This Week in Startups - Why Data Is the Next $1 Trillion Market

Starting point is 00:00:00 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 re-centered 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 DigitalOcean.

Starting point is 00:00:28 Want to see what building on a true and. AI Native platform looks like, head to DO.co slash twist to start building on DigitalOceans AI Native Cloud today and cut your AI workload costs by up to 50%. Agree.com. Stop chasing invoices and automate 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. Nikiel Basu Trevedi of footwork. Last fund was $225 million. He's a backer of companies like GPT Zero and Winborn. Nikiel, hey, glad you're here.

Starting point is 00:01:14 Great to be here, Alex, and great to be with you, Michael as well. Speaking of which, we also have Michael Kim of Sandana 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, Welcome to the show. Great to see you guys. Thanks for having me on. So I'm glad we have both of you because we have the traditional VC perspective and then we also

Starting point is 00:01:36 have kind of the LP side of things. And the biggest point 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 Andrel, the well-known late stage American Dynamism Defense Company, essentially catching people up who don't know, USVC claimed they purchased exposure, essentially, to Anderil at its Series H price. And then Mr. Grimm, a co-founder of Anderrol, said, no, you didn't. And there was a big blowup on Twitter trying to figure out how this all went down. The gist gentleman, as far as I can tell, is that people are figuring out that public markets had reasons for some of their rules about

Starting point is 00:02:19 transparency, disclosures, and so forth. And secondary markets are still a bit like the Wild West. 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? 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.

Starting point is 00:02:46 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 provenance 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. So when you say that some firm managers are using SPVs as a way to get LPs to invest in their funds,

Starting point is 00:03:20 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? Yeah, exactly. They might be raising a fund right now. And 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,

Starting point is 00:03:45 you can come into our fund. So, you know, that's a dynamic that I think a lot of emerging managers use. Nikiel, I've never heard of that particular method before. Is that common? Am I behind on this? I think what's happened is a few factors that lead up to the situation between Andrew 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-pilled, more power-law-obsessed than ever before.

Starting point is 00:04:15 And so there's just a small handful of companies that, you know, GPs and LPs want to 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. But when you have that obsession over a small handful of companies, the sort of downstream effect is that, you know, people are so tripping over themselves to invest in those and find creative ways to invest in those and be a part of them 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.

Starting point is 00:04:58 And, and that's a mechanism for me to get potentially a fun going by enticing LPs. And so we have definitely heard about this. But it is for a very small set of companies such as Anthropic Open AI, Andrew. And again, maybe like 10 others that this phenomenon is occurring. And then the other sort of factors that lead into this are, you know, companies want to stay private for longer. And so, you know, you have to find creative ways to be part of these companies in the private markets versus them just going public. Another is the founders want as much cap table control as possible. And so unfortunately, these factors don't fit perfectly together, right?

Starting point is 00:05:42 They're at odds. and hence why you get dynamics such as what's unfolded between Andrew and Angelus. Okay, so here's the problem I see with that, because if you're going to stay private, essentially forever, and I was just talking to 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 want to 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, is you end up essentially locking up people's capital, what feels like forever or only, Michael,

Starting point is 00:06:18 at the whim of the 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? Yeah, I mean, I think if you're going to be buying into one of the six companies that Nikiel's 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

Starting point is 00:06:51 tender offers. And so that effectively is a public market for a private company. And I think that dynamic, that motion is a lot better understood now, competitive state, 10 years ago, and it's exactly, as Nikhil said, companies are staying private longer. 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 a dirty word. Yes. Why would you do that? And now it's a well, well used tool in the toolbox. And I think,

Starting point is 00:07:37 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 data bricks. 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. Back to the point that Nikiel said about being power lines.

Starting point is 00:08:07 law-pilled. I mean, this also applies to exactly what we're talking about here. I laughed at the Databricks comment because having spoken to Ali Godsey over the years ad nauseum 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 the second, but first, we're going to pay the piper. Dear friends, we hear at Twist are big fans of the Pplod PIN. We've talked about it on the show endlessly. Jason's an enormous fan. We wear them all the time as our note-takes.

