Rusty Ralston and Jay Patil of Swell VC joins Nick to discuss Investing in “N-of-1” Companies, Focusing on Category Creators, How to Invest in AI While it’s at Peak Hype, and Using Recruiting as a Key Differentiator. In this episode we cover:
- Assessing Category Creation and Founder Caliber
- Sector Potential and Investment Strategy
- Syndicate Structure and Fund Size
- Talent Model and Sync Playbook
- Market Conditions and Future Outlook
- Investing in AI and Navigating Hype
- Defensibility in AI and Future Investments
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0:18
Rusty Ralson and Jay Patil join us today from NYC. Rusty and Jay are Co-founders and Partners at Swell VC. Swell invests in extraordinary founders building category-creating companies and gives them an unfair recruiting advantage. They have backed companies including Crisp, ScienceIO, and LoftOrbital, amongst many others. Prior to Swell, Rusty and Jay both worked at Urgent Career, a startup that partnered with venture-backed startups to build their sales teams. Rusty and Jay, welcome to the show!
0:49
Thank you very much for having us. Appreciate it awesome.
0:51
So give me your quick background, guys. I, you know, I touched on it in the intro, but what was your path to launching? Swell.
0:57
Yeah. So you know, Rusty and I, we met in New York City almost 15 years ago now, as the first employees, had a very small venture backed AI talent assessment startup, really a recruiting tech startup, and this is way before AI is the AI we know to be today. This was back in 2008 when the company is founded. I was the first to go to market. Hire. Rusty joined soon after that, and our job there was straightforward. We were building tech to help founders identify, assess, recognize great talent and build world class teams. And the tech we were working on at the time wasn’t just about matching people to jobs is really about finding those, we said, those intangible qualities. Well, we had a coin that phrase startup DNA at the time right to build this AI, we had to build training sets, and that meant we spent, you know, to spend over 10,000 or so hours speaking to 1000s of founders, Rusty and I and our team interviewed 1000s of potential hires to help assess and identify great salespeople and then recruit these teams for startups that eventually were our earliest customers in this company. And these companies went on to get acquired and become industry leaders. And so we were doing this kind of manual recruiting motion and building a framework for assessing people while we were building the training sets for the AI in parallel and pretty quickly while doing this. And we did this for about three and a half, four years, almost. We realized that a success for any startup comes down to one thing, it’s the people, where the people determine the outcome. And it’s this key learning that has defined our core thesis to investing. It was, it’s a central nervous system, if you will, right? We had already in doing all this work with the companies and helping build teams. We had already validated this thesis through the formation of at the time, was like 5060, successful startup teams that we helped build, who are these early customers, and unlike a lot of what we saw in venture in the last 567, years, where funds are raised, and then you figure out what the thesis is, this thesis was kind of core to and came from the learning at this company, and rusty and I looked at each other, and what we realized we were doing along The way was really honing judgment right? In venture, there’s a lot of talk about markets and thesis and valuations and competition, but rarely do you ever hear anyone talk about the real driver that we think behind successful funds is judgment. And so we knew we had the beginnings and the makings of a venture franchise, right? But we were total outsiders at the time, no corporate VC background, no Wall Street ties, no Ivy League networks. When I moved here as an immigrant from India, we had no big name VC backing. So before we could even take a single dollar from anyone, we had to prove this with our own money. And that’s how fund zero was born. It was this proof of concept fund, if you will. It was built on small investments all rooted in this one belief that people are the key to success in venture. And the very first investment we made was a company in New York called tapad. The founder was a trust all rusty, and I came in at the pre seed round. It’s like the first money end with a bunch of very, very notable New York angels. We invested kind of own personal capital, and then we helped them make their first sales higher. Eventually went on to recruit 40 out of 150 employees at this company, you know, tap out. Eventually scale. They became very successful. They kind of defined this category in the ag tech, martech space, and they scaled to over 50 million in revenue, acquired for $360 million in cash. And the rest is history. You know that success laid the groundwork for fund one, and now here we are with fund two. DPI, Jay, where
4:51
has that been? We’re in a weird time, and I do want to unpack the model and get into it. But you know, when you partner with founders and you’ve got this kind of. Recruiting edge and recruiting advantage. Do you become kind of an outsourced recruiter, or is it more of a train, the trainer, like you’re you’re trying to help those founders understand how to source great talent, how to select great talent, how to level them up and develop them over time. You know what? What is kind of the model there?
