#97: As ChatGPT’s Market Share Drops, What’s In It For You?

About Jim Ferry

Jim Ferry is a distinguished Partner at Volition Capital, recently named a Top Growth Equity Firm of 2024 by GrowthCap, a premier Boston-based growth equity firm renowned for investing in high-growth, founder-owned businesses within the software, Internet, and consumer sectors. Since joining Volition in 2014, Jim has been instrumental in evaluating and executing investment opportunities, particularly focusing on ad tech, consolidation platforms, mobile, supply chain & logistics, marketplaