Why Data Is the Next $1 Trillion Market

This Week In Startups is made possible by: Digital Ocean - do.co/twist Agree.com - agree.com Every.io - every.io. Today's show: How many startups matter in tech? Fewer than you think. That's why venture capitalists are tripping over themselves to get onto their cap tables, no matter the cost. Why? Footwork's Nikhil Basu Trivedi argues that the Valley has never been more "power-law-pilled" than it is today. Basu Trivedi joined Cendana Capital's Michael Kim and TWiST's Alex Wilhelm to go deep on secondary markets, the state of startup M&A, why the SaaSpocalypse may be temporary, and what could trigger a retrenchment of the AI trade. It's Wednesday, so it's time for our venture capital roundtable to go deep on how VCs are investing today, and where on the horizon they have their eyes fixed! Guest links: Nikhil Basu Trivedi https://x.com/nbt Footwork https://www.footwork.vc/ Michael Kim https://x.com/MKRocks Cendana Capital https://www.cendanacapital.com/ Show links: The USVC-Anduril blowup https://x.com/ankurnagpal/status/2072701195714531398 Kline Hill Cendana Partners https://www.secondariesinvestor.com/kline-hill-and-cendana-raise-400m-for-second-vc-secondaries-fund/ GPTZero's exit https://gptzero.me/news/preserving-whats-human/ Salesforce buys Fin https://www.salesforce.com/news/press-releases/2026/06/15/salesforce-signs-definitive-agreement-to-acquire-fin/ Vercel buys Better Auth https://vercel.com/blog/vercel-acquires-better-auth Figma buys Bud https://techcrunch.com/2026/07/07/figma-acquires-team-behind-a-vibe-coding-app/ Protoge https://withprotege.ai/ Windborne https://windbornesystems.com/ Etched https://www.etched.com/ Lovable's reported raise https://sifted.eu/articles/lovable-300m-13-2bn-valuation Josh Browder https://x.com/Joshuabrowder Timestamps: 0:00 Introduction: Nikhil Basu Trivedi (Footwork) & Michael Kim (Cendana Capital) 1:59 The Anduril vs. USVC secondary market blowup 4:08 Why Silicon Valley is 'power-law-pilled' 8:23 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at https://Plaud.ai/twist and use code TWIST for 10% off! 9:37 Information asymmetry in the secondary markets 9:45 Every.io — For all of your incorporation, banking, payroll, benefits, accounting, taxes or other back-office administration needs, visit https://every.io 15:02 Is SPV fraud smoke or fire? 16:32 Superhuman acquires GPTZero 19:54 Agree.com - Stop chasing invoices and automate your entire contract-to-cash stack. Go to https://agree.com and tell them Jason sent you to get 50% off for life! 21:10 The M&A wave 27:19 The SaaSpocalypse debate 29:59 DigitalOcean - Head to https://do.co/twist to start building on DigitalOcean's AI-Native Cloud today — and cut your AI workload costs by up to 50%. 30:44 Data's moment in the energy → compute → data loop 35:01 Where will AI value accrue? 40:04 What could cause an AI correction? 42:17 Why some companies are "too big to miss" 46:23 China's possible open-weight model ban 53:28 Young founders: Etched, Thiel Fellows, Z Fellows, Neo 55:33 Portfolio spotlight: WindBorne's weather balloons and data moat 58:47 Michael's favorite fund manager: Josh Browder Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp Follow Lon: X: https://x.com/lons Follow Alex: X: https://x.com/alex LinkedIn: ⁠https://www.linkedin.com/in/alexwilhelm Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis Check out all our partner offers: https://partners.launch.co/ Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland Check out Jason's suite of newsletters: https://substack.com/@calacanis Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  Hey everybody. Welcome back to Twist. This is Alex and it's Wednesday, July 8th, and that means it's time for yet another venture capital roundtable. Today, we are going to dig into how exposed American startups are to a possible ban on open model exports from China, secondary markets and their needed fixes, startup M&A, and why the AI conversation has recentered around the value of data and more. To help me understand all of this, I brought a couple of friends. This week in startups is brought to you by Digital Ocean. Want to see what building on a true AI native platform looks like? Head to do.co/twist to start building on Digital Ocean's AI native cloud today and cut your AI workload costs by up to 50%. Agree.com. Stop chasing invoices and automate

• 0:44Speaker 00

  your entire contract to cash stack. Go to agree.com and tell them Jason sent you to get 50% off for life. And every.io for all your incorporation, banking, payroll, benefits, accounting, taxes, and other back office administration needs. Visit every.io. In one corner, we have Mr. Nikhil Basu Trivedi of Footwork. Last fund was $225 million. He's a backer of companies like GPT-0 and Winborn. Nikhil, hey, glad you're here.

• 1:14Speaker 01

  Great to be here, Alex, and great to be with you, Michael, as well.

• 1:16Speaker 00

  Speaking of which, we also have Michael Kim of Cendana Capital, a fund of funds investing LP capital into early-stage venture funds. It also runs a secondaries fund and a co-investment fund for Series B startups and later. Michael, welcome to the show. Great to see you guys. Thanks for having me on. So I'm glad we have we have both of you because we have the traditional VC perspective, and then we also have kind of the LP side of things. And the biggest points of conversation, or contention, really, I think in venture circles for the last week may have been the blow up between USVC, the angelist-aligned, open-ish venture fund, and also Anduril, the well-known late-stage American dynamism defense company. Essentially catching people

• 1:58Speaker 00

  up who don't know, USVC claimed they purchased exposure essentially to Anduril at its Series H price. And then Mr. Grimm, a co-founder of Anduril, said, no, you didn't. And there was a big blow up on Twitter. They're trying to figure out how this all went down. The gist, gentlemen, as far as I can tell, is that people are figuring out that public markets had reasons for some of their rules about transparency, disclosures and so forth. And secondary markets are still a bit like the Wild West. At the same time, aren't they supposed to resolve the liquidity issues we've seen in venture recently? So first of all, Michael, what was your take on the back and forth mess? And also, was anyone in the wrong per se? Or is this just kind of a case of everyone's trying to do their best and ended up at cross purposes?

• 2:38Speaker 02

  Yeah, I think it's more of that. And you know, what we see often is the playbook where fund managers have access to an interesting asset. They'll create an SPV and they actually use that to entice LPs to actually make a commitment to their fund. So, you know, that's been going on for a while. The issue with SPVs, of course, is the providence of whether they actually have the shares. And then when you start stacking multiple layers, you know, most investors don't do the diligence to ensure that each layer is legitimate. And that's where the trouble can start.

• 3:14Speaker 00

  So when you say that some firm managers are using SPVs as a way to get LPs to invest in their funds, are you essentially saying they're putting together one-off deals to get, I don't know, relationships with LPs and then using those to later raise a traditional fund?

• 3:28Speaker 02

  Yeah, exactly. They might be raising a fund right now and, you know, in their prior fund, they might have a very interesting asset, a consensus deal that everybody wants to get into. They might have some prorata in it. They might create an SPV and say, hey, LP, if you come into this SPV, you know, you can come into our fund. So, you know, that's a dynamic that I think a lot of emerging managers use.

• 3:52Speaker 00

  Nikhil, I've never heard of that particular method before. Is that common? Should I be, am I behind on this?

