching is, like there was, for enterprise software, this rule where one to X was like triple, triple, triple, double, double, right? That was best in class, right? You'd go one, three, nine, 25, 27, something like that, right? But that's because of what's going on in AI, the bar has really changed. So if you're a founder that wants to raise seed or ARB, you need to know that basically, I think right now it's probably one to five or one to four and a half, depending on what you're doing, and then probably five to 20. So you really have to be growing at them to be able to raise venture capital from the folks who do A's and B's. SPEAKER_59: The growth curve looks very different in 26 and 27 than it has before. SPEAKER_126: So quintuple, quadruple, not triple, triple. I think that's a lot harder. SPEAKER_21: What do you guys think? I agree. I don't think that it is overall a good thing for the ecosystem that we've moved into this sort of – like I think it is preventing capital from flowing into certain kinds of businesses that want to do harder things and that want to enter businesses where the moat is more difficult or where the sales cycle is more difficult. And I think there's sort of – I honestly think one of the big problems is it's forcing money into companies that are solving problems for right now, like problems for the next few months. Chamath Palihapitiya: I see so many companies that are building based on what the models do today, and they're solving a problem that is like a problem that exists for the next 11 days, raising a bunch of money and going and chasing it and getting like very easy come, easy go revenue. SPEAKER_21: And it's – I find it to be very frustrating, and we as a fund have a little bit of a sort of bias to being gluttons for punishment and like liking things that feel a little harder. And the problem is right now when I want to be brave, you know, bravery is maybe not the right word, but when I want to go sort of encourage something really difficult, but if it works, there's an actual moat around that business, I have to do so into the void. I sort of fund that business knowing that I can't take it – there's a very low likelihood that Sand Hill Road is going to be interested in the next round, and that I think there's a big gap right now in where we can go take really interesting, great sort of hard things with teams that don't look like they're out of the central casting for following capital. I assume you're seeing the same thing, but, you know, you guys are in San Francisco and closer to the sun, and, you know, I'm here in New York and, you know, see some of what's going on and feel like, you know, I don't want to say bubble because I do think AI is the most, you know, fabulous, you know, innovation that I've seen in my career. Chamath Palihapitiya: But there's just some, you know, this idea of consensus seed rounds getting done at 50 and 60 and 70 million valuation. SPEAKER_131: I mean, we could go on to the next topic, but, you know, this is why I come in grumpy today, Alex. SPEAKER_133: No, I'm here for, you know, old man Ben, you know, stamping on the ground. SPEAKER_14: Okay, cool. Thank you. Yes, good. Because, well, this is all insane to me. I love this. So Mike says rule of 70. When I was taught this by the guys who founded HubSpot, it was rule of 40, rule of 70. Dear God. Now it's no longer triple, triple, double, double, double. Now it's 5x, 4x. SPEAKER_00: And Ben, you're saying that everyone's trying to solve the problems for this minute. So are we just essentially... SPEAKER_136: Not everybody, but I think that's a general... I'm generalizing. SPEAKER_14: Yeah, yeah, yeah. No, I'm not trying to... I'm just trying to summarize here. So essentially, it seems that only the things that have instant takeoff today are attractive to the multi-stage funds, which is changing what you can invest in. Going back to the top of the show, I didn't think it's going to be that pertinent, but why don't you then raise more money, Ben? SPEAKER_138: I mean, if you're not going to be able to go get Sandhill to take the next round lead, why not do it yourself? Chamath Palihapitiya: I have had some of my LPs ask me that question recently. You know, I think that for me, that has to do a little bit with building... SPEAKER_21: You know, each fund we've raised has been a little bigger than the one before. Our eighth fund was 145. Our ninth fund's 200. Chamath Palihapitiya: We have grown, but, you know, I don't know that I can solve the problem for these businesses if I have a $300 million fund. SPEAKER_21: And I don't... You know, in our bones, we are an early stage group. We are really about talent. That is sort of like what we're built for. It's what we know how to do. It's what we love doing, frankly. I'm jealous of people that manage many billions of dollars because I think that like those fees are probably super sweet. I want to do early stage. I don't suddenly want to be the like series B lead. I think it's a different skill set. SPEAKER_142: Yeah, but I think, Mike, you're famous for saying your fund size is your strategy. SPEAKER_143: Yeah, I guess that's my story and I'm sticking to it. Yeah, by the way, Mike, like you're... SPEAKER_144: That's a huge inspiration for me. And I really... SPEAKER_145: I think it is... I think it's true and it's something that we try to live by here. SPEAKER_147: One of the themes we talk about over and over again on This Week in Startups is making sure you do your chores. I'm no expert on these things. I have some experience. Steven Estes from CLA is an expert. Let's talk about being cash efficient. Tell us about efficiency and what you see in the top tier startups in your practice. SPEAKER_151: We're seeing kind of an interesting trend out there where companies aren't needing to raise quite as much as they had in the past. You really have to be careful as a founder to only take on as much money as you really need. You've got to do the forecast and you've got to do the modeling and you've got to dial it in and get it right. Otherwise, you're going to end up either not raising enough capital to get to where you're going and you're going to have to go get venture debt or go back, have an extender to the round. Or you're going to give up too much of the company because you just didn't recognize how much money you actually needed. SPEAKER_154: Yeah, very important to get this stuff right, folks. And that's really a bummer when startups don't do things in a button-up way, always have a great partner, a good partner to have on this adventure. While things change, my friend Steven over at CLA. SPEAKER_157: So if you want a trusted advisor by your side who will navigate you through taxes, accounting, and everything in between, it's time to