Starting point is 00:08:37 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. We recommend the Plaud Notepin S. And if you want to get one for yourself, you can go to plod.a-u-d-plu-D-P-L-A-U-D-A-I-S-Twist. Use the code, twist, save 10%. Be cool like Jason or like myself and therefore never having my wife nagged 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

Starting point is 00:09:14 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 maybe just more liquid secondary markets 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 response.

Starting point is 00:09:43 So you're on the by side of this at times. One of the most important things you can do as a busy founder is stay focused. You need to prioritize the decisions and workflows that are going to move your company forward, not get lost in extraneous details and minutia. That's why the best decision you can make for your business is signing up with every. Every is the all-in-one platform for incorporation, banking, payroll, benefits, taxes, basically your entire back office. They're going to keep up with all the bookkeeping and paperwork so you can stay laser-focused on your next big product or hiring, features, customers, all that important stuff. If you're just getting started, they're going to handle your Delaware Seacorp and getting yourself a registered agent all with no legal fees and no delays.

Starting point is 00:10:25 And Every has worked with over 1,000 startups already. That's the kind of know-how and experience you can rely on. So head over to every.io and stop wasting time on stuff that isn't growing your company. That's e-v-e-r-y-R-Y. 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

Starting point is 00:10:57 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 have a strong conviction, high conviction that the company is actually going to be worth a lot more. So that that's actually the price discovery and how transactions get done. You know, I wouldn't say necessarily that either side is right more often than not, but secondary funds do perform pretty well. There are never going to be a five to 10x kind of return, but could they deliver a solid two, two and a half three times? Yes.

Starting point is 00:11:36 And we've seen that time and again over the past 10, 15 years. So, Nikiel, 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 market's pooling over there. What does that do to a fund of your size, $225 million in its 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? Well, I mean, first of all, our fundamental job is to get into companies at an early stage in our case that end up being in that power low basket down the road.

Starting point is 00:12:18 Of course. 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 ended up with shares in those companies by those companies acquiring our portfolio companies. And so then we actually have the chance of liquidity. You know, this is actually an interesting aspect of the information rights conversation as well, is sometimes we get real access to that information at a company that's acquired one of our portfolio companies, and sometimes we have zero, which is another interesting dynamic.

Starting point is 00:12:59 But I think the fundamental job we all have is to back those companies that are parallel companies. 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 get back $75 million, that for a couple hundred million dollar fund is actually quite meaningful. It is really not meaningful, though,

Starting point is 00:13:28 when you have a billion dollar fund. And so those are some of the dynamics that I think are really relevant to fund sizes, like hours. 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 11 Labs, you can actually do secondaries along the way and no one cares.

Starting point is 00:13:51 In fact, everybody wants you to do secondaries because then, you know, from the founder perspective, it's just one pocket going to the other. But, you know, if you're like a lead investor, like say a Sequoia or an Excel or, you know, whomever founders fund and you own 20% of the company, you really can't do secondaries because then aside from what Nikiel'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, say Sequoia, selling right now. And so they're...

Starting point is 00:14:22 Negative signal risk, essentially. Yeah, exactly. Whereas no one cares about the early stage guys selling. In fact, they encourage it. Make this work for me because on one hand, we see Andrew Roll stressing founder cap table control. And I don't think they're making that point only about super late stage hottest companies.

Starting point is 00:14:38 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 CapTable 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.

Starting point is 00:14:57 I think I haven't seen actually that much conflict, 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 the shes. And so, you know, I think as long as folks are communicating well and transparent,

Starting point is 00:15:54 I haven't seen that many problems with misalignment. Okay, so that's encouraging. Michael, one more question about this topic before we move on to M&A, but there's been a bevy of slightly vague posts from VCs over on X in the last a couple of weeks about a rise in fraud in the SBV secondary market. How much of that is smoke and how much of that is fire? Because based on what Nikiel just said, it doesn't seem that there's that much conflict, which to me sounds like a low fraud environment. 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

Starting point is 00:16:30 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've 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?

