Investing Billions - E99: How to Pick Top Decile Venture GP’s

Episode Date: October 1, 2024

Albert Azout, Managing Partner at Level Ventures sits down with David Weisburd to discuss how to spot unicorn founders early in Venture Capital, what separates great fund managers from the rest, and digging deep into the role of data in unpacking venture fund performance. The 10X Capital Podcast is part of the Turpentine podcast network. Learn more: turpentine.co – X / Twitter: @dweisburd (David Weisburd) @levelvc (Level Ventures) -- LinkedIn: Level Ventures: https://www.linkedin.com/company/level-ventures/  Albert Azout: https://www.linkedin.com/in/albertazout/  David Weisburd: https://www.linkedin.com/in/dweisburd/  – Links: Level Ventures: https://levelvc.com/  – Questions or topics you want us to discuss on The 10X Capital Podcast? Email us at [e-mail] -- TIMESTAMPS: (0:00) Episode Preview (1:39) Data-driven approach to investing and predicting top-performing managers (3:20) Building social capital and early investment indicators (4:38) Follow-on investments, market timing, and macro factors (6:33) Ownership strategies and discipline in seed investments (8:13) Offensive strategy and value-add for GPs (10:18) Evolution of Level VC's value-add approach (13:16) Flywheel effect in investment networks (14:31) Learnings from Coda Capital and systematic sourcing (16:03) Recognizing great founders and contextual quality of GPs (17:07) Fund size control, co-investing, and portfolio construction (20:28) Collaboration, differentiation, and venture capital insights (22:11) Closing remarks

What we really look for at the end of the day is a flywheel. You know, what is it about the investing behavior of the manager such that as they have more success, they're likely to get more success? And I think that comes in a variety of different forms. You know, one form is just specialization. If you have access to a particular network, you know, like SpaceX founders or aerospace founders, etc., you're going to develop an expertise and a network that's very beneficial to the next founder. There's definitely a huge bifurcation in the market in terms of like super high quality and the rest. It really starts with access because if you're able to detect and really understand what does a great founder look like, that's a repetitive motion that will

compound. I use a baseball analogy where you have single A, which is the lowest league, double A, triple A, and then you have major leagues. And a player could be very good at single A or double A and can be completely crushed at the major league in terms of fund size and round. And writing a 25 or 100 or 250K pre-seed check is very different than trying to lead a series A where you're competing against the multi-stage firms. I think the most interesting thing for a fund-to-funds investor that's focused also on co-investing is... Albert, I've been excited to chat. Welcome to 10X Capital Podcast. Thank you for having me. Thanks for jumping on. So you are co-founder of LevelVC. What is LevelVC?

LevelVC is a next generation fund of funds. We focus on building a platform for emerging VCs, which for us means funds in their early iterations focused on funds one, two, three, mostly. Funds are all pre-seed and seed, typically under 100 million fund target sizes. And so we have a strategy of fund to funds that invests and backs those managers. And then we also have a co-invest strategy that invests with managers in breakout companies as they get to Series B and beyond. You guys have a pretty substantive data set. What does your data set say in regards to investing in GPs? Yeah, so we collect data from a lot of different sources.

We look at private market data. We have our own data sources that we get as well. We have millions of profiles of people, business filings. We have scientific journals, a few other different sources. And what we try to really understand are the networks that are forming and evolving within venture. We believe a lot of the quality and centrality of GPs in their relative networks is a strong indicator of future performance. And given that these networks are so dynamic,

you're really trying to understand where managers are positioned, enables us to have a view on whether the manager will be in a place where they'll sort of outperform. And since the part of the market that we're operating in, typically fund manager, it's a sort of high dispersion of performance, and sort of smaller funds are riskier in a way, but there's the potential for outlier performance.

