Glenn Solomon of Notable Capital joins Nick to discuss 3 Multi-Billion-Dollar Exits in 1 Year, Lessons from Airbnb, HashiCorp, Slack, and Square, The VC Case for Staying Small, and the Battle Between Open-Weight vs. Closed Models. In this episode we cover:
- Identifying Unique Investment Opportunities
- The Impact of Fund Size on Investment Strategy
- Challenges of Overfunding and Market Dynamics
- Growth and Real Success in the AI Era
- The Role of Hyperscalers and Frontier Labs
- Public Market Sentiment and IPO Considerations
- Future of Venture Capital and Notable’s Strategy
- Investing in Anthropic and Market Dynamics
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0:17
Glenn Solomon joins us today from Menlo Park. He’s the managing partner at Notable Capital, where he leads the firm’s cloud infrastructure and AI practice. Over more than 25 years in venture, Glenn has led investments in companies including Anthropic, Airbnb, HashiCorp, Slack, Square, Zendesk, and Versal, and has helped guide 14 portfolio companies through IPOs and billion-dollar acquisitions. Glenn, welcome to the show.
0:49
Hey, Nick, it’s it’s a pleasure to be here. Thanks for having me.
0:51
So, Glenn, you’ve been investing for nearly 30 years. What do you believe about venture today that you would have rejected 10 years ago.
1:01
That’s a great question. You know, like you said, I’ve been I’ve been doing this 30 years, and I’ve I’ve come to realize during that tenure that the best opportunities arise when when computing paradigms shift. You know, I saw the mainframe and mini computer give way to client server architectures, the emergency internet, the rise of mobile computing-each of these shifts created a lot of disruption and laid the groundwork for startups to emerge. You know, as a venture capitalist, if you played those shifts right and you bet in the right companies, you did great. In the 2010 era, about 16 years ago, the cloud really emerged as the next competing paradigm shift. And if you would ask the Glenn of 10 years ago, I would have definitely said at that time. I remember saying at that time that the cloud shift is absolutely the biggest shift I’m ever going to see in my lifetime. It was an amazing time to invest, and along with mobile, which it really was kind of intertwined with the cloud. My partners and I invested in some great companies. HashiCorp was born in that era. We invested in a five-person company at Series A and rode it through a 20 billion plus IPO, an ultimate sale to IBM. My partner Hans led around in Rednote at a $60 million valuation back then, and we just sold some shares, if you can believe it, at a $70 billion valuation, so that company’s grown more than 1,000x, and thankfully we still own a bunch more. We led a Series A and a company called Streamlit, sold it two years later to Snowflake for a billion dollars. You know, those are just a few. Like it was a great era, but if you ask me now, obviously I was wrong about the cloud being the biggest shift I’d ever see, AI is literally one order of magnitude, if not more, larger than the cloud. It’s a very exciting time in the venture capital space, and I’m sure we’ll get into it. But our performance at Notable has reflected the conducive nature of the environment. Our funds are really hitting on all cylinders.
3:03
So some of these super cycles are relatively predictable. Others are not. Like you were an early investor in Airbnb, right? I don’t think anyone necessarily said that people would be sharing their homes or sharing their cars, you know. So how how did you catch things that maybe don’t map to consensus, large scale tech paradigm shifts like the internet or mobile or cloud?
3:38
Well, so to parse that question a little bit. I do think you know, Airbnb, amazing set of founders and an incredible company, but Airbnb doesn’t is is never born unless you have mobile computing becoming an important shift and and and trend in in our industry. You could say the same about Uber, for example. And those those two companies are frequently grouped because, you know, they created a new way for property owners to share the benefits of that those those in those cases, you know, homes or cars with others that we’re looking to share in those assets. Those don’t happen if people can’t connect in a regular, liquid, coordinated way. So when I say computing shifts, oftentimes these shifts give opportunity to new startups in existing spaces where they where you can see startups disrupting incumbents, but also in new spaces like in the case of Airbnb. Yeah, you just couldn’t have had a a service like that before you had mobile. And allowed people to really have at their fingertips the ability to search for a place to stay.
5:06
It’s a good point, very fair point. So you know the the GGV split rebrand well documented at this point. My question for you is: What did starting Notable allow you to change about the way your team invests.
5:24
Yeah, so we we launched Notable two and a half years ago, and so in many ways we’re we’re a startup. But as you allude to, you know, we we were the U.S. team of GG Capital, GGV Capital. We were founded 26 years ago in 2000. So we we have a lot of history as well. And for those who don’t know, we split from our colleagues in Asia in 2023. It was amicable. We still have a great relationship, but with our former partners. But geopolitics, you know, dictated that we separate. There’s a lot we were doing as GGV at our time as GGV that we’re leveraging, and you know we learned a lot. One thing while we’re a multi-stage firm, most of what we do is early stage. Seed and Series A represent about 75% of our deals, as notable. This allows us to build a high conviction, concentrated portfolio. We own over 10% of our companies on average, and unlike many firms today who are investing their entire funds in one year and continually reloading, we we’ve learned the value of pacing and and time diversification, and so we’ve stayed disciplined and plan to continue to stay disciplined, like two and a half to three year pace. But I’d say most importantly, as notable, we’ve really leaned into our core sector focus. We’re overweight what we call software infrastructure, and AI is having a huge impact on this space in a good way. These infrastructure companies are built to solve the needs of technical folks and organizations, be it the software developer, the AI or data leader, the security leader, and this has been a great area to invest. The 20 companies we’ve invested in so far in this most recent vintage, as notable, about 75% are right down the middle of fairway in this infrastructure category. We’re also investing a minority of what we do in areas we we consider like where AI is meeting the prosumer, the consumer, and also the physical world. These are exciting areas, but we’re being measured and careful in these spaces because Frontier Labs, while while they can be an accelerant in these areas, they can also be a competitor.