5:20
That’s a great question. So, you know, we think that, you know, the model for us is really partnering directly with founders. You know, there is this principal agent problem in venture where you have a signer and a servicer, you have the GP that signs the check, and it’s like, oh, go talk to my talent platform team, right? And they typically don’t have the skin in the game, or, you know, the financial incentive to carry the GP has so, you know, for us, we saw this early on. So, you know, we really partner directly with founders after we invest in the company. You know, we get in the trenches. You know, as far as conducting interviews, you know, actually reaching out to potential candidates, you know, selling candidates on the roles. I mean, negotiating offers and helping close the candidates. So, you know, we really get, you know, very hands on when it comes to, you know, almost like a retained search in many ways, but also a talent assessment layer. And also, you know, we kind of a playbook for, you know, how to recognize greatness in people perfect.
6:09
Love it. And then give us, give me the broad strokes on your thesis. You know, what is the stage, entry point, check, size, sector, orientation, just the basics. Yeah,
6:20
for sure. So as well, you know, we’re early stage investing in our thesis is really investing in extraordinary founders, building one of a kind category, creating companies. So we love to have, you know, invest in founders and partner with founders who have this unique mix of an insider’s edge, you know, with this Outsider’s mentality. And so that combines, you know, people with really deep domain expertise and a proven track record of commercializing products. But also, you know, every founder has to have a burning desire to solve real customer pain points. And I think that’s something that people overlook a lot, is that, like deep kind of psyche of the person that’s that’s that important on the marketing side, you know, I’m sorry, on the market side, we want ideas that fundamentally transform an industry and how it works, how it operates, you know, not incremental improvements. And so we invest early, pre seed and seed, our average check size is around 600k right now. Out of fund two, we have a particular emphasis on B to B, which is, you know, really included software, you know, sectors like AI, space, supply chain, food, you know, defense, healthcare, and we love being the first check. You know, being in early as we just talked about, you know, our real edge is helping founders hire like top 1% people. And that’s, you know, how we get on cap tables. And that services component is so critical. Because, you know, ultimately, the team determines the outcome of the company. You know, the real investment is the people. It’s not just the check. And so we believe, like, that’s really what kind of drives exceptional outcomes and returns. It’s where we place all our emphasis. And, you know, we’re fortunate that the wins, like you mentioned, from fund one include loft orbital and crisp includes dpi, and now we’re actively deploying capital from fund
8:04
two awesome. So you’ve been talking about sort of investing in these n of one companies, rather than N of many. What do you mean? You know, when you’re talking about these category creators, I think there’s some different definitions for that. You know, how do you assess the degree to which one is creating a category. How do you measure that? How do you determine, you know, if it is really competing with non consumption or brand new market, versus not?
8:30
Yeah, good question. I think you know what a swell deal looks like for us is this cross section of category creation and founder caliber, you know? So I think first and foremost, it’s like we dive deep into the founder and the origin story, their drive, their unique insights, this customer focus, the track record, that’s really key. I would say, you know, we can look back on fund one and probably just evaluate all 12 deals without even knowing what the market was, just who the founders are, and probably be able to make the same dots. So it’s that much of an emphasis. If we can get past that founder piece, then it’s the category creation piece hinges on, like, a really, a few critical elements, you know, I think, you know, the market wise, you know, I think, well, first, technology wise, it has to be a breakthrough, you know, or a key inflection point, which allows a company to solve problems that were previously unsolved. You know, the market has to be really ripe for transformation. So think about, you know, the kind of the market shifts that are happening that, you know, answer that, like, why now question. And you know, the markets have to be, they have to be huge markets, right? And so you can easily tell the company, you know, kind of the obvious answer is, does the company, when they’re launching, already have 30 competitors? You know, the non obvious answer is getting a bit deeper than that. And if they are, if they don’t have any competitors already when they’re launching, you know, why is that? And, you know, can they build a business that keeps, you know, competitors at bay? And so I would say it’s maybe easier to talk about in examples. You know, loft orbital is a great example. It’s like they created a new category in space tech by building infrastructure. Here to make space really simple. So like satellite Infrastructure as a Service, right? It combines this new way of thinking that you had this inflection point of of satellites are not snowflakes anymore. They come off the shelf, right? So what did that mean? That? That meant that you could actually build this type of model that loft is building, and they saw it because they had this insider mentality, I’m sorry, experience of working at Spire, which is now a company that’s public, they were the first employees there. They closed some of the first government deals, you know. But they had this outside mentality of, we can really see this massive opportunity and change the way that the government, you know, private companies, access space. So I think that’s kind of a good example of, like, you know, the categorization plus the founder caliber is really that sweet spot. And then there’s some just, you know, some context around, you know, how you start to narrow it down, and then ultimately, when you narrow it down further, you know, you get further and further along, you know, then it’s just, you know, it gets to the judgment piece of whether we truly think that’s the case or not. Got
10:59
it. And it sounds like there has to be the presence of a strong technological or technology factor, absolutely,
11:05
yeah, for sure. I mean, you can’t that’s the thing is, like, we really think that in all the companies that we’ve invested in, there is a technology breakthrough, like, there’s real innovation happening. And it’s not just because it’s buzzy, you know, it’s not just because it’s Oh, AI, you know, AI, this, AI, this llms. It’s because, you know, there is actually a technology breakthrough that fits the customer problem. It’s not just, you know, cool technology for the sake of being cool technology, very
11:31
good. And I know that you’re actively investing in space, as you’ve articulated. Ai, first enterprise software. You’ve done some defense, you’ve done some healthcare, which of those sectors do you think will have the most category creating potential or successes over the next five to 10 years?
11:50
You know, it’s we’re not in the business of predicting the future, right? We had to. It’s like, you know, we have a pretty diverse portfolio, and there’s no way for us to really know today which one of them will be the biggest winner. I think that’s a hard thing to do, given our model and who we are, but I think we found a lot of promising ideas, a lot of promising a lot of like serious, like massive problems that haven’t been fixed right across several areas. And that’s kind of going back to be it AI first enterprise right, where the problem’s been waiting to be solved. It’s been a while. The founders have been obsessing about these problems for years now, right? And then maybe AI and llms kind of give this surface area right to creating a solution now that wasn’t possible before, right? And that’s we’ve seen that happen in enterprise data security, it has happened in like supply chain optimization, happened in healthcare, and seeing it happen in a lot of these different verticals. But, you know, we didn’t come into this with a strong opinion viewpoint, saying, Oh, it’s gonna be legal tech, oh, it’s gonna be space tech. Right for us, it’s, again, it’s a confluence of things. And if the problem is real and it’s unsolved, and there are founders are incredibly driven and obsessive about it, and have been obsessive about it for a long time. Now, some of these inflection points give them the ability to build a solution that customers are desperately need of and want to pay money for. Right going back to like that commercial mindset too. Can this be turned into a real business? Is a question. So yes, enterprise software, space Tech and a rusty alluded to in a loft. Why has that been a success? Right? It’s because of those deep insights that the founders already had. They saw market evolving, 5678, years out, and they invested in building the infrastructure, which, at the time, didn’t make sense for a lot of the VCs, right? We saw that. We gravitated to it right away. And you know, we’ve been lucky to be partners with them. Same thing with healthcare, right? A company called Science IO had a fund, one that already got acquired for one 40 million in cash just a few months ago. They were kind of early to this LLM thing. OpenAI had obviously started building their foundational models. But this is back in like 2017 2018 when science IO came around, and, you know, AI and llms weren’t quite the target town as they are today. And they didn’t even call it an LLM startup at the time, but that’s exactly what they were building. And it was their insights from their time at Foundation Medicine and their work with flatiron health that informed the need for this kind of modern day data infrastructure for healthcare, right, taking unstructured data, turning that into real, actionable insights.
