Pod Insights How I Invest with David Weisburd E133: Lessons from Investing in 2200 Startups (in 23 Minutes) About this episode In this episode of How I Invest, I connect with Lorenzo Thione, Managing Director at Gaingels, one of the most active and inclusive venture syndicates in the world. Lorenzo discusses his philosophy on diversity, equity, and inclusion (DEI), the democratization of venture capital, and his thoughts on the AI revolution. From his experience building a portfolio of over 100 investments to lessons learned from co-founding PowerSet, Lorenzo provides invaluable insights for investors and entrepreneurs alike.
Transcript Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.
0:00 Speaker 00 Unlike the public market where everyone has the same access to everything, the private market is highly asymmetric. And so if you invest for a long time, but you only have access to a corner of the market, you may be at one or the other end of that spectrum. Maybe that you have like uniquely qualified access and you do better than everybody else, or you have uniquely adverse access and you do worse than everybody else. So to some extent, if you are a very large family office or a very large investor and you can be an LP in every major VC fund now there, that's a great strategy, right? Over years and years and years, you'll do really, really well. That's borne out in the DEI. But what if you aren't?
0:47 Speaker 00 Tell me about your philosophy on DEI. I tend to be a very moderate person in my views. But I also think that like everything in life, even when there is a really good, solid moral reason to do something or to stand for something, there is always almost an inevitable kind of risk that people co-opt these things for their own, for their own purposes. And so you have the good version of DEI, which is, which says, you know, talent is universally distributed and doesn't see races or genders or any other characteristics.
1:31 Speaker 00 But opportunity isn't. And that's the reality of the world in which we live and we have lived in, is we can absolutely, and I am the first one to stand by saying merit is the most important thing. Right? It's not just about being an incredible worker, hard worker person. It also matters where you grew up, what kind of networks you had access to, what kind of resources you had access to. And so realizing that talent is uniformly distributed and opportunity isn't, is not a bad thing. What is bad is co-opting this mission in ways that are perverted and that...
2:10 Speaker 00 That ultimately don't do anything to advance equality, sometimes perpetuate different inequality. So I think there's a lot of absolutely legitimate criticisms that need to be levied at what DEI had become almost as an industry. At the same time, we at Ganges believe that there is work that we can do to provide more access and more opportunities to people, entrepreneurs, investors, uh, folks that have traditionally just haven't been able to access the incredible uh wealth uh and value and innovation engine that is venture capital. And we exist to do that.
2:52 David Weisburd? What is Ganges?
2:53 Speaker 00 Ganges today is one of the largest, most active venture investment syndicates in the world. Um, we invest in companies that look to us as being partner with them to help them build truly inclusive organizations at the levels of talent, governance and capital. We help them with hiring, recruiting, bringing on boarding, board members, advisors, and we represent an incredibly diverse group of investors that come from all paths of life, uh, all genders, all ethnicities. Really all type of peoples that traditionally have found it hard to get access to the type of opportunities that Ganges is able to bring them. And because of them, we've built a really, you know, vibrant community of investors that care about our mission
3:37 Speaker 00 and get to invest in some of the best and most highly performing venture-backed companies in the world.
3:44 David Weisburd? When you guys started, you made a very interesting decision. You allow LPs to invest as little as a thousand dollars per company. Walk me through that decision-making.
3:53 Speaker 00 And you know, when you bring on a group um of investors and you're basically trying to um.
4:02 Speaker 00 Position yourself and message to folks that often, while they have the means, because you know, we work only with accredited investors, they have the means, they maybe traditionally have never had the opportunity, the access, the ability, the education, the experience of investing in the venture asset class. Then, you know, making it easy for them to do so becomes an important piece of the equation. So accessibility can take many forms. And one of them is to allow people to make investments as little as a thousand dollars into opportunities. When you take an amount of capital that an angel investor would want to allocate to
4:44 Speaker 00 this asset class, say twenty five, fifty thousand dollars, and you get to split it and diversify across, you know, ten, twenty, thirty investments across the year, then you're doing a lot of things. You are educating yourself, you're getting in touch with different terms, different type of companies, different sectors. You get to provide these individuals with both that access and an education into what it means to be an investor in private companies.
5:15 David Weisburd? So let's say you had a friend that was worth five million dollars. Half of it liquid, half of it not. How much should a friend or a high net worth investor invest into venture capital as a category?
