What Investors Look for in the AI Era

Welcome to Startup Success, the podcast for startup founders and investors. Here you'll find stories of success from others in the trenches as they work to scale some of the fastest growing startups in the world. Stories that will help you in your own journey. Startup Success starts now. Welcome to Startup Success. In this episode, I sit down with Jim Ferry, partner at Volition Capital, a growth equity firm known for backing high growth, often bootstrapped companies. We break down what truly makes a company investment ready, how founders can stand out in today's competitive market, and how the bar for raising capital has shifted. Jim also shares his personal perspective on evaluating AI companies, what separates real innovation from hype, and. And what founders need to do today to build durable, scalable businesses. Welcome, Jim. So thanks for being here, Jim. We're excited to get into this conversation. Yeah, thank you for having me, Kate. So, to kind of set the stage, can you give us a quick overview of your background and kind of what led to your partnership at Volition Capital? Yeah. So I am a, as you mentioned, partner at Volition Capital. We're a growth equity fund out of Boston. Tend to be kind of series A, series B, be investors in tech companies. I actually joined there right out of undergrad. That, for this industry is a little bit unique, but that's kind of where Volition tends to hire is right at undergrad. So we can kind of train people the way that we want to and make sure that they think like us. So 12 years later, I kind of went from analyst all the way to partner, the second person at Volition to do that. And we always want to kind of promote from within and, you know, make sure that we're training people the right way so they can kind of scale within our organization. That's great. That is unique. Not many firms do that, but I can see where that could have its advantages, for sure. So what, like, you're looking at a lot of companies in your trajectory there. Founders always ask what stands out the most, you know, as a good company, like, and the answers have, you know, run the gamut. But for you, like, what first catches your eye? Yeah, I mean, right off the bat, Volition has a pretty tight investment criteria, so it kind of needs to fit that mold of 5 million plus in revenue scaling. Well, having taken on huge sums of capital to get there after that, I like to see big, total addressable market opportunities and kind of underneath that, a big serviceable, addressable or serviceable market opportunity. Because I think that one mistake that, you know, I think a lot of investors make, including ourselves We've made this mistake is kind of overestimating tam. So you want to feel like there's a big market to go after. And after that, I'd probably say the next biggest thing is management. We really spend a lot of time getting to know the management. There's kind of an internal joke that is probably, we're probably half getting on that there's five things that matter as product, market, management, management management. So we spend a lot of time with the management team. Like you kind of, it's hard to quantify. We've, we've tried to look at a lot of different attributes of some of our best investments and there isn't really a pattern in, in what makes a great entrepreneur. But you kind of feel it in your gut and just being in this industry long enough, you know, you kind of have pattern recognition for someone who you think can build a really big business and has aspirations to, to do just that. I want to get into that because I've heard a lot of investors say that. But before we do, you said something interesting about tam and I think a lot of founders can get sideways on that. And can you share with us some things that, that founders can do to make sure they're not, you know, they're looking at that in a realistic way? Yeah, you know, one, I'll give you an example of something that I see in like a lot of pitch decks is it's like, hey, we are serving, you know, SMBs, right? And we have this software that serves SMBs. And according to the U.S. census data, there's this many small and medium sized businesses. So our TAM is this, you know. Yeah, but realistically you can't, you're probably not addressing every single one of those businesses because there's a wide array of sub verticals. So thinking about taking as many cuts as you can to say, hey, this is who we're actually serving. And that number is probably a small fraction of whatever that big number is. And honestly I think doing that, you kind of gain credibility in my mind with investors. Because if you're just flashing this big number, I think some people think, oh, I got to show the biggest number possible. So people think this is a massive market opportunity, but all investors are going to do their own TAM analysis as well. And ultimately I want to feel like, hey, someone's already thought about this and you know, maybe the market isn't at, you know, $1 trillion market like AI or something, but you know, there you can build a really strong business in a small TAM if you gain A disproportionate share of it. And that's fine. And you know, we've seen exits even within our portfolio where the exit valuation was greater than the total addressable market opportunity. So it's not always a bad thing to say, hey, this is smaller tam. But we, here's why we think that we can gain a disproportionate share of it. I think that's really helpful because you're right, so many founders, I know, they just want to go for the biggest number as possible. And I think what you're saying is that it's better to be realistic and get to your number. Like show how you could really get to the number for sure. And don't get me wrong, like I love to invest in big tams. I'm not saying that that's not. But I think sometimes big total addressable market size means there's a lot of competition because a lot of people are probably looking at the same data that you are. Where, you know, I'll give an example of one of my portfolio companies, a business called Automatic. It's in the live event secondary ticketing