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Google PodcastsAaron Holiday of 645 Ventures joins Nate to discuss The Second Wave of SaaS, Using Software to Scale a Venture Firm, and Predictions for the Future of Venture Capital. In this episode we cover:
- Creating an OS for VC
- Statistical Predictors of Success in Founders
- Early-Stage Investing: Art or Science?
- And more!
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0:00
Today we welcome Aaron Holiday to the show. Aaron is the co-founder and Managing Partner at 645 Ventures, an early-stage firm headquartered in New York that has invested in startups that include Fiscal Note, Iterable, Squire, and many more. Prior to founding 645 Ventures, Aaron was a software engineer at Goldman Sachs, a business analyst at GFI group, and associate at Gotham Ventures. Aaron, welcome to the show.
0:24
Thank you so much.
0:25
I’d love if you could walk us through your background and your path to venture.
0:30
Yeah, happy to walk you through my path to venture. So I’ve been building and designing software for over 22 years now. And it started really in undergrad. So when I started undergrad, I actually ended up going to school a couple of weeks early, because I was a part of this program called Student Support Services. And I met a mentor there. His name was Mr. Reese. And Mr. Reese asked me about my major. And I said, Hey, you know, I’ll study math. Let me say, Well, why are you going to study math? And what are you going to do? I said, Oh, I’ll be a mathematician. And he said, Well, what are you going to do as a mathematician? I was like, I don’t know what that petition does. But like, I’m sure I’ll be very good at it. And so he said, Okay, what you need to do is go back to the drawing board and read the entire course handbook. If you want to study math after that, then you’re good. So I read the entire course handbook. And I came back and I said, Hey, you know, I want to study computer science. He was like, Well, why do you want to study computer science, I said, well, the entire curriculum is quantitative. So I knew I would do well. But most importantly, it looks like a shift is happening. Because this was in 2000. In the 90s, I remember going from a typewriter to a word processor. I remember kind of going into chat rooms and discovering and meeting new people. And I said to myself, well, if this is what software is, and if software is built by code and the core principles of code that’s quantitative, this is something I want to be a part of. So I ended up studying computer science did really well, and then ended up working at Goldman Sachs on equities program, trading desk as a software engineer immediately after school alongside have some PhDs in artificial intelligence. And so that was just a fantastic, amazing experience to just build new technology in finance. And after several years of that, I was recruited to a firm called GFI group, which is an inter dealer broker that trades derivatives. And they wanted me to come in and help architect a system that will allow us to trade foreign exchange option derivatives electronically through something called a fixed protocol. And so we did that. And we altered the way the products were traded. And then I sat back and I said, Wow, if you look at the leaders of these financial institutions, none of them are technical. But over the course of my career, the Alpha was being generated from software. So I said, Okay, I need to go to school and get a business degree, marry it with my computer science background, and then maybe I can run one of these financial institutions. So I ended up learning about venture capital when I went to business school at Cornell, because I was running the BR Venture Fund, which is a student run venture capital fund, as a part of the business school. And it was there that it really functioned as an apprenticeship into the venture capital business for me. So I met Howard Morgan, Doug Leone, Ben Horowitz, Scott Cooper, these people kind of were just opening up their arms to me, and just kind of being kind of very free with their time to help me understand kind of how the venture capital business works, and why software was such an important component of it. And so that’s kind of how I got exposed to the venture capital business. And then when I finished Business School, effectively been doing and working in the venture capital industry since then. Got it. It’s interesting that you have a background on public equities. But when you became exposed to venture, you know, that ultimately became your path, I guess, going into business school. Did you know that you wanted to pursue more of the private markets versus the public? Or what was that transition in thinking? Yeah, that’s a really thoughtful question. So when I went into business school, I did not know I wanted to go into venture capital. Believe it or not, I didn’t know what venture capital was, which is crazy, right? Because I was working in public equities, which is on the other end of the spectrum of venture capital, right. But I never thought about company formation, that these companies that we were building algorithms for the hedge against like these public stock, it had to start somewhere, right. And so before I started business school, I was in a program called MLT. It stands for management leaders for tomorrow. And that program helps people of color think about, you know, why Business School is a good fit for them. And if you go to business school, what are you going to do? And so I was visiting different campuses, and I visited HBS, and I met this guy named Jose. And Jose was kind of running the Latinx affinity group. And he asked me, What did I want to do? And I said to Jose, I said, you know, I’m coming off of Wall Street. Software is playing a major role in driving value, but software engineers are not running a company. So what I want to do is help companies understand how you use software to scale and run an investment firm that can help companies do that. And he said, Oh, you want to do VC? And I’m like, What is VC? Right? And so I didn’t even know what venture capital was, even though I was in high finance. And so it was that moment where I started to investigate venture capital. And it became very clear to me that this could be a perfect fit, right? Because you’re talking about finance, which is something I know, as well as technology. So there’s VC investors invest in software, which I thought I had a leg up on, because I was a software engineer. So I continued to look at business school programs. And the Cornell program was quite appealing because it had that student run venture capital fund, called br venture fund. So when I went in, at that point, I knew I wanted to do venture capital. But it wasn’t until I kind of talked to some people about what I thought I wanted to do. It’s and this guy Jose described venture capital to me, and I just started to lean in ever since.