14:29
And when did that company launch? Jay
14:31
those launched, science was launched. We invested in them right around covid. It was basically committed to investing in March 2020 I think they were launched. They founded in 2018 and then they just exited earlier this year,
14:43
wow. And they were working on large language models since then, correct, interesting. So as one syndicate lead to another, we were one of the first syndicates on Angel List way back in 2015 I think. But I know that you have created some unique SYN. Kits and vehicles to give founders and LPs, you know, exposure to these breakout companies like loft orbital, you know, why? Why have you structured this way instead of just doing everything out of a fun vehicle?
15:11
Yeah, good question. So for us, you know, we just think of it like a dual threat approach when it comes to early checks on one end and SPVs on the other. And that’s just for our LPs, which, you know, we have a lot of LPs that are founders. So we believe we can drive the best returns, you know, for our LPS by investing 100% of our capital in early rounds, and then offer our LPS direct opportunities to follow on in our winners. And so, for example, like we just talked about loft, you know, we’ve doubled and tripled down on loft, and we’ve doubled down on crisp we’ve raised several million for lofts and given our LPS access to this, you know, to amazing companies as they scale, which just feels, you know, stronger returns across the board. I think the thing that LPS like is, they like the optionality of direct deals in specific companies, companies, versus a fun vehicle that’s just follow on in general. So, you know, gives them exclusive access. It gives them more control over how they allocate their capital, and ultimately, you know, it’s our job to serve them and their investment goals. So I think that that approach has just worked really well for us and the companies. You know, we’ve helped most of our companies raise, raise capital, whether it’s in the initial round that we invest in alongside us, or the follow on, perfect. And
16:23
what would you say is the optimal fund size force? Well, you know, given the fact that you’re trying to do this structure, you know, what would be kind of the optimal size? Yeah,
16:33
I think the optimal for us is a series of $50 million funds. And that’s, you know, that’s what we think that over the coming, you know, the coming, 30 plus years, that’s something we can do,
16:46
and you tend to do, you know, how many different companies in each fund? Trustee, yeah, so
16:51
we’re really concentrated. You know, to start out, our fund one was only 12 companies, and fund two will be, you know, 17 or 18 companies. Perfect.
17:00
You know, we talked before about kind of the recruiting and the people element that you all bring to the table with your portfolio companies. I know that you prefer, you know, investing in people over trends. How is that foundational principle played a part in the evolution of swell? Yeah.
17:19
So, you know, I think on the surface, VC feels like this sexy, trendy way of investing in shiny things. And I think that attracts, you know, I spoke to a panel of students who went to Miami of Ohio, where I went. It was like, alumni thing in New York. And, you know, so many students now are like, I want to get into vcvc. And it is really exciting and interesting, and the innovation part is incredible. But on the surface it feels like that, but I think in reality, it’s simply about like timeless principles and character traits intersecting with that innovation. So, you know, this plays a big part of not chasing the trends, which leads to not overpaying on deals, and it also leads to building, you know, lifelong partnerships with founders. I mean, we think when we go into business with a founder, and we partner with them to build their company and help them and empower their vision and help them grow that. It’s a lifelong partnership. It’s going to be first company to their next company. It’s going to be, you know, when we’re when we’re having dinner and, like, retired. So, you know, we kind of think it in that way. But, you know, this, this focus on, on these types of, you know, timeless principles of character traits, you know, has made our growth like quite organic. It’s really been via word of mouth, via founders, leading to more investments. It’s it’s also been, you know, just with our LPs, trust that we have with our LPs, DPI also. But you know, that really leads to organic growth in how you scale and grow funds. So, you know, I just look at it is like, you know, one of our LPS said this actually, after we had an LP gathering, was that, you know, swell is this trusted circle of people, you know, that kind of really flows from the LPs to the GPS to the founders, and it all connects, right? And so that’s just kind of how we look at
18:53
it, awesome. And you’re, you know, quite known for sort of this talent model in what you call your sync playbook. Tell us about this playbook. How does that work?