And so we try to really, you know, predict and understand is who will be in the top decile or top, you know, ventile of performance, you know, leveraging data, but also a lot of qualitative work that we do on top of that. When you look at these networks, are you focused on depth? Are you focused on breadth. What we do is we reconstruct the networks based on the data that we're getting, whether it's deal streams, you know, essentially transactions between investors or whether it's talent investments into founders, talent joining the company. And really there's a lot of ways to succeed with networks. What we do find is that having social capital and having sort of long durable relationships within the right circles is actually a strong indicator of performance. And we try to understand is like how that behavior takes place given the deal streams that that we're seeing. In our networks, you know, there's not only just the relationship between people, but there's also the notion of direction and the notion of strength. And it's continuously changing based on the data that comes in. And we see, you know, terabytes of

data. Say social capital, how does a manager go about building social capital? You know, it's what we find, interestingly enough, especially as a young manager, that you can tell a lot by the first few investments that they make. And of course, like a priori, we don't know if we don't have data. But you know, as we start to see the investing behavior unfold, we can quickly get a sense for where they're situated in the network. It's not to say that's the only thing that matters, but it's a really strong indicator retroactively in terms of what they're doing and where they're sort of placed in the network. And so we use that information to then essentially get a sense for where they're going to be in the future performance. As you know, in venture, things are very path dependent.

And so where you start in the network, whether let's say you're an operator that spun out to build a business, you have a network there, or whether you're an angel turned sort of fund manager, or whether you're a GP at a large firm. And so a lot is already embedded in what you've been doing and the networks you have. And so we just try to understand what's actually happening underneath the surface. You could tell a lot from the first couple of investments. What are you looking for in the first couple of investments? Even with the first couple of investments, we'll have a strong indicator as to the access

to both the co-investor pools. Are they creating signal for other co-investors? What are the co-investors either before them or sort of in the same syndicate? But also, what is the access to talent networks that they have? It's a signal for us. Of course, as we have more data, we have more certainty. But if you're trying to essentially find managers, discover things before others, or maybe things that others have not seen, it's important for us to get an early signal as soon as possible in the data set. And we can do

that with a few investments. How do you look at follow on? How should emerging managers look at follow on their portfolio? Yeah, so we get that question a lot. And I think most people have an answer like, oh, you should do this much follow on or this many reserves. I actually believe it's dependent on time and where we are in the market. And there are markets where, you know, the time between financing is slow and you need to allow your companies to mature a bit. And there's the ability to take more ownership in companies preemptively before there's a financing or before they hit sort of a milestone that that's sort of you can have proper price discovery. So I actually think it depends on the market and sort of what's happening these days, given that the time between financings is increasing and sort of the graduation

rates have declined so much. I think it's important for, you know, for managers to have a good amount of reserves because a lot of times companies just need more time to hit milestones. And since managers have such an asymmetry of information, they can kind of get a sense for, you know, for who can break out relative to the progress that they have. So I think it really depends on the environment, the market environment, and whether you want to be sort of more offensive or defensive. But in this environment, I think it's important to have a good amount of reserves. So there's a macro factor in terms of follow on, is there a macro factor as it relates to portfolio construction? I think so. I mean, we like to sort of our preference for portfolio construction is we don't want a portfolio that we, like sort of our preference for portfolio construction

is we don't want a portfolio that's too concentrated and we don't want one that's sort of too market beta. And so we think there's an optimal size between somewhere between 20 and 40 companies, depending on the strategy. I think what really matters though is just given the outlier nature of outcomes in venture, you want to make sure that the relative ownership

that you have in the companies is such that, you know, obviously should one be breakout, you get multiples of performance on the fund, multiple turns of the fund. And so there is like an optimal ratio between ownership and sort of fund size that needs to be maintained. And of course, in environments where there's, you know, better valuations, you can spread out a little bit wider and have more bets. But what we've seen and see and precede is like valuations have maintained, they're pretty healthy. And they stay pretty healthy, even though deal counts have gone down sufficiently. And so I think you just need to have a portfolio that's