7:49
So, you know, Glenn, the hot thing today is asset aggregation, right? The old the old $1 billion fund is the new $10 billion fund. So, so why is a $650 million fund the right size for Notable?
8:05
I love that question and you’re right. Like it feels like today almost every VC founder and LP I speak to somehow believes that more capital is a sign of a better company, you know, a better investment, a better potential return. And look, AI is creating the need for more capital in many examples, but I firmly believe capital is not a competitive advantage. And companies that do more with less capital are going to outperform they have in the past, and that will continue. And the mega VC funds that are pushing huge amounts of capital into companies themselves are going to underperform, and many of the under these overfunded companies are going to fail to reach potential. Look, we think bigger outcomes in tech should drive bigger returns for LPs, not just bigger funds for GPs. And and look, I 100% believe bigger outcomes are part of today’s market. You know, if I think a decade ago, the most valuable company on the planet was Apple at about 630 billion, and I can remember thinking, “Wow, there’ll never be a company worth more than a trillion dollars. Today we have 10 public companies, actually more than 10 public companies. Last time I checked, with valuations over a trillion, and there are obviously more coming as as the the IPOs come for some of the frontier labs. But if you’re an LP looking to invest, you know, 1020, $50 million in a venture capital fund, a fundamental question I think you need to be asking is like, do better funds drive better returns? It’s a bigger fund, sorry, drive better returns, and I don’t, I don’t think that’s a good bet. It’s it’s it’s simple math. You know, ours is a 650. Million dollar fund, we’re investing at seed Series A. We can drive outsized returns in a market where the outcomes get bigger, particularly if we own enough of the right companies. By nature, like the bulk of the capital that we’re investing is invested early, so we can own big chunks of the companies we invest in, but if you’re a $10 billion fund, you know, almost the math dictates you got to write big checks. You’re going to come into companies later at much higher prices, and it’s going to be much more difficult to own the right percentage of the companies that ultimately produce great outcomes. And we’re seeing this with our current vintage. You know, our initial fund after we split is a 2024 vintage at 650 million in size. We’re sitting in the top 1% of all benchmarks that we see for this vintage right now. We’re over 160% net IRR, nearly 4x gross, and that’s across. You could take our best investment away, and it’d still be over three and a half x gross. So it’s not a one hit wonder kind of thing because we again, given our size, we own enough and have bet on enough the right companies. We can really produce great returns. And I think if we were 10x our size, if we were a $6 billion fund, we’d we’d by definition have had to have written much larger checks into the companies that we’re in and probably others. We wouldn’t have been able to be as highly concentrated, and maybe we’d be sitting at 2x best. So I think just in our own little laboratories as a as a test case, we’re just able to do much better, you know. And if I look, I look across our companies that are driving the returns, whether it’s Anthropic or Fal, Vercel, Quince, Databricks, you know, these are the the types of companies that can drive great outcomes, and we fortunately own enough that we can earn big multiple on 650 million. Look, and you know, if you’re an LP and you got to put 500 million to work, I get it. Like we’re not the right fund for you at 650 million. We’re not going to take that much from any one LP. So you’ve got to look for big funds. But I think anybody with you know appetites in the 10 to $50 million range should be looking at funds our size and not the mega funds. I just I just think the math dictates that these funds are going to struggle. These large funds will struggle to perform well.
12:34
What do you think breaks first when a fund gets too large?