5:56
So you graduate business school, you found 645. Be curious first to hear where the name comes from. And then I’d be also curious to hear what the investment thesis is at the firm?
6:06
Yeah, yeah. So 6-4-5. It is an exchange code. Exchange code is a three digits in the middle of a phone number for an area in Martha’s Vineyard called Chilmark. And so my business co founder, Nnamdi Okike, he grew up in Boston, and he and his family would go to Martha’s Vineyard, when he was a kid to vacation. And so when Nnamdi and I met each other, and we decided we will start this firm together, he was suggesting that we call it 645. Because it was a place that was near and dear to his heart, it was a place that represented family. And I said, I’d love this, because it’s a number. And when you saw the number alpha, numerically show up at the top. So I could start going to mark as being here too. But I like the idea of having a number as the name because if we’re on a list of 1000, VC funds at a conference or something, our name will be at the top. So that’s kind of how we ended up making a decision. And then my wife and I, and our family actually now go to Martha’s Vineyard every summer. Awesome. So that’s kind of where where the name came from. Got it, as far as the founding of 645, and why we decided to do it. For me, founding a venture capital fund was kind of the biggest economic opportunity of my lifetime, specifically at the early stages of venture capital. And the reason I say that is because I remember when I went to work for Goldman Sachs, and myself, and all of my peers who were on Wall Street had to read all of these crazy books, more money than God when genius failed liars, poker, the partnership kings, a capital, all of these books, right. And these books were about the formation and founding of these kind of very large juggernaut financial institutions like KKR, Goldman Sachs, you know, Blackstone, BlackRock, et cetera, long term capital management, which kind of it since going out of business that came out or when genius failed. And I always had the same sentiment after I read these books. I was like, man, it was so easy back then, because the market was incredibly inefficient, structurally inefficient. And these firms are built in a way that it took advantage of these market inefficiencies. And then they kind of built on top of that. And now there are these kinds of very large financial institutions. And I always thought I would never see anything like that. Until I graduated Cornell and got into the early stage venture capital business. It was kind of one of the most structural inefficient business models that I had ever seen in industries that I’ve seen. And I started to think back I said, Okay, if venture capital is a subset of private equity, venture capital has to be the final frontier as it relates to alternatives. So if you looked at all of the other alternatives, hedge funds, private equity, growth, equity, private equity, um, they were very mature, and very institutional, but venture capital was still kind of very boutique. At the same time, there was a sea change happening. So the rate at which companies were being formed were outpacing the networks of general partners in our associate teams, because of the complexity of the code was becoming easier to cost of creating something was coming down to your ability to deploy software to a consumer or enterprise was becoming a lot easier and faster because of the cloud. And so what that did is kind of accelerated the rate of startup formation, to a point that it would overwhelm I thought would overwhelm the small boutique venture capital operations. So I said, there has to be a way to kind of do this better. Secondly, when you look at deal flow from a venture capital firm, back then when we started the fund, even still to this day, it’s primarily driven by networks, but networks geographically constrained based on where you went to school, where you worked and where you live. But the formation of billion dollar companies were happening everywhere. And Florida you had Chewy – billion dollar company, Qualtrics – Utah billion dollar company, and if your network cannot be augmenta in a way to see opportunities that can become billion dollar companies that are outside of your network, then you’re at a structural disadvantage. More so in the future, especially when the denominator, the number of companies that are being started in the venture capital industry is growing so much, that getting lucky becomes harder, right? Because the sample space is so much bigger, plus it back and I said, Oh, wow, I think this is the biggest economic opportunity in my lifetime. Because I believe that in a future venture capital funds can run on top of operating system. So I started to think about what that operating system would look like how that software operating system would augment traditional venture capital networks, how would that operating system kind of help venture capital firms kind of communicate information better and faster? How might we kind of use software to create value for portfolio companies? So I started to kind of sketch all of this out. And I ended up meeting nom de who was speaking the same language, Nabil had come out of Insight Venture Partners, which is a growth equity fund, and won a few funds that pioneered outbound deal sourcing at the growth stage. And so when we came together, we said, Okay, we believe that we can actually pioneer outbound deal sourcing at the early stage using proprietary software. And that was the beginning of 645.
