Meet Jim Ferry and Volition Capital
Jim Ferry is a Partner at Volition Capital, a Boston-based growth equity firm that invests in Series A and Series B technology companies. Jim joined Volition right out of undergrad and worked his way from analyst to partner over 12 years.
Volition’s investment criteria are fairly specific. The firm generally looks for companies with $5 million or more in revenue, strong growth, and a capital-efficient path to scale. As Jim explained, Volition is especially interested in businesses that haven’t needed “huge sums of capital” to reach that level of traction. From there, the firm evaluates market size, serviceable opportunity, durability, and, above all, the management team.
As Jim put it:
“There’s five things that matter: product, market, management, management, management.”
~Jim Ferry
That mindset is especially important in the AI era, where product velocity has accelerated, competition can appear overnight, and investors are asking tougher questions about what will still matter three, five, or ten years from now.
The Right Way to Present TAM to Investors
Founders often feel pressure to show the biggest possible total addressable market. Jim understands why. A massive TAM can make a startup look more exciting, and no founder wants investors to think the opportunity is too small.
But according to Jim, overstating TAM can backfire.
One mistake he sees often is when a founder says they sell software to SMBs, then uses the total number of small and medium-sized businesses as the basis for their market size. The problem is that most companies don’t truly serve every SMB. There are industries, customer profiles, price points, workflows, buying cycles, and use cases that narrow the actual serviceable market.
Jim’s advice is to take “as many cuts as you can” to show who you actually serve.
That means founders should separate a broad theoretical market from the real market they can win. For example, instead of saying “there are millions of SMBs, therefore our TAM is enormous,” a more credible approach would define the specific verticals, customer size, budget range, pain point, and adoption readiness that make up the true opportunity. This kind of realism builds investor trust.
The key point for founders: investors will run their own TAM analysis. A huge top-down number won’t survive diligence if it isn’t backed by a thoughtful bottom-up case.
Founders should be prepared to show:
- Who the ideal customer really is
- How many of those customers exist
- What they can realistically pay
- Why the company can capture meaningful share
- Which segments are in scope now, later, and never
Jim also made an important point that many founders overlook: a smaller TAM doesn’t automatically make a company unattractive. A company can still create a strong outcome by gaining a disproportionate share of a focused market.
“You can build a really strong business in a small TAM if you gain a disproportionate share of it, and that’s fine.”
~Jim Ferry
He shared the example of Automatic, one of Volition’s portfolio companies, which serves the live event secondary ticketing market. It is a finite market, not an infinite one. But Volition believed the company had a path to capture meaningful share, and the company executed well.
For founders, that’s the lesson. Don’t inflate the market to make the business look venture-scale. Show investors that you understand the market deeply enough to win it.
In the AI Era, the Defensible Moat Question Comes First
AI has lowered the cost and difficulty of building software. That’s exciting for founders, but it also creates a strategic problem: if a product can be replicated quickly, investors need to understand what makes the company durable.
That shift is reshaping how Volition evaluates companies. Historically, building a strong engineering team and product could be a meaningful advantage. Today, AI tools can help small teams ship quickly, prototype faster, and create products that previously would have required far more technical capacity.
That means the “why can’t someone else build this?” question has become more urgent.
“Coding and engineering is no longer the barrier to entry that it was. So you need to have some other type of durability or defensibility in the long run.”
~Jim Ferry
Jim listed several possible sources of durability:
- Proprietary or first-party data
- Non-public integrations that are hard to secure
- Deep domain expertise in a specific vertical
- Distribution advantages
The best AI-era startups won’t rely on product novelty alone. They’ll build around an advantage that compounds over time.
This is especially important for companies that might otherwise be dismissed as “wrapper” businesses. If a product is mainly a thin layer on top of someone else’s model, it may be easy for competitors, incumbents, or model providers to replicate. But if that product is tied to proprietary data, unique distribution, deep customer workflows, or hard-won domain knowledge, the business becomes more interesting.
Jim said durability now comes up constantly in Volition’s internal discussions:
“The durability, the defensibility, that is the question that we’re asking in every single investment committee when we’re talking about potential companies.”
~Jim Ferry
For founders, the implication is clear. Your pitch needs to answer the moat question before investors have to ask it.