take action. Visit claconnect.com slash with you. And don't forget to drop a mention that your boy Jake Al sent you. That's claconnect.com slash with you. Start today. SPEAKER_63: Mike, same question to you. SPEAKER_76: Why don't you just raise more money and solve the problem of backing outlier people and just take on those later rounds yourselves? I'm not sure if you have a different answer than Ben, but I want to get more than one perspective on this point. SPEAKER_08: Yeah, well, so the way, the way, so I do believe your fund size is your strategy. So, you know, and the reason is the power law is real. So to me, your fund size is a commitment to your LPs about what your largest exit will be. So let's suppose that you have a fund and your aspiration is to have a 5X fund. SPEAKER_31: And I believe that what you're really saying is your biggest exit will be 2.5X the size of the fund in terms of exit for profit. So if you have a $100 million fund, your best exit needs to be $250 million if you're going to have a 5X fund. And so then it's just a function of what you own and what you get in at and what you get out at. SPEAKER_08: But I guess in today's world, I don't know if others would agree with this. I'm really seeing two kinds of projects. One is what I would call hot projects. And hot projects are, you know, the multistage firms love them. And they may not necessarily have any momentum at all. It may be somebody peeling out of Anthropic or OpenAI rockstar credentials and a few good white papers and stuff. SPEAKER_31: And what I believe is the non-consensus play for hot deals is the upside's even bigger than you thought it could be. And so it's not that nobody thinks it's exciting. It's that it's even more exciting than you thought it was in spite of the fact that it's exciting. Um, so Anthropic was not done at a cheap price early, but I don't think most people thought it was going to be worth a trillion dollars. Uh, and then, and then there's what I would call weird projects. And those projects aren't even on the radar of the multistage firms ever. Uh, so, you know, my colleague and Miraco invested this company called SmarterDX in 2022, and it exited for a billion dollars. And, uh, you know, that's, that's good living for a seed fund, but I, I don't think it even matters if you're a multistage fund. I don't, I, I don't think even if you had that exit, it's interesting. SPEAKER_08: Uh, and so, um, so I think that there's, there is a different strategy for each type of project, right? If you're going to go after something hot, you've got to work your way in. You've got to build a relationship with a founder. You have to count on the fact that the multistage guys are going to de-risk it financially. And in the weird stuff, I think you've got to be prepared to go it alone or to get enough momentum for its own sake. SPEAKER_31: But you can't count on the Silicon Valley echo chamber bailing you out, right? SPEAKER_164: You've got to, it's got to make it a, it's, it's almost like venture capital in the eighties or something, you know, or the nineties. SPEAKER_125: Yeah. Uh, before we move on, uh, Ben, I think Lair Hippo backed, um, board, the board, the digital board game company, which I quite like. SPEAKER_00: I have a picture here of it. Um, oh wait, no, I'm sorry. That's the original Microsoft surface table. Here it is. SPEAKER_167: Oh, okay. I see what we're doing here. SPEAKER_14: I did think that up before the show and thought I was brilliant. SPEAKER_168: I knew something snarky was coming there. SPEAKER_14: I'm just, I am, I am a big lover, but it is my job literally to sprinkle some, some sprinkles on top of, uh, physical product. SPEAKER_144: Yeah. It's a physical product. It's super cool. It is doing extremely well and people love it. Yeah. I bought one for Christmas. Have you been using a mic? Yeah. Cool. SPEAKER_21: It's, um, it's Bryn Putnam who built mirror, uh, the workout device that she sold to Lululemon. Um, and it's, it's, it's her next business. And, uh, it's a, it's a very, look, you know, I love consumer. I've always loved consumer. I've done a bunch of consumer. I think, uh, you know, so much of consumer over the last few years has just been very incremental. And so even though there was this Microsoft product from a long time ago, I think in general, this, there's a lot of novelty to the way that Bryn is building this and the way that over time, the community will be building their own games and the physical pieces and the creation of new kinds of IP. And I think there's also some big sort of tailwinds to get people and kids off of screens, or at least the screens that we are currently addicted to and move to more collaborative play. And so, um, and by the way, the usage data, which you're, you're always, you know, terrified when you invest in something like this pre-product and it goes out and you start to sell and you're like, is anyone going to actually use it? Or did people click on Instagram ads? The usage data is, is pretty stunning. People use it with SPEAKER_144: extreme regularity and, uh, it's a fun one, but you know, there's still plenty to go. SPEAKER_00: When you combine board the product with the ability of people to now make their own software, which is still a little bit nascent today, we're working on making games with cloud code and so forth. But I can absolutely see in the future, my children, you know, thinking of a game idea or SPEAKER_14: taking pictures and then having that kind of baked into it. So I think it's a really cool company, but Mike was just talking about, you know, stuff that doesn't really resonate on Sandtill. And if SPEAKER_00: I was thinking about a category that's out of favor right now, it would be children's games. You know, I mean, like it's not agentic orchestration for the- SPEAKER_21: USV did the last round there. It's not so wildly out of favor. You know, Mike- SPEAKER_131: Where is USV based? I don't know. I'm not sure. I can't remember. SPEAKER_185: Yeah. Is it, is it, is it, is it on the West Coast or the East Coast? SPEAKER_131: I think there's probably a union square in San Francisco as well. Well, there is, but I mean- SPEAKER_144: It's definitely based in New York. Anyway, I will say that this is the, SPEAKER_21: Bryn is the kind of founder who maybe to Mike's earlier point, Bryn has some of the qualities that I do think are very attractive to the sort of multi-stage Sandhill vibe. And, but, but the product SPEAKER_188: itself is, is definitely, you have to be sort of a creative thinker to, to get your head around it. SPEAKER_187: I'm just glad things like this are getting funded, straight up. Like, I mean, and first of all, SPEAKER_76: I loved the original Microsoft Surface. We had one in the old TechCrunch