11:14
Got it. And can you give us any insight into what that proprietary software, it looks like to source seals at the earliest stage?
11:21
Yeah, yeah. So it does a lot of different things, not only sourcing, but on the sourcing side, the first problem that we said we would solve is what we call information arbitrage. So when I was working on Wall Street, we would build algorithms that would do price arbitrage. So you can kind of with really nearly statistical precision, kind of estimate the ability to kind of make money on a trade in the public markets. And that’s because there’s just a lot more information and more and more information was becoming available for public market securities that you can kind of reasonably predict that you can kind of make money on a trade. The first thing that we agreed to, when we started 645, is that early stage venture capital has so many data points that you actually cannot reasonably predict whether or not what you’re looking at is going to be successful. But what you can do is get in front of opportunities ahead of your peers. And so that’s what we call information arbitrage. Can we get in front of opportunities before our peers? And then if you see a very large set of opportunities, how do you sort them in such a way that you bring the aces to the top of the deck, right, and so we can sort them in such a way that you we cannot predict that the top five companies will be billion dollar companies. But if we look at a set of a 400 companies, or 1000 companies, we can reasonably assume that that top 20 has a massive company. And therefore you can kind of direct your outbound dual sourcing strategy against that organized list. As far as some of the insights around kind of what drives that scoring, it’s multiple different data points. And this was kind of this is what went against conventional wisdom when we were building the firm. So conventional wisdom said, a very early stage company actually won’t have data points. But because founders were actually building software faster, and pushing code faster, and kind of doing what we call startup experiments really, really quickly, they start to generate data points. So you can see kind of app store download, you can see web traffic, you can see founders and whether or not they’ve had exits in the past, you can see founders and whether or not they’ve worked together in the past. So there’s all of these different data points that kind of come together that can give you a sense of what you’re looking at may have a higher likelihood of being successful. That’s something that you’re not looking at. And that’s how software in our organization is applied to deal sourcing and how it augments deal sourcing. But as I mentioned, that’s just a fraction of what the operating system does. So for instance, we have anytime a person joins our firm, we have access to all of their LinkedIn data. And what that allows us to do is search across the entire firm’s network anytime a portfolio company has a problem on the sale. So if a portfolio company needs access to a new customer, or portfolio company, you know, wants to recruit ahead of engineer instead of coming to me and saying, Aaron, you know, you’re on the board, like, what do you know, and me trying to use my mental Rolodex to think about who I know, I take that request and give it to our success team in a run a search across the entire firms network, coming back to me with a list that I then provide to the founder, here are the top people in our network that might fit your needs. And this is more efficient, right? Because my network is changing in real time. I cannot have a recall of what everybody I’ve ever met does. But if you actually bring software into your operation, you can do things that scale.
14:44
Got it, Got it. So you’re gathering this data from startups, a lot of it is available on the web, how much of that data do you marry or supplement with data that you’re collecting directly from founders and you know, if you accrue those signals over time as you’re developing those relationships You almost have both halves to the data component. I’m curious, is that also part of the evaluation of the startups? or at what point? Or what data do you get directly from the horse’s mouth?
15:10
Yep, that’s exactly right. So we have we call automated data. So automated data is information that you can get via API are scraping through websites off the internet. And that information is pulled on a daily basis. And it updates every single record in our database. But what you’re describing is what we call manual data. So as our outbound team kind of engages with founders, we can kind of gather more subjective data, and tangible data on our founders that also kind of get put into the database that just helps us get smarter at understanding what success looks like. Because you we’ve been collecting this data like this over an eight year period, and we we won’t stop, we’ll just continue to collect that type of information. Now, this information doesn’t really drive investment decisions. It does drive prioritization, right? Like, where do we spend our time? Right, like we might be able to see based on the data that we’re collecting both manual and digital, that certain trends are emerging, right? And so we can say, okay, what are these interesting trends that are happening in AI? are what are these interesting trends that are happening in blockchain? And maybe we can, we can follow some of those trends to figure out whether or not a billion dollar company could be formed there. And again, this is information gathering and information arbitrage not investment decision making, or investment decision making as an entirely different set of frameworks that we kind of designed and put together that are the more art part of the venture capital business, that helps us to kind of identify founders that we want to go into business with.
16:43
Got it. I actually wanted to talk about that specifically, like those the frameworks that you have at 645. And whether or not you agree that early stage investing is more of an art, or is it more of a science?