What Volition Learned by Studying Founder Attributes
Investors love patterns. They want to know whether great founders share common traits, backgrounds, or experiences. Volition tried to answer that question systematically by analyzing outcomes across its portfolio and mapping roughly 100 founder attributes.
The result was surprising: there was no obvious founder formula.
Volition found successful founders from elite academic backgrounds and successful founders who never went to college. It saw strong outcomes from first-time founders and from founders who had failed several times before. There was no simple biographical pattern that reliably predicted success.
That doesn’t mean founder evaluation is random. It means investors are often looking for qualities that are harder to quantify: judgment, resilience, execution speed, adaptability, ambition, and the ability to attract and retain strong people.
One pattern Jim did call out was that two-founder teams have often worked well for Volition. He likes when co-founders bring different temperaments, especially when one is more optimistic and the other is more skeptical. That balance can help teams make better decisions under pressure.
As he put it, an optimist and a pessimist can “balance each other out.” Two optimists may underprice risk. Two pessimists may struggle to move fast enough. A balanced founding team can debate hard questions without getting stuck.
That said, Jim was careful not to turn this into a rule. He has seen strong outcomes with solo founders and even with five-founder teams. For solo founders, one of his first questions is often: who is your number two? He wants to see someone close enough to the founder to push back, challenge assumptions, and help the company make sharper decisions.
“Who is your number two? You need to make that person feel like an equivalent to you so they can push back.”
~Jim Ferry
Investors are evaluating the people around the table as much as the product on the screen. They want to see whether the team can handle market shifts, AI disruption, go-to-market challenges, and the inevitable moments when growth is not “up and to the right.”
The Bar for Raising Capital Has Changed
AI has compressed startup timelines. A company can now reach $10 million or $20 million in run rate with a much smaller team than would have been typical in the past. That can be impressive, but it also creates new diligence challenges for investors.
If a company grows extremely quickly, investors may not have much historical data to evaluate. There may be limited renewal history, limited cohort data, or no full customer lifecycle to study. In those cases, Jim said Volition puts more weight on customer references and usage patterns.
The questions become:
- Is the product mission-critical, or merely interesting?
- Are customers using it repeatedly?
- Does the product sit inside an important workflow?
- Will customers renew once the novelty wears off?
- Is the pricing model masking weak engagement?
Jim pointed out that some AI products are purchased casually, often through freemium plans or low-cost monthly subscriptions. A $35-per-month tool bought on a company credit card may not go through the same procurement rigor as traditional enterprise SaaS. That makes usage and customer love even more important.
In other words, revenue alone may not be enough. Founders need to show quality of revenue.
That could include product usage data, customer expansion, embedded workflows, retention signals, reference calls, and clear evidence that the product solves a painful problem. In the AI era, investors know that growth can happen quickly. They also know it can disappear quickly if the product is not essential.
Jim’s advice to founders is to stay realistic, especially when building plans around AI-fueled growth. Yes, some companies are going from zero to tens of millions in revenue at remarkable speed. But those companies are still rare. If founders put an aggressive plan on paper, they need to back it up with data.
Every Business Needs to Be Somewhere on the AI Spectrum
Jim believes every company now needs to think of itself as an AI business in some way. That doesn’t mean every startup needs to train models or become a pure AI infrastructure company. But it does mean founders need to be actively using AI to improve operations, product, and decision-making.
He described a spectrum. On one end are companies using AI internally to solve problems without simply adding headcount. On the other end are true AI-native companies building models or AI-first products. Many companies fall somewhere in between.
But standing still is dangerous. Jim’s advice was blunt:
“You need to be somewhere on [the AI] spectrum, if you’re not you’re dead.”
~Jim Ferry
For founders, this means AI adoption is now part of operational credibility. Investors want to know that the team is experimenting, learning, and adapting. They want founders who are “tinkerers” with AI, people who test new tools, use different models, follow what is changing, and understand how AI can alter their own business before it alters the market around them.
That same mindset applies at Volition. Jim said the firm holds weekly internal sessions called Volition AI Labs, where team members demo AI tools, experiments, and workflows. Some are directly relevant to the firm’s day-to-day work. Others are more exploratory. The goal is to build shared fluency, not let AI expertise sit with only a few people.