• 3:58Speaker 01

  I think what's happened is a few factors that lead up to the situation between Anduril and USVC. So let me try to unpack a few of these. The first is that Our industry is more power law pilled, more power law obsessed than ever before. And so there's just a small handful of companies that,

• 4:21Speaker 01

  you know, uh, GPs and LPs wanna be a part of. I've heard from some LPs, it's a hit list of 10 companies. I've heard from others, it's 20. I've heard from some, it's actually just six.

• 4:34Speaker 01

  But when you have that obsession over a small handful of companies,

• 4:39Speaker 01

  the, the sort of downstream effect is that, you know, people are, are sort of tripping over themselves to invest in those and find creative ways to invest in those and be a part of them in, in some manner. And so to Michael's point, like one of the methods is I have access to, you know, a couple of those companies in that, in that small basket. And, um, and that's a mechanism for me to get potentially a fund going by enticing LPs. And so, uh, we have definitely heard about this, but it is for a very small set of companies such as Anthropic, OpenAI, uh, Android, and again, may, maybe like 10 others, uh, that this phenomenon is occurring. Um, and then the other sort of

• 5:22Speaker 01

  factors that lead into this are, you know, companies wanna stay private for longer. And so,

• 5:29Speaker 01

  you know, you have to find creative ways to be part of these companies in the private markets versus them just going public. Uh, another is the founders want as much cap table control as possible. Um, and so unfortunately, these factors don't fit perfectly together, right? They're at odds. And hence why you get dynamics such as what's unfolded between, between Android and, and, and Angelus.

• 5:48Speaker 00

  Okay. So here's the problem I, I see with that because if you're going to stay private essentially forever, and I was just talking to, um, the CEO of Hippocratic AI for our AI show the other day about this, and he was like, why would I ever go public? Private markets are super deep and I wanna have all this control and not deal with the headaches of being public, I guess, fair enough. But if you also then ban or preclude secondary activity to provide liquidity to your investors, you end up essentially locking up people's capital, what feels like forever or only Michael at the whim of the CEO. CEO, which seems like a pretty difficult place to put capital under a stewardship model. Because if you can't guarantee you can get it out, then what are you actually buying other than a stock of monopoly money?

• 6:30Speaker 02

  Yeah, I mean, I think if you're going to be buying into one of the six companies that Nikhil is talking about, you have to have some confidence that ultimately down the road, you can actually get liquidity yourself. And so, you know, if you take Stripe as an example, they have regular tender offers. If you take SpaceX, and that's probably the best example, historically, they've had regular tender offers. And so that effectively is the, you know, a public market for a private company. And I think that that dynamic, that motion is is a lot better understood now compared to say 10 years ago. And it's exactly as Nikhil said, companies are staying private longer.

• 7:12Speaker 02

  And so, you know, I think the CEO founder has the understanding that, you know, you've got to provide some liquidity to your people. And, you know, it's great that that's happening. The other great thing is that, you know, secondaries used to be almost shameful. It was almost embarrassing.

• 7:31Speaker 00

  A dirty word. Yes. Why would you do that?

• 7:33Speaker 02

  And now it's a well, well used tool in the toolbox. And I think, you know, obviously, part of that is because of the dearth of distributions over the past few years. We're going to be entering in a new phase where there is going to be a lot of distributions, you know, largely from SpaceX, OpenAI, and Anthropic, probably Databricks. But, you know, we can talk about this, but those, the beneficiaries of those distributions are a handful of groups, a handful of VC firms, a handful of LPs. So it's also going to be the case of have and have nots in the LP world.

• 8:05Speaker 00

  Back to the point that Nikhil said about being power law pill. I mean, this also applies to exactly what we're talking about here. I laughed at the Databricks comment because having spoken to Ali Godzey over the years, I'm nauseam about when he will finally list and being told forever, no, I've given up on that company. I don't think they're ever going to list. I think they're going to be the next Stripe and just stay private forever. We're going to get back to information rights and transparency in the secondary markets in a second, but first, we're going to pay the piper. Dear friends, we here at Twist are big fans of the Plaid pen. We've talked about it on the show endlessly. Jason's an enormous fan. We wear them all the time as our note-taking devices. If you are someone who creates a lot of information, goes to a lot of meetings, runs a company, has a family to organize, keeping track of what's going on is incredibly useful and important.

• 8:46Speaker 00

  We recommend the Plaid Note Pen S. And if you want to get one for yourself, you can go to plaud.ai/twist, P-L-A-U-D dot A-I slash twist, use the code TWIST, save 10%. Be cool like Jason or like myself and therefore never having my wife nag me about things that I've forgotten. It's aces. So on the information point, you guys talked about how the markets are getting a bit better, much more than they were 10 years ago. But one thing that Matt Grimm raised, the end roll guy who was mad, was that a lot of these investors simply don't have access to any information about how these companies are performing. And so to me, Michael, the point that we now have more professional or, you know, maybe just more liquid secondary markets

• 9:25Speaker 00

  doesn't solve the information problem and therefore puts a lot of other people that want to get access to these companies at a material disadvantage. And that just doesn't seem like a good long-term solution to the lack of IPO problem. To me, it just seems very uneven. And so I'm curious, like, is that a reasonable perspective? Because you have a secondary fund, so you're on the buy side of this at times.

• 9:45Jason Calacanis?

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• 10:29Jason Calacanis?

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• 10:40Speaker 02

  Yeah, I mean, the asymmetry of information is certainly the dynamic that secondary funds, you know, I wouldn't say prey on, but take advantage of. And, you know, it could go both ways. You know, someone who's selling may accept a 50% discount because they know that company's actually probably worth a lot less. Whereas the buyer, you know, the secondary firm thinks that they have the information arbitrage that they they have a strong conviction, high conviction that the company is actually going to be worth a lot more. So that that's actually the the the price discovery and how transactions get done. You know, I wouldn't

• 11:19Speaker 02

  say necessarily that either side is right more often than not, but secondary funds do perform pretty well. They're never going to be a five to 10x kind of return, but could they deliver a, you know, a solid two, two and a half, three times? Yes. And we've seen that time and again, over the past 10, 15 years.

• 11:41Speaker 00

  All right. So Nikhil, on the point you made about there only being so many companies that are of note, it's 10, 20 or six, whatever it is, and all the liquidity from the secondary markets pooling over there. What does that do to a fund of your size, 225 million in his last case? You're only going to have so many bets in those few companies that have high amounts of secondary liquidity. So how do you approach providing what your LPs need if you can't just put all of your funds into, let's say, Anthropic?

• 12:08Speaker 01

  Well, I mean, first of all, we've got a, our fundamental job is to get into companies at an early stage in our case that end up being in that power law basket down the road.

• 12:18Speaker 00

  Of course.

• 12:19Speaker 01

  The other interesting thing that is happening is those power law companies are acquisitive. And so a number of us at the early stage have have ended up with shares in those companies by those companies acquiring our our portfolio companies. And so then we actually, you know, have the chance of liquidity. You know, this is actually interesting aspect of the information rights conversation as well, which is sometimes we we get real access to that information. At a company that's acquired one of our portfolio companies and sometimes we have, we have zero, which is another interesting dynamic. But I think the fundamental job we all have is to, is to back those companies that are power law companies.