16:55
Yes, so early stage venture capital, I still think the investment decision making is more of an art, right, there’s going to be science that’s going to really come into scaling and institutionalizing certain aspects of the business, like how your deal sourcing and how you manage data, but the investment decision making process is still very much art. And that’s why venture capital follows the power law distribution. So only a small number of companies can drive majority of the returns. But not only that, a large percentage of companies that actually go out of business. And the reason you see that curve is because it’s not hard, it’s not a science, if it were a science, you would actually have a much lower failure rate in the venture capital business. So the fact that the failure rates could be anywhere from 7580 plus percent, is saying that the best investors are using some type of art to kind of determine whether or not what we’re looking at right now has a statistical likelihood of becoming mass. Right. And that is that is the art part. And so, for us, when we think about investment decision making, there’s a number of factors that kind of go into those decisions. For instance, there’s this concept that we created called purity of motivation. So purity of motivation is kind of what is intrinsically driving the founder to solve this problem. And the founders that have the highest purity of motivation, will want to solve this problem no matter what. And you actually need that type of purity of motivation and intrinsic value to go through the stages of building a company because you’re going to inevitably face an incredibly hard milestone that actually looks impossible, it practically it is impossible. But it’s only these founders who have this purity of motivation, and intrinsic motivation to solve that problem that breaks through the wall. And we’ve seen this multiple times. So if you think there’s a company that we invested in called Gold Valley, and if you ever meet Joe Ariel, and you sit down with him for 1520 minutes, you’re gonna say he was born to Bill Gobelet, he was born to solve the problem of making national delivery, as easy as takeout for local specialty foods that people love. And then his community ends up influencing more and more people to love food, right? And so it’s people like that, that kind of break through these brick walls and kind of can achieve extraordinary outcomes. So that’s kind of that’s the art part, like how do you know if a person happier to be motivated? And it really, you have to sit down with them and understand them and really spend time with them as a human, and then align yourself with them and align yourself with a vision that doesn’t exist. And so that’s kind of a part of the kind of art form of venture capital investing.
19:37
Did you find it difficult to assess purity motivation during 2021 at the height of exuberance, where deals would move in less than a week at times? How would you assess one of the most important variables are characteristics of your investment process when these deals are moving so quickly?
19:54
Yeah, so we were pretty disciplined for and so when the market accelerated as you’re describing, we had to figure out how to augment our process to make sure that we can spend the time understanding the people that we’re investing in. So one of the things that we did was, we might kind of put some of the due diligence that help us tease out purity motivation, on the back end, and kind of meet the founder where they were looking to be met, which is, will you be able to invest at this valuation. And so we will kind of put that decision for, and we might not be able to make an investment at the valuation, and therefore we will pass. But if we thought that we can make an investment at the valuation that was kind of put forth or that we were putting forth, then we would kind of continue to do references on the founders, we would try to spend time with them understanding kind of what they care about, we would try to look through anything they had written or anything in that their past to try to assess whether or not they kind of had the purity or motivation. But to your point, it was a challenge, because we had to figure out how to be flexible and adjust our model, as the market started to move a lot faster. And frankly, we didn’t move as fast as the market, we didn’t deploy all of our funds. Last year, we slowed down a little bit based on kind of where meeting entry prices were, and kind of somewhat of irrational exuberance that we saw in the market. And we had written about that in 20 2019, actually, because we started to see like the market ticking up pretty aggressively.
21:35
So one of the characteristics that we’re talking about is purity of motivation. And that being a key driver of making investment decision, as you look across other early stage venture firms. Do you find or do you think that investors are over indexing too much on a characteristic that, in your opinion just doesn’t matter as much? Whether it might be market size, or the founders backgrounds? It could be anything? I’m curious what comes to mind?