market. They provide basically the entire software C from automated pricing to distribution to the POS for that market. And it's not an infinite market. It's finite, you know, depending on what data source you look at, it's kind of in the low double digit billions and in total GMV and they're taking a percentage of that. But they've executed really well. And there are reasons when we made the investment, we felt like they could gain a disproportionate share of the market. And you know, they've been able to do that and they've executed really well to do that. So that was a smaller everything's relative. So, you know, smaller TAM where, you know, we've seen a really successful business, that's a great example. And I really like how they like went off after such a targeted market. The other thing you said, and I love that how you said the founding team three times because I've had investors come on here and say things like, you know, one idea is a little bit weaker, but the founding team is stronger. I'll go with the founding team all day. And so I'm. You're saying the same thing. In a sense, the founding team is critical. Yeah, I mean this is a people business. At the end of the day I invest in people just as much if not more that I invest in their, their business. And I've seen it where the best product doesn't always win. I think the best execution does and it's never up and to the right. So you want to feel like you have someone that can weather the storm of macro market changes or the introduction of AI and how do they navigate that? And a really strong management team can do that, especially if they take on capital and they kind of maintain a relatively healthy cash balance. They live another day, so they can always have enough time to figure it out. And we've had companies who have been kind of up and to the right and the management teams are amazing and they're in a great market, but we've also had ones where they might take two steps forward, one step back and ultimately it winds up being an awesome outcome from an exit perspective, really, because the management was able to shift strategies. I don't, I don't like, not necessarily pivot, but maybe, you know, change your go to market strategy or something like that. So management matters a lot. It's really hard to quantify. That's why, as I mentioned, we spend a lot of time on the road just hanging out with founders, getting a meal with them. Like face to face. You can really get to know someone a lot better than you can over zoom. Yeah, interesting. So you've said that twice that you can't really quantify what it is, but it's more like that gut feeling when you meet with them face to face and have a meal with them. Are there any kind of characteristics you can put around it that. I'm sure you get asked this all the time, but it's just interesting. Yeah, we tried to, I mean, it's a relatively small sample size, I'd say to the broader market, but within volition's, you know, 15 or 16 year history, we tried to map all of our outcomes and I don't know, a hundred or so attributes of the founding team and tried to see if there was any pattern. Like I said, there kind of wasn't. Okay. Like we've had amazing outcomes for, you know, Ivy League educated founders and then founders who never went to college. We've, you know, seen young founders, it's their first business, have an amazing outcome and then someone who's failed four times, another startup and, you know, this is their fifth time around and they've learned from all those, have a great outcome. So it was kind of eye opening that there wasn't anything, I think some of the commonality that, you know, I don't know if it's causation or correlation was, was really that I think two founders was kind of the sweet spot. If it's like one founder, they may not have their counterpart to bounce ideas off of. I think some of our biggest wins have had a founder that like two founders, a very different personality. I personally love a founding team where you have an optimist and a pessimist because they tend to balance each other out. And find if you have two optimists or two pessimists, that's probably like a recipe for disaster. So I think that's a strong attribute. But yeah, punchline is it's really hard. I think you got to feel it in your gut. And that's why, you know, we talk to thousands of companies on an annual basis. I meet with, you know, hundreds face to face and kind of through that pattern recognition, and you're kind of building that muscle of trying to suss out the founders that you believe in and want to back. Interesting. I love that you all went through that exercise, though, just to try to see if you could find something Right. That's. We're always looking for an edge. Yeah, I know, that's. That's a great exercise. I think that you're onto something with the co founder thing. We've had people come on the show that talk about co founder dynamics and how they've seen when they have that balance that you described that you described it as optimist, pessimist, it can really help weather the storms and like talk through needed changes, pivots, you know, sounding boards. Just from my own personal experience, the startups I've worked for that had two founders are the ones that made it. So, yeah, I think that, yeah, there's something to be said there. I'll talk on the other side of my mouth. One of my bigger one bigger outcomes was five founders, which is unique too. But so like I said, it's not. I'm not saying that like, hey, we're all. We're only investing in founding teams of two. No. But yeah, you know, there's a spectrum. Yes. Yeah. Interesting, Bob. I think it just speaks to the fact that it's a really difficult role. Right. And there's so many ups and downs and changes. And so if you have someone there, like, to navigate it all together, it can be a benefit. Makes sense. Yeah. Even like another one of my portfolio companies is a solo founder, and one of the first things I asked was like, who was your number two? You need to make that person feel like an equivalent to you so they can push back. Because I think what happens sometimes with the solo founder is Everyone feels like that's