12:38
It’s a good question. I think you know, look, we’re a small, tight partnership. We work as a team, and we have huge amounts of focus. I mentioned our sector focus, that allows us to say no way more than we say yes. And you know, when when we want to do something together, when we we decide we want to make an investment, we will swarm everybody in our team. All the partners are going to be adding value to the process of selling. Our platform team, you know, is is heavily involved in our pre-sales process, and we’ll start to add value to companies and founders even before we invest. We’ll get founders who’ve worked with all of us to call into founders we’re trying to sell, and it’s working. You know, our our win rate right now is 84% We’ve invested in 24 company 20 companies. We’ve put out 24 term sheets. That’s probably the highest. If if you injected truth serum into the partners, Nick, that you talk to from other firms. I don’t think anybody would tell you their their win rate. Honestly, is as high as has that
13:45
gone up over time? Because you’ve been at this a long time. It it is
13:50
as high now as it’s ever been, and I think in large part it’s because we’re working. You know, I mentioned we’re although we have 26 years of history. We are a startup, and we are swarming like a startup. The only other firm I see gang tackled the way we do as consistently is Sequoia. They do it very well, and I have a lot of respect for them. And it’s not that other firms aren’t great, but when you get large, it’s very natural. The only way to manage with 15 partners, 20 partners, 25 partners is to start siloing and having sub funds. You know, and and and larger funds tend to act that way. There’s as much competition internally as there is externally for good deals and allocations and deals. You know, if you’re a founder who’s on your third or fourth board member from a larger platform fund, or you’ve had to balance, you know, competing interests from the same fund family but from their sub funds as to who’s going to get allocation in your next round. You know, and. Talking about,
15:02
you know, I want to ask you about raising too much money. So we just saw an exit this week, right? Airtable sold to Bending Spoons, and like on the order of half of the transaction size was cash that Airtable still had from their fundraise that was unspent, and so the question I have for you is like, you know, what what’s the earliest sign that a startup has raised more capital than it can productively deploy?
15:31
You know, I want to just double click on Airtable. I’m glad you brought it up. It’s a great example. I mean, Airtable was a phenomenal business, and you know, and a great product, right? I’m much more familiar with the product than than I am the business itself. But from the outside looking in, great business. And if you look at the early investors in that company, it was financed pretty normally. What I’d say normally in the early rounds, and I think you know from memory, two of the earlier VCs in that company, Caffeinated Capital, Ray Tonsing, I think did did the seed there. Ray’s great and very disciplined, and is in a lot of good companies. We’ve done a few deals together, and CRV I think led an early round there. And CRV, you know, I think it would be a poster child for kind of this this conversation we were having about fund size. They’ve kept their funds disciplined in our size range. You know, I’ve talked to some of the partners there, and they they had a dalliance at one point in their life with larger later stage growth funds, and they couldn’t make it work. They just, and so they’ve retrenched, and I think view the world similarly to the way we do, which is, if you have discipline and focus and fund size that makes sense, you can make big return. And I think their returns have been very good. And in Airtable, their return is probably pretty darn good, but if you look at the rounds post that, this is a company that, as you say, raised way north of a billion dollars in total, and I’m not going to name the names of the funds. You can go look, but some of the bigger funds, very smart people at these funds. I’m not anything against any of them, but in this case, I think they got their money back at least. But they way overpaid and put way too much money into this company. And unlike a lot of other businesses, and again, I don’t know the founders at Airtable. But to your question about what happens when you overfund a company, oftentimes what ends up happening is the company feels the need to spend that money to try to justify the valuation. You know, in this case, I think the valuations on Airtable went from you know a couple 100 million early to multiple billions, and then over 10 billion in the last round or two. Yeah,
18:00
that’s right.
18:00
And so they need, you know, it. So some management teams take that money and say, “Well, the VCs didn’t invest for us to not give them their money back. If they’re investing at 10 billion, they want us to be worth 2030, or 40 someday. The only way to do that is for us to grow really fast for a really long time and get really big, and even if our metrics aren’t working so well, even if we’re spending money and not seeing the return, we better spend it. We better keep going for it, and that happens time and time again. And what ends up happening to most companies who shouldn’t have raised that much, who shouldn’t have tried to tempt fate and go against what the metrics were saying, and and keep going and keep trying to get bigger and more valuable. Most companies squander that money and end up in a situation where they have to fire sell or go out of business and and create you know big potholes for the investors in those companies, in this case, it looks like Airtable’s team said, “Well, great, we’ll put the we’ll take the money, we’ll put it on the balance sheet, but we’re not going to spend it. So they had more than a billion dollars when they when they sold, and they stayed relatively disciplined and built a nice business. Sold it for what was it, 1.3 billion or so. They probably you know in in a normal market they never would have raised those last few rounds. They didn’t need the money, and they would have, you know, the early investors would have done well, and there never would have been this this influx of capital at prices that were not justified. But this is happening time and time again across companies today. And look, there’s a lot of enthusiasm about AI. I am enthusiastic. I just told you I was, and I think there will be bigger and bigger outcomes. There’s good data that suggests, you know, that the outcomes keep keep getting bigger in venture capital, but that really doesn’t. The math still doesn’t work with these. Massive funds, and then the massive investments they’re making into most companies, because most companies won’t be able to achieve those big outcomes. I’ll tell you, like I just, you know, I spoke to a very smart LP who mentioned, you know, that they appreciate that we’re staying disciplined with our two and a half to three year pacing, but this LP said to me, “Well, one of our other funds that’s a mega fund that we really like just came back to me after one year, and they said that they came back after one year because they saw 10 once in a generation companies in the last year, and they felt like they had to invest in every one of them, so they did. And I bit my tongue and didn’t say anything. But there’s no way I don’t, you know, I’m not naming names, but there’s no way that any one fund found 10 once in a generation companies in the same year and invested in all of them at prices that made any sense, and so these one-year vintage class funds are just there’s going to be problems. I don’t know exactly when, but there will be there will be return issues on on a bunch of these funds.