22:02
Yeah, I mean, I think in the venture capital industry, there is a herd mentality. You know, everyone wants to believe that they’re investing in something that is not consensus and right. But if you actually look at the behavior, people are actually grouping around consensus areas. Right. So right now, where there to me, the greatest degree of consensus right now is in crypto, right? So not only a crypto but crypto infrastructure. So everyone is saying, hey, you know, I’m investing in crypto, but you know what, I’m invested in crypto infrastructure, right? But no, I think everybody kind of agrees that if if crypto and if the blockchain creates the next aside or reset like the internet, then infrastructure software is going to be a core component of that. And so you do see kind of venture capitalists having consensus around markets, and then also characteristics around founders, you know, where they went to school. So one of the things that we did early in the early days of building software, five is we weighed all of those different characteristics, like, for instance, where you went to school to go to Stanford, or Harvard, etc. And in the early rubric, school was actually weighted higher, kind of weighted higher than market, it was weighted higher than where you worked as an example. After two years, we ran a regression analysis against all of the data in our database, and kind of what were attributes that were most predictive. And what we found was that school was actually less predictive than where you worked, right? And so I do think sometimes there is this expectation that a person coming out of ivy league school, or Stanford or MIT might have higher probability of success. And what we found in a data, that’s actually not true, what is actually more predictive than what we’ve seen is kind of where you worked before. And whether or not you’re working on a problem on a problem set that you have been solving and working on in a prior experience that ends up being kind of relatively predictive. When we think about it, it’s intuitive to because it’s, you’re more likely to be to have an insight, right? Where you went to school doesn’t necessarily give you a competitive insight on the market. But working in a certain industry where you can see things that other people can’t make give you a competitive insight. So that in our opinion, tends to be a little bit more predictive.
24:21
So you’re talking about some of the learnings that you’ve had since growing the firm and I know 645 has been around for it’s eight years, is that correct?
24:29
That’s correct.
24:29
If you could rewind eight years to when you’re first launching the firm and give yourself one piece of advice, what would you have told yourself?
24:37
You know, so Mike Maples gave us this advice several years in and I wish we would have known it earlier. So Nabil and I had sat down with Mike Maples. And he started to explain to us return to fund to exit concept. So for every investment that you make, you need to see a scenario in which it can return the fund. That’s a very important puzzle piece to To invest in, in a industry that follows a power law distribution. And so if you adopt this, and this is what we’ve adopted since version two, is, anytime we make an investment, we need to understand what is the exit value that can potentially return the fund at least one time, and is after you kind of factor in how much more money we think it needs to raise how much more dilution will happen. Once you have that RETURN to exit number, you can start to really understand, well, if the company has to exit at this value, and trading multiples are in a certain range, you can figure out how much revenue the company needs to have to figure out how many customers that company needs to have. And it just gives you a roadmap for how big this needs to be to make economic sense for the fun. And can you actually paint that picture for the founder so that you both are the entire team, the investor team, as well as the founder team are marching toward the same goals. What it also does, it breaks down the notion that for every company that you invest in, you need 2% ownership, we don’t care. We don’t have to have 10% ownership in a company, we can get 8% ownership or 5% ownership in a company and still return the entire fund. Because we believe the company can kind of hit or exceed our tip number. And that has very little to do with the ownership that whether or not the ownership is 10%. Right? That is really how big is the upside? And then how good are we at assessing the probability of that company getting close to it?
26:25
Got it. Is there anything that you believed eight years ago that you no longer believed to be true?
26:32
So one thing that we believed was that internet web traffic was a proxy for revenue growth for direct to consumer businesses, and any company that had very rapid internet web traffic, and exclusively sold their products online? What inevitably kind of become a potentially massive business, and I’m oversimplifying the thoughts. But that was kind of generally speaking, what we believe what we found over time is that top line revenue growth is not the end all be all for business. unit economics are incredibly important. So you can grow top line super fast. But if the company can never be cashflow positive, do you actually have a long term sustainable business. So you can only look at kind of top line growth or internet web traffic as a proxy for whether or not the business is going to be good. In the early days, when we were kind of looking at different data points, and kind of designing algorithms to help kind of score companies, I think we would get overly excited by companies that had kind of very rapid internet web traffic. If you fast forward to where we are today. We still look at those data points. But we spent a lot more time under trying to understand what is the new business model this company might be coming up with? Or what might be unit economics suggest. We might look at cohorts when companies kind of are at the series A or later stage to try to understand whether or not the company has negative net revenue churn. That is kind of a lot more exciting to me, then how fast your network traffic is growing.
28:10
Have you found that internet traffic has a correlation with the success of b2b SaaS businesses? I know we’re talking about consumer here and direct to consumer brands, but I’d be curious what you found as it applies to b2b SaaS?
28:23
Wow. Yeah, that’s a good question. So we have different rubrics based on the business model and industries of companies. And in a very early days, what we saw as being more predictive of success for enterprise SaaS companies is a company’s ability to onboard and partner with big name design partners. So for enterprise, SAS, how successful is your team at getting in front of a potentially large customer and then closing them? If you’re a very early stage company, and you’re able to do that consistently, you have one, you may have a competitive advantage over your peer group might be starting a similar business. And then the next question is, is your product better? Right, and the product will be better depending on the churn rate. So internet, web traffic for enterprise SaaS companies is not as important as it is for direct to consumer businesses. But I would say kind of early adoption from big logos is quite telling about a company’s ability to sell into a big business. But that is not necessarily telling of how good your product is. That’s true.