Starting point is 00:16:54 I'm sure it does. And there are people who have been sent to jail because of it. But I think they're just more like headline grabbing kind of, you know, tidbits. Yeah, because when SpaceX was going to list, people were like, oh, man, how many people bought essentially fake SpaceX X shares. And I was kind of waiting for those stories to bubble up after the IPO. I didn't see a single one. And so to me, it seemed like people were really over-indexing on a concern that wasn't there.

Starting point is 00:17:17 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, Nikil, I think you are an investor in. That's right. Yeah, we led the company Series A. I served on the board. 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?

Starting point is 00:17:36 and then we're going to talk a little bit about numbers. But start there, please. 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, Gramley, Coda, and now Superhuman as well, and sort of change the name to Superhuman of the whole company when Gramley acquired Superhuman.

Starting point is 00:18:01 And Cheshire, their CEO, has known Edwin and Alex, the founders of GPT Zero, the last couple years. The companies, you know, 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 GPTZero founders got really excited about was the opportunity to have a lot more distribution through superhumans distribution from their various products to tens of millions of active users.

Starting point is 00:18:29 And so while GPTZero, you know, it's publicly reported, they got to tens of millions in revenue. They actually never burned a dollar that we invested. The company's 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. And so that plus the opportunity to go built 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. So, Alex, I have a couple stories here. And I'm a personal investor in your fund, so I'm very happy for myself and for you, so thank you.

Starting point is 00:19:14 But, you know, we're also an investor in Sundana is a investor in Uncork. And one of the partners there is Tripp 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 Nikiel 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.

Starting point is 00:19:46 But the founder of that firm was supposed to get on a call, blew off the call. So basically Trip won the deal. Agree has an incredible new offer exclusively for Twist, fans, and family members. Go sign up at their easy to use all in one. contract to cash stack. And if you tell him Jason sent you, you're going to get 50% off for life. Agree is the number one fastest way to go from contract to cash. This means gathering all those e-signatures, the invoicing, the billing, the payments, and of course revenue recovery, no more jumping between four or five different platforms, just to write out your contract

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Starting point is 00:21:11 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. Yeah, but that's not financial pressure. That's familial pressure, which I've never seen come up in a case like this. Yeah.

Starting point is 00:21:35 I understand parents wanting their children to take money off the table to avoid owning Princeton and their lenders more money for a long period of time. But that's crazy. Nikiel, when this deal came together, were you in favor of it from the very beginning? As we talked about earlier, when companies are really working, they have the chance to be, you know, part of that power low basket. And so my initial reaction, you know, when we first started having conversation, superhuman was we absolutely shouldn't do this, we should go for it.

Starting point is 00:22:09 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 chance to be a big independent company, you know, we have to give that perspective to the founders. And so I, you know, I strongly, you know, voiced that opinion. And thankfully, we didn't pursue an acquisition a year ago. Instead, we did a secondary as Michael referred to. 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

Starting point is 00:22:45 to making sure everyone had the best outcome, possible here. And so that's what we worked, you know, closely together on. So I ask about your relative interest in the deal because we're seeing a little bit more of this. We just saw Versal. They bought Better Off, 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 Crunch Base showing Global Venture-backed M&A counts 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

Starting point is 00:23:25 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, and so forth, or the public said, and who's more interested in picking up startups today? And Michael, why don't we start with you on this? Yeah, I mean, I think we're a beneficiary. because we're in Cursor through Neo. And obviously a $60 billion exit is always welcome. They are outliers, but it shows how with power law,

Starting point is 00:24:01 a small firm like Neo can return multiples of their fund with one investment. I would say that given where we are on valuations and 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 $2.5 trillion market cap, it's less than, you know, what, 5%, it's low single digits to them. And you could argue that SpaceX is overvalued. You can 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 data bricks is valued at $150 billion for them to issue a billion or $2 billion,

Starting point is 00:24:48 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 were arguing that that basically was their R&D strategy. But you know, Cisco is trading at 100 times PE. And so they have the currency. Why not? Yeah, no, there are some advantages to be in 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 described. But you have that in the private markets now, right? I mean, open. AI, Anthropic, companies like that, they have, you could argue, overvalued currency,

Starting point is 00:25:24 but they're going to use it. Yeah. No, no. By that point, the overvalued currency part, yes, less liquid, but still very useful. 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, Nikol, 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 produce their overall human headcount.