21:13
Yeah, I feel like a lot of a lot of these companies, if you give them capital, they’ll find a way to spend it, and you know try and grow into the price. You know, kind of a fuzzy.
21:25
If we see, you know, the return of the lavish launch party offices and swag that’s over the top, those are bad signs. A real story, and and this is kind of like VC firms raising too much money. I’m aware of VC firms that that have spent a whole bunch of money getting celebrities to come hobnob with founders, fly founders to exotic destinations to play pickleball. You know, for pickleball tournaments. These are real examples. You know, serious founders don’t take this stuff seriously, and yeah, you know when when people have money, they spend it, and I don’t think it’s being spent very well.
22:08
So so let’s talk briefly about growth and real growth versus not in building real companies. So there’s kind of a buzzy tweet going going around from Harry Stebbings, you know, my podcasting counterpart across the pond, and he was saying that going from 1 million to 4 million in year one, and four to 12 in year 212, to 30 in year three, and 30 to 75 in year four is just not interesting. This is not, you know, something that’s fundable in today’s environment. And you know, he’s catching heat. I think some people may believe believe what he’s saying. You know, I’ve had companies with tremendous growth that I sent to you know great tier one investors that said if the growth isn’t 1,000x. We’re not interested. So, would love to hear your take on the example that he presented. You know, is that company interesting? Is it not? You know, what’s your position on growth in this AI cycle we find ourselves in?
23:20
Listen, you know, I mentioned some of the companies we’re involved with, and and the fact that we’re we’re our current fund is clearly in the top 5% probably top 1% of all funds for its vintage class. We didn’t get that way by investing in slow growth companies. We have invested in some extremely high-growth businesses, you know it’s well documented. Obviously, Anthropic has been been has been crazy, and we could talk more about it. But like companies like Fal, in our most recent vintage, are growing at leaps and bounds. Whisper Flow growing incredibly, incredibly quickly. Huge fan. So we we love growth. We love growth. I do think that there is a disconnect, and and you know I’ve I’ve had the great pleasure of being on Harry’s podcast, and and and Harry’s done a great job. I think you know when you’re a venture capitalist, you have to try to read the future as best you can with limited data, in particularly in the early stages where we’re investing, right? And so, I do think that it makes sense to look very closely at growth and be very sensitive to slight changes in in the in you know in in the slope of the line of growth and to try to divine what a company could look like in the future, but you know as a firm and. Personally, I’ve been doing this long enough, where I’ve I’ve been involved with many companies that haven’t just raised lots of up rounds, but have actually achieved real exit exits through IPO and public trading, exits through M and A at significant prices. I was had the good fortune of selling three companies last year, calendar 25 for a billion or more, and you mentioned earlier. You know, I’ve been involved in many, many companies that have gone public, and many IPOs, sorry, many M and A’s, and have increasingly been working with a few of our companies on on secondary selling strategies. So I feel like I’ve seen a lot on the exit front, and what I would say is there is a disconnect between fast growth and markups, which many venture firms and venture capitalists seek, and they should. But the difference between markups and ultimate success as a company, and exits that justify some of those markups is more difficult to divine early on. And we just talked about Airtable. Airtable would be a great example. At some point, somebody wrote a check at you know 10 or 12 billion, and every you know, and the round before that was done at probably 5 billion was like I, I did my job. I’ve got a double in a short period of time, and this company’s going places. It’s a big up round. You know, unfortunately, years later, it turns out like that was, that was not a great job, and that’s a perfect example of where this disconnect can exist. So while I believe, and I think Harry’s right, growth is at a premium today, and you know we tell all our companies getting in the token path is very important. We can talk more about what that means and how you do it, but that really means ensuring that your growth is very much linked to the growth in in token generation, token consumption going on right now, which is like nothing I’ve ever seen, and I think will continue for some time, and ultimately building viable long-term businesses that have good margin, that can create cash flow, that could protect against you know competition, which inevitably comes, and that are in big enough markets to matter. And so you know, it’s it’s not an easy job, and I I I so I don’t disagree with with Harry, but I think there’s a lot more to getting it right than just getting you know finding a company that’s growing early on at fast rates.
27:54
Yes, yes, there’s a real product market fit. There’s phantom product market fit. There’s, there’s like,
28:02
there’s like, there’s startup venture fit, and that only that only solves for so long.
28:08
That’s right. That’s right. So, so Glenn, if if LPs offered you twice as much for your next fund, what would you have to change?