sort of wide enough that you have enough shots at bat and not too concentrated that you're sort of overexposed to just uncertainty. In terms of the relationship of ownership versus fund size, give me specifics on what you're looking for. It's more of a rule of thumb. We want to make sure that should a company in the portfolio, a single company become a breakout, let's say over a billion or so in valuation, also given what we expect to have in terms of dilution, either a pre-seed or seed, we have some dilution expectations, etc., that it should return at least 1.5x, 1 to 1.5x of the fund with some notion of recycling, which actually is a very high bar. And so you want to make sure that the ownership is there in the companies. And I think in order to have really good ownership, you either need to be there first and lock in price

and sort of not get adverse selection, or you have to be very disciplined just generally in the market. And there's a lot to say about, you know, when we look at the fund managers, whether they've had pricing power over time, it's one of the metrics that we track, you know, whether like over time, there's been sort of a notion of pricing power or whether it's just been sort of market beta. Do you fall into the camp that one should be very disciplined at seed or are you more like a hot company? If it's a good company, you should pay out. There's a brand value to being part of really great company stories. And I think that that sort of translates into recurring social capital in that space. There's a lot of benefits that are not necessarily returns benefits to being

into really great companies. And I think that has to be considered, especially in a fund one. And we've seen that many, many times. And I think it's very useful. I do think there's a point at which valuations are no longer feasible and there's prospective returns that are just going to damage your ability to raise capital downstream. And we have $150 million pre-money valuation or $100 million pre-money valuation. The story is no longer access. It's more about you got into a deal at a very high price. It doesn't really tell the story. But I think there's benefit, there's social capital benefit to getting into really great companies early that may be a little bit more high priced. But generally speaking, the returns come from, you know, sort of good

discipline and investing. You want your fund managers to be offensive when it comes to seed extension, a bit of a contrarian view. Why is that? Most of what we do here in the firm is focused around technical risk versus go to market risk. To the extent that a lot of the dollars go to R&D and sort of executing against sort of R&D milestones. And typically we're in markets that are really, really, really large. And so it happens, generally speaking with more complex businesses that it takes, it's hard to predict when certain technical milestones will be hit. But there is an asymmetry of information that the manager has as to what it'll take as the company progresses to hit those milestones. And so if you know, if you believe that, you know, it's a six month or

one year timeframe that they need, then there's a benefit to taking more ownership at typically a similar price before sort of a big inflection. And that's what I mean by being more offensive. And then of course, there's the situations where companies break out and, you know, there's price discovery and there you just want to kind of like maintain your ownership. But the offensive situations are ones in which you can really have asymmetric returns. How do you add value to your GPs? We're focused on technology as the value add. We've collected a very, very large scale data set, which is complex to do because you have to take in very noisy data sets that are very heterogeneous and be able to map them, map entities and things like that. And these are very hard problems that I guess few people have solved. And so with that, we do a lot

of analytics on top of it and just try and understand talent, you know, trying to understand investors. And so what we've been doing with GPs is, you know, either they'll send us like an ad hoc data request, like we want to track this company, what are the best engineers that are leaving? We get those all the time, or we can enrich existing workflows that they have. So if, for example, they're getting a lot of inbound in their pipeline and they want to be able to understand what's high quality in that sort of inbound, then we can do that kind of enrichment. And then there's a slew of other things that we can provide for them, including tracking open source GitHub repositories for interesting projects that are taking off or research labs that are developing interesting,

highly cited research. So it depends on what they need. But what we try to do at the onset is understand the infrastructure they have, where they are in their journey of being data-driven. And then we have a process by which we unpack that and see where we can add value. How has your value add evolved since you started in Jan 2021? Yeah, I just think when we first started, we were new to the business and we had to learn a lot as well ourselves and sort of understand the nuances of what, you know, GPs need and where we can differentiate, you know, at the end of the day, like we want to be able to get access to constrained opportunities in the best GPs, you know, on the top quintile of VCs. And so we've evolved over time as to that. But what we found

was like the, we want to align our own investing process and what we build in terms of the capabilities and value that we have for ourselves with what we can offer others. And so a lot of that has been just exploring things around data and ways in which we can give managers an opportunity to augment and to have a sense for things that they may not see. If they needed our help sourcing, that's obviously adverse selection. But what we can do is given a particular sourcing motion, how do we unlock or give them enough coverage such that they can see everything? The best LPs have a sandbox that they like to play and know exactly what kind of fund they're looking for.