19:03
Yeah, that’s love this question. You know, we, you know, we Rusty, and I, when we came together to start up like we really know from our learnings, we believe that, okay, we’ve identified what we think has been a critical misalignment in traditional VC model, right? When it comes to talent acquisition, Rusty. Alluded to this earlier. It’s like a principal agent problem, right? The deal making teams are separating from a separate from the support teams. It’s like a disconnect. There’s no skin in the game. They don’t necessarily have GP carry. And I think this has led to a lot of diluted effort in what we believe is the most critical aspect of a startup success. It’s it’s people, the team building, it’s talent acquisition. So what we’ve done over the years really fruitless model in its head. So as GPS, we’re not just signing checks, we’re rolling up our sleeves, diving deep in the trenches, right, getting offers out, closing people on offers, actually sourcing candidates, interviewing them, running processes. It’s not something we just delegate our outsource to someone who’s on a platform team. And that’s always been the core, that’s been a backbone of our thesis, and that’s how we created value. So, you know, we’ve spent 15 or so years now holding our ability to identify that greatness and that startup DNA in people, and also being able to attract that top tier talent. It’s one thing to know when you see greatness, I think, to actually be able to successfully turn that into introductions and hires for our portfolio companies. So having done this, you know, for decade plus now, we kind of put a playbook together. It’s basically all of our learnings. Put it on paper, and it’s it dives into this proactive, systematic approach to talent acquisition, right? Everything from process. So the questions you ask, How do you even recognize startup DNA people? How do you ask those questions? Right? While it’s still feeling like a natural interview process, and I think when it comes to kind of building these amazing teams, the challenge is two for it. First, there’s a real scarcity of amazing, exceptional talent. It’s those rare individuals with a perfect blend of intellect and drive and hunger and the integrity, right? And then secondly, it’s a founder’s approach to recruiting, like we view recruiting as sales. It’s not HR, right? The minute you try to turn into some kind of a repeatable, scalable process, this method breaks down. So when we work with founders, we’re not trying to create perfect job descriptions. That’s not where the real wins happen, because the best people are never looking right. They’re not going around throwing resumes and blasting them on ANGEL lists to LinkedIn right. We’re looking at the way we look at team building and recruiting is like we work with the founders directly. It’s very hands on. We look at the problems, look at the hurdles that a business is facing at the time, we look at the massive opportunities in their crosshairs, and then we’re able to map that to skill sets, which ends up resulting in higher awesome
21:37
and recently, on the podcast, we’ve spoken with a lot of folks about when is the right time to bring on the first head of sales from the outside. You know, there’s different viewpoints. Some, it’s early, pre product market fit. Some, it’s post. You know, how do you advise your startups on that? We
21:53
think that, you know, as far as first sales hire, first you need to have founder led sales, right? You can’t expect a head of sales are a first sales hire to close deals when the founder hasn’t done it right. So I think that that means, you know, that there is some semblance of product market fit. It may not be full on product market fit, but, but you’re, you know, solving a customer’s pain point, and they’re willing to pay for it, and the founder is able to do that, right? I think once, once you the once you get some some traction there, and you have enough case studies, you know, call it a handful of case studies, that you can go out to the market, we think it’s time, right? And that really varies. So I wouldn’t put a, put a stage, you know, I wouldn’t put a like, capital raised on it. I wouldn’t put a month or a year on it. It obviously depends if the company is, is a is an enterprise first company, or a bottom up company. There’s a lot of factors to go into it. But I would say, you know, when you have traction, when there’s case studies at that point that could be, we’ve seen that as as early as, you know, the fourth month of a company, or even, you know, upon launch when founders already are that dialed in. That was the case with our first angel investment with tapad, you know, we that was almost immediate. And then in other cases, we’ve seen where, you know, that’s in year, year two, you know. And so it really varies, I would say. But you know, there’s some criteria that we think about helpful. Thank you.