5:27 Speaker 00 This is not financial advice to anybody and everyone should kind of think in the context of their own risk aversion. I would say probably ten to twenty percent of your overall liquid net worth should be going into a venture capital type of asset. And so out of that five million, probably five hundred thousand dollars is probably, I would say, okay, I want to put this into venture. But then venture is, especially now, it is such a broad category. So I would really look at, you know, just like you diversify by asset class and by risk exposure, you can diversify within the venture asset class by risk exposure and
6:12 Speaker 00 time to liquidity. And so you can invest in different companies, different sectors, and at different stages.
6:19 David Weisburd? Brought up a couple of points. One is, of course, Liquidity or illiquidity in venture capital. When you invest in a startup, especially at the seed stage, you should expect a minimum of 10 years before you get your money back, which a lot of people say, yeah, I could handle that. But in reality, they're not set up to do that. So maybe they should be investing a later stage. The second one is thing I've never seen any data on this is, what is the actual correlation among different startup sectors? My intuition is that venture as an asset class, whether you invest into nuclear or defense tech or SaaS or consumer goods should have not that much higher of a correlation from the S and P 500.
7:04 David Weisburd? Just much more, much more volatility. So you have companies that are going up 100x. You have half the portfolio going to zero. It's not clear to me that the diversification should be significantly worse than the S and P 500.
7:18 Speaker 00 You certainly want to diversify by sector, primarily because of the fact that you might have like different type of strategies or different type of understanding of different sectors, or simply because at different points in time, there are cyclical sort of tailwinds that kind of push certain sectors more than others. You certainly see it today with things that are early, mid, or late in the adoption curve for how potential growth of those sectors may represent. And you know, there certainly is some correlation to the S and P 500, but there are technologies in venture that or entire pieces of the venture economy
8:03 Speaker 00 that emerge long before they become a significant part of the public market. A good example is quantum technology. Five years ago or 10 years ago, if at all, was pretty much only a purview of private holdings, private companies and venture backed companies. I think there is some correlation and some importance that comes along with looking at the diversification within your portfolio to be not just by ticket and stage, but also by sector.
8:37 David Weisburd? We've had the DuPont family, Verdis, on the podcast. And one of the things that they figured out is that if you just invest into everything, or you get exposure to everything in venture, over many decades, you get a really good return. You know, high teens, low twenties. So venture is one of those asset classes where you don't have to be too smart. You don't have to pick, you know, AI over crypto or, you know, over AR, VR. If you just continue and slowly and really in a boring way, continue to invest in the asset class over years, it is an asset class that has rewarded its investors for many decades.
9:15 Speaker 00 I'm glad that you bring this up. It relies on having a pretty broad funnel of access. Unlike the public market where everyone has the right, the same access to everything, the private market is highly asymmetric. And so if you invest for a long time, but you only have access to a corner of the market, you may be at one or the other end of that spectrum. Maybe that you have like uniquely qualified access and you do better than everybody else, or you have uniquely adverse access and you do worse than everybody else. So to some extent, you know, if you are a very large family office or a very large investor
9:59 Speaker 00 and you can be an LP in every major VC fund out there, that's a great strategy, right? Over years and years and years, you'll do really, really well. That's, that's borne out in the, in the data. But what if you aren't? If you are just an angel investor, or if you don't have the capital or the connections to be a large LP or an LP in all of those funds, your options are pretty, pretty small. And so you rely on either alpha, you know, alpha because of access or because how smart you are or what kind of career you've had and the fact that people seek you out. Or, and you know, you can look at something like angels and see like, okay, through the
10:43 Speaker 00 power and the size of that network and the fact that we collaborate and. We're non-competitive, we're cooperative with pretty much every large fund out there. You get almost like the ability to kind of invest into a really broad portfolio across the entire venture spectrum. And so, you know, to some extent, if I had a lot of money, I could be like, okay, I'm going to invest that $1,000 or $5,000 into every company that the network gets to invest in. And then you'd have really broad exposure to the venture asset class as a whole.