office, right in the entryway. And it was fantastic. And I was a long-time Surface user. So I just like that some things are a bit early. And then when the technology is a lot better, this is not the size of a couch. It can really meet its mark. All right. Now we were talking earlier about SPEAKER_14: enormous seed rounds. I also prepared some notes on what I'm calling the $100 million Series A round. So a couple of names recently, StarCloud, 170 million Series A, general intuition. I think that was 320, scale cognition, 100 million, Scout AI, 100 million, et cetera. Lots of these companies going on. How should founders think about these insanely large seed and Series A rounds and what they say about the state of the company and its prospects, Aileen? Because I don't even know how to SPEAKER_15: describe them because the dollar amount so does not match the stage as I understand it. I don't even know what to tell people when I read these headlines. Yeah. I mean, I think they're, SPEAKER_191: they're calling it a seed or an A because it's their first institutional round or their second, SPEAKER_49: but it's not a seed or an A in the sense of how much they're raising the valuation, who's going to do the next round and the metrics that people are eventually going to hold you accountable to when you go out again. So if you're raising at 400 or you're raising an eight, you know, you're raising a seed at, I mean, I, yeah, in 2026, I can't, it's of all the years I've been doing this. I have never seen more people who started a business three weeks ago and have decided that they're going to raise a $20 million seed down a hundred pre it's wild. And like Ben said, a lot of them are very tuned to like this point in time. And this point in time, generally every idea, every problem that people are facing has 15 or 20 competitors. And you know that like the ecosystem is evolving so quickly, you don't know what free tools, the hyperscalers or the frontier models are going to give out and wipe you out quickly. And I think when you raise some, and I think people are also planning on spending a lot of it on tokens, which that's also a moving puck where I think the number of models that are coming out that are going to be like the open source models, the open weight models, like they're a lot cheaper and they're getting so much better that I think also token spend, hopefully for startups will go down. So that won't be the reason why you need to raise 20 million bucks. Cause you won't need 10 for tokens. But it just sets you up. If you're at 120 post after your seed, then you, you and your employees and your investors want to fill a markup. So you probably want to be at 200 or 300 for your next round. So you're calling on people who are basically doing 50 to a hundred million dollar round sizes, and they're going to be looking for traction and customers. And I think like what Ben alluded to earlier about revenue quality versus just like everyone trying stuff and the renewals not looking great. And a lot of people falling out because they're trying everything right now. Like you just have to really be on your game and know what you're signing up for when you raise those prices. SPEAKER_76: Yeah. I keep seeing companies doing like agentic security, like giving agents identities and so forth. And I'm like, this is cool, but I think I've lost track of the number of companies that SPEAKER_131: have raised $50 million to do that. Well, a lot of these early rounds though, Alex, this is like, there's, there's king making going on in a way that has never, that I've never seen before or SPEAKER_144: queen making or, or, or, or them making, they making whatever you want. Uh, there, there is, there's makings happening where, you know, like a company gets knighted as the, you know, the one Chamath Palihapitiya: or a big multi-stage, you know, puts in the first check and sort of likes what they're seeing, but it's a competitive category and they, they want to communicate something to the market, which is stay away, watch out. We've got this. And in some categories you have two or three Kings or Queens or whatever, but it doesn't always work. Like, no, no, no, no, no. It was, we are still in the part of the cycle where right now people, we have, we don't have the blowups yet. We don't have the collapses of the companies that have raised the a hundred million dollar series days. So everything only goes up into the right at this moment in time, at some point in the next 12 to 36 months, SPEAKER_21: the rubber meets the road. And we figure out what companies are real and what companies raised SPEAKER_144: hundreds of millions of dollars and don't have anything. And if you're going to have companies that are worth tens of billions of dollars in a year, then you are going to have companies that are worth tens of billions of dollars that also go to zero, which traditionally SPEAKER_205: like wouldn't happen on the speed, you know, it has to happen. Yeah. Yeah. You know, it's, SPEAKER_08: it's interesting. If you look back at the.com days, where did the big exits happen? Everybody remembers Amazon, Google companies like that, but most of the people got really rich in that era are the people who got exited in a window of time at the end of 98 until early to mid 2000. You know, if, if Mark Cuban had raised a hundred million dollars for a series a broadcast.com, we wouldn't know who Mark Cuban is today. Right. And so I think that what a lot of the founders are missing is that great. You can raise a hundred million dollars in your seed round. Nobody that I can find in history has ever had a greater than $10 billion exit raising that much in their seed round. Like the biggest seed round I can find on record with the exit that size is whiz and it was $21 million. And so what happened in the.com era was people raised money at these crazy prices and then everything crashed. And the venture firms are like, okay, I've got to figure out which companies are real and which aren't real. And a lot of these companies that had to give the money back or pretty much had to shut down because there's just no way that even if they executed perfectly that they could ever be what they raise their seed round at. And, and the venture firms are like trying to figure out who the winners are, who to stick with. And so, um, I think that a lot of SPEAKER_31: people lose sight of the fact that you lose an amazing amount of optionality by raising rounds this SPEAKER_08: way. Um, and if your goal is to create generational wealth and you believe we're in a bubble, SPEAKER_31: this is the last thing you would do. You know, you would, you would position yourself to profit SPEAKER_76: in a wide variety of scenarios. People keep throwing the phrase generational wealth