How Investors Are Using AI to Source and Evaluate Deals
AI isn’t just changing the companies investors evaluate. It’s changing how investors work.
Jim said Volition is using AI to automate and analyze parts of the investment process. That includes taking a data pack and putting it into Claude, training AI agents to understand what kinds of companies specific investors like, and helping analysts source companies that match a partner’s investment style.
That matters for founders because the investor workflow is becoming faster, more data-driven, and more personalized. Investors can screen markets, synthesize materials, identify patterns, and search for companies in increasingly efficient ways.
AI doesn’t replace judgment. It sharpens the process.
Volition still spends significant time with founders, including in-person meetings and meals, because the human side of investing remains critical. AI may help investors find and evaluate more companies, but management quality, adaptability, and trust still require human judgment.
For founders, the takeaway is to assume investors will be better prepared. Your claims about market size, growth, retention, and defensibility need to hold up under scrutiny that’s faster and more analytical than ever.
Building a Durable Company When Software Is Easier to Build
The AI era creates a strange paradox for founders. It is easier than ever to build a product, but harder than ever to build a durable company.
That means founders need to think beyond the first version of the software. They need to ask:
- What do we learn that competitors cannot easily learn?
- What data do we collect that improves our product over time?
- What customer relationships or integrations become harder to displace?
- What distribution advantage can we build before the market gets crowded?
- What workflow can we own so deeply that customers do not want to switch?
- How does our team keep adapting as models, tools, and customer expectations change?
Jim is optimistic about the startup landscape. He sees AI as another major transition period, similar to the shift from on-prem software to cloud-based SaaS. That shift created enormous value for founders and investors, and he believes AI will do the same.
But the winners will be the companies that combine AI-native speed with old-fashioned business durability: a real market, credible economics, strong execution, customer value, and a moat that improves with scale.
Final Thoughts
For founders raising capital today, the investor conversation has changed. A big TAM slide and a fast-growing AI product are no longer enough. Investors want realism, evidence, usage, durability, and a team that can keep adapting as the ground shifts.
The strongest founders will show that they understand their true market, know why they can win it, and are building advantages that last beyond the next model release.
Thank you to Jim Ferry for joining Startup Success and sharing his perspective on what investors look for in the AI era.
Brenda Hernández Jaimes: Podcast Producer & Talent Coordinator, Ellas Media
Angela R. Chong: Audio Editor & Post-Production Producer, Amplify Podcasts
Intro 00:01
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.
Kate 00:18
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 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.
Jim Ferry 01:05
Yeah. Thank you for having me, Kate.
Kate 01:06
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?
Jim Ferry 01:16
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 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 as we’re at an 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.
Kate 01:50
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 as a good company. The answers have, you know, run the gamut, but for you, what first catches your eye?
Jim Ferry 02:16
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, haven’t 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 overestimated 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 kidding on, that there’s five things that matter: product, market, management, management, management. So we spend a lot of time with the management team. It’s hard to quantify. 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 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 do just that.
Kate 03:25
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,
Jim Ferry 03:47
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 SMBs, and we have this software that serves SMBs. And according to the US census data, there’s this many small and medium sized businesses, So our TAM is this time. 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, you know, small fraction of whatever that 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 there’s 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 a smaller TAM, but we here’s why we think that we can gain a disproportionate share of it.
Kate 05:13
I think that’s really helpful, because you’re right. So many founders, I know they just want to go for the biggest number 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.
Jim Ferry 05:30
For sure. And don’t get me wrong, like, I love to invest in big TAMs. I’m not saying 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 get 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 suite, 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 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.
Kate 06:27
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.
Jim Ferry 06:53
Yeah. I mean, this is a people business. At the end of the day. I invest in people just as much, if not more, than I invest in 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 into 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, you know, 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, you know, have been kind of up into the right and the management teams are, you know, amazing, and they’re in a great market, but we’ve also had ones where, you know, 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, was able to shift strategies. I don’t, I don’t like, not necessarily pivot, but maybe, you know, change the 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.
Kate 08:12
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 all the time, but it’s just interesting.