23:20
You know, carta recently released a report highlighting how capital deployment has slowed. You know, seed to a graduation rates have declined from 30.6% to 15.4% over the past 24 Sorry, that was comparing the 18 to 22 vintages. And you know now DPI is at a low, with only 10% of 2021 funds having any dpi. What do you think is next for the asset class? Jay, you mentioned before. You’re not in the business of predicting the future, but what are your observations on kind of the behaviors and the leading indicators of what VC might look like over the prevailing, you know, 12 to 18
24:03
months. I’ll jump in here. And this is a good one. So I think, you know, you mentioned the carta fund performance report. A lot of interesting things were highlighted there. You know, like you’ve mentioned slow capital deployment, not a lot of dpi, elusive LP distributions, I think is what they they called it, maybe graduation rates, you know, all these things. I think that, you know, here’s our takeaway on the carta data, you know, one was that it’s all about small but mighty funds. You know, small funds outperform bigger funds. And this has been shown, you know, several studies. You know, returning a fund of 1020, 50 million is a lot easier than returning a fund of 250, or $500 million second. I think one thing that the report, you know, at least one takeaway for us was there was a lot of tourist VCs, you know, and the carta data showed that manager selection is critical. So yet another VC with the same approach as everybody else will not yield top decile returns. And this is why so many fun ones did not make it. Fund too. You know, a lot of tourist VCs join in the bubble, and then they move on to do other things. And then I would say the third thing, the third takeaway would be, you know, this, like, at least, I call it like this, GP, fade out. GP, fade out cycle. And that’s where, you know, you have these large venture funds. And even fund to funds, they mostly underperform when the original managers are effectively retired in the investment decision makers are different than who built the firm. So, you know, you see this time and time again when a firm scales like, you know, go back to the first fund. The GPU founder launches a fund. One has great judgment deals, you know, invest in some huge winners. You know, wins big, scales out to hundreds of millions of AUM hires a bunch of people MBAs, or, you know, others that aren’t making that are now making investment decisions that really don’t, you know, have the experience or the eyes, for what truly makes a great founder at a pre seed, seed stage. And so the fund loses this edge in the ability to drive returns because the GP is effectively retired. They do the podcasts, you know, they’ll write the blogs, they’ll be active on Twitter, but they may only do one deal a year. And so, you know, we see that. So, you know, we just think, as far as swell like, you know, we think we can be a top decile Fund, which we are in these numbers, you know, consistently, by building a venture brand with this differentiated value prop, with the strong judgment and just being, you know, continuing to stay hands on with founders in a series of $50 million funds. So that’s kind of the sweet spot for us and and, you know, kind of how we look at it, and how it, you know, applies to swell.
26:32
And what do you think about the market? Right? We’re in a weird spot. You know, it’s the exits have, kind of, the IPO window has been closed. Exits have been shut. I think regardless of what happens in the election in November, we’ll probably get a better platform when it comes to the FTC, but two different platforms there, like any thoughts on, sort of the exit market and more dpi, coming back from two guys who have actually generated some dpi, which doesn’t always happen on this show. Well,
27:03
I mean, I think you have to actively and aggressively look for dpi. It’s not enough to just, you know, look at the macro and kind of wait, but at the same time, you know, they call it a feature and not a bug, is the liquidity of VC, and being in such a long time horizon and not being able to sell it. And so I think that obviously we need some big macro shifts. We need, you know, environment that propels acquisition acquisitions, you know, politically, you know, economically, there’s a lot of macro things that we’re hoping, you know, start to shift in the next several years. But you know, what we can control is, is really the investment decisions, you know, finding companies that solve real problems and do it in, you know, truly, like, breakthrough ways. Yeah, we
27:47
want to stop, you know, stay away from, like, trying to predict, like, the nature of these cycles and the length of these cycles, right? It’s not a timing game for us. It’s like, invest in the right people solving really hard problems that have massive, you know, market potential, and then let the score take care of itself. In a way, it’s truly an investor’s mentality, like 10 year cycles. Like we don’t see ourselves as anything less than a 10 year farm. Yeah, it’s
28:10