28:17
Well, probably the first thing we’d have to change is my partners would have to cart me out the door, or maybe they’d have to try to keep me? Because I I would say guys like that’s not what we do, and you know let’s let’s let’s not let’s not let’s not take twice as much money as we’re investing now. You know, we’d be flattered by the interest, and we’d think long and hard about the LP base that was offering it, and try to make sure we, as we always do with our LPs, you know, we have a very open dialog about what we’re trying to achieve, what they should expect from us, and and make sure that we’re aligned, and you know they should expect from us that we’re going to invest over two and a half to three years. We’re going to try to run a concentrated book. We’re not going to chase and invest in companies at you know very very very high prices in our first round of investment and not own much of them. Or if we do that, it will be a rare occasion like an anthropic. We better be right when we do that. But in general, that’s not our strategy. And so, as long as the LPs understand what we’re doing and believe in us, and we have kind of a sympathetic way of looking at the world. Then we want to work with them, and you know we’ll be happy to take capital from them. We’ll try to size it right for the market. I always say, fund size should be a byproduct of fund strategy. And not the reverse, and so fund size is a byproduct of strategy. You got to look at your strategy first, and as I’ve tried to articulate, our strategy is to be concentrated, and you know, and to be early. And so, you know, we’re we’re very happy to see the the larger funds come into some of our companies in later rounds and pay big prices and fund what in some cases are pretty capital-intensive models. That’s great. In some of those rounds, we’re bringing our LPs directly in, and so that’s one way that LPs can get more exposure to our companies. So even though we’re going to stay disciplined on fund size, if a if an LP really likes what we’re doing, and they want to put more capital to work in the companies we’re invested in. We can facilitate that in later rounds for them to come in through direct investing, co-investing, etc. SMA type programs. So we are working with them, but you know, expect us to keep our strategy.
31:00
Okay, so so Glenn, I’m going to give you a few data points here. SVB data shows that deals over 500 million now represent 47 of all VC dollars. Correct. That’s up from yeah. That’s up from 10 between 2010 and 2020. Another data point: half of all venture dollars invested in 25 went to 0.05% of deals. Also, the top decile of funds by size accounted for more than 71% of capital raised in 24. So, you know, taking these things into account, we’re in a strange and unique and new world. If we look out five years from now, what impact do you think these figures may have on on startups in venture?
31:58
Look, it’s it’s a great question, and we mull over it. I think one of the one of the data points people are using as logic to support this kind of very very high concentration and move into the mega funds and the mega rounds that are happening because there are so many mega funds is some data that David Clarke tracks over at VenCap, which I think is really good data. And what he’s shown is the outcomes keep growing. So I think it’s like every five-year increment over the last several years, what he’s seen is that the top 1% deal of all venture outcomes in those five years is kind of doubling in terms of price and size, and so I believe the 2025 to you know as yet, or well, a 2020 to 24 five year increment, the top 1% those deals, you know, that one percentile deal represented like a 10 billion ish dollar outcome, which was up from 5,000,000,005 years prior, et cetera, and so he’s positing that the next five years, 25 to 29, are going to be 20 billion type valuations of the top 1% and so I think that logically people say, “Hey, if if there’s, you know, they’re bigger outcomes, then I can invest in bigger funds. You know, I think the average LP is has been around long enough to remember those. I’m sure, Nick, you remember the the Kauffman Foundation reports that you know were so prevalent a decade ago that said, “Hey, billion dollar funds are bad, and $500 million funds or less are where all the money’s made in venture. And obviously, that narrative is completely out the window. And I think one of the one of the logical underpinnings of smart people who are choosing to invest in large funds and manage large funds is this view that hey the outcomes keep getting bigger. The problem is when you go one step underneath the data and look at the number of outcomes per those five-year periods, they haven’t changed at all. It’s about 2000 outcomes for every five years. So, you know, the top 1% of 2000 is 20 outcomes every five years that are at that size range, or about four per year. And if you’re investing a big, big fund over one year, then you’re really indexing to only one year’s of outcomes, because presumably you’re going to do this multiple times, and that’s what’s happening. And you know, so even if somebody caught every top 1% deal in a year. In their fund and own 10% of it at exit, which not easy to do. Look at Airtable, right? None of those big funds owned 10% of Airtable, and they they but they still put a bunch of money in. But if someone happened to own all four and 10% of of each at 20 billion, you’re talking $8 billion. Well, that that doesn’t even pay back a $10 billion fund. So you’d have to get a lot of the 90th percentiles exits as well, a lot of them, and the math doesn’t work. Back to our earlier question about size, the math doesn’t work. So five years from now, like at some point, this dam is going to break, Nick. And I think you know people will retrench, and I’ve I’ve seen this happen before in different ways, and you know that the the what will be in vogue at some point in the future, is what probably should be in vogue now, which is hey, like funds that you know the the money the real money is being is made in venture capital in the earliest stages, and funds that are disciplined in size. We talked about CRV earlier. I think Benchmark has done a good job. I think we’re doing a very good job in this space. Are going to do very well. The
36:22
math matters, you know. Math part of math, unfortunately,
36:25
matters. Physics, laws of physics don’t break.
36:28
That’s right. You know, part of my challenge with these huge asset aggregators, and granted, they’re they’re much smarter than I am, but they’re fishing in a pool. Maybe there there’s 20 deals per year that makes sense to do, and they got to pick. To your point, they got to pick the right four and win them, and and
36:51
own enough of them, which means and
36:53
own enough.