11:16 David Weisburd? You'd be getting to the mean. So it doesn't help if you could invest in any fund in the world, but you have $5 million and the minimum is $5 million. You're not going to invest 100 million of your net worth into just one venture fund. So it's a, it's a mix of both having access as well as the minimum investment size. So going back to this hypothetical, so you have 5 million to invest. Let's say you put 10% in venture. How and when would you allocate that $500,000? Thank you for listening. To join our community and to make sure you do not miss any future episodes, please click the follow button above to subscribe.
11:54 Speaker 00 Look at what your expected returns and liquidity needs are and just kind of project out. Okay, so maybe 30 to 40% of that, I'd like it to be liquid sooner than the mean. And so maybe in the three to five kind of year timeframe. And I could allocate those into series C or later. Those investments will return lower multiples on average. They've already kind of are higher valuations. And if and when they exit and go public or get acquired, those multiples on investments will be lower, but you'll have a larger pool that has been invested into those and you will get it back sooner.
12:39 Speaker 00 You'll have a positive effect on your IRR. Whereas you could take, you know, 10 to 20% of that and invest it into series A and series B. And then again, another 10% invested in seed and pre-seed opportunities. And that will kind of, you know, give you some exposure to the go big or go home kind of potential.
13:03 David Weisburd? Prior to co-founding Ganges, you had this portfolio of 100 investments. How did that affect and instruct how Ganges is run?
13:12 Speaker 00 I learned a few lessons that I think a lot of other angel investors in, you know, end up learning. When you're truly an angel investor, meaning you're investing at angel rounds, pre-seed, you know, a pitch, an idea, a founding team, but like not a lot more than that. There just isn't much more that you can invest in than the team and the founders. And so your own assessment of, you know, their agency, their grit, their, their kind of doggedness, their unique, unique positioning within that market, all of those become like the really important things that you can leverage to invest. And, and in fact, you
13:53 Speaker 00 know, very early in my angel investment career, the first thing I did was to just kind of reliably go after and invest in whatever companies the people I had worked with or knew really well, were going to go in and start. And sometimes being their very first investor. And, and that paid out really well, especially because we had some amazing people within the team at PowerSet. That was the name of the company I founded back in 2003, whose companies, you know, they, they went on, the folks from that team went on to start companies like GitHub and Wits and Biases and Touring and Runway Financials. And, and the ones that didn't
14:38 Speaker 00 go and start companies went to lead very large entrepreneurial organization within a large company. So really a fantastic team. And then you know that, you know, great founders just attract other great founders.
14:54 David Weisburd? You mentioned investing in your friends. Some of the top portfolios in venture capital history were actually the angel portfolios of a David Sacks or a Marc Andreessen or Chris Saka, because they have such intimate understanding of the execution ability of their friends. One of the hidden things there is that their friends were not pitching to them the full five years that they knew them. They got this ability to observe their friends in a way that they were not always selling to them.
15:20 Speaker 00 Investing in people that you've worked with? That you've observed up close, maybe your students, if you're a professor, people that you've gotten a chance to really kind of see how they behave under pressure, see what kind of character they have and what their approach to kind of moving mountains that kind of got put in front of them. That's probably the single most, you know, best predictor of a first time entrepreneur. With the second time or serial entrepreneur, then you've got those points, right? And I think that the other aspect, the other side of what you were saying, which is, I think is equally true, is you've got great portfolio of people who invested in first time entrepreneurs because they knew who they were and they had worked with them.
16:04 Speaker 00 And then you've got investors who bet again on entrepreneurs that did well the first time and they worked with them before and they wanted to back that horse again. And I think that there is a really high correlation of repeat success for entrepreneurs. So I would say that's the other aspect of it. And I think that it puts us, meaning angels, in a good position, again, having such a broad portfolio. We can see what the execution ability of founders that may make it or even may not make it the first time for a lot of reasons. There's so many reasons why a startup doesn't, you know, doesn't go well or doesn't go as
16:45 Speaker 00 well as one would have liked and, you know, be able to assess much better the second time around, whether or not, you know, you would want to invest in that, in that entrepreneur again.
16:57 David Weisburd? You've been in the AI market longer than 99% of investors and VCs out there. Tell me about your thoughts on AI today.
17:05 Speaker 00 As I mentioned, I started, co-founded a company called PowerSet 20 plus years ago, which was bringing to market a lot of the ideas and visions that are only becoming reality now. You know, we were one of the pioneers in trying to bring semantic into AI into web search at scale. And some of the intuitions we had, you know, we're not very kind of removed.