• 13:04Speaker 01

  And then the benefit of having a smaller fund is that it isn't just those companies that can matter for us. And so, you know, if you have a $500 million exit, let's say in a company where you own 15% and you, you get back 75 million, that for a couple hundred million dollar fund is actually quite meaningful. It is really not meaningful though, when you have a billion dollar fund. And so those are some of the, the dynamics that I think are really relevant to fund sizes like ours.

• 13:38Speaker 02

  Yeah, you know what? I would also add it's the stage. So like, if you're a very early stage investor and you're in a company like Cursor or Eleven Labs, you can actually do secondaries along the way and no one cares. In fact, everybody wants you to do secondaries because then, you know, from the founder perspective, it's just one pocket going in the other. But you know, if you're like a lead investor, like say a Sequoia or an Axel or, you know, whomever founders fund, and you own 20% of the company, you really can't do secondaries because then aside from what Nikhil's talking about in terms of the fund math, it also sends a negative signal to other investors like, oh, why is the lead investor, you know, say Sequoia selling right now? And so they're, they're gonna signal risk essentially.

• 14:23Speaker 02

  Yeah, exactly. Whereas no one cares about the early stage guys selling. In fact, they encourage it.

• 14:28Speaker 00

  Make this work for me because on one hand, we see Andrew stressing founder cap table control. And I don't think they're making that point only about super late stage hottest companies. And then also what Michael's telling us about how early stage investors are almost encouraged to sell some of their holdings. So how prevalent is the, I don't know how to phrase this politely, founder iron grip on cap table and disallowing these transactions? They often need to be blessed and also the demand to let people like you cash out. I'm just trying to figure out the balance between the two, if that makes sense.

• 14:57Speaker 01

  I think I haven't seen actually that much conflict.

• 15:05Speaker 01

  You know, from my own primary experience with this because the founders ultimately want folks that are long-term aligned on the cap table and they understand, especially for those investors that believed in them early, I think they're sort of grateful for that belief often and they understand the needs of those early investors and you know, transferring positions over to folks that are more long-term aligned is actually in their benefit. And so I think that the situations that are more hairy are when, you know, those things are trying to be done more under the table. And then there's a lack of understanding of who actually holds

• 15:45Speaker 01

  the shares. And so, you know, I think as long as folks are communicating well and transparent, I haven't seen that many problems with misalignment.

• 15:57Speaker 00

  Okay, so that's, that's encouraging. Michael, one more question about this topic before we move on to M and A, but there's been a bevy of slightly vague posts from VCs over on X in the last couple of weeks about a rise in fraud in the SPV secondary market. How much of that is smoke and how much of that is fire? Because based on what Nikhil just said, it doesn't seem like there's that much conflict, which to me sounds like a low fraud environment.

• 16:22Speaker 02

  Yeah, you know, it gets headlines, but you know, we work very closely with a firm called Klein Hill. So we have a joint venture secondaries fund with Klein Hill. And I was actually just talking to them the other day about, you know, are you seeing a fraud in these SPVs? And generally speaking, we don't and they have not. And they're very active in the market. So, you know, but then again, they're not necessarily buying into a bunch of SPVs. But, you know, I think they have a very strong network. We have a strong network and we don't really hear of fraud. Does it exist? I'm sure it does. And there are people who've been sent to jail because of it. But I think they're just more like headline grabbing kind of, you know, tidbits.

• 17:03Speaker 00

  Yeah, because when SpaceX was going to list, people were like, oh man, how many people bought essentially fake SpaceX shares? And I was kind of waiting for those stories to bubble up after the IPO and I didn't see a single one. And so to me, it seemed like people We're really over indexing on a concern that wasn't there. All right, let's talk about exits in a different way. There's a company called Superhuman, had them on the show a bunch of times. They just bought a company called GPT zero, which Nikhil, I think you are an investor in.

• 17:28Speaker 01

  That's right. Yeah, we led the company Series A. I served on the board.

• 17:30Speaker 00

  Yeah. So, well, first of all, can you tell us a little bit about how that deal came together? And why was the right exit for GPT zero? And then we're going to talk a little bit about numbers, but start there, please.

• 17:38Speaker 01

  Yeah, the companies have known each other for a long time. And there are a lot of parallels in their businesses. So Superhuman is a combination of a number of companies. Grammarly, Coda, and now Superhuman as well. And sort of changed the name to Superhuman of the whole company when Grammarly acquired Superhuman. And just here, their CEO has known Edwin and Alex, the founders of GPT zero for the last couple of years.

• 18:09Speaker 01

  The companies have been talking about doing this together for a while because there are a number of parallels in their products. And I think what the GPT zero founders got really excited about was the opportunity to have a lot more distribution through Superhuman's distribution from their various products to tens of millions of active users. And so while GPT zero, you know, it's publicly reported, they they got to tens of millions in revenue. They actually never burned a dollar that we invested. The company is lifetime profitable, has more cash on the balance sheet than it has ever raised. So they didn't need to go find home. But this was a very attractive offer for them.

• 18:51Speaker 01

  And so that plus the opportunity to go build something even bigger together is what got everyone really excited to do this. And so an amazing outcome for the founders, a great outcome for all the investors.

• 19:04Speaker 02

  So Alex, I have a couple of stories here. And Nikhil, I'm a personal investor in your funds, so I'm very happy for myself and for you. So thank you. But, you know, we're also an investor in, Cendana is an investor in Uncork. And one of the partners there is Trip Jones. And the funny story I want to tell you is that he learned about the founders of. GPT zero because he was reading the Princeton Alumni Magazine. And he was hearing about like what these kids were doing because they were, I think, still at Princeton. Right. And Nikhil went to Princeton as well. And, you know, so he actually got on the plane and went and met with them. And so now it was coming down and there was a tier one firm, a multi-stage firm that had a term sheet.

• 19:46Speaker 02

  But the the founder of that firm was supposed to get on a call, blew off the call. So basically Trip won the deal.

• 19:54Jason Calacanis?

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• 20:57Speaker 02

  And then the other element that I think that's kind of interesting, based on what we were just talking about. The parents of these founders were saying, were pressuring these kids to like sell the company. Not now, but like this is a while back. And what they did ultimately was they did a small secondary. Which got the parents off the backs of these, the founders. Because they're like, okay, now you have some dough in your, in the bank account. Just go execute. So secondaries can actually be very, very beneficial in terms of alleviating financial pressure.

• 21:29Speaker 00

  Yeah, but that's not financial pressure. That's familial pressure, which I've never seen come up in a case like this.

• 21:35Speaker 02

  Yeah.

• 21:35Speaker 00

  I understand parents wanting their children to take money off the table to avoid owing Princeton and their lenders more money for a long period of time. But that's, that's crazy. Nikhil, when this deal came together, were you in favor of it from the very beginning?

• 21:49Speaker 01

  As we talked about earlier, when companies are really working, they have the chance to be, you know, part of that power law basket. And so my initial reaction, you know, when we first started having conversations with Superhuman was, we absolutely shouldn't do this. We should go for it. And I think part of the responsibility that we have as early stage investors and board members is if we feel really strongly that a company has that, that chance to be a big independent company, you know, we have to give that perspective to the founders. And so I, you know, I, I strongly, you know, voiced that opinion. And thankfully, we didn't pursue an acquisition a year ago.