around. It feels like it's like a, it's like a tick tock theme. I don't even know why people don't realize that 10 million is generational wealth. You don't need to have 500,000 trillion billion dollars. Anyways, um, alien, you mentioned, you know, raising 20, spending 10 on tokens. That to me implies that the startups that are raising relatively outsized, even series A rounds are doing so not simply because they can, but because they have a relatively high cost basis. So do you think that startups are kind of forced into raising this type of capital early because they have expenses they need to meet, not just humans. Now you also have your token budget, or are they just making a mistake and kind of just getting over their skis too soon? I think it's both. I mean, it's, SPEAKER_213: it's getting better. I think, I mean, if you, uh, chat with your portfolio companies right now, SPEAKER_59: like, I think one of the interesting things is obviously like cloud cowork is amazing and tags is really fascinating, but it's really, and it's smart because it can create lock-in. Right. But a lot of folks know that they need to build layers so that they can switch models. Right. Cause I mean, most of the frontier model CEOs will say like, you don't need to use the best, most expensive model SPEAKER_60: for everything. Right. So you actually have to build things that you can swap things in and out. And meanwhile, the labs are going to try and lock you into using their model as much as, and using their tokens as much as they can. Um, so I think that there is just, SPEAKER_59: what is exciting for investors and founders is like, there's a lot to be built for this new SPEAKER_194: ecosystem of AI. There's a lot of infrastructure. There's a lot of security. I mean, there's a reason why those are hot areas is because we need a lot of new stuff. Yeah. Uh, just to throw some notes on SPEAKER_76: that. Etch just announced that it's raised $800 million for its transformer, specific ASICs, SPEAKER_00: light matters raised 850 DG matrix raised 20 million for solid state transformers, which none of us here ever thought about until like 20 minutes ago. Uh, there are even a number of companies, startups that are working on data center cooling alone. So alien, do you think that those SPEAKER_218: companies fall under the companies for this moment? Yeah. Or my old, my old portfolio company, SPEAKER_59: bloom energy, which I worked on at planner is one of the beneficiaries of like this incredible data center. Cause they need people need power. Yeah. Uh, and so, yeah, there's a whole like, yeah, you may do a map of all the things you need in data center or for AI compute and like memory, SPEAKER_00: like look at Micron's numbers is incredible. Yeah. Go, go read Micron's earnings. I'm telling SPEAKER_14: people just go look at them. It's it it'll, it'll, it'll blow your top. Now, Ben, you're slightly more consumer focused. So how much of this translates over into your world? Um, I mean, I am more consumer SPEAKER_21: focused as a fund. We are probably, you know, 75%. Sure. Uh, I look, I I'm, I'm very excited about consumer right now. I'll be it. Uh, I'm still searching for the sort of like application layer boom on the consumer side that feels really differentiated. We see a bunch of lightweight wrappers that, you know, have a bunch of explanations for why they're not lightweight wrappers that are still lightweight wrappers. Um, and you know, it's, it's obviously unclear what you chat GPT or anthropic or Google or whoever will, you know, where they will sort of extend their products. Um, I, I am very open for business on the consumer side. I would love to find, uh, but, but I, I really to find companies. I really do think though that, uh, building a, you know, another agent to do something that is built on everybody else's infra is, is just like, not that exciting. I, I, I keep getting to not the finish line on those. Yeah. Now, Aileen, you shared this SPEAKER_73: back in May, uh, over on X back to your. Best share of the year, Aileen. Oh, but it wasn't, SPEAKER_228: it wasn't my chart. I think. Well, then I give you credit for, but I love this. SPEAKER_237: Yes. Aileen, uh, for folks who are on the audio version, can you just quickly sportscast SPEAKER_70: what this is? Yeah. It's like, there's this, it's funny. I would love to work with anyone who wants to build like a tech gestalt machine because every year there's like a hot theme, SPEAKER_59: right? So 2013 it was wearables, 2018 it was VR, 2019 it was scooters, but then the best companies that are actually founded in those years never match what the theme of the year is. Um, so like anthropic was when crypto was really hot in web three whiz was when we were talking about future of work. So, um, yeah, you just can't, first of all, like to Ben's point, it takes, it takes, usually takes a long time for a great company to be built. And a lot of these companies for the first three to five years, no one's heard of them. They're not cool. You know, they're kind of baking. Uh, and so you kind of have to have faith and take these, these leaps of, um, these risks on. I, I, we love backing kind of to the earlier point, like we love pedigreed founders. We also love what we call off-Broadway founders, like people who don't have the perfect pedigree. And when you SPEAKER_60: look at the list of the companies who founded, like the founders of a lot of those companies, they are off-Broadway founders. They are not perfect pedigree founders. SPEAKER_133: The founders of Databricks were academics and open source software kids, you know, hard, SPEAKER_231: hardly your, I think in today's world that's considered pedigreed. Okay. But at the time, SPEAKER_14: that was kind of a non-consensus, but I know we've, we've raided academia and now there's like SPEAKER_05: three people left. Yeah. So it's like a whole venture firm strategy is just spending time in SPEAKER_14: university labs. Well, you've sold me on venture at last, Aileen. I volunteered. That sounds like, that sounds like a hell of a good time. Um, so why is the conversation so wrong? And in this case, what are the categories that are hot now that are not going to manifest great companies later on? SPEAKER_00: Because I know you guys place bets, but a lot of founders listened to this and I just, I, if we can give people a way to not go down the wrong path, I think it'd be very helpful. So, so Mike, what do you think is the most overhyped thing to build today? Apart from agents, of course, um, that founders probably should stay away from. Oh boy. Um, yeah, it's, it's a tough SPEAKER_244: one for me to answer because I root for all of them, you know, uh, uh, you know, I think that, SPEAKER_08: that, um, I would say that, uh, agents