29:35
Got it. Have you ever found yourself in a situation, or do you have a story for us where you have all these signals, maybe their bottom quartile whether it’s web traffic or their ability to convert in the funnel? There’s a number of metrics that you’re tracking, let’s say their bottom quartile, but your gut tells you that this is an interesting opportunity and that the founder is the right person to be building this business. So I’d be curious if you find yourself in that situation and would love to hear a story around that.
30:05
Okay. Okay, so this is great. So, so oftentimes, massive new venture opportunities are built in markets that don’t exist. Okay. And so in kind of brand new markets that don’t exist, there are some times not much data that you can go on. And so what we do is kind of, we created this framework called Dementia investment triangle, which is a derivative of Warren Buffett’s circle of competence, right. And this framework kind of is usually very helpful when we’re looking at these like low signal type opportunities that are going after nascent market opportunities. So if you think of, if you think about Warren Buffett’s circle of competence, right, it’s kind of based on two types of mistakes, a mistake of comission and a mistake of omission. So the mistake of omission is effectively you did not invest in something that you should have, because you have knowledge of that space industry, you have data to go on, that suggests to you that you should be able to make an intelligent investment, you do not invest, you’re mad at yourself, because the company comes to you. That’s a mistake of omission. And then there’s something called a mistake of comission, which is effectively, you invested in something that had no business investment, right? Like because you didn’t know the market, there was no data to kind of suggest that this is going to be successful, right? Like, you should not be investing there because you just don’t have enough information. So that framework that Buffett created works really well in public equities, growth, equity, private equity, in kind of really known established markets, it breaks down when it comes to looking at opportunity, like the one that you’re describing. That’s low signal. So what we did is by super impose the circle of competence on top of a graph that has an x and y axis that’s important to the venture capital industry, where the y axis is market is existing. Is it known as a speculative? Where the x axis is the innovation? Is it a gimmick? Is it incremental? Is it radical, is it disruptive? And what we found is when you superimpose a circle of competence, on top of this graph, the areas that have the highest opportunity for return in venture capital are those that are kind of approaching or are in a speculative market, on top of technological inflation that is, like radical to disruptive. And so when things fall in that space, had the formation at the very beginning, it’s a low signal. And so when we see it, we say to ourselves, like, is this a space where we believe this technology inflection is sustainable and scalable? Do we want to take a bet that a behavioral change will happen where this speculative market will at some point become a known market? And so that you asked a question earlier about art versus science. This is where it becomes a little bit more artsy, to try to figure out whether or not the combination of this kind of speculative market and disruptive technology can result into like a very massive company in a future that just doesn’t exist today.
33:10
Got it. How would a business like SpaceX fall on that triangle or that graph that you’ve laid out for us?
33:17
So SpaceX kind of blows it out, right, because it’s on the y axis, it’s like super speculative, you know, colonization of Mars, like might be a part of the vision statement. And then on a technolog technology standpoint, you know, especially when it was getting started, some of the things that they were trying to build just didn’t even exist, right. So that company like, it’s on the far end of the spectrum, both market as well as innovation. And so what it tells you is that that’s the opportunity that if it worked, could have extraordinary returns. However, the probability of success is even higher than your kind of traditional venture investment. And so if you’re going to invest in a SpaceX, our belief is that you should actually have a firm that does a lot of that. And so a good example of that is Lux capital. So Lux can be very successful, because they invest in a lot of companies that are far on each edge of the spectrum. And the probability of any one of those companies that making it, it’s just super low, but you have to have a lot of them. If you want to just kind of one off make a SpaceX type of investment, you know, your likelihood of success with that is going to be really, really low. And you got to be careful about that because it can substantially negatively impact your portfolio construction.
34:33
On the x axis, do you think there’s a particular type of company that appears the most so we’re talking about radical being all the way on the right, right, like, I’m guessing there’s a very, at least I think, from my own perspective, I would say the companies that I think fall into that segment are probably fewer than that of those that are disruptive compared to that that might even be further left. But I’m curious as you see the distribution of these companies on the x axis, where do you see See The majority of these companies been started?
35:03
Yeah so it happens in waves, right? So if you if you go back to around 2008, when the iPhone was just created between 2008 and maybe like 2012, there was a lot of startup experimentation happening around mobile. And so because we have this new radically disruptive technology that is kind of coming into existence, and then you have a lot of positive entrepreneurial energy that’s running startup experiments against that technology. And so over time, there’s all of these different waves, these technological wave that emerge, where you have startup experimentation, where we’re seeing it right now is around blockchain. Right? So there’s a lot of stuff right now, that’s kind of on the radical to disruptive into the spectrum that is blockchain related. We’re also seeing a lot of companies that are AI related that kind of end of the spectrum right now.