• 22:32Speaker 01

  And instead, we did a secondary as Michael, as Michael referred to. But, but this time around, it was a very attractive offer. And so my responsibility shifted once the founders decided they really wanted to do it to making sure everyone had the best outcome possible here. And so that's what we worked, you know, closely together on.

• 22:54Speaker 00

  So I ask about your relative interest in the deal because we're seeing a little bit more of this. We just saw Versell. They bought Better Oth, which had only raised 5 million. Figma, I know it's now public, but they just bought the team behind Bud, which I think was a vibe coding platform. And if we take a look at the data here, this is from my friends over at Crunchbase, showing global venture-backed M and A accounts and exit value. There's been a pretty steep ascent in total dollar value from kind of the nadir in the late 23, early 24 era to what appears to be a relatively robust amount of money changing hands here. The total number of exits doesn't seem to be changing too much, but I'm curious about what you guys are seeing in the market regarding. Kind of inbound from either the largest private companies, the stripes, the anthropics

• 23:39Speaker 00

  and so forth, or the public set and who's more interested in picking up startups today? And Michael, why don't we start with you on this?

• 23:46Speaker 02

  Yeah, I mean, I think we're a beneficiary because we're in cursor through Neo. And, you know, obviously a $60 billion exit is is always welcome. They are outliers, but, you know, it shows how, you know, within with with power law, a small firm like Neo can return multiples of their fund with one investment. I would say that, you know, given where we are on valuations and, you know, it's basically currency that a company can use to acquire other companies. And so even though SpaceX is paying $60 billion for cursor, you know, when you have a two and a half trillion dollar market cap, it's less than, you know, what, 5%? It's low single digits to them.

• 24:31Speaker 02

  And you could argue that SpaceX is overvalued. You could argue it's undervalued, but they have the currency to do it. And so that, I mean, obviously SpaceX is now public, but even for private companies, if Databricks is valued at $150 billion, for them to issue a billion or 2 billion of their stock, it's less dilution to them and they can do that and they can actually turbocharge. And you saw that in the late 90s with Cisco and Cisco had acquired over 120 companies. People are arguing that that basically was their R and D strategy. But, you know, Cisco was trading at 100 times P E.

• 25:04Speaker 00

  Spend the money when it's free. Why not? Yeah, no, there are some advantages to being public. I hate to sound like the old broken record, but like to me, you have a lot more firepower to do stuff because you have the liquid currency that you're describing.

• 25:15Speaker 02

  You have that in the private markets now, right? I mean, OpenAI, Anthropic, companies like that, they they have, you could argue, overvalued currency, but they're going to use it.

• 25:25Speaker 00

  Yeah, no, I, by that point, the overvalued currency part, yes, less liquid, but still very useful.

• 25:32Speaker 00

  I'm curious about if there's a genre of startup that's seen the most interest because I was a little surprised to see Nikhil, the Bud deal be more of a talent acquisition. I thought aqua hires were kind of out of vogue, given that everyone's trying to reduce their overall human headcount. So in your portfolio, who's not, who's getting the most kind of door knocks from other companies?

• 25:53Speaker 01

  I mean, I think that there is such a premium right now on talent because it is,

• 26:00Speaker 01

  it is relatively easy to go start a company and get funded. And so, you know, a lot of really talented people are doing that. And, um, and so, and then it is just hard to hire great people, um, based on a set of dynamics. So, yeah, I mean, our, our teams that, that, that have a lot of talent are absolutely getting reached out to. And then the companies that have momentum in their businesses. You know, that, that's what a company like Superhuman wanted in the case of GPT zero, along with of course, the team. But, but you know, there, there's a real business that they're picking up as well.

• 26:37Speaker 01

  So it, it does feel, again, if I, uh, I'm sure if I, uh, if I leverage the models to ask about like our M and A conversations in our team meetings and how that's turned it over time. The last couple of quarters has probably been the high watermark since we started for five years ago in terms of the number of discussions that we've had internally about our own portfolio companies getting reached out to by potential acquirers, which is an interesting data point that kind of matches the, the Crunchbase data that you shared.

• 27:09Speaker 00

  Yeah. Are the prices being discussed attractive? Because we mentioned earlier that many secondary deals often trade at a discount to last private prices. You're holding primary shares, so you don't want that. So when these acquisition offers come through, are they being put forward at a price that you think is fair and attractive?

• 27:27Speaker 01

  Again, of course, there's, uh, there's nuance in every situation, but, um, I think the dynamic that, that Michael, and you were talking about is really interesting, which is when the consideration is not cash, but instead. equity, then the key question is, what is that equity worth? And and so you can believe that perhaps an offer is unfair if you think the equity is far overvalued relative to the fundamentals of the business. On the flip side, you know, if if Anthropic had acquired one of your companies a year ago, you would probably feel terrific about that equity position today. And so, you know, I think

• 28:11Speaker 01

  the the main conversation that that we're having in each of these situations is, okay, like, what is this offer actually? And what is the equity actually worth? Whether it's a public company or a private company doing the acquiring, because in both cases, that equity may not be really tied to the fundamentals of the business.

• 28:32Speaker 00

  Are you trying to say that the NASDAQ keeps going up every time the state of her most explodes? And that's slightly confusing to all of us.

• 28:37Speaker 01

  It is a wild time on how to value anything. What, you know, I think, you know, when you look at a company like HubSpot in the public markets, that's three plus billion of ARR, and I think valued at less than $10 billion versus some of the companies in the private markets that are valued at $10 plus billion with not much revenue. It's just a, it's just a crazy time.

• 28:57Speaker 00

  Exactly 10 billion today, actually.

• 29:00Speaker 02

  I mean, we're talking about Anaral, you know, Lockheed Martin trades at about $125 billion market cap with 75 billion of revenue. And, you know, Anaral shares are trading above that market cap in the private markets. And, you know, Anaral has a fraction of what Lockheed Martin has. So one thing I'd also point out, Alex, is I do think that you're going to have a lot more acquisitions going on. Partly because of the SaaS apocalypse, right? The rerating of enterprise software companies. And, you know, you look at Meritex index, it's, I think, four revenue multiples are like at 3.6, 3.7 times. And to Nikhil's point, you have good companies that are trading at substantially lower valuations.

• 29:44Speaker 02

  I think it's part of that fear that these legacy SaaS and enterprise companies aren't going to make it because of AI. You know, you have a rule of 40 company like Monday, Monday.com trading at two times. I mean, that's crazy.

• 29:58Speaker 00

  It's legitimately insane.

• 29:59Jason Calacanis?

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• 30:43Jason Calacanis?

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• 30:59Speaker 02

  Yeah, but you could also see how AI could wipe them out. So like what we have, you know, just very recently, Intercom was acquired. It's a portfolio company of freestyle. It returned more than the entire fund. It's an interesting case study because it's a company that has been around for a while. People thought it was dead because of, you know, Sierra and other companies like that. But I think they were, they actually had a really good story about implementing an AI native solution and then getting traction on it. So they kind of revitalized the company and that's actually what this sort of messy middle of like SaaS and enterprise companies need to do. I also think that Salesforce acquired them because they wanted Owen as a senior executive.

• 31:40Speaker 00

  Yeah.