17:33 Speaker 00 From some of the things that that we see today in how semantic searches approach, right? So things like RAG, ultimately, what we were doing at the time is you can you can describe it as a precursor to RAG. So, you know, pre-deep learning, cost of computation was 10,000 times, maybe more, what it is today. There just was a universe of approaches that was not open to us. We clearly brought attention to something which was, search was not, keyword search was not all that there needed to be in order to to advance the market. And, you know, we sold to Microsoft, became some of the foundational pieces of
18:15 Speaker 00 the early Bing.com and integrated in there and gave a spawn to a lot of other really cool company in the AI space. Crowdflower, Weights and Biases, Turing, Runway, all of these folks, you know, went on to really make big innovations and and a big impact on the market today. It's exciting from my point of view, just because I see so much of that vision and those thoughts kind of like finally being realizable and being able to to be brought to market in a way that is compatible with the cost and the scale of delivering services to the world, to consumers. And so I've been, you know,
18:57 Speaker 00 excited about, on the side of the investor, backing a lot of founders in the space. The way that I've constructed my my investment thesis, and I've been investing now in the space for the last three and a half years or four years. So just as like the the GPT kind of LLM revolution really kind of started to take place, is to think about it in buckets that are kind of staggered.
19:28 Speaker 00 With respect to when they will become or they have become ready for commercial exploitation and therefore revenue generations.
19:37 David Weisburd? When it comes to your portfolio in AI, are you basically just making a directional bet on the space and trying to build a large portfolio of smaller investments? Are you concentrating in a couple of names? Are you doing some hybrid? How do you attack a thesis like AI in your portfolio?
19:54 Speaker 00 So Ganges broadly, I think, will continue and does continue to invest in a lot of companies. And so spreading out that risk, both because different people will like different things. People will invest in the companies that they want to invest in. And so bringing them high quality access, but for a lot of companies is part of that. And the way that we kind of make sure that the quality is high is by co-investing with great funds that are, you know, bringing their own alpha to the market in terms of the the deal access, the deal flow access that they have and the diligence that they that they put. I also run an AI fund within Ganges.
20:36 Speaker 00 And so a more traditional kind of VC approach while maintaining some of the elements of the Ganges network, meaning we still don't lead rounds. We're still a kind of a co-investor alongside others and therefore benefit from, you know, that additional social proof and diligence. We do a lot more direct diligence and directional betting for that fund than with a syndication process. And there, you know, the my North Star, you know, I'm actually working on this fund with a former colleague of mine from the PowerSet days, who most recently was leading AI development at Adobe. My North Star there is on top of the kind of three pillars that I mentioned earlier
21:21 Speaker 00 is really looking at, you know, companies that can have a generational category defining kind of opportunity there. Sort of just trying to stay as much as possible away from things that feel like jumping on the bandwagon and kind of me too things. And really from first principles, kind of things where that team is uniquely motivated and positioned to make an impact on something that has an opportunity to start from a small market and expand into or create a much larger market down the road. The thesis is around those three buckets.
21:58 David Weisburd? We saw last week Trump with SoftBank and with Sam Altman, who I know you have a relationship with, announces $500 billion investment into AI in the US. What are the repercussions of that investment? How do you think that will affect the AI space?
22:16 Speaker 00 Clearly, you know, Sam and others who are really close, and I'm thinking about Dario Moday and others who are really think close to the economics and the dynamics of scaling out, not only the services that they are already providing to the world, but the services that they know they are going to provide to the world. They understand the requirements from a power compute perspective better than anybody else. And while I think, you know, to anyone looking from the outside, investing anything, investing $500 billion into anything seems like a gargantuan amount of money. I can't look at this as anything but a good thing, especially for the United States.
23:01 Speaker 00 I think it's it's an opportunity to kind of create a lot of innovation and a lot of scalability and a lot of resources within the US in a similar way to say, if you had looked at, you know, the last century oil production and be like, if oil, if compute is the new oil, then you want to ensure as much of that as you possibly can.
23:29 David Weisburd? Well, Lorenzo, we first met in 2012 in San Francisco. We've sat on ICs together. It's great to have you on.
23:37 Speaker 00 David, it was such a pleasure. Thank you for a really fun conversation.
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