The Distribution by Juniper Square
00:26:57 · Nick Shalek
[00:26:57] S0: Yeah. Our our thing, I I'd say from, you know, kinda from a a principle standpoint is it's concentration and conviction in in all things and and compounding. Those are, you know, kind of the, I guess, call... We'll call them the three c's that that drive a lot of the way that we think. We've... You know, we're now on, I guess, stats wise, we're we're now on the the twelfth fund or something. We've we've had a lot of different vehicles. We've always tried to undersize our funds so that we can be flexible in the moment and have had the belief that, you know, you take some vintage risk if you invest, you know, in a small number of companies in a fund, but that's more our problem. Our LPs are highly diversified across a lot of managers and asset classes. And so we've always, you know, we've we've always had the attitude that we should have a a smaller number of investments per fund than other people. That's led us to have, you know, have more funds, and I I can say more about that. But I guess by AUM, we've gotten quite large. Some of technology industry has grown a ton in the period that we started. So... But we've we've actually made our core funds smaller. And we've done that in a period of time where the asset class is getting bigger and other funds are are raising larger and larger funds. And I think that makes a lot of sense strategically for them. I think for us, going smaller has been a commitment to the idea that we wanna find, you know, we wanna find these entrepreneurs, these these rebels, and we wanna try to be their most consistent, pragmatic, trustworthy partners through cycles of greed and fear and change and and be there for them along the way. And you just can't do that with hundreds of companies. You you you can only spend that kind of time and attention and be that type of partner with a small number of bets. So we'll try in a fund to, you know, invest in 10 or 12 core positions. You know, that that might be six or seven or eight core investments a year and plan to work with those founders if we can for a decade or longer. I mean, with some of the the early companies we backed in Ribbit one or two, we're still buying their stock or, you know, going to their board meetings, talking to the execs and team all the time. And that's what we're... Was trying to do with the firm.
00:29:14 · Brandon Sedloff
[00:29:14] S1: Before we we kind of advance, I have a I have a lot more questions. But, you know, for our listeners who aren't familiar, you know, kind of a sampling of some of the portfolio companies or companies' founders that you've backed, help us help us understand.
00:29:27 · Nick Shalek
[00:29:27] S0: Yeah. Well, we we... We've invested on names, some companies, Coinbase, Robinhood, Stripe, Credit Karma, MercadoLibre, Juniper Square, of course, you know, extremely importantly. So I'm starting with the the the fintech entrepreneurs we backed. A bunch around the world that listeners may not... May or may not know but have been, you know, phenomenal companies. Maybe I mentioned New Bank or Groww in India. Just went public this year. It's the leading stock brokerage in in India. We backed an amazing founder in Korea in a company called Toss. Some great entrepreneurs in Southeast Asia, Forrest. Li and and team who run a company called Sea that's become a a really big, impressive Internet company. A bunch of a bunch of great, great folks. Revolut in Europe, which has, you know, become a monster business, has really special culture and team. More recently, we're... You know, because the... I'm talking about things we invested in, you know, seven, eight, nine years ago. We've been investing quite a bit in the AI, you know, broader AI space. And in, we would say, the intersection of money, knowledge, and power, and especially those intersections, things around, you know, entrepreneurs building capabilities that apply... You know, that that can make every organization better. That would be companies like Decagon, which is an AI platform for customer support. Or recently, we announced a round with Listen Labs. That's a a company building a really amazing tool that we were using internally. You can think of it as an agentic version of customer research like Qualtrics. But my opinion, you know, easily 10, maybe a 100 times better product experience when when you use it. So a wide range of things, but that maybe gives people a sense.