interesting. Like, I was at the primary summit in New York City in your backyard last week, and it seems like there’s some optimism. It seems like people are seeing more activity. Seems like more deals are getting done at the same time in that Carter report. Like, I think they also mentioned that there were the most startup failures ever on record in history, in q1 of 24 so you’re dealing with that. And like, you know, the exits have been fairly closed. And you know, we’ve long held the belief that the market is really not going to get liquid again until the exit capital comes in, and that fees the entry capital. So it’s kind of a weird spot, but maybe, hey, maybe post November, maybe we’ll write the course here. Well, while I’ve got you guys, I don’t, I don’t want you to get away without talking AI. So you know that may be the most interesting area to invest in, but it’s also peak hype, right? How do you navigate investing in AI when it’s been so overvalued in recent quarters, and in many cases, you know, the business models and the monetization, you know, are still nascent? Yeah, no,
29:12
definitely, right. Can’t go without talking about it. I mean, it’s it is an exciting area, right? There’s no doubt. There’s also a massive hype cycle around it. Think it’s hard to say most people would agree with that, and the challenge is that a lot of these AI companies are now being overvalued without strong business models right to support those valuations. The tech itself is nascent. We’re still trying to figure it out, what in all the limits of llms and beyond what else is required alongside llms to really solve real business problems. So, yes, it does present a challenge, but it’s an amazing opportunity. And the key for us at swell and for us Tina is like, how do we navigate this landscape? Right? How focus on fundamentals over right? We approach AI at large asking a few questions, is the cost? Is the founder solving a real customer problem? I think, rather. You alluded to this earlier, like, we don’t invest in companies because, just because they’re using AI, it’s not a hammer looking for a nail, right? We invest because they’re addressing an urgent need, but AI now happens to solve better than anything else that has existed before, right? So the main reason why a lot of these AI start struggling, we believe, is because they’re not really solving a real problem. And then we avoid the trap of like, AI for AI’s sake, by prioritizing the companies that have a clear value prop and a real understanding of those pain points that need to be solved for. And also, we try to stay away from over reliance on any one type of AI, like when you say, AI, what are they really? It’s llms. It’s these large language models, right? They have the limitations, and I think that has come to bear. There’s no silver bullet solve all problems at once, using just llms alone. So we also had a lot of interesting conversations with founders and learning a ton about combining llms, today’s version of llms, with other technologies and other approaches. Might be planning engines, reasoning engines, to really create these unique solutions. Again, going back to real problem solving versus just following the hype cycle now. So long story short enough focus on substance over excitement. That’s a hard thing to do, because it really takes a lot of discipline and backing founders who really, really deeply understand the problems they’re solving. For Is
31:15
there a way that you think about defensibility and long term sustainable competitive advantage when it comes to AI, you know, with the speed of innovation there, and the degree to which llms are evolving, and new ones are coming up, and infra is changing, is there, you know, a framework around defensibility long term when it comes to AI investments, I
31:37
don’t think the defensibility is purely about the llms, you know, I think the develop the defensibility is, I think what’s, what’s coupled with the llms, right? I mean, if you look at else, you know, we’re talking about more, more and more compute. Or, you know, we’re talking about like this, it seems like this convergence, where the foundational models, you know, all look pretty similar. You also have in there, they maybe have different use cases that are better but, but then you also look at all the foundation models, or just look at AI as a category, like, who making the money, like Nvidia is making all the money, you know, are any of the foundational models, like profitable. So I think that, you know the defensibility comes in, what you surround the llms with, and you know that might be innovation in the business model. It may be innovation and how you combine different types of technology. It may be innovation in, you know, how you solve, solve for problems, but also, like, abstract away, like complexity. I think there’s a lot of other ways to to create a mode, but I don’t think you know just the LLM will necessarily be the most Very good. All right,
32:42
guys, if we could feature anyone here on the show, who do you think we should interview and what topic would you like to hear them speak about?