• 31:40Speaker 02

  And they were not going to buy Sierra and bring Brett Taylor back. And so you have also companies like Airtable, which were darlings. You know, they, their, their, their, their last round was at 11 billion. And which, by the way, Freestyle was able to top tick as a secondary.

• 31:57Speaker 02

  But you know, a company like Airtable, other legacy companies, they have the customer base, they have the workflows, they have the proprietary data. And so I think that's actually what what's going to drive a lot of acquisitions down the road, as well as senior executives. You know, I mean, I think Marc Benioff would love to have, you know, is excited to have Owen as a senior exec. He would probably be very excited to have Howie from Airtable as a senior exec. So I think you're gonna see that, as well as the the technical acquisition, the acquisition of technical people that, you know, the smaller acquisitions are representing.

• 32:35Speaker 00

  All right. So we talked about workflows there. We talked about data. Let's get into that. So Nikhil, we were talking about this before we jumped on the show. There's been a host of posts from venture capitalists and founders in the last couple of, I want to say the last week, digging into the concept of data. Now, if you go back to the early AI era, you know, right after ChatGPT came out, people were saying, oh, data is so important on the training side of things to create these models. Startups were spun up to facilitate data licensing. That kind of went okay, as far as we can tell. Then for a while, everyone just talked about intelligence and reinforcement learning and so forth. And now, finally, we're back to where we were before, which is the value of data often locked behind corporations just not really accessible to the world. So I'm curious if you can tell us why the

• 33:20Speaker 00

  conversation has shifted from the founder and venture perspective to data being so important today, and then also what that does for companies like Monday, which Michael just pointed out, has a lot of this, but is trading out essentially zero for how much revenue it does.

• 33:34Speaker 01

  Every few months, it feels like there's a different, you know, substrate to the AI revolution that the world gets excited about. And so, you know, when you think about the stack, right, it is, it is energy, compute, and data that are the fundamental substrates for these models. And the models are sort of the fundamental substrate for AI. And it feels like, you know, the market gets really excited about, you know, energy and then compute and then data in different moments. And right now,

• 34:10Speaker 00

  It's kind of a loop.

• 34:11Speaker 01

  Exactly. Data's having its moment in, you know, in the X eco-chamber with a number of people posting about it.

• 34:23Speaker 01

  You know, I think the interesting thing about data is uh whereas in energy and in compute, you have enormous companies, enormous public companies, right? Like the biggest public company in the world, in the case of Nvidia, for example.

• 34:39Speaker 01

  You don't have on the surface such enormous companies that are just, you know, in data. And so that is an interesting opportunity. Now, of course, you have uh every company that sits on data that could be important um and relevant to what's happening in AI. So that's just one dynamic to think about, which is that the company is like purely focused on data. Um, there aren't that many of those that are huge public companies versus in the other couple key areas. And so um you can argue that there's like more white space there than in other areas. And then it does feel like what the labs are really focused on is is data at the moment. You know, they've been

• 35:25Speaker 01

  they've been, you know, there've been a number of projects underway at the labs to solve the energy and compute challenges. And those have been more publicly talked about, but what's happening on the data side is more murky. And therefore, I think like interesting for people to be weighing in on. And the companies out there beating their chest about data are particularly the ones in data labeling. Um, Merkle, Handshake and others. And it's interesting that they constantly talk about like their revenue run rate and where that's going. But that's not the only piece of data that is interesting. There's also data licensing and the model companies do a tremendous amount of licensing of data.

• 36:08Speaker 01

  Not just labeling uh uh of data through humans. Um, data licensing applies, for example, to real world data that they're trying to get access to. And then, of course, the models themselves have data from usage that they're using to improve their models. So those are just some of the parts of the stack. We have one of our, one of our portfolio companies that's growing the fastest is a company called Protege, which is in that data licensing realm. Um, and then, you know, I think, again, what is intriguing about this whole space is how little we actually hear about from like how companies and the model companies themselves are leveraging the data to improve their models. Because that is their secret sauce.

• 36:45Speaker 00

  So I'm pulling up Protege here. So how much have they accelerated in the last six months? Because if these people are talking about data becoming more important, again, as we talk about the different layers of the stack, I would presume that they've seen a pretty big uplift in their business.

• 36:58Speaker 01

  Yeah, this is a company that has, again, not been that public about how well it's doing. But in year two of its business, it's hundreds of millions in revenue. And what they do is they enable data providers, folks sitting on data, to license their data to the model companies and application layer companies that have a need for that data and a purpose for licensing that data. And so it's a very simple idea on the surface, but one that makes a ton of sense when you think about the importance of this in this moment in time. You know, you've heard about there are public deals such as Reddit's deal or the New York Times deal with with OpenAI.

• 37:40Speaker 01

  But you can imagine that there's a lot more of those types of deals that are happening. And Protege has emerged as the leader in in sort of facilitating those types of licenses.

• 37:52Speaker 00

  Michael, there's been a lot of questions about where the value will accrue in the broader AI race. Will it be people who just sell GPUs, kind of the fix and troubles argument? Clearly, there's a lot of money you made in interconnects, high bandwidth memory, photonics, et cetera. The app layer, the model layer, it all kind of predicates on data. So I'm curious what your perspective is on how startups are going to be able to to capture when they often don't have as much historical customer data as your sales forces and hubspots.

• 38:17Speaker 02

  Yeah, I mean, that's a really good question. I think having proprietary data is actually where the economic value is going to accrue. You know, in a way, you can look at token economics, a token as a unit of human labor, actually. Because ultimately, you're trying to complete tasks around that. And that's the sort of expenditure that you need to do.

• 38:38Speaker 00

  Yeah.

• 38:39Speaker 02

  But in order to do anything, to have any insight, to have anything actionable, you have to have the data. And that's why I think the SaaS apocalypse is overblown. You know, I think it's it's it's almost hubris to dismiss all these companies that have the workflows, that have the proprietary data, that have the customer relationships, and just assume that, you know, AI is going to blow them away. AI is actually going to help them leverage what they have and actually create more economic value if they do it right. And Intercom is a good example of that.

• 39:10Speaker 00

  Intercom is a great example of it. They did refactor their whole business, rebranded as Finn and really went all in early. I mean, frankly, I think Owen was, he's kind of stuck his neck out frankly on that point and ended up selling for Michael back in the 3.6 billion.

• 39:23Speaker 02

  Yeah, I think 3.3, 3.4.

• 39:25Speaker 00

  3.3, awesome.

• 39:26Speaker 02

  Yeah.

• 39:27Speaker 00

  But the inverse of your, oh, it's a great outcome, especially for a company that had for a while their stagnant ARR and was actually shrinking a little bit. That is, I mean, that's coming back from the dead and I say that with respect as opposed to being a diss.

• 39:38Speaker 02

  Right.

• 39:39Speaker 00

  But your point about SaaS apocalypse being overblown, the importance of data, the power of workflows. I think about a company that as we all know, Box with Aaron Levie, they have tons of customer data. They're expanding into workflows. They seem to be accelerating their revenue a little bit. I track their earnings more carefully than I should. And as of today, they're trading at a 3.4X trailing price sales multiple. So is the market just systematically undervaluing data and its eventual value today as the private markets get it right?