36:53
Yeah, it’s a tough it’s a tough business as is. I mean, we’re very proud of the results that we’ve achieved. I should say. You know, we’re not perfect. We’ve had over our last five fun vintages. If you look at our notable performance, we’ve actually we’ve produced three top, clearly top 10% of their benchmark. You know, their their vintage benchmark top 10% fund performance three of the last five, which we’re very proud of. Now we’re not five for five. We got work to do. We’re not perfect, but I am glad to say, like you know, it was the the the the fourth ago and the third ago that were the ones that weren’t as good, so the last two have been great, and I think that shows that we’re learning and getting better and better. And you know, I’m very optimistic for our future as well. But you know, this is not an easy business, even with fund sizes that are in the right range. So it is going to be real difficult, even though we’re in a super cycle with AI, and their outcomes are going to be huge, and there are going to be some truly once in a generation kind of companies created now. And I think we’re, you know, we’re we’re excited to be in some of them. You know, this is still a tough business, and the you make it much much tougher on yourself as a firm if you raise too much money.
38:26
So let’s let’s talk about one of the big ones that you got in at what what looks like a very nice price, right? Notable invested in Anthropic at a $61.5 billion valuation. What do you think the market was underestimating at that price and continues to underestimate.
38:45
Yeah. Well, I can tell you that at at 58 billion pre 61 billion post whatever it turned out to be, like this was by an order magnitude plus the highest valuation I’d ever paid for a venture capital investment, so and and you know my partners felt the same way. This was this was really a difficult decision. It looks simple and easy in hindsight, but go back to November 2024 when we began in earnest to evaluate the opportunity, and you know, Anthropic was a about a 900, rounding up to a $900 million ARR business. It had grown from 100 million about 12 months prior. So, you know, I’ve never seen growth like that. It was awe-inspiring to see a company go from 100 million to almost a billion in a year in ARR, but it was still very much a second player in the frontier lab space to OpenAI. The the stretch plan they gave us that we were evaluating was to get to 3.8 billion by the end of 25. Gross margins were low, and the cost of training models was very high. So it was a tough investment to make at that time. What we loved about the company was first we thought the team was excellent. Chris Narao, who’s the CFO, we had known, gotten to know very well during his Airbnb days, where he ran Corp Dev, and we’d tracked and and kept in good touch with him in in the ensuing interim years, and when he joined, that meant a lot to us, because one of the biggest risks we saw with the business was the cap the the capital need to keep training frontier models, and you know we’re a $650 million fund. There’s no check size we could write large enough to protect anthropic if things start not going well, and this was in our mind in late 24, and and and so Krishna joining plus us seeing that all three hyperscalers had now backed Anthropic and were on the cap table with meaningful positions in the company that told us, hey, like there is unlimited capital now at you know at the ready to continue to back Anthropic in its development, and if they miss a cycle, there’s enough good people on this team that one of those hyperscalers is going to acquire this business, and we’ll, we’ll, you know, we we can take the risk. Um, and so that you know, all those things plus the fact that this, you know, that for us, Anthropic was very focused on the enterprise, which is which which was strategic to us, and we love the strategy and their vision around getting deeper and deeper into high skill verticals. They articulated that to us. They’ve since done that really well. And look, I’d like to say that we saw them not doing the stretch plan of 3.8, but more like 10, and you know a funny story. Even late last year, late 25, we were talking to the finance team, and they said, “Look, it’s been a great year. The plan for 26 is 25 billion by the end of the year. But Dario is going to be really pissed if we don’t get to 30, and you know, and and that was in like think December of last year, and here we are in July, and they you know they zoom past 30 in a few months, and you know they haven’t reported numbers in a little while, so I won’t I won’t divulge or or or guess at anything today, but you know, rest assured, they’re a lot bigger than the last number they reported. So they they’ve grown much much faster than even they realized they would, and it’s you know it’s it’s been and will continue to be an incredible investment for
43:17
us. So so the most formidable competitor that is both a hyperscaler and a Frontier Lab is Google. Absolutely. How do you how do you think about that? Right. You’ve got a Frontier Lab investment in Anthropic. How do you think about a company that’s doing both? Is that a significant advantage, or do you think that that will limit Google’s ability to compete.
43:42
Well, I personally been a Google shareholder for really almost since the day they went public. So you know, with my own dollars, you know, sometimes actions speak louder than words. Nick, I’m I’m a tremendous fan of what Google has built, and I’m very optimistic about their future as well. I think Google is an Google’s an incredible business. It’s it’s really a series of businesses. What I think is most remarkable about what Google’s done over the past 12 months is how quickly they were able to turn a weakness into a strength. You know, there they obviously have more search traffic than any other company, and the risk I think that they saw and everybody saw was, hey, if the chat, like if the Chat GPTs of the world give better responses. People are going to move, and how quickly they have improved. You know how quickly they they’ve basically developed a competing Gemini, which didn’t ask users to change behavior. But gave users a much much better experience rapidly that in many ways matches or exceeds what you can get from ChatGPT. It’s pretty incredible in my mind, and I think that was big move number one. I think the other thing that they have going for them is their infrastructure, which is a direct result of them being in the cloud business. We’ve talked about the importance of hyperscalers, the importance of hyperscalers, and and you know they are one of the very biggest and most important hyperscalers, and they’ve invested in their own hardware, and so they’re they’re in in in great position, I think, to manage and control their own destiny. They succeed when Anthropic succeeds. They succeed when OpenAI succeeds. But they’re going to succeed when their own models and own AI efforts succeed as well, so multiple ways for them to win. I don’t think them winning means Anthropic can’t win because this pie is so large. But both both companies, I think, are doing amazing things right now, and they will ultimately be competitors. But we’re in a part in the market where that almost doesn’t matter.