00:31:09 · Brandon Sedloff
[00:31:09] S1: Are you and your colleagues thinking about AI? If so, you're not alone. Nearly every conversation that I have with private markets leaders today involves a discussion on AI. Firms are trying to benchmark where they are relative to their peers, but more importantly, they're trying to figure out how they can improve and adopt more AI in their own business. I wanna introduce you to Juniper Square's five minute AI assessment. This will help you find your current level and also see what it takes to reach the next level of AI maturity for you and your organization. To take the assessment, go to junipersquare.com/assessment. That's awesome. So I think, you know, there's a few tidbits to pull on, but, you know, this notion of kinda backing founders through periods of change, whether it's, you know, to the upside or the downside. You know, right now, we're going through kind of an AI revolution. You know, the cost of intelligence is is going down to to near zero. You know, from from your seat as a as a venture investor backing founders focused on fintech, like, how how would you... How do you think about AI and the impact that it will likely have, you know, on society, but but really just on kind of the the the businesses that you back in the way that, you know, we collectively as a society do business and and think about interacting with with different tools and applications?
00:32:31 · Nick Shalek
[00:32:31] S0: I mean, there's so there's so much to say, and I would start with I don't know. Because, you know, anybody who who pretends to be certain right now, you know, is is probably missing on the point. The world's just evolving really rapidly. I mean, we... There's clearly an unfathomably large opportunity in AI. And I think it... The first thing we should say is it'll probably accelerate what's been happening in the past twenty years and just add fuel to the fire. So you'll see a continuation of multiple, you know, multiple trends. You know, the... You know, for example, like, the usage and absorption of as much compute as the world can figure out how to build. You know, I think a a useful mental model for data centers is they're just we made chips smaller and smaller and smaller. We, you know, we followed Moore's Law and added transist... You know, transistors at an accelerating rate to to semiconductors. And we kinda got down to dimensions where you can't really get smaller until you, know, you build quantum computers or you change the paradigm. And so now we're just scaling up the the number of of chips that we can deploy in coherent clusters, and we're turning... Your data centers are kinda like the next version of the chip. And so you just... You can see AI as something new. You can see, you know, what we're doing with GPUs and matrix multiplication as something new. But you can also just see it as the same thing that's been going on for a long time at an accelerating pace. And now we're just... You know, it's it's like we're in the steepest... Steeper part of an exponential curve. So now you can really witness it with your own eyes. You can see these enormous data centers that are are going up. The second thing would be, like, the growing power of small teams and technically sophisticated, motivated, creative people. You know, the the the ability, you know, the ability to to start a company. When we started when we started Ribbit, it was like it had gone from... You know, you had to raise tens of millions of dollars and hire very specialized people, and it took a long time to build software, and then you didn't have a way to ship it. We were starting at a time when distribution channels were open. And now for relatively small amount of money, you could build a prototype.
00:34:38 · Nick Shalek
Today, you can be one person, and you can build something in an hour or two. You can build something sophisticated over a couple weeks. You can ship it. You know, people people like to talk about the potential. You know, when's the first billion dollar company run by one person? I don't think it's very far off. So that that trend's just gonna kinda continue, and the value of agency will keep going up in the world. I mean, agent... You know, not agency, like, from a technology standpoint, but individuals with with the gusto to just get started and and go for something. Know, the next one I would say is, like, the importance of data as an asset. Again, a thing, I think data is the new oil. That phrase comes from, like, 2004 or maybe even earlier, 2005. But it's it's it's more true today than it ever has been. And people who have proprietary data or figure out how to create proprietary data through interactions with users are going to be the companies that become the biggest companies in the world and, you know, will continue to lead to this trend of, you know, increasingly large winners in in the tech space. And then maybe a last one I'd say is, like, software being the interface. So at this... I told you at the start of Ribbit, you know, one way of describing the opportunity would be to say, hey. People used to go into branches, but now the point of sale on financial services isn't gonna move. It's gonna move to mobile for consumers. It might move to your your payroll platform or your ERP or your cloud accounting platform if you're a small business, or it might be your fund admin. You know, why why why is fund administration and fund banking, why have those historically been different functions? It's really, you know, all software, all financial services are ones and zeros. It was really, you know, part of this broader trend, I think, where just like software or what with AI we're now calling intelligence was gonna be fused with everything, every part of the economy. And so I think the next ten, twenty years, what's happening with AI is just more of that. You know, as the cost of software or building software goes to zero, you know, you... I think it's worth asking the question, you know, what's the... What is software a complement to? And I think in every part of the economy, you can say, hey.