Starting point is 00:25:47 So in your portfolio, who's getting the most kind of door knocks from other companies? I mean, I think that there is such a premium right now on talent because 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 so and then it is just hard to hire great people based on a set of dynamics. So, yeah, I mean, our teams 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's what a company like Superhuman wanted in the case of GPD Zero, along with, of course, the team. But, but, you know, there's a real business that they're picking up as well.

Starting point is 00:26:37 So it does feel, again, if I, I'm sure if I, if I leverage the models to ask about like, our M&A conversations and our team meetings and how that's trended over time. The last couple quarters has probably been the high watermark since we started four 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 acquires, which is an interesting data point that kind of matches the crunch-based data that you shed. Yeah. Are the prices being discussed attractive?

Starting point is 00:27:12 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? Again, of course, there's nuance in every situation. But I think the dynamic 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

Starting point is 00:27:43 what is that equity worth? 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 Anthropi 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 the main conversation 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

Starting point is 00:28:24 doing the acquiring? Because in both cases, that equity may not be really tied to the fundamentals of the business. Are you trying to say that the NASDA keeps going up every time the state of Hermos explodes and that's slightly confusing to all of us? It is a while time on how to value anything. 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.

Starting point is 00:28:55 It's just a, it's just a crazy time. Exactly 10 billion today, actually. I mean, if you were talking about Anderol, you know, Lockheed Martin trades at about $125 billion market cap with $75 billion of revenue. And, you know, and rural shares are trading above that market cap in the private markets. and, you know, Annerol 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 rewriting of enterprise software companies.

Starting point is 00:29:31 And, you know, you look at Meritex index. It's, I think, Ford revenue multiples are like at 3.6, 3.7 times. And to Nikiel's point, you have good companies that are trading at substantially lower, 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 it two times. I mean, that's crazy. It's legitimately insane. Every time we see a revolution in how software is built and used, one company ends up owning the infrastructure that everyone else depends on.

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Starting point is 00:30:57 C-O.com slash T-WI-ST. 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, a 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 revitalize 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.

Starting point is 00:31:40 And they were not going to buy Sierra, didn't bring Taylor back. And so you have also companies like Airtable, which were darlings. You know, their last round was at 11 billion. And which, by the way, Freestyle was able to top tick as a secondary. But, you know, a company like Airtable, other legacy companies, they have the customer-based. They have the workflows. They have the proprietary data. And so I think that's actually what's going to drive a lot of acquisitions down the road, as well as senior executives.

Starting point is 00:32:15 You know, I mean, I think Mark 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 going to see that as well as the acquisition of technical people that, you know, the smaller acquisitions are representing. All right. So we talked about workflows there. we talked about data. Let's get into that. So, Nikiel, we were talking about this before we jumped on the show. There's been a host of posts from intra-capitalists and founders in the last couple of,

Starting point is 00:32:47 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 Chad GPT 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 conversation has shifted from the founder and venture perspective to data being so important today.

Starting point is 00:33:25 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. 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 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 it's kind of a loop. Exactly. Data's having its moment in, you know, in the X eco chamber with a number of people

Starting point is 00:34:20 posting about it. You know, I think the interesting thing about data is 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, 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 every company

Starting point is 00:34:52 that sits on data that could be important and relevant to what's happening in AI. So that's just one dynamic to think about, which is that the company is like pure, Fully focused on data, there aren't that many of those that are huge public companies versus in the other couple key areas. And so you can argue that there's more white space there than in other areas. And then it does feel like what the labs are really focused on is data at the moment. You know, they've been, you know, there have been a number of projects underway at the labs to solve the energy and compute challenge.