35:58
Got it. Got it. I feel like everything you’re describing today is almost a new wave of venture capital, right? Like the integration of technology in the processes to identify these companies using systems to collect benchmark data. And it’s almost a self reinforcing flywheel, the more mature the firm gets. I’m curious, from your perspective, where are we in terms of the evolution of early stage venture being a mature asset class as a whole?
36:25
It’s, it’s happening very rapidly right now. So everything in we’re seeing it from multiple angles, one you’re seeing kind of large multistage funds start to participate more in the early stage. And they’re being forced down because the later stage is right now at this moment in time, meaningfully mispriced, because of the change in the public market values, which kind of trickled down to private market, so they got hit first. So a lot of growth equity firms and late stage venture capital firms are kind of at a deadlock with the opportunities because they seem to be overvalued. But a lot of these firms are sitting on a tremendous amount of capital. And if you apply that capital to the early stage, then you have an opportunity have a higher likelihood of kind of capturing alpha, like capturing and investing in a company that might become a breakthrough, and that it’s most certainly undervalued, right, so at the Series A, or at the seed stage, whether or not a company is valued at 10 million or 20 million. If it’s a breakthrough company, it’s undervalued, because it could become a billion dollar company, right. And so what we’re starting to see from an institutionalization standpoint is large multistage firms starting to build out kind of systematic ways of engaging in the early stage kind of startup community. And so that’s one angle. The other angle is, is crypto is really, really disruptive in how companies are being formed, and also how companies are accessing capital. And I think it’s something not to be ignored how blockchain and cryptocurrency can actually create either another product line in a traditional venture capital investment set of opportunities, but also how venture capitalists themselves do business. And so this is all happening at the early stage. And I think the early stage has a unique position to own kind of some of these changes, and to kind of build storied firms that could in the future, be more like a Blackstone or a KKR. Because we’re the early adopters of a lot of this change as it relates to either crypto currency coming into our impact investment practice. So how do you invest in companies? How do you invest in tokens to how software can be adopted to create more efficient organizations. So we at the early stage, have the kind of first right to kind of experimenting with how you kind of bring these things together to build something more institutional. But at the same time, you have large multi state firms that are coming down and saying that we want to own the entire asset class, entire venture capital asset class from pre see all the way to pre IPO.
39:01
Do you think for pre seed and seed firms to compete? They’re gonna have to adopt a similar trajectory to that multistage funds, or I guess, what will the effects be of these multistage funds coming down and trying to invest across the entire stack for the preceding seed funds today?
39:19
Yeah, I think it’s hard. To be honest with you. I do think there’s going to be a shakeout, I do think there’s going to be a number of firms that exist existed over the last several years that will not exist in the future. And that’s not novel. This has kind of happened across multiple venture capital cycles. So there are firms that existed in the early 2000s and 2010s. That just don’t exist today. I think that is going to happen again, I believe that multistage firms will remove some of the what looks like high probability companies like companies that have a high likelihood of becoming successful from a sample set. like pick super founders as an example, I think most multistage funds have already adopted that concept that a super founder, which is a founder that has had an exit over $50 million, or have built a company that got to more than $10 million of ARR has a statistically higher chance of building a billion dollar company, like this is kind of almost common knowledge, particularly amongst multi stage firms. Now, in a multi stage firms usually have a competitive advantage at getting in front of the most successful super founders. So take as an example, and treat and Horowitz investing in Adam Newman’s company, like he, they have access, because he’s known, they can access him. And so he is now taken out of the sample set. Now, there was controversy around him. So maybe some people don’t even want him in a sample set. But there are founders like that, who get removed from the sample set of where a traditional precede investor will invest. Now, the good news is, they’re still going to be massive, multibillion dollar companies that are formed, that are not founded by Super founders, and your precede funds, your state funds will still have access to them. But I do think the likelihood of kind of investing in a certain set of founders that seem high likelihood are going to be all by the primarily, oh, by the multistage.
41:18
What do you think will separate the precede seed series A funds that are around in five or 10 years today, compared to the ones that ultimately fail, obviously picking great investments? But if you had to put that aside for a moment, what do you think some of the other either strategies or tactics they’ll need to adopt in order to compete and build a legacy.