• 40:10Speaker 02

  Yeah, I do think so. I mean, if you actually look at Salesforce, they're growing at 10 to 12%. So why, why is Salesforce that has all this amazing data, you know, it's a database company, right? Ultimately CRM company and they're, they're only, you know, they're, they're down 40% for the year. And I think, you know, it really is that investors are chasing after growth fundamentally. And you have that with, you know, Samsung and SK Hynix and, and Micron. You have, you know, I think VCs chasing after companies that are going from zero to 100 million in six months now, not, not 12 months.

• 40:51Speaker 02

  And it's to the detriment of the companies that aren't growing that fast, but yet are probably, you know, very well, maybe building enduring companies. Yeah. And I think that's, that's actually where the alpha is going to be made. Yeah, you could get on the, the bandwagon and go off and have FOMO and chase after the high momentum deals. But I think there's going to be very thoughtful founders and companies that are building enduring businesses that are going to take advantage of this just as well. And from a VC perspective, to have good ownership in those kind of companies actually will potentially play out better. The fear, of course, is from the LP perspective, you know, I hear this all the time. You know, how much exposure do you have to SpaceX, OpenAI and Anthropic?

• 41:35Speaker 02

  That's all that people talk about and it's it's it's an important point. But I think they're missing the bigger point of what early-stage ventures are supposed to do.

• 41:43Speaker 00

  Yes, which is not back the super late-stage bloated consensus companies that we already all know. I mean, that's not venture, that's just basically IPO investing under the mantle of PE with venture capital stenciled in front of the building. Like, it's not.

• 41:55Speaker 02

  Yeah, I mean, I'm sure Nicole has a lot of thoughts around this, but you know, and from our perspective, what we do is we try to back VCs who are finding non-consensus founders building non-consensus companies. And that's where the alpha comes from, because ultimately, if they become consensus, then there's unlimited capital coming in, right?

• 42:12Speaker 00

  Yeah.

• 42:12Speaker 02

  I I I posted this a while ago, it's like basically Zerp 2.0. Instead of the US government giving all that money, it's actually the the the platform firms that have pretty much unlimited capital.

• 42:23Speaker 00

  And that's why we're back to 2021-era revenue multiples. I mean, like, how many VCs were on my phone back then be like, I just heard about a Series A done at, you know, 10,000 ARR and 10,000 X multiple? I'm like, that's crazy. And then it was crazy. And now I think we're right back to it.

• 42:36Speaker 02

  Yeah, I mean, I I I think, you know, you look at Nvidia, you look at their Ford PE, it's like 24 times. It's not crazy. It's not like Cisco at 100 in 1999. And then, you know, the what's happening, though, is that E is doing a lot of the work, right? And you're assuming that that E is going to, the earnings is continuing to be like amazing, right? Samsung just announced that they had $59 billion of of EBITDA. And, you know, it's just like, holy shit, where did that come from? You know, um, I think the the biggest risk over the next 12 to 18, maybe 24 months, and no one knows, is that suddenly that that growth is not going to happen. There's a lot of catalysts in the market that could create major issues.

• 43:20Speaker 02

  And you can easily see Nasdaq going down 20%. Easily.

• 43:23Speaker 00

  Okay, before we let Nikhil jump in, I want you to tell me, I have my own list of catalysts that could lead to such a correction, which I don't think actually would be that a miss. But what are you looking at as possible tripping points?

• 43:35Speaker 02

  Well, you know, I think some of the catalysts could be, you know, clearly like if Nvidia or any of these semiconductor companies have a miss, if you have projects like, you know, the, the, the star cluster that Oracle is working on with OpenAI, if the, you know, their bonds are being, have, have even a higher premium now in order to, to, so it's really the financing risk, being able to raise the capital in order to do this, because it is a circular economy. And, you know, if any part of that circle stops, you know, the, the musical chair stops, then you can have a serious correction, because then all the growth estimates are off the table. And that's going to be a catalyst. It, it, one, one world that I don't know very well is private credit.

• 44:18Speaker 02

  And a lot of that is funding these data center build outs. And I think, you know, if there's any hiccup there, the, the other thing, of course, people are talking about recently is like these leveraged ETFs, right? The three times leveraged ETFs of these semiconductor companies. You can see where if that crashes, then retail takes down all the hedge funds that were long. And, and suddenly you have contagion. We've seen this movie many, many times over the past.

• 44:45Speaker 00

  You're not supposed to say contagion, just like you're not supposed to say recession. It's bad luck. I mean, you're gonna, you're gonna curse us all. All right, Nikhil, we've been talking for a minute, let's bring you back in.

• 44:53Speaker 01

  You know, the, the phrase that I think is on my mind as I think about what happens in the markets is, you know, is, is not too big to fail as it was in, you know, some, some prior corrections, but it's too important to miss. Like there, there's a set of companies that just have to hit their numbers, beat their numbers on both top line and bottom line. Yeah, I actually worry more about the bottom line for a set of companies that are just consuming tremendous amount of capital. And obviously, I think like OpenAI is high up on that list. I worry more about that than I do the top line of a company like Nvidia, for example, which I think has a lot

• 45:40Speaker 01

  of predictability to their business.

• 45:43Speaker 00

  I think we've also seen predictability baked into the memory sector, for example. Michael mentioned a couple of memory companies. I think Micron was the one in its last earnings report that noted they dropped in like multi-year contracts for some of their biggest buyers, a lot of stability there. The thing that I'm looking for the most is a decline in the compute crunch at the hyperscaler level. So I think that will tell us where CapEx is going for the biggest buyers. It'll tell us how much they're spending on their own AI projects and also customer demand. So it's kind of a good proxy for overall health. And I think we are one major like alphabet pulls back from its CapEx plans away from at least a 10% correction, which I think puts a lot of pressure on the upcoming earnings cycle. Because once again, here we are, everyone's worried.

• 46:28Speaker 00

  And every single quarter so far, every hyperscaler said we're compute constrained and it will be for quarters to come. And one day that won't be true.

• 46:35Speaker 02

  Yeah, I mean, Alex, one really recent example, and I mentioned it, Samsung reported like $58 billion of EBITDA. Up from like a billion eight or something, like some astronomical increase year over year. It actually, the stock price went down 7%.

• 46:50Speaker 00

  8%.

• 46:51Speaker 02

  7% or 8%. It went down and that's sort of the sentiment you have in this market is like, you know, that's great, but you know, you have to keep outperforming and that's what's worrisome is that unrealistic expectation.

• 47:08Speaker 02

  You know, every time Nvidia reports, I'm like very, very nervous because even if they have an amazing earnings report and Nikhil correctly points out, they have really stable growth. If it's not exceeding, you know, sort of market sentiment and expectations, you could have a disaster.

• 47:27Speaker 00

  What's the private market version of this? Because the latest news is that lovable, everyone's favorite European hypercorn is looking to raise, I think it's 300 million and more at a 13.2 billion. They've crossed 500 billion in annual run rate, not annual recurring revenue. To me, that's incredibly impressive company. But I mean, Nikhil, if they miss two quarters in a row, what happens to their valuation?

• 47:50Speaker 01

  I think the thing that worries me is less them and other companies missing on the top line. It's just a set of companies that require a ton of capital because of their, their burn levels. I think the ones that are scarier, like, you know, reports that OpenAI needs to go raise another several hundred billion dollars. That is the thing that worries me much more so than.