that improve productivity and the function of agentic workflows, I would stay away from. So I think that you've got to have something, uh, that's attached to it that creates some type of, uh, path to network effects or some type of, um, uh, cumulative, uh, increasing returns power. So I would stay away from, uh, any type of AI productivity or workflows that doesn't embody some type of increasing returns mechanism at the core design. And, and most of them, SPEAKER_31: unfortunately don't, right. You, you look at it and you say, that's awesome. I can totally see why I would want that, but I don't know why Sam Altman's not going to have that in his next demo. Um, SPEAKER_76: so that's, that, that's what I would look for. I, I just realized that I, I made my agentic trust point and, uh, Aileen's company, uh, firm is back to Drata. So. Yeah. Uh, do you want to, do you want to tell people why my slander was incorrect? Sorry. Well, you're, I know, SPEAKER_70: I was going to say, well, actually like, I mean, I think that's an example of a company that SPEAKER_59: was started before, um, LMS, but it's not that old of a company. It's grown really quickly, Drata and, but trust is really important. So I think when you have, when you've got mid-market and enterprise, um, relationships and you are helping them with compliance and SPEAKER_60: trust and visibility when, because so many companies are interconnected and you need to, if you're going to poke a hole in some and pull data in or out of a company, you need to make sure that they're doing it securely. And, um, they've got the right business processes in place. Like that's not a burn the boats. Whoops. We're replacing everything completely tomorrow because you need to have, these are relationships where I think, um, consistency and trust is really important, but Drata obviously is going to be helping people monitor agents and the trustworthiness of agents. So that's kind of more of an evolution of the relationships they have with customers and what SPEAKER_249: their customers want. So we're really happy to see where it's, that's more of an evolution than a burn the boat situation. And I think it's a smart one to prevent Ben from thinking I'm only picking on SPEAKER_251: him alien. Uh, tell me why that the either major AI labs themselves or the current owners of enterprise SPEAKER_76: workflows won't do that themselves and consume what Drata is trying to build. I mean, I think like, SPEAKER_213: I don't know, Mike is so good analogies. He'd be kind of like, that's like letting the fox watch the SPEAKER_59: hen house. Is that the analogy? Like you want to have a, you want to have a trusted third party, um, that isn't your current vendor. That's trying to use all your data. Yeah. So, so I'm, it's funny SPEAKER_08: because I've been working, doing a lot of thesis work lately and Drata was one of the companies that I kind of regret missing, uh, based on some of the work that I've been doing. It's only a SPEAKER_262: $2 billion valuation. Get your money in now. So the way, the way I've internalized it is that, um, SPEAKER_08: AI creates abundance in terms of work products. It, it, it creates generative AI is generative, but what people are going to want to start having is what I would call acceptance AI. So like, like for example, when you have financials, you have an audit firm, audit your financials. It's, it's not enough for you to just say, I'm really good at doing my financials. You, you have to have some trusted third party certify, uh, and that, that, that, that credible neutrality is important. And I think what's going to happen is there's going to be a lot of AI generated SPEAKER_31: slop across the board. And, uh, it's, it's no longer going to be just the work that gets outputted. It's going to be the work that counts. It's going to be the work that is, uh, that there's a consensus mechanism for validating. And, uh, quite often you're not going to want to trust, you know, the, the frontier labs to do that. You're going to want a credibly neutral third party. Uh, so I, I agree with Aileen. It reminds me a little bit of why we invested in Nocta back in the day. We thought that, uh, you know, identity management should have a neutral, trusted, uh, person, right? Yeah. So like to me, if slop is abundant, then you start to ask, well, what's scarce. And I think what's scarce is correctness and proof of correctness. And if you can, if, if you can be seen as a credibly neutral network effects, scalable provider of that, I think that that's, uh, in many ways, that to me is where the application layer is going SPEAKER_00: to come alive in a lot of these. So we're talking a lot about costs here, controlling them and kind of owning, um, your own data and alpha. A lot of people in the last couple of weeks have been talking about moving to open weight models, especially GLM 5.2 seems to be quite hot. And this is due to the government essentially precluding us from accessing the latest models SPEAKER_14: from both anthropic and open AI lately. Can we just kind of look through the headlines a little bit and tell me how prevalent is it that startups are actually either rolling their own models or simply turning to existing open weight models to either reduce costs or to ensure that their data SPEAKER_48: doesn't go to training anthropic into building what they've already put together. And alien, SPEAKER_268: why we start with you and then we'll go to Ben. I was just thinking, I keep thinking that GL, SPEAKER_59: GL one was like the, was the new, is the new GLP. Like, you know, like this, the gestalt of this year is like the GLP one and maybe like we had this deep seek moment and now we have this GLM moment, right? Which is, it was, it's quite good. Like a lot of our portfolios have been playing with it and they're saying that they're getting equivalent results for a fraction of the cost. And I think that's why they are all getting ready if they're not like to be model agnostic and to not spend as much time fine tuning. Cause you could spend a lot of time and money fine tuning something. And how long SPEAKER_115: is that going to buy you a month? It's not a great use of time and money because stuff is moving so SPEAKER_76: fast. So unpack that for us. So essentially, if you train, if you fine tune Kimmy K 2.5 as cursor did to make composer two and 2.5, by the time you're done with that, they'll have Kimmy K 2.6 and then 2.7. So you're always, you're chasing a ball that's going faster in front of you. Okay. That's almost a spiriting alien, because I would love it if founders were able to take the best from the open SPEAKER_14: way open source world and then really turn it into a weapon they can take to market. But it sounds like you have to kind of take what