41:39
So I think the biggest weapon that small precede seed stage funds have against multi stage funds is the ability to be hands on with the founders. Now, that might sound counterintuitive, because you have these large platforms that have hundreds of people. But in fact, like those hundreds of people just cannot serve the size of their portfolio, because their portfolio is also very large. So if you can build an early stage practice that has a smaller portfolio, and you have a way of creating measurable value for those founders, then you’re more than likely able to win a position on to the cap table, if not leave the round. And then also kind of create opportunities for yourself to buy one investment, because you’re actually driving value for the founders. Now this can be done in two ways. One, you can build a vertically focused fund, right, like a fund that is exclusively investing in enterprise as companies. And therefore you have built a value add practice that can service that population. So you can have a smaller portfolio that’s concentrated on a certain type of company. And so that can be your secret weapon. And so there are a number of firms that have kind of really moved into to that category. And I think they’re going to be incredibly successful, then you can also have firms that can help companies with some of the nuances and challenges of getting a company off the ground, getting product market fit, and getting access to top talent and institutionalizing that type of value, add whether or not it’s on a platform that’s more industry agnostic, or if it’s a firm that vertically focus is going to be what ultimately separates the kind of top tier early stage funds from those that won’t won’t survive. And it separates them because of what you said, it’s going to give them access to the best deals. So as best deals with draft the best returns, and therefore they will be able to raise subsequent funds
43:37
is the path or 645 to become a multi stage fund investing all the way through Series B Series C, or as you think about the future for 645. What do you see?
43:48
Yeah, I think the biggest opportunity for 645 is the same as when we saw it eight years ago, which is the early stage has to institutionalize. So we didn’t start a firm that would help build one of the kind of best firms of our generation at the early stage to ultimately become a multi stage fund. We think there’s a lot of work to be done at the early stage by partnering with founders to help them kind of really bring their vision to life. Now we’re gonna raise, we’re continuing to raise more capital to help our founders do that. But our primary investment focus will be investing at the seed stage in a Series A, but having more capital to kind of participate in the journey along the series B and Series C. And we think that’s the best place for us to be right now is to just continue to focus on investing in early stage founders and helping early stage founders build growth stage businesses, and then let the spectrum equities, the Ikonics the Andreessen Horowitz kind of take these companies all the way through to IPO.
44:53
Got it. Got it. To wrap up here. What tips would you have for VCs looking to raise their next fund
45:00
Yeah, so for VCs looking to raise their next fund, there’s something that we do internally called pulling people into orbit. And so when we, when we started to raise funds, one, we pitched a whole bunch of institutions, and none of them came in. So fund one was primarily high net worth individuals. However, every person that we pitch, every institution that we pitched, we kept them in orbit and keeping them in orbit means keeping them posted for our quarterly reports, inviting them to our annual meeting, you know, periodically just going to sit down with them and share what we’re seeing in a market and asked what they’re seeing in the market. And then that process actually helped inform our future investment strategy. And if you fast forward to today, several of the investors that we started building relationship, if on one have become investors in our fund, it just took time, it took time for them to learn us, it took time for them to see our firm evolve. So the advice I have is, you know, don’t take it too personally, if an institutional investor says no, or investor says no, think about how to keep them in your orbit, figure out ways that you can be helpful and supportive of them in their career. And you never know like down the line, they may come in and they could potentially come in in a big way.
46:20
Aaron, if we could feature anyone on the show? Who should we interview on? What topic would you like to hear them speak about?
46:26
So I’m not sure if you guys have had a head and Elliot from Battlestar.
46:32
We’ve had Ed. They’re great.
46:35
Yeah, they’re great, man. We really respect those guys a lot. So it sounds like you’ve already had them but yet, having you know them come and talk about you know, what’s new and enterprise SAS could be super exciting. David Tisch, I don’t know if you’ve heard David Tyshaun. David Tisch runs and founded Fox group, just a really prolific early stage firm, and have also taken a contrarian approach as it relates to portfolio construction that I believe is going to work really well. So that’s another person I think you might want to consider.
47:08
Aaron, what do you know that you need to get better at?
47:11
I need to sleep more.
47:13
I’m there with you on that one.
47:14
Yeah, I gotta sleep more. But I just, I’m passionate about this. I’m passionate about my business. I’m passionate about my family. So I oftentimes find myself up reading and doing work. And it’s like, okay, I actually need to sleep.
47:27
And what’s the best way for listeners to connect with you?
47:31
Oh, man, you can hit me up on Twitter. So follow me there. Connect with me on you know, LinkedIn and send me a message. I try to be super responsive. So yeah, just Twitter and LinkedIn could be a good starting point.
47:46
Awesome. Awesome. Well, I think there are great things ahead for 645. And again, I appreciate the time really enjoyed this.
47:53
Yeah, thank you so much.
Transcribed by https://otter.ai