• 48:17Speaker 00

  Okay, but, but, but isn't there a direct connection here between ability to, to finance that build out you're describing and their revenue growth? Because, you know, once Anthropic hit like 64 billion run rate, whatever, you can kind of double that for next year. And then they'll have at least 100 billion revenue in 27, or you can do fun math that way. It's not that hard, but that does cover a lot of spend. If there's a reasonable amount of margin on those tokens, and if they're not making hella margin on Fable at 50 bucks per million output tokens, then the whole industry just throw it in the bin.

• 48:46Speaker 01

  Yeah, I think that's the key question. Like, how much are these companies over investing in compute to capture demand and how expensive that is? And then what their margin is? And, um, and so, uh, again, we, we shall see, but right now, uh, the music feels like it is very much playing.

• 49:08Speaker 00

  Music is blaring, but it tends to blur before the speakers blow out. Now, on that point, I want to just talk about Chinese AI models for a second because I do think they fit into the margin conversation. Going back two months, suddenly everyone stopped paying subscription for AI and started to pay on a usage basis. Everyone freaked out, seems to have quieted down a little bit now that everyone realized you shouldn't use Opus 4.8 fast for everything you're doing. Simple enough. But a lot of companies did lean into either. Using off the shelf open weight models, usually from China, some from France. Or also fine tuning or post training their own versions of them. We saw examples like Cursor using KIMI K2.5, I think.

• 49:49Speaker 00

  Airbnb used Quinn, the list goes on. Recently news was out this week that the Chinese government may preclude the release of future open weight models. Essentially, kind of the same fight we're seeing in the US about accessibility, kind of cutting edge AI. And my, my question to you is, what does that do to startup margins? Because a lot of companies were moving their inference off of state of the art, closed source to either, you know, cheaper open weight or self hosting them frankly. And if they can't do that, what happens to their business?

• 50:17Speaker 01

  We have seen our own portfolio companies use a mix of models. And, you know, I think many of them are using the frontier models for coding. And so that is a significant area of spend for them. But, but they're also using the open, the open source, open weight models for elements of their product where the frontier models are just not necessary. Now, the, the, the good news, I think for them is that the non frontier models at the closed source companies are getting cheaper. And so, you know, you can redirect a lot of stuff to some of the older models that are still very capable.

• 50:58Speaker 01

  And I think that is an option for a set of companies that, that again helps the, the margin conversation. So, I don't know, you know, I, I think obviously a key thing for, for us in the US is figuring out how to have a vibrant open source ecosystem, open weight set of models here. I think that's really important. But I think what is plugging the gap is that, you know, the, the, the non frontier models from the closed source companies are just getting cheaper. And I have to believe that what will happen is, you know, more of a stratification there where of course the frontier capabilities get expensive and and will be needed for a set of tasks.

• 51:40Speaker 01

  But I think we can redirect a lot of tasks to these, these, these models that are cheaper.

• 51:44Speaker 00

  Michael, that doesn't solve the whole problem, though, I don't think, because there's been a lot of conversation. We saw Alex Garp from Palantir and a lot of other people begin to really beat the drum about not using closed source models, be they, you know, at the absolute cutting edge or a generation behind or just a sonnet-sized model, because the major labs are going to train on your workflows, train on your data, and essentially put you out of business. So in a world where we don't have open weight Chinese models and you don't want to trust the closed source models from the major labs, where does that leave startups?

• 52:13Speaker 02

  Yeah, I mean, I think ultimately it gets back to my comment about enduring businesses. And, you know, the joke was EBITDA plus C, you know, the cost of compute. And, uh, you know, economically speaking, you, you, you want to take advantage of, of, of that pricing delta between the open source models and the proprietary models. I think it's really good for the US AI industry. I mean, I think that kind of pricing pressure is, is really good. You see a lot of startups working on orchestration, uh, layer and, and trying to figure out how to optimize which models to use when. And I think that kind of innovation is very important. And so I don't have any more insight other than that.

• 52:56Speaker 02

  But I do think from economic, you know, the, the free hand of the, the, the invisible hand of the free market, I think it's really good to have that pricing pressure put on the proprietary models.

• 53:06Speaker 00

  Agreed. I mean, shout out Adam Smith and all sorts of, you know, invisible appendages. But I'm just worried, uh, Nikhil, that

• 53:13Speaker 02

  Yeah.

• 53:14Speaker 00

  the models from Nvidia, the Nebitron family, that the models from, uh, Google's Gemma family aren't sufficient to replace what we have from DeepSeek, from Zippo, from Moonshot, from Quen. And we're going to end up in a place where a lot of people are betting on rolling their own, especially startups that don't want to pay OpenAI's margin for them. And they're just not going to have something to fall back on. And to me, that seems like a, an almost structural risk in the startup market today.

• 53:39Speaker 02

  Yep. Yeah, I think you're right to be concerned about it.

• 53:43Speaker 01

  And I think the other thing here is just all of this requires teams that are capable enough of leveraging different models, of switching models in and out of, you know, potentially fine tuning, building their own model. And I think as we discussed earlier, like the set of really talented people is finite. And so there are a set of companies that just don't have another option but to, but to work with either application layer companies that are using the closed source models, or just work with the frontier labs because they don't have the talent level to do anything else.

• 54:27Speaker 02

  Well, Alex, the other thing is that, you know, ultimately, you can see where different industries have, you know, are leveraging small language models, right? And so that, you know, if there are companies that were helping develop these small language models for an enterprise customer, they that can actually take advantage of the data that they have and the workflows that they have, that would be probably more cost effective than just, you know, using anthropic or OpenAI.

• 54:55Speaker 00

  I'm just disappointed that we've now said several times in this conversation that there's only so many companies that matter, so only so many founders that matter, only so many researchers. It seems disappointing that we seem now, back to Nikhil's earlier point, but being more power law pilled, that the number of things that matter in the market, companies, founders, etc., is going down, it feels like, at a time in which it's more easy than ever to build something. And to me, those seem to be contrasting in a way that doesn't help the current political situation around AI being relatively unpopular. So, you know, is there a way to, I mean, I'm going to sound like the mayor of New York City here, but hear me out, to spread the love a little bit and have more companies

• 55:37Speaker 00

  become market leading, so that way we don't end up with just like six people from Andreessen and their friends making a bunch of money and everyone else sitting around with a tin can, going, please, Laura, give me some tokens.

• 55:48Speaker 01

  I think two things can be true, right? Like, there's, there's a concentration of resources and power, the bigger companies are getting bigger. Can can coexist with it is easier than ever to start a company and it is uh it is more possible than ever for two people to build a business that is that that gets big quickly and gets wildly profitable quickly like I think both of those things are happening before our eyes and and so it is an amazing time to go build um and you know it is an amazing time to be one of these massive companies that is only getting bigger.