they offer, just the whole cloth. I don't know. Others should SPEAKER_59: weigh in here, but from what we're hearing from portfolio companies are not, I think some people considered it and they started doing it and they're like, wait, this is not a great use of our time and money. There's a lot of other ways we can benefit customers. Ben, jump in here from the firm SPEAKER_14: enterprise perspective. And also if you have any consumer notes on this particular topic, I would love Chamath Palihapitiya: to hear them. I don't know that I have consumer specific notes. I think in general, SPEAKER_21: in the, everybody is building everything multimodal and has to out of the box, be able to say, I am not beholden to any one model. And everyone's long-term business model is predicated on token prices going down and down and down and down and down. And so I think, you know, I mean, Chamath Palihapitiya: generalized models are going to get better and better. The fact that this conversation is happening SPEAKER_21: is actually though, like the flip of it is it's why Anthropic and open AI and Google are so scary, because they are aware of the quality of open source and the fact that they're not going to be able to just go and endlessly charge more and more and more, and that they're going to move further in the application layer. And like, they're going to do it too, which makes the application layer right now, just like a finicky, weird space to invest in, because it's not clear where infra and application layer sort of bump into each other. And, you know, I do think though, we will move to, and actually a colleague of mine wrote an interesting little sort of sub stack yesterday. Yeah, I wrote it. Chamath Palihapitiya: I thought it was well-written. I was, I gave him a hug. You're talking about the end of decisions by SPEAKER_21: Maurice Rousseau. And just the idea that we're sort of real high level decisions are starting to be more possible with AI. And, you know, I don't know exactly, like, I think that's where we end up with like the most expensive models, having a real expansive market for a kind of decision-making that I don't know is really, that we're quite yet relying on AI for. To summarize what we're SPEAKER_37: talking about here. And if you're watching this later on, it'll be in the show notes, a link to SPEAKER_00: the post, the end of decisions. But what Maurice argues is that we've seen the effect of essentially computation in fields like chess and most recently in poker. If you play cards, you know about GTO and so SPEAKER_14: forth. And he says that AI is quote, the first general purpose reasoning layer that can start to function as a solver for domains that have historically been too qualitative for software. Now, if that's true, Ben, then to me, the actual incremental or marginal intelligence gain you can SPEAKER_76: get from a new frontier model version is incredibly valuable because if you can literally have the brain that runs your entire business be smarter, that's quite useful. That's quite useful. And that's why SPEAKER_21: I think the like, that's where that business model makes more sense than doing the, you know, checking my inbox and preparing some drafts for me and, you know, whatever. SPEAKER_08: Yeah. The way I've kind of internalized it. And I, I really owe this thinking to my partner, Ann Mira Co. So Ann's been doing all this work with what companies that she calls AI pilled and, um, an AI pilled company basically thinks in terms of what, what processes, what decisions, what, uh, mechanisms do they have that define competitive advantage that can be thought of as an SPEAKER_31: ever improving compounding loop. Uh, for that, you want to use the best models and you're, you're using those to gather customer feedback, come up with new product ideas, uh, AB tests, different things. Uh, SPEAKER_08: you want the most intelligent models possible that I think is different from what goes in the bill of materials of the product you ship. And so sometimes, you know, you can, you can get by with not the very SPEAKER_31: best model for certain func, you know, sorting email or like, you know, performing certain functions SPEAKER_08: within a product. And so what I'm finding that once people create new knowledge with the frontier models, they capture and transfer that knowledge with the cheaper models. Um, and so it's, it's kind of like, SPEAKER_31: uh, how do you, how do you turn a deep work discovery into a checklist manifesto deliverable? Uh, and, and, you know, you, you, you progress down the ladder of model, uh, expense as you do that. SPEAKER_251: Do you think most startups are capable of building the routing mechanism and collecting the necessary SPEAKER_76: context to actually enact something like that? Or is this only the companies that are the most AI pilled, no one's sleeping, everyone looks frazzled, they've got Alex carp hair going on and they're just wizards, you know, at the top of the tower. SPEAKER_08: Well, I think when you're an AI pilled company, you're not, you're, you don't mind spending money on the frontier models because you're, you're, you're token maxing as a person or as a C level SPEAKER_31: manager or as a, as a team, uh, to me, that's a separate issue from, you know, I'm shipping an AI travel agent as a consumer app. And I want to know what aspects of that travel agent need the frontier models versus what aspects of that, uh, can be, uh, adequately solved, right. With open source models. And I think that that's where, um, I think that's where the open source models SPEAKER_208: really come in. SPEAKER_13: And there'll be a bunch of interesting companies helping with routing and evals. And, you know, SPEAKER_21: I don't know that, I don't know that, that companies will have to build that infrastructure SPEAKER_145: themselves versus buy that infrastructure and focus on like their core value prop. SPEAKER_187: Then what are, what are they owning? If they don't own the routing, they didn't build the model. They're not doing the compute. They don't have the customer data. Then what the are they for? SPEAKER_293: Well, hopefully they have the customer data. SPEAKER_297: Yeah, they better have the customer data. SPEAKER_00: So they're just, they're just a bucket of data that isn't even theirs and they're just doing whiz bang stuff with it. And that's the whole jam. That does not sound defensible. That sounds like this is why the job is hard right now, dude. SPEAKER_293: Okay. We're looking at so much non-defensible stuff every day that by the way, it then goes and gets done at 50 by someone who looks pretty smart, but like, let's just take an example, SPEAKER_08: right? Like a applied intuition, you know, they're, um, they have a very differentiated product