46:25
So, so let’s talk about open weight models a bit. Why or why not does this spell doom for the Frontier Labs, like an anthropic? This is
46:37
like the question of the day, right? And you see the public market just undulating back and forth. Sentiment swings wildly, and you know, I neglected to mention the week we invested in Anthropic was the the first Deep Seek week. So, you know, Hans, Orin, Jeff, myself, and our entire team got lots of questions from our LPs in the entire. So only
47:07
imagine
47:07
months. Like, what were you guys thinking? Deep sea gonna take over. And look, our view then, and I think it’s you know even even higher conviction now, is that the growth in AI, and the best way to measure that is token generation, is like nothing we’ve ever seen before. And so, forgetting about which model drives which token for a second, just tokens as a whole and the infrastructure behind tokens is growing so fast; it’s exceeded even the most wildly optimistic expectations now, month after month after month. I mean, you know, Dell, who’s pretty close to this market, had to raise their their late 2025 token expectation by 57x, and then Goldman Sachs more recently came out with their own view of token generation through 2030. That’s I think they came out with a number in May, and here we are in in July, and they’re already half. They’re they’re they’re too low by half in the their first month out of the gate. So it really is tough to predict, and the only thing we’ve seen is upward revision, and I think that’s going to continue for a while. The just demand is so high for intelligence, and the opportunity. You know, people keep discovering more and more ways to use this stuff in very productive ways in companies and in consumer use cases. So I think like you can’t, you you know, you can’t be anything but very bullish on long-term token. Now, where you could have concerns if you’re in the frontier labs is like, hey, are they the most expensive tip of the spear token? And what happens is open weight models, you know, from from China or you know from the U.S. start to emerge that can perform a lot of the intelligence tasks adequately that are being done today by frontier tokens, and I think that’s fair. But it loses sight of the fact that the pie is growing so fast. So yes, like open weight token pie share will grow, but total pie is growing so fast that even if, and we see this in the data from a bunch of the gateways like Vercel’s AI gateway, like it’s not like demand for or share of total tokens month to month is falling off a cliff for the Frontier Lab. It’s it’s anything but doing that, and at the same time, the total n, the number is growing so fast that we’re seeing still very dramatic growth at the frontier labs. So I think you know we’re and and there’s real opportunity for frontier intelligence. People keep discovering new areas, but whether it be you know I don’t know space travel or biotech and pharma exploration. You know, drug discovery. There’s just so many areas where frontier intelligence will outstrip what humans have been able to do. And I think as long as we have those areas, there’s going to be a huge opportunity, a huge market for the frontier labs, and you know, sky in my mind is really the limit for how big they can get as a result.
50:51
So, public market sentiment swings wildly on AI, right? The bulls and the bears keep the the pendulum swinging far and fast, we invest in companies. They sell product to customers. We buy and sell equity, right? And so our ultimate customer is the public markets in many cases.
51:12
Yep.
51:12
How do you think? You know, how do you reconcile the swings, the multiple, you know, arb and and and just wild ups and downs, and you know, think about this destination of ultimately IPOing in a market that is you know very hard to to pin down in the current climate.