Starting point is 00:35:33 And those are 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 McCor, 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, not just labeling of data through humans. Data licensing applies, for example, to real world data

Starting point is 00:36:15 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 pots of the stack. We have one of our portfolio companies that's growing the fastest, is a company called Protege, which is in that data licensing realm. And then, you know, I think, again,

Starting point is 00:36:34 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 them all's, because that is their secret sauce. So I'm pulling up protege here.

Starting point is 00:36:47 So how much to be accelerated in the last six months? Because if these people 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. Yeah, this is a company

Starting point is 00:36:59 that has, again, not been that public about how well it's doing, but in year two of its business is 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 Open AI. But you can imagine that there's a lot more of those types of deals that are happening. And protege is emerged as the leader in sort of facilitating those

Starting point is 00:37:50 types of licenses. 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 GPU? It's kind of the picks and troubles argument. Clearly, there's a lot of money who 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 capture when they often don't have as much historical customer data as your sales forces and hub spots.

Starting point is 00:38:17 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. Yeah. 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 SaaSpocalypse is overblown.

Starting point is 00:38:48 You know, I think it's almost hubris to dismiss all these companies that have the workflows, that have the proprietary data, that have the customer relationships, and to 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. Intercom is a great example of it. They did refactor their whole business.

Starting point is 00:39:13 We branded it as Finn and really went all in early. I mean, frankly, I think Owen was kind of stuck his neck out, frankly, on that point and ended up selling for Michael back to me up $3.6 billion? I think 3.3. 3.4. 2.3. Awesome. Yeah.

Starting point is 00:39:27 But the inverse of your point, oh, it's a great outcome, especially for a company that had, for a while, their stagnant ARR, I mean, is actually shrinking a little bit. Like, that is, I mean, that's coming back from the dead,

Starting point is 00:39:36 and I say that with respect as opposed to being a diss. Right. But your point about SaaSBocalypse being overblown, the importance of data, the power of workflows, I think about a company

Starting point is 00:39:45 that, as we all know, box with Aaron Levy, they have tons of customer data. They're expanding into workflows. They seem to be accelerating their revenue a little bit. I tracked their earnings. earnings more carefully than I should. And as of today, they're trading at a 3.4x trailing

Starting point is 00:40:00 price sales multiple. So is the market just systematically undervaluing data and its eventual value today as the private markets get it right? Yeah, I do think that. I mean, if you actually look at Salesforce, they're growing at 10 to 12%. So why is Salesforce that has all this amazing data? You know, it's a database company, right? Ultimately, CRM company. And They're only, you know, 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 Micron. You have, you know, I think VCs chasing after companies that are going from zero to 100 million in six months now, not 12 months.

Starting point is 00:40:51 And it's to the detriment of the companies that aren't growth. that fast, but yet are probably, you know, very well maybe building enduring companies. Yeah. And I think that's actually where the alpha is going to be made. Yeah, you could get on the bandwagon and go 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 the SpaceX,

Starting point is 00:41:33 Open AI, and Anthropic? That's all that people talk about. And it's, it's an important point, but I think they're missing the bigger point of what early stage venture are supposed to do. 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, venture capital stencil on the front of the building. Like, it's not, yeah, I mean,

Starting point is 00:41:56 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

Starting point is 00:42:07 because ultimately, if they become consensus, then there's unlimited capital coming in, right? Yeah. I posted this a while ago. It's like basically ZERP 2.0. Instead of the US government, giving all that money,

Starting point is 00:42:18 it's actually the platform firms that have pretty much unlimited capital. And that's why, were 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 a crazy.

Starting point is 00:42:34 And now I think we're right back to it. Yeah, I mean, I think, you know, you look at Nvidia, you look at their Ford P. It's like 24 times. So 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 the earnings has continued to be like amazing, right? Samsung just announced that they had $59 billion of EBITDA.

Starting point is 00:43:01 And, you know, it's just like, holy shit, where did that come from? You know, I think the biggest risk over the next 12th to 18, maybe 24 months, and no one knows is that suddenly that growth is not going to happen. There's a lot of catalyst in the market that could create major issues. and you can easily see NASDA going down 20%. Easily. Okay, before we let Nikolranven, I want you to tell me, I have my own list of catalysts

Starting point is 00:43:28 that could lead to such a correction, which I don't think actually would be bad a miss. But what are you looking at as possible tripping points? 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 star cluster that Oracle is working on with OpenAI, if their bonds are being

Starting point is 00:43:51 have even a higher premium now in order 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 musical chair stops, then you can

Starting point is 00:44:08 have a serious correction because then all the growth estimates are off the table and that's going to be a catalyst. One world that I don't know very well is the private credit And a lot of that is funding these data center buildouts. And I think, you know, if there's any hiccup there, the other thing, of course, people are talking about recently is like these leverage ETFs, right?

Starting point is 00:44:29 The three times leverage ETFs of these semiconductor companies, you can see where if that crashes, then retail takes down all the hedge funds that were long. And suddenly you have contagion. We've seen this movie many, many times over the past 30 years. You're not supposed to say contagion. just like you're not supposed to say recession. It's bad luck. I mean, you're going to curse us all.

Starting point is 00:44:51 All right, Niciel, we've been talking for a minute. Let's bring you back in. You know, the phrase that I think is on my mind as I think about what happens in the market is, you know, is not too big to fail as it was in, you know, some prior corrections. But it's too important to miss. Like there's a set of companies that just have to hit their numbers, beat their numbers on both top line and bottom. line. I actually worry more about the bottom line for a set of companies that are just consuming a tremendous amount of capital. And obviously, I think like Open AI 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

Starting point is 00:45:36 I think, you know, has a lot of predictability to their business. 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 a smaltly 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 hyperscalor level. So I think that will tell us where CAPX is going from the biggest buyers.

Starting point is 00:46:07 It'll tell us how much, you know, 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 cap-X plans away from at least a 10% correction, which I think puts a lot of pressure on the upcoming earning cycle. Because once again, here we are. Everyone's worried. And every single quarter so far, every hypersaler said, we're compute constrained and we'll be for quarters to come. And one day that won't be true. And that's, I mean, Alex, one really recent example.

Starting point is 00:46:38 And I mentioned it, Samsung reported like $58 billion of EBITDA. Yeah. Up from like a billion eight or something. like some astronomical increase year over year. It actually, the stock price went down. Eight percent. Seven or eight percent. It went down.

Starting point is 00:46:53 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. You know, every time in video reports, I'm like very, very nervous. Because even if they have an amazing earnings report, And then Nikiel correctly, you know, 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. What's the private market version of this?

Starting point is 00:47:29 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 an incredibly impressive company. But, I mean, Nicol, if they miss two quarters in a row, what happens to their valuation? I think the thing that worries me is less than and other companies missing on the top line. It's just a set of companies that require a ton of capital because of their burden levels. I think the ones that are scarier, like, you know, reports that Open AI needs to go raise another several hundred billion dollars. that is the thing that worry is to be much more so than

Starting point is 00:48:16 Okay, but but isn't there a direct connection here between the ability to finance that bill that you're describing and their revenue growth? Because, you know, once Anthropic hit like $64 billion run rate, whatever, you can kind of just double that for next year and then they'll have at least $100 billion in $27. Or you can do fun math that way. It's not that hard.

Starting point is 00:48:34 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 out the bend. Yeah, I think that's the key question. Like, how much are these companies overinvesting in compute to capture demand and how expensive that is?

Starting point is 00:48:55 And then what their margin is. And so, again, we shall see. But right now, the music feels like it is very much playing. Music is blaring. But it tends to blur before the speakers blow out. Now, on that point, I want to just talk about Chinese A.M 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.