and they're doing very well, but they, they're AI pilled in the sense that they've created a real time performance feedback system where, you know, they, they can get input about, uh, which managers are most effective and what's working best and things like that. And they can, they can implement SPEAKER_31: these systems at enormously fine grain detail, uh, that you could have never imagined doing in the past. And so, um, so they're not, they're not necessarily AI pilled in the sense that they're doing all this to make their end products different, but the, but they're the way they do business and compete is fundamentally impacted by it because they're, they're embedding AI into the, just the lifeblood of how they force multiply every employee. Have you seen, um, bedrock robotics? SPEAKER_307: No, I haven't. Well, I've heard of them, but I haven't spent time there. SPEAKER_63: We had them on the show the other week. They're doing something kind of related to this. And I SPEAKER_00: really love them because what they're doing does seem defensible because they're going to a very specific part of the world where there's no other companies, maybe applied intuition and they're building essentially Waymo for diggers. And it's a great idea. What an enormous industry that no one SPEAKER_14: cares about because no one in ventures ever held a shovel in their life or startups, you know, tech people. Um, so I think it makes, it makes a lot of good sense now. Okay. Um, we're going a little bit long, so I want to do a couple of final questions for us and Mike, we're going to start with you and we're going to go around, uh, give the Trump administration a grade on how it handled mythos and fable. And, uh, do you think that major AI labs have been actually harmed in the last couple SPEAKER_08: of weeks or do you think this will blow over? It's hard for me to grade the, the Trump administration SPEAKER_31: because I just don't know all the things behind the scenes. And so, um, I'm reluctant to, I'm, I, uh, I do get nervous nervous about, um, these frontier models are so important now that they've got the attention of the government and that's always a very mixed blessing. And so I, I, I get nervous about the government sort of backdooring its way into regulating AI in the way that I was afraid that the Biden administration was going to do. And, um, I think that would be very bad in terms of our competitive posture with China. So I, I do, I do hope that we can resolve this, but I, it's hard for me to give a grade because I think in some ways it is a work in progress. And I don't, I don't think that the hyperscalers have done themselves any favors in the discussion either. And so I think this is an Amazon, but it was definitely Amazon. I think, unfortunately, this is an example of us muddling through a situation where you're seeing the sausage be made in real time. And it's hard to, SPEAKER_208: it's hard to say that there's an optimal strategy, you know, I don't think I can say it better than SPEAKER_60: Mike. I mean, it's hard to know, obviously we're not behind closed doors. We don't know what those SPEAKER_59: guys know about what can be done with the models. Uh, and you know, there's, um, yeah, there's, there's a lot of, uh, history here, right. About like whether it was developing nuclear, uh, weapons and the scientists who were building them having concerns and wanting to talk to people about what should we do about this? Should we build this? Should we not build it right there? So we, we obviously want the United States to, to maintain its edge, but we also have to be prepared for, there's a lot of nefarious actors who can do a lot of bad things. And a lot of our companies, SPEAKER_60: both our, our federal institutions and companies are not ready for the fact that, you know, basically we can be trying to hack into systems 24 seven with agents. SPEAKER_76: Yeah. The, the, the struggle that I have with that, and thank you both for answering that with such, uh, clarity and honesty is that the rest of the world isn't stopping. And so unlike the Manhattan project, when we were very much ahead of the Soviets, of the Germans, um, China's really banging SPEAKER_00: on. I mean, we all saw the GLN 5.2 headline about how they think that it's going to be roughly commensurate with maybe fable, maybe mythos, you know, I want to do you next. Your SPEAKER_319: question is very simple. Um, how's crunch base doing? I think great. We love crunch base. We're SPEAKER_309: proud of more. I own a lot of shares of crunch base. So tell me about how it's doing. SPEAKER_213: I'm not, they have raised it quite a few rounds and we were this, we were early investors. So I SPEAKER_59: am not as close to the latest and greatest, but I think like you were saying before, having data is really important. Having proprietary data is really important. Crunch, a lot of proprietary data and private and a lot of private company data, which is, as you know, like it's, it's very valuable. A lot of VCs will use the models to ask for competitive intelligence and information, SPEAKER_60: but private company data is one of the hardest things to find out about. SPEAKER_00: I'm really hoping that comes good. And that way my children can eventually, um, go to school where I went to school. It'll be good. All right, Ben, uh, to round us up here, SPEAKER_14: uh, for you, I'm curious what you think we should do at the startup level, the venture level, the technology industry level, and maybe even the government level to ameliorate SPEAKER_00: what I think we can all see as rising discontent amongst the populace, uh, against AI. And this is often seen in data center protests and so forth, but what are some proactive steps that the tech SPEAKER_76: industry can do to get on the right side of public opinion before this becomes an electoral issue? SPEAKER_323: My question is so much harder than me. This is, this is like a setup. I'm like, SPEAKER_326: I can't believe that you just laid that on me. It's like you're being punished. SPEAKER_11: Like I came here, I was trying to be nice. Well, the cool thing is about me is that I don't want your money, so I don't have to be nice. Okay, great. Cool. So everyone else has to kiss your ass. SPEAKER_21: Look, that is a, that is a great question to which I do not have a great answer. I, I think that, uh, I am always amazed by how negatively AI is viewed by people that don't work around this business. Like friends that I have that are one or two degrees removed are generally terrified. And I think, think of, by the way, there's also this narrative that you're somehow, like, I think people actually think anthropic is like pretty good, but open AI is like totally the, like, you know, the empire in star Wars or