32:49
Oh, man, love this one. I mean, it’s Jeff judge, an investor, a friend, a mentor. It’s an amazing person. He led, like that first investment in this AI startup that rusty and I were at the way we met. He was an earliest, the earliest believer in us. He’s one of the most prolific angel investors in New York City. He’s done over 200 possibly closer to 250 investments alone. Operates very much under the radar as one of those OG New York angels. He’s both former founder who had an amazing exit and kind of shaped, kind of the early kind of infrastructure for the world of advertising and marketing, you know, technology. And it was actually Vc as a GP as well. So he’s been everything to us. We love him. Be an awesome guy.
33:32
Guys, what book, article or video would you recommend to listeners? There’s so many,
33:36
I would say, like just right now, you know, being a tennis player. I’m now reading Andre Agassi autobiography open, and it’s this really vulnerable port portrayal of his life. You know, he’s grappled with all these circumstances, his sport, his inner demons, you know, transformed all these things into a fulfilling life. And that’s so I’d say that. And also, it’s just been really cool to see him come back into the into the spotlight this year, you know, at the US Open and NYC. He’s, you know, such an American original.
34:03
Are there any current players that are going to reach the level of the big three? Oh, I
34:08
don’t know that. That’s, that’s a great question. But watching, I just, I mean, Alcaraz is just phenomenal. I mean, yeah, I love watching him, but I really liked watching I don’t know if he’ll get there, but tiafoe in this current, the current US Open, this past US Open, was was amazing and so fun to watch, but Alcaraz is just watching Alcaraz run around to the opposite side of the court to hit a forehand is just insane. He’s phenomenal.
34:35
Seeing the best of the best do what they do in any domain is always great. Guys. Do you have any habits, tactics or behaviors that are a force multiplier?
34:43
Good question I would say, I would say, like, context, context shifting, you know, like, I think when you move around from in your work environment, right? And when you work from home, which happens a lot, you know, but also, you know, going to the park, like going to portfolio companies often. Is what we do. You know, meeting at a coffee shop, meeting at a bar, holding a meeting, walking, holding me outdoors. I do think there’s something about this, like, mental space that’s created in different environments that can bring, like, clarity and creativity to problem solving that’s helpful. Yeah, I
35:14
second rusty here. I mean, I love throwing myself into new and very uncomfortable environments. And part of why we’re in Spain at the moment is put our kids in school. We wanted to learn a new language. Want to take them out of the comfort zone. Been in New York for 18 years. We’re like, let’s switch things up. And, you know, having that routine, having structure, it’s great when you’re optimizing for efficiency in different ways, like if you require a lot of focus and repetitive structure, process driven kind of tasks, then great. But they like, given what rusty and I do with swell is like, there’s no data, right? Like, there’s two things we have. It’s a track record of the person, the founder. It’s like, who they are and what they’ve done in the past, who you’re about to invest in. And this is like, massive vision that they laid out to reimagine industry, like a way that the rest of the world is completely missed, right? So we’re trying to see the unseen, and I think that requires a certain level, like training yourself to do this, like mental and emotional, like contortion, and then thriving in that state of contortion. I think you have to be uncomfortable all the time.
36:10
Perfect. And then, guys, what is the best way for listeners to connect with you and follow along with swell? Absolutely,
36:16
yeah, swell.vc, is our website. You can find our email address, email us. We’re also an X and LinkedIn, so we’d love to connect. So first names at all right,
36:26
they are rusty Ralston and Jay Patil, and the firm is swell. VC guys, congrats on all the progress in the DPI that’s exciting in this market and in any market. And I wish you know the best going forward as well. Amazing. Thanks
36:40
so much for having us on. Really appreciate it. Thank you
36:42
so much. Thank you so much. It’s been great.
36:49
All right, that’ll wrap up today’s interview. If you enjoyed the episode or a previous one, let the guests know about it. Share your thoughts on social or shoot them an email. Let them know what particularly resonated with you. I can’t tell you how much I appreciate that some of the smartest folks in venture are willing to take the time and share their insights with us. If you feel the same, a compliment goes a long way. Okay, that’s a wrap for today, until next time, remember to over, prepare, choose carefully and invest confidently. Thanks so much for listening.