Starting point is 00:49:28 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-tune or post-training their own versions of them. We saw examples like cursor using Kimi K2.5, I think. Airbnb used Quinn. The list goes on. Recently, news was out this week that the Chinese government may preclude the release

Starting point is 00:49:55 of future open-way models, essentially kind of the same fight we're seeing in the U.S. about accessibility to kind of cutting-edge AI. And my question, he kills, what does that do to start-up 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? 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.

Starting point is 00:50:27 And so that is a significant area of spend for them. 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 good news I think for them is that the non-frontier models at the close 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. And I think that is an option for a set of companies that, again, helps the margin conversation.

Starting point is 00:51:05 So, you know, I think obviously a key thing. for us in the US is figuring out how to have a vibrant open source ecosystem, open a set of models here. I think that's really important. But I think what is plugging the gap is that, you know, 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,

Starting point is 00:51:34 the frontier capabilities get expensive and, and will be needed for a set of tasks, but I think we can redirect a lot of tasks to these models that cheap up. Michael, that doesn't solve the whole problem, though. I don't think because there's been a lot of conversation. We saw Alex Garb from Palantir and a lot of other people begin to really beat the drum

Starting point is 00:51:52 about not using closed source models, be they 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 major labs, where does that leave startups? 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.

Starting point is 00:52:21 And, you know, economically speaking, you want to take advantage of that pricing delta between the open source models and the proprietary models. I think it's really good for the U.S. AI industry. I mean, I think that kind of pricing pressure is really good. You see a lot of startups working on orchestration layer and trying to figure out how to optimize which models you use when. And I think that kind of innovation is very important. And so I don't have any more insight other than that. But I do think from economic, you know, the free hand of the invisible hand of the free market,

Starting point is 00:53:02 I think it's really good to have that pricing pressure put on the proprietary models. Agreed. I mean, shout out Adam Smith and all sorts of, you know, invisible appendages. But I'm just worried, Nikol, that the models from Nvidia, the Nebatron family, that the models from Google's Gemma family aren't sufficient to replace what we have from Deepseek, from Zippoo, from Moonshot, from Quinn. 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 opening a nice margin for them, and they're just not going to have something to fall back on.

Starting point is 00:53:35 And to me, that seems like an almost structural risk in the startup market today. Yeah, I think you're right to be concerned about it. And I think the other thing here is just all of this requires teams that are capable enough of leveraging front models, of switching models in and out, of 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 work with either application layer companies that are using the close source models or just work with the Frontier Labs because they don't have the talent level to do anything else. 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 open AI.

Starting point is 00:54:55 I'm just disappointed that we've now said several times in this conversation that there's only so many companies that matter, only so many founders that matter, only so many researchers. It seems disappointing that we seem now back to Nikkel's earlier point about 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 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 Lord, give me some tokens. I think two things can be true, right? Like there's

Starting point is 00:55:50 there's a concentration of resources in power, the bigger companies are getting bigger, can coexist with it is easier than ever to start a company and it is more possible than ever for two people to build a business that gets big quickly and gets wildly profitable quickly. I think both of those things are happening before our eyes. And so it is an amazing time to go built. And, you know, it is an amazing time to be one of these massive companies that is only getting bigger. Yeah, you know, Alex, one of the things that we've had an idea around is this arms race to find younger founders. And in an ADI Native world, you know, everybody needs to be the first check.

Starting point is 00:56:38 And that also could mean younger founders. And you look at, you know, some of the groups that we work with, like Josh Browder, who is a Tiel Fellow. He helps on the selection committee. We have Corey Levy at Z Fellows. We have the guys from prod. You know, you look at companies that, for example, are like Neo. You know, they're spending time with university kids. And especially at Harvard, MIT and Stanford, you have, and Carnegie Mellon and some others,

Starting point is 00:57:07 you have kids who are actually want to start companies who have are almost fearless. Like, you know, one of the companies that we're in 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 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's actually what's very, you know, heartening and very exciting about entrepreneurship. So, yeah, you do have these big incumbents. They're getting bigger.