What are you exactly looking for? Everything we do is typically under 100 million fund target sizes. I think the small fund itself is a big thing. You know, like your fund size is your strategy sort of mantra. I think that's important to us. We do believe in small funds generally. We like early VCs, young ones, in terms of like where they are in their life cycle. So funds one, two, three versus sort of, you know, sort of more established firms.

Within that bucket, what we really look for at the end of the day is a flywheel. You know, what is it about the investing behavior of the manager such that as they make more investments, they're more likely to make better investments? Meaning that as they have more success, they're likely to get more success. And I think that comes in a variety of different forms. One form is just specialization. If you have access to a particular network, like SpaceX founders or aerospace founders, etc., you're going to develop an expertise and a network that's very beneficial to the next founder.

There's others, you know, there's sometimes it's just community centric. You know, you have a community of individuals that are maybe like top engineers, or you have sort of a way of accessing a set of people that's unique, that sort of scales over time. And we have that with some of our funds, but we look for that flywheel because what we don't want is just, you know, you've done these deals, but then you can't, you can't replicate the same activity in the next, you know, cohort of deals. And so that's something that we look for sort of intuitively in the firms. And then on top of that, you know, we do a lot of work on studying the portfolios that they've been investing in, studying the, sort of the founder set, starting the philosophy. You know, we do want to make sure that the GPs

have an investment philosophy, you know, cause a lot, a lot of them do deals, but not all of them have sort of an overarching philosophy, because you can't always determine success by outcomes. It's really by process. And so we do a lot of work on understanding, like, you know, the philosophy and how they think about underwriting and markets and thematic areas, if they have original thought. You mentioned the flywheel in funds, just to unpack that, you're essentially saying that, to use your example, you have a former SpaceX engineer. He or she spends all of his time in space technology. He or she gets deal flow from space technology, which makes them better investors and continues. That's the flywheel that you're talking about. It goes back to networks. Typically in networks, generally speaking, and in economies, there's notion of increasing return. And there's these

positive feedback loops that occur in the economy, which is why you have these sort of extreme speaking. And in economies, there's notion of increasing return. And there's these positive feedback loops that occur in the economy, which is why you have these sort of extreme behaviors in terms of market prices and things like that. And networks form in a similar fashion. So you have this notion of sort of the rich get richer over time. And what we look for in that flywheel is if you're able to access a network that as you access that network, you're more likely to access a network even deeper. And that's what we're looking for is that sort of behavior. It's somewhat nuanced, but at the end of the day, we're looking for this sort of increasing returns as they start investing versus just having a bunch of deals that they don't look like there's an order to them.

Yeah. Something that I see over and over the most successful, the top 0.01%, they just continue to compound their benefits. And it's one of those things that sounds easy, but is difficult in practice. And you have to say no to a lot of things as well. Congratulations, 10X Capital podcast listeners. We have officially cracked

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content. Thank you for your support. You spent four and a half years at Coda Capital. What learnings do you bring to your position at Levels? Coda was an amazing experience for me. It was actually my first experience investing institutionally as a VC. We had a methodology for investing, a philosophy for investing that I sort of hold in my head in terms of being able to really understand a product, a team, a market. But I think just from an ecosystem perspective, one of the things that was challenging was really just keeping a tab on the ecosystem and really understanding where should we build relationships and how should we source and what's happening? And what are the trends that are happening? What

are the niches that are forming? And that takes a lot of work. And also it's very difficult to do because it's a very opaque industry. And so that was something that I realized was, how do you build a systematic way to source the best opportunities and understand where the best opportunities are