51:44
So one of the things, so we have a lot of experience taking companies public, and you know what we tell our companies when they go public is, you really need to understand your business, the drivers of your business, you need to have visibility and predictability because you need to have messaging that you can communicate over and over again to the public market that keeps your story simple, understandable, and predictable for what inevitably will be, as you say, Nick, like ups and downs in the cycle. So you want to make it very easy for investors to own your stock. You don’t, you know, the the the the more left and right turns in the storyline, and the more changes you have to metrics you want people to track, and you know the changes in guidance that you give, or not beating guidance, but you know changing what you want to focus on, you make it hard for investors. The more you do things like that, you know, and and even for the companies that are completely, you know, that that have it totally nailed, there’s still ups and downs in stock prices. You have to be ready for that. The good news for us is, look, we’re we’re involved in some great businesses that are thinking about the public markets. You know, we talked a little bit earlier about Vercel. Versel is a business that is very clearly in the token path. They’re very scaled. They are developer focused company. They’ve positioned themselves squarely in the AI market. They have two or three of the most popular AI products on the planet for developers, and they power some of the most important AI companies on the Vercel platform today. Their business has accelerated dramatically over the past six months, even at scale. And for them, you know, I think they have all the ingredients. They’ve got they’ve got the customer names, they’ve got the management team, and they’ve got the financial performance and predictability in that performance that is really going to attract and excite investors, and again make it easy to own. It’s a story that they they will understand, they will have confidence in, and I believe the company will be able to deliver quarter after quarter to kind of keep earning that confidence and have it grow, and that is the recipe for success as a public company. So you know, I think there’s a good chance they’ll be public next year. Look for that one. You know, obviously, there’s a lot of scuttle about both Anthropic and OpenAI. You know, Anthropic being a portfolio company of ours going public in the near term. And I was talking to some bankers recently who told me, “Hey, you know, those two companies will have will be looked at very differently than.” SpaceX, SpaceX has been like a you know SpaceX is a is you know all deference to Elon Musk and I think it’ll do really well over time most likely because he’s just such a force of nature, but there’s so many different things in that basket. Again, it’s not so easy to own. The only thing that’s easy about is it’s Elon Musk, but it there’s just so many moving parts, and I think the Frontier Labs, you know, their their challenge will be to help people understand what their businesses really do and how to think about them and how to measure them over time, since we haven’t seen anything like this in the past. At least public investors haven’t, but I think if they do that well, and knowing Krishna as CEO and the team he’s putting together, I have a lot of confidence in them. You know, they should they should do well. It may take some time, but again, if they articulate a clear story, deliver quarter after quarter, and make it an easy thing to own. People will ultimately flock to it. So that’s my recipe for success,
56:08
Glenn. If we could feature anyone here on the show, who do you think we should interview, and what topic would you like to hear them speak about?
56:14
Great question. I think I mentioned Vercel, Guillermo Rausch, founder of Vercel, I think would be fantastic to talk to. He’s a great interview. He has been in the software business a long time, and up with just about anybody else I’ve met. I can only think of one other founder with whom I’ve worked who has as much his finger on the pulse of what developers really need, want, and will use in the future, and it’s just so interesting because developers and now the agents that developers orchestrate are creating so much of the product and magic that we see from AI, and Guillermo really has his finger on that pulse, so I think he’d be a really, really interesting person for you to have,
57:06
Glenn. What book, article, or video would you recommend to listeners?
57:14
I’ll give you two books. My all-time favorite book is Sapiens Yuval Hari is a it’s it’s just a it’s an amazing book that I think is grounding as a human to read because it it takes you all the way back to the time when Homo sapiens you know roamed the earth and and but we’re not the only species that could have evolved and kind of what ensued next, and how we got to be who we are today-just fascinating stuff. The other book I’d say is is very different. If Sapiens talks about the beginning of mankind as we know it, nuclear war: a scenario, which is by Annie Jacobson is a very scary book that posits how humanity may end, and I think it’s an important book to read, both because it’s fascinating and very detailed, but also because like it could happen. And I think the more people that read it, the less likely tragedy like that would happen. And so I hope people read it.
58:22
Glenn, do you have any habits or behaviors that are a secret weapon?
58:28
My wife would say I have a bunch of habits that are the reverse of secret weapons. I would say mine
58:34
as well.
58:35
Yeah, I would say that one thing that I do that I feel like I’ve done more and more of, and it’s made me better and better at my job. Is I just have developed a informal and usually over text thread with most of my founders, and when you do that, you can start to talk about things that are not always exactly on topic with respect to whatever the the most important matter of the day is at the company, but you get a little bit more of a well-rounded conversation going that can be helpful in times when things get tough. So I think that’s been a force multiplier for me, and hopefully for the founders with whom I’m communicating, and something I hope to keep doing in the future.
59:28
And finally, here, Glenn, what is the best way for listeners to connect with you and follow along with Notable?
59:34
Oh, thanks for asking, Nick. I think you know I’m relatively active on X, so DMing me on X works. LinkedIn is, I’d say, I love LinkedIn, but and you could try direct messaging me on LinkedIn, but that’s a little. I’m a little less. I just get get bombarded on on LinkedIn, and so it’s a little more difficult to get through the noise sometimes. See the best the best thing to do is if you’re able through connectivity through a network to get a warm intro to me or or someone else at Notable. That’s the best way to get to us. And look, we’re relatively open. We try to be available, particularly if you’ve read some content we’ve put out or listened to you know this or other podcasts or videos that we’ve done, and you find it interesting, or you feel like there’s reason to talk because of the topics or the company you’re working at or working on, and where our interests lie. Like we we we we welcome the the advance, and we’ll try to find you as well.
1:00:38
He is Glenn Solomon. The firm is notable, multi-time Midas lister. This is a bucket list item for me. So, Glenn, thanks so much for sharing your time with me and the audience today.
1:00:50
Thank you, Nick. Great talking to you.
1:00:52
All
1:00:57
right, that’ll wrap up today’s interview. If you enjoyed the episode or a previous one? Let the guest know about it. Share your thoughts on social or shoot them an email. Let them know what particularly resonated with you. I can’t tell you how much I appreciate that some of the smartest folks in venture are willing to take the time and share their insights with us. If you feel the same, a compliment goes a long way. Okay, that’s a wrap for today. Until next time, remember to overprepare, choose carefully, and invest confidently. Thanks so much for listening.