Starting point is 00:57:44 But you also have really smart kids who are, you know, fearless and are trying to build companies that are totally going to disrupt. And that is the beauty of capitalism. Gavin is the CEO vetched, I believe, right? Yeah. Yeah, we had them 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. Yep. I forget the time frame, but soon, which I think is going to be great for cutting inference prices overall if you're not into Cerebrus or Sanvenova,

Starting point is 00:58:19 which just raised a billion at an $11 billion post. 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 in question about why they picked that one. Now, Windbourne, 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, Nikiel, 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 nailing the right time, right market moment? Because I feel like they must

Starting point is 00:59:01 be just fending off customers. Yeah, it's one of the companies we're most excited about. And some of the characteristics here, I think, are interesting to come of a founders, which is when born collects its own data through its own weather. 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, it's a 50-person company based in the Bay Area.

Starting point is 00:59:41 And then on the commercial side, you're right that unfortunately, the cuts in the National Weather Service in the U.S. 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 models should get better. Unfortunately, there have been a lot of issues with. 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 U.S. government, for example, not only do we work with the National Oceanic and Ammospheric Association, NOAA,

Starting point is 01:00:29 we also work with the Department of War. And you can imagine there's lots of reasons for why weather data is important to both those departments. So really fascinating company. It actually is related to the data conversation we were having earlier because of its own data edge and moat there. And the one other thing I'll call out about this is the company was actually started back in 2019. 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.

Starting point is 01:01:04 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. 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 fleet of agents. And so a company that feels very well set up for the next 10 years. You get 10 points for the answer and minus 5 points for dodging saying climate change during your response. But still 5 points, not bad.

Starting point is 01:01:36 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 Nikiel. I love Nikiel. Right now, I would say Josh Browder. I mentioned him earlier. He's a TIP fellow. He has a company called Do Not Pay.

Starting point is 01:01:54 It's very profitable. And, but, you know, he has hustle. His average post money is $5 million. He's on the TIL selection committee. And so he meets, you know, these two. 200 kids who are in the final process. And that's an amazing pipeline of potential entrepreneurs. So, you know, I think Josh has done a very good job harvesting that.

Starting point is 01:02:17 And I feel like, you know, that 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. 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 YC, but, you know, getting into YC is kind of a credential now. Or becoming even a teal fellow is kind of a credential.

Starting point is 01:02:45 So you got to really suss out who's going after what for what reason. And I think Josh is extremely good at that. 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 if there's one thing that's true, it's building a company,

Starting point is 01:03:08 it's hard as hell, and it takes a really long time. Guys, we're going to leave it there, but I really enjoy 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 Nick Hill, where can people find your firm online? And is there anything else you want to shout out before you go? Yeah, just footwork.com. And I'm at nbt.nbhti on X.

Starting point is 01:03:29 And nbt.com is where I write as well. Fantastic. Michael, where can people find Sondana and anything else you want to add? Sundana Capital.com and my Twitter handle is MK.K. Rocks, which was my gamer tag from the early 90s and I use it for everything. MK.K. Rocks.

Starting point is 01:03:47 We're not going to stop now then. What are you playing lately? Call of Duty. At one point I was the top 10% in the world on that. But I don't play as much, but yeah, I like first person shooter games. I'm an old Quake guy myself, a big fan of Doom 3, but I've really branched off into factory automation games lately.

Starting point is 01:04:05 I can't help myself. Right. So good. Nikiel, do you game? Oh man, I used to. But now, like in high school, I played Warcroft 3 and I was high U.S. West with one of my best high school friends. But in this current zone where I have two

Starting point is 01:04:22 young kids and started a firm, it would be a bad situation if I was gaming as well. So I'm off. You just have to do it after everyone else is asleep and just cut back on your sleeping now. It works every time. That's the time to write and think these days. All right, guys, this has been an absolute treat.

Starting point is 01:04:37 This has been this week in startups. My name is Alex. We're back on Friday. We'll see you all then. Thanks for watching this week in startups. If you liked this episode, check out more. If you're a startup founder, Founder University Cohort 13 kicks off this fall.

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