my boss and I can't push back on them. And obviously in a respectful way, it's not, you know, you might want someone that challenges your ideas and that may ultimately make the founder and the company better. Yep, absolutely. I think that happens a lot. So then how does this differ now in the day of AI companies? Like, how are you looking at those companies a little differently? It's a great question. It's one we get a lot. It's very broad. I can take it a lot of different ways. But pre AI, we used to look for companies that have 25 plus employees that are scaling well. And that's kind of a good signal that they're for Volition's investment criteria at kind of 5 million plus run rate, which is where we tend to get involved. And that may have taken a couple of years because you need a certain amount of engineers, a certain amount of salespeople, certain amount of executives, etc. Now, with an AI company, you could be 10 million, 20 million run rate with a few people, and they can get to that run rate so fast that there may not be a ton of historical data for you to run the analysis. So there are some unique things like we're getting more comfortable with. Okay. We haven't really seen a renewal cycle here yet, so customer reference calls are going to be really important to understand. Is this mission critical or is this a nice to have? You have to look at usage patterns. How often are people logging into the platform and actually using it? Because I think a lot of the Pricing on these AI platforms is like, you know, a freemium model or $35 a month, and someone just slips the company credit card and they don't really think about it. And it doesn't go through like the typical procurement cycle that a historical kind of enterprise SaaS company has gone through. So it's nuanced. But I also, you know, going back to the founder, that you want to feel like they can adopt really quickly, especially in an AI world where things change so fast. You want to feel like you're backing someone who's like a tinkerer with AI, someone who's playing around not only for their business, but just, oh, this new tool came out. Let me, let me just play around with this because. And we're doing that internally at Volition as well, because our general philosophy is, how are we going to invest in an AI, native AI business if we don't even know how to say so? You know, every Monday we have Volition AI Labs, we call it, for lack of a better term. And we get together as a team and people sign up to do demos and they could be stuff that's aspirational, stuff that is very relevant for our day to day. And then kind of a third bucket was just like cool, fun AI stuff that people are building that has nothing to do with our job. Just because we're encouraging people to experiment and have knowledge transfer. Because last thing I'll say on this is I feel like a lot of companies have like a couple of people who are maybe experts in AI now and then a bunch of people who are still using the AI tools as more of a glorified search engine than really automating tasks and building agents. So there isn't that knowledge transfer happening internally A lot of companies. So we're cognizant of that and like trying to make sure that everybody's on the same page, which I think is ultimately going to benefit us in the long run. Absolutely. That's a great approach because when it, I mean our company is kind of going through something similar. In the beginning it was just a few people, but now we're all demoing when we've built a skill in Claude or somebody built an agent. Right. So it kind of inspires everybody. And then I'm guessing that must really help you in evaluating opportunities because you get it more just intuitively, right? For sure. And I think there's times when you're like well so I think that there's a lot of companies out there and you know, there's kind of been this term of like wrapper companies where they're, they're literal wrapper on top of someone else's technology, very easily, easy to replicate. And once you play around with it, you start with AI and start to just try to create something on your own. You start to realize how coding and engineering is no longer a barrier to entry that it was. So you need to have some other type of durability or defensibility in the long run. And there's a lot of different paths for that. It could be some type of data first party data moat, non public integrations that are hard to get even just domain knowledge and expertise in a specific sub vertical can be one distribution advantage, et cetera, et cetera. So we're kind of constantly thinking like what is the durable moat of this business over time because it's not going to be engineering anymore now. Very well said. So that being said, how are you feeling about the whole startup landscape with AI? I mean it kind of runs the mix. Some people are very optimistic, some people are pessimistic. I am optimistic. I view this as just another transition period that ultimately is going to create a lot of value for both investors and founders. So you know, there, if you think about the last big transition period, it was a transition off of on prem license and maintenance software to Cloud hosted SaaS. And to me this is just the next wave of that. And the more that, you know, I learn, I start to feel like for the Most part these LLMs are going to be akin to the AWS or azures of the world where they're going to be like the platform that enables a lot of entrepreneurs. I also think that people are underestimating the convenience factor. If someone showed up on our doorstep with the perfect set of agents in AI software for growth, equity for abolition, we would probably use it. None of us are coders, we're all hacking together solutions and vibe coding on our own to make our day to day more efficient. But I think about even my portfolio companies, they don't have time to vibe code every single piece of third party software that they use. So there is a convenience factor that I think people are overlooking a little bit when it comes to some of these companies when they're, you know, I think some of the pessimists will either say, you know, a software's dead because people can just vibe code anything that they want. Sure. But there's a convenience factor like I said, and they may not have the time and resources to maintain that and to, you know, build all the integrations and features that if that's what someone is focusing on on a day to day basis that they can do. And then I think the other part or the other talk track of some of the pessimists is that you know, open AI and anthropic are just going to become every single software company. And I just don't even know how that's possible. Like, I mean they are, it just gets back to the durability question. They are, you know, killing some software companies that lack some type of moat and defensibility over the long run for sure, but they're not going to create every single software company that's ever existed. If that's the case, the stock market would be, you know, in an absolute free fall right now. And it's not. And I think part of that is I think some of these, some traditional kind of enterprise SaaS companies are in a good position to implement AI and they have a head start on having the first Party data or distribution or so forth that someone starting from zero doesn't have. Excellent point on that one. Absolutely. So then is it changing the way you look at companies to invest in 100%? I just think we're trying to do two things. Our process to finding companies and everything has been so automated and analyzing them from getting a data pack and just putting it into cloud and kind of spinning it, spinning around for us. And you know, we're working now where I'm training and Adrian and someone else in our, one of the other partners at our firm has already done this where over, you know, 50 plus hours of just talking to and training cloud, we, it tends to know like, all right, this is the type of company that this person likes. So then you can, the analyst can then build a skill on top of that to go source companies in their wheelhouse. So you know, that's one when it comes to like automating and everything. But two is, you know, I don't like going back to my original point that engineering and the actual coding used to be a moat. Right. And because it's not anymore, the biggest thing that's changed is I sound like a broken record here. But the durability, the defensibility, that is a question that we're asking in every single investment committee when we're talking about potential companies. And we want to feel like the founder is someone that is able to kind of ride any updates because things are just moving so fast that they need to be, you know, truly AI, native. No, it's really helpful. You don't sound like a broken record. It just, you're making it very clear and you're framing it very well for the founders listening who are, you know, there's so many questions about this. So I appreciate it. You've shared a ton with us, it's been fascinating. I appreciate you being so open. We always wrap up the show with just general advice you might have for the early stage startup founders listening. This is their favorite question. So how early are they typically now with the way seed rounds are? Right. With these 50 million seed rounds. So our listeners tend to be more seed through series B. Yeah, but well, well funded seeds, well funded seeds. Let me just, just clarify that. Yeah, I mean I just think every business is an AI business now and I think there's a spectrum of what, what does native AI mean? That can mean a business that thinks about their operations as, hey, we're going to solve every problem with AI instead of throwing bodies at it in its simplest form. And then on the other end, it's like a true AI company where, you know, we're building models and then there's a lot of, you know, companies in between there. But you need to be somewhere on that spectrum if you're not dead. So I think that's one and two would be, you know, be realistic. Going back to the TAM exercise, I think that applies to a lot of different things. Like, you know, we've seen, I think everyone hears the stories about companies that go 0 to 30 million in their first year and then 100 million. But yeah, that's happening. It's such a small percentage of companies that have ever done that. So I think, and by the way, like, I do think that, like, the trajectory because of the viral effect to some of these businesses has changed. So it can still be a very aggressive plan, but if you put it on paper, you gotta be able to back it up with data. And last thing I'll say is just like, continue to be a tinkerer with AI. Use different models. Anytime there's a new update, even if it's not relevant for your specific business, you should be playing around with it. It's hard to keep up. Twitter's the best way to do it and just see whatever, whatever other people are doing. But just continuing to explore or you're going to fall behind. Because I heard a great quote how you're adopting AI and your competitor waits three months. It's not linear, it's kind of a J curve and they'll never catch up to you. So the more you can do now, the better you're setting yourself up in the future. I think that's great advice for anybody in the professional world right now. So thank you. Yeah. So thank you so much, Jim. Where can listeners go to learn more about Volition Capital? Yeah, you can go to our website, volition capital.com if you're a founder, kind of 5 million plus revenue looking for a series A Series B. Feel free to shoot me an email. Jimolitioncapital.com it's pretty easy and I'm starting to, you know, I get hot and cold, but I'm, I'm trying to be more consistent about tweeting on X. So feel free to follow me at jimferry vc. Nice. I hear that. Thank you so much for being here today. Really appreciate your time. Thanks, Kate. Really appreciate it. You've been listening to startup success to make sure you don't miss out on future episodes. Subscribe to the show and your favorite podcast player. Like what you hear. Tap the number of stars you think the show deserves in Apple podcasts. For more tools and resources for your own startup success, check out berkeland associates.com thank you so much for listening. Until next time.