• 56:27Speaker 02

  Yeah, you know, Alex, one of the things that we've had uh an idea around is this arms race to find younger founders and in an AI native world, you know, everybody needs to be the first check and that also could mean younger founders and you look at, you know, um, some of the groups that we work with, like Josh Browder, who is a Thiel Fellow, he's helps on the selection committee. We have Corey Levy at Z Fellows. We have um the guys from Prod, you know, you you look at companies that in for example, are like Neo, you know, they're spending time with university kids and especially at Harvard, MIT and Stanford, you have and and probably, you know, Carnegie Mellon and some others, you have kids who are uh who actually want to start companies who have

• 57:13Speaker 02

  are almost fearless, like what uh you know, one of the companies that we're in is is etched and you know, these young people are like, hey, we're going to totally disrupt Nvidia and build inference specific chips and you know, what what 20 year old goes around thinking that, but they're unencumbered by the fear and they're not 20 year veterans thinking, oh, it's an impossible task. And so I think that that's actually what's very um, you know, heartening and very exciting about entrepreneurship. So yeah, you do have these big incumbents, they're getting bigger, but you also have really smart kids who are fearless and are trying to build companies that are totally going to disrupt. And that is the beauty of of capitalism.

• 57:53Speaker 00

  Uh Gavin is the CEO of Etched, I believe, right?

• 57:56Speaker 02

  Yeah.

• 57:57Speaker 00

  Yeah, we had him on the show. One of my favorite conversations I've ever had, one of the nicest people I've ever met and also they just came out of stealth, announced, Michael, correct me here, 800 million in funding and they're bringing a chip to market soon. They're building a test data center of a couple megawatts in Taiwan and they're going to bring out rack scale systems.

• 58:13Speaker 02

  Yep.

• 58:13Speaker 00

  I forget the timeframe, but soon, which I think is going to be great for cutting inference prices overall, if you're not into Cerberus or San Benova, which just raised a billion at an 11 billion dollar post. Uh guys, bringing this to a close. I want to do some kind of fun questions here and I love to go through portfolios and pick one out and then ask the venture firm and question about why they picked that one. Now, Windborne, as far as I can tell, is a company that wants to put a bunch of balloons up into the sky and provide essentially a private weather observing network and then sell that data to energy traders and everyone else. I love this idea, but Nikhil, it does seem that right now, we've seen headlines about how we've reduced funding at the national level here in the States for our own weather gathering technology. So is this company just

• 58:57Speaker 00

  nailing the right time, right market moment? Because I feel like they must be just fending off customers.

• 59:03Speaker 01

  Yeah, it's one of the companies we're most excited about. And some of the characteristics here, I think, are interesting to cover for founders, which is Windborne collects its own data through its own weather balloons. So it has proprietary data on the atmosphere in their case. They leverage that data to build their own models and they use AI for those as well. And so AI plus their own proprietary data has led to some of the most accurate weather forecasting models in the world now for this company. And this is, by the way, you know, it's a 50% company based in the Bay Area. And then on the commercial

• 59:44Speaker 01

  side, you're right that unfortunately, the cuts in the National Weather Service in the US and issues with these atmospheric associations around the world have led to, in a time where like the weather is changing more and where you would think, you know, models should get better. Unfortunately, there have been a lot of issues with accurate models, with accurate weather forecasts. And so Windborne is one of those companies that's filling that gap. And they sell both to governments and to companies. And by the way, within the US government, for example, not only do we work with the National Oceanic and Atmospheric Association,

• 1:00:28Speaker 01

  NOAA, we also work with the Department of War. And you can imagine there is a lot Lots of reasons for why weather data is important to both those departments. So really fascinating company. It actually is related to the the data conversation we were having earlier because of its own its own data edge and mode there. And the one other thing I'll call out about this is the company was actually started back in 2019. The the four founders all went to Stanford together. They were part of the Stanford Space Industries Group at Stanford. So well pre this AI era. But it's one of those companies that now feels more interesting than ever based on what's happened in AI the last three and a half years.

• 1:01:10Speaker 01

  And the company itself is one of the most AI-pilled companies that we work with. They've automated everything possible internally. They actually have their own AI lead, software lead at the company that's managing their their fleet of agents. And so a company that feels very well set up for the next 10 years.

• 1:01:30Speaker 00

  You get 10 points for the answer and minus five points for dodging saying climate change during your response, but still five points, not bad. All right, Michael, now over to you. I don't, I'm not going to press you about a particular company, but I am going to say, who is your favorite fund manager in your broader portfolio? And you cannot say Nikhil.

• 1:01:47Speaker 02

  I love Nikhil. Right now, I would say Josh Browder. I mentioned him earlier. He's a Teal fellow. He has a company called Do Not Pay. It's very profitable. He's and but, you know, he has hustle. His average post money is $5 million. He's on the, he's, he's on the Teal selection committee. And so he meets, you know, these 200 kids who are in the final process. And that's an amazing pipeline of of potential entrepreneurs. So, you know, I think Josh has done a very good job harvesting that. And I feel like, you know, that that he, he, I wouldn't say he's neurodivergent, but he can read people very, very well. And I think he sees the spark in young people who are actually going to walk through walls to build amazing companies.

• 1:02:33Speaker 02

  That's the problem right now with these younger founders. A lot of them are actually just trying to get the credential. You know, nothing against Y C, but you know, getting into Y C is kind of a credential now. Or becoming even a Teal fellow is kind of a credential. So you got to really suss out who's going after what for what reason. And I think Josh is extremely good at that.

• 1:02:53Speaker 00

  So essentially, in the Zerp era, we had a lot of tourist money flowing in. And today, when you can grow a company from zero to 100 million revenue in a year, we have a lot of tourist founders. Okay, well, you know what? Neither will last because what if there's one thing that's true? It's building a company is hard as hell and it takes a really long time. Guys, we're going to leave it there, but I really enjoyed this. I'm really curious to see in six months how this data conversation changes and where we are in the broader arc of going around in a circle between energy, compute and data. But Nikhil, where can people find your firm online? And is there anything else you want to shout out before you go?

• 1:03:25Speaker 01

  Yeah, just footwork dot VC and I'm at NBT on X and nbt.substack.com is where I write as well.

• 1:03:32Speaker 00

  Fantastic. Michael, where can people find Cendana and anything else you want to add?

• 1:03:36Speaker 02

  Cendana capital.com and my Twitter handle is MKROX, which was my gamer tag from the early 90s and I use it for everything. MKROX.

• 1:03:47Speaker 00

  We're not going to stop now then. What are you playing lately?

• 1:03:49Speaker 02

  Call of Duty. At one point, I was top 10% in the world on that. But I don't play as much, but yeah, I like first person shooter games.

• 1:03:59Speaker 00

  I'm an old Quake guy myself, a big fan of Doom 3, but I've really branched off into factory automation games lately. I can't help myself.

• 1:04:07Speaker 02

  Right.

• 1:04:07Speaker 00

  So good. Nikhil, do you game?

• 1:04:09Speaker 01

  Oh man, I used to, but now like in high school, I played Warcraft III and I was high US West with one of my best high school friends. But in this current zone where I have two young kids and started a firm, it would be a bad situation if I was gaming as well, so I'm off.

• 1:04:29Speaker 00

  You just have to do it after everyone else is asleep and just cut back on your sleeping hours. It works every time.

• 1:04:33Speaker 01

  That's the time to write and think these days, so.

• 1:04:36Speaker 00

  All right, guys, this has been an absolute treat. This has been this week in startups. My name is Alex. We're back on Friday. We'll see you all then.

• 1:04:40Speaker 04

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• 1:05:25Speaker 04

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