and develop thematic focus areas that make sense within some period, some timeframe. And that challenge was, it resonated with me. And so when we started Level, we wanted to be in a situation where it was more about picking than sourcing. And really, if you have a good understanding of what's going on

and you can sort of focus your efforts and your networking in areas where you think they'll be the most value, it's a much easier problem. Not that it's easy at all, but it's a much easier problem. We do believe that that starts with data. And the availability of data has increased even since my time at Coda and before, like there's really just been an

exponential increase in the amount of data, both private markets, but just around sort of technical contribution communities and things like that. And we just feel like there's an opportunity to potentially get edge from that and to see things that maybe others don't see. That's like sort of the thing we believe in the ethos of the whole organization. How much of being a good picker comes down to seeing what great is meeting those first unicorn founders at the seat stage and having that standard of excellence early on? I think it's the most, it's the most critical thing. There's definitely a huge bifurcation in the market in terms of like super high quality and the rest. It really starts with access.

If you're able to detect and really understand what does a great founder look like, you know, that's a repetitive motion that will compound. It doesn't compound forever, but it compounds for quite a while. And so that's what we look for. And we believe that you can get a sense for that very quickly in investing behavior. But you couldn't do that unless you had a complete ecosystem view of what quality is and where is it located, and how to benchmark one quality firm against another around similar metrics. Quality is contextual, not only on the entrepreneur level, but on the GP level, probably every GP that you come across is certainly top 10, probably top 5% in society,

but maybe if they're only in the top 5%, they're not investable. There's a context to that, to that quality. What do you wish you knew before you started at Level? You know, I think when we first started, one thing is just is having more control, or at least understanding where a fund manager's fund size will end up. You know, because sometimes what ends up happening is that it balloons, especially in the period of time when we started investing, there was a lot of ballooning of fund sizes, and we didn't have much control over that activity. And so I think that's one thing is really just to have a GP that is very thoughtful about portfolio construction and sizing. Because

the really smart GPs understand that it's really, it should be all about carry and that there's an optimal construction relative to the strategy that they're pursuing and relative to their capabilities. But sometimes, you know, obviously it's appealing when you get a lot of capital coming your way to balloon the size with the expectation that you can maintain the same quality for a size that's much larger, which is very difficult to do. So I think that was a big lesson for us. And we had a few funds that sort of ballooned larger than we would have liked in that period of time. And, you know, in retrospect, we wouldn't have done that. That's sort of one big learning as well. I mean, the other thing is just, you know, our models have gotten better over time. We're very

happy with our portfolio. We're happy with all the managers. you know, our models have gotten better over time. We're very happy with our portfolio. We're happy with all the managers. You know, our models have gotten better over time. We have new ways of looking at things. I think we've refined our approach. We have much more of a brand presence and we get a lot of inbound. Our just quality over time is just getting better and better. And then at the end of the day, we want to be the first call for new GPs. You need to really be associated with the best and being that first call.

And that's something we, of course, want to keep working on so that we're seeing things before they go to market. The last thing is really around the co-investing. I think the most dangerous thing for a fund-to-funds investor that's focused also on co-investing is adverse selection. Typically, you're going to get opportunities in a very reactive way. And if you're seeing it, the first question is just, is that what the company does? But literally, why am I seeing it? What we believe is that you need to have a really good understanding of the portfolios preemptively, have value that you bring to the GP and value, you know, essentially also to the entrepreneurs over time, such that you have a really good sense of what quality is before they go out to market and you can preempt some of those situations. You know, that's something that we've been working on for quite a while. How do you suss out whether a manager is going to scale their AUM? Most managers aren't going to tell you. So what have you found best practices to predict