something. And, uh, I don't, you know how, Chamath Palihapitiya: how these stories get told. I, I think it's a, I think it's a big issue, maybe to touch on the, the question that, that the other two answered, I don't, it's, I don't trust our government to know SPEAKER_21: how to monitor this and to, to sit over and to, and to figure out what, how we should or shouldn't Chamath Palihapitiya: use AI models or what, or like what the rule should be at the same time. We're in a, like, we're in a cold war and have been for a while. And, you know, even though it's not called that, SPEAKER_21: and like, this is national security, but against what's best for jobs and the economy. I mean, Chamath Palihapitiya: the, the wealth gap is only getting worse by the minute in a way that is like, I don't know how this SPEAKER_21: ends anything other than terribly. It is, we're, we're set up in a, in a really unfair, awful way right now. And this is, uh, and AI is, is not going to make this better in, in any short or medium SPEAKER_251: term. Yeah. And, uh, if you're on the video version, I just pulled up a chart from our dear friends over at Fred, which shows the, uh, the share of labor comp as a percentage of GDP. And if SPEAKER_76: you go back to the fifties, the era that people like to kind of pine for, uh, fairly or not, it was up in the high sixties and it's fallen down very sharply lately, all day down to about 57, which I think is really the root of a lot of discontent. And I don't have a solution either, but I think it would also be incredibly sad if we ended up shooting our own feet or tying our own shoelaces and preventing a lot of future economic gains, because we couldn't figure out a way to share the pie a bit more effectively. Now that just seems to be a, a non GDP, a creative approach, SPEAKER_144: but you guys are not, by the way, maybe, but, but like going in, you know, some of these, SPEAKER_21: you know, I'm not in California, but the billionaire tax and some of these sort of, you know, very, uh, brute force measures feel like, you know, at best band-aids or, uh, punishments, they, that does not feel like the solution to figuring out how we fix this problem. SPEAKER_76: No, because everyone's going to leave. I'm already talking to founders who live in Nevada just across the border because they want to get away from the tax. SPEAKER_08: It's interesting. Cause like, when you think about it right now, um, if you're a free market capitalist wanting to make a pro common sense argument for it, you have no home, you know, the, the left is becoming Democrat socialists and the right is MAGA and saying we hate immigrants. And so, you know, like you can't even make a credible case for why AI is good because the, the, the people driving the discussion don't want to hear it from both ends. And so that, that part of it really bugs me is that SPEAKER_31: there's no, there, there's no natural home for the adult in the room conversations about what the SPEAKER_143: right answer is. Well, there shouldn't be no party for it. Uh, and candidates for it at, uh, SPEAKER_35: you know, like, I don't let's, let's see where we're getting to. Although Ben, what you were saying SPEAKER_59: about, I don't know if I, it's not about the trust or the effectiveness of the government, but I, I certainly wish looking back that we had had more regulation of social media and that we have a SPEAKER_115: whole generation of kids that have been so negatively impacted by the fact that there was no oversight SPEAKER_322: whatsoever for social media. And obviously the ramifications from a security perspective are so much more grave with AI. If we weren't able to keep people safe. It's a fabulous point. It's a fabulous Chamath Palihapitiya: point. And I, I, at having young kids, you know, we've been left holding the bag to try and, you SPEAKER_21: know, make them the only kid in the grade without access to Snapchat or something to punish them for the fact that nobody got in front of us. Yeah. I'm not looking forward to those days. SPEAKER_352: I literally had a question in my fun section at the bottom of our notes today. That was how are SPEAKER_76: you teaching your kids to thrive in life and the post intelligence era? And I wrote that as a joke to myself, but I really meant the post AI era, but I think post intelligence actually may kind of better encompass. One thing I'm really concerned about is that a lot of people just can't read and can't do math. And I don't think that giving people during their learning years, access to tools as powerful as AI is going to encourage them in a lot of cases. And I don't think parents know what the hell they're doing either. And now that I have kids that can reach for things, I see how they react to screens and it's made me rethink my entire relationship with technology, but here's some good news. Technology historically has made things better. And I think it's going to keep doing that even though there will be some bumps in the road. I'm a long-term optimist and I think that this is all going to end up being very good. I just hope we don't throw a couple generations of kids into the ma as we get to that point. This is not where I thought the show was SPEAKER_14: going to end. I'm not going to lie. Maybe I should have shaken up how we do things, but guys, an absolute real treat today to have you on to talk about all this stuff. Just before we go, SPEAKER_00: where can people find you online? And is there a category your firm is looking to invest in? And SPEAKER_31: Mike, let's start with you. Yeah, I guess you could find me on X at M2JR. And then our website is www.floodgate.com. And basically I'm investing in companies that complement the abundance of generative AI. I call it acceptance AI, but it's the companies that ensure the correctness of the work rather than just generating more stuff. And so that's what I'm looking for. SPEAKER_363: All right. Aileen. I'm Aileen Lee on X and also on LinkedIn and we're cowboy.vc. SPEAKER_60: And we're generalists. Like these guys, we've been doing this for a while. So some of our best investments have been things that we never would have had on kind of like our shopping list. It's really what founders have insight about. And so open for business. And Ben, take us on. Chamath Palihapitiya: Yeah. As you mentioned earlier, I'm not very active on Twitter, but I'm Ben Jlierer. And I use LinkedIn a little bit more, but not a ton. And we're at LiererHippo.com. SPEAKER_179: But probably LinkedIn is the best place. And like Aileen, we are generalists. We're looking for SPEAKER_319: great people early. Yep. If you guys are doing the investing, I think the future will be okay. Thanks all for coming on. This has been Twists. My name is Alex. We'll see you all next time.