Jim Ferry 08:32
Yeah, we tried to, I mean, it’s a relatively small sample size, I’d say, to the broader market, but within Volition’s 15 or 16 year history, we tried to map all of our outcomes, and I don’t know, 100 or so attributes of the founding team, and tried to see if there was any pattern. Like I said, there kind of wasn’t. 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 as their first business have an amazing outcome. And then someone who’s failed four times at 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, with 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 talked to 1000s 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.
Kate 10:13
Interesting. I love that you all went through that exercise, though, just to try to see if you could find something right? That’s pretty cool
Jim Ferry 10:20
We’re always looking for an edge.
Kate 10:22
Yeah. I know. That’s a great exercise. I think that you’re on to 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, yeah, there’s something to be said there.
Jim Ferry 10:56
I’ll talk on the other side of my mouth. One of my bigger, one bigger outcomes was five founders, which is unique too. (Five! Wow.) So, like I said, I’m not saying that, like, Hey, we’re all, we’re only investing in founding teams of two. But yeah, it, you know, it, there’s a spectrum.
Kate 11:13
Yes, yeah, interesting. 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.
Jim Ferry 11:28
Yeah, even like, another one of my portfolio companies is a solo founder, and one of the first things I asked was like, Who is 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.
Kate 11:56
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?
Jim Ferry 12:08
It’s a great question. It’s one we get a lot. It is 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 sales people, certain amount of executives, etc. Now with an AI company, you could be, you know, 10 million, 20 million run rate, with a few people. So, and they can get to that run right so fast that there may not be a ton of historical data for you to run the analysis. So there are some, 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 uses heir 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 just play around with this because, and we’re doing that internally on Volition as well, because our general philosophy is, how are we going to invest in an AI native AI business if we are not using AI? 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 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 currently at 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.
Kate 14:32
Absolutely, that’s a great approach, because when it I mean, our company’s 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?
Jim Ferry 14:57
For sure, and I think there’s times when we’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 literally a wrapper on top of someone else’s technology, very easy to replicate. And once you play around with it, 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.
Kate 15:50
No, 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.
Jim Ferry 16:05
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 trying to 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 Volition, we’d probably use it. None of us are coders. We’re all hacking together you know, solutions and vibe coding on our own, you know, to make our day to day more efficient. But, you know, 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, software is dead because people can just vibe code anything that they want. Sure, but there’s a convenience factor, like I said. 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’s focusing on a daily basis that they can do. I think the other part, or the other talk track of some of the pessimists is that OpenAI 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, you know, implement AI, and they have a headstart on having the first party data or distribution or so forth that, you know, someone starting from zero doesn’t have.
Kate 18:28
Excellent point on that one. Absolutely. So then is it changing the way you look at companies to invest in?
Jim Ferry 18:36
100%. Like, I just think, well it’s two things, like our process to finding companies and everything has been so automated and analyzed, from getting a data pack and just putting it into Claude and kind of spinning, spinning around for us. And, you know, we’re working now where I’m training an agent, and 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 Claude, it tends to know, like, all right, this is the type of company that this person likes. So then 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 the 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.
Kate 19:47
No, it’s really helpful. You don’t sound like a broken record. It’s 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.
Jim Ferry 20:18
How early are they?
Kate 20:20
Now with the way seed rounds are right with these 50 million seed rounds, our listeners tend to be more seed through Series B. But well well funded seeds, well funded seeds, let me just clarify that.
Jim Ferry 20:36
Yeah. I mean, I just think every business is an AI business now. And I think there’s a spectrum of 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 doing models, and then there’s a lot of 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 zero to 30 million in their first year and then 100 million, but, yeah, that’s happening, but 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 the viral effect of some of these businesses has changed, so it can still be a very aggressive plan, but if you put it on paper, you got to 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 is 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 if 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.
Kate 22:31
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?
Jim Ferry 22:41
Yeah, you go to our website, VolitionCapital.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 Jim at Volition Capital.com it’s pretty easy, and I’m starting to, you know, I get hot and cold, but I’m trying to be more consistent about tweeting on X so feel free to follow me @JimFerryVC.
Kate 23:02
Nice. I hear that. Thank you so much for being here today. Really appreciate your time.
Jim Ferry 23:07
Thanks, Kate. Really appreciate it.
Outro 23:10
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