this? We literally just ask them, you know, one way we do it is just sort of ask them, you know, what's your vision for the firm? What will be the size of your next fund? How are you thinking about team composition? You know, how are you thinking about strategy moving forward? You can get a sense really quickly. And most of them are very honest on what their, is in terms of growing and scaling the firm. There's many that we speak to and they say, look, we really just want to stay at a range that we think is doable and feasible. And that's actually a very big criteria for us, that they're very introspective and intellectually honest about whether they can compete as the fund size gets larger. Because there is this quantum leap. I don't know exactly what size it is. It's probably around maybe 40 or 50

where you have to start leading. And the game theory, of course, changes in the market in terms of your ability to actually compete and win allocation and not be adverse selected, especially when you're competing not only with peers,

but also with large multi-stage firms that have big platforms. So there has to be that intellectual honesty there. The knowledge, I use a baseball analogy where you have single A, which is the lowest league, double A, triple A, and then you have major leagues. And a player could be very good at single A or double A and could be completely crushed at the major league in terms of

fund size and round. And writing a 25 or 100 or 250K pre-seed check is very different than trying to lead a series A where you're competing against the multistage firms. What do you believe that other fund of funds do not believe? The biggest difference I think we've seen, and we collaborate, it's sort of an interesting world, is that you have a lot of people you collaborate with. You're not often competing for allocation against them. And so we spend a lot of time talking to other LPs, whether they're fund of funds or whether they're sort of more institutional investors or even a lot of family offices that are investing in this area. And we try to collaborate a lot and help our funds raise as well. I think what makes us very different and why we get a lot of questions coming our way is really the data angle. Typically, like when you meet a manager

for the first time, even if you look at their presentation and their track record, you know, which either is either not applicable or non-existent, is you have a very difficult time unpacking and understanding whether this is a good investment or not-existent is you have a very difficult time unpacking and understanding whether this is a good investment or not. And especially as you go earlier in this sort of fun life cycle, it's just almost impossible. And there's a lot of studies that show there's just not even a correlation between the early IRR and sort of the asymptotic IRR of the firm. And so since we have an angle which helps us unpack the manager in a lot of different ways using sort of market-based data, a lot of people come our way and ask us, what do we think about this manager? And what does

your data show? And that's sort of one piece of it, which I think is critical. And over time, we should also have our own flywheel in terms of getting more and more data, more network data. The other piece of it is the whole ethos that we have with GPs is quite different. We're not just treated only as an allocator, because we're also builders. It's a small nuance, but when they talk to us, we can go very deep into the nature of LLMs or what we think about the market or the technology infrastructure with regards to gender AI or other areas. And they really appreciate that lens and that angle. And when they look at our demo and our infrastructure, they feel like there's a good synergy between us. And I think this new generation of GPs, it's a younger generation. They're very switched on. They want to see often another kind of LP

around the table. Who are the most thoughtful institutional investors that invest in the venture asset class? I think some of the endowments are really good. I think they have a good sense for... Not all of them, but some of them are really, really good in terms of their investing behaviors. Not all of them go down to this level in terms of like the sizing of funds and all that. But we've seen some really good ones. There's actually a lot of very smart family offices, family offices with investors that we've seen as well. Whether it's family offices for some of the well-known sort of large GPs that are very just in the know and have a good sense for talent and quality. I think those are really, really smart investors.

And then, you know, there's a slew of other groups that we've interacted with as well. And also on the fund to fund side that are super sharp and, you know, they have a good sense for what's a quality manager. But we have a set of people that we just like interact with on a regular basis that we think are really good. Albert, this has been a fascinating interview. What would you like our listeners to know about you, about Level Ventures or anything else you'd like to shine a light on? Yeah, we want, well, we want to be the first call for emerging VCs and we want to be the best at what we do and really build an infrastructure that we think will be durable

and deliver returns for LPs and really just deliver value for GPs. And so that's what we're trying to build here. We have no other agenda besides that. So we're hoping that we can do that over the next few years. Thanks for listening to the audio version of this podcast. Come on over to 10xCabot Podcast on YouTube by typing in 10xCabal Podcast into youtube.com and clicking the subscribe button. On the YouTube version of this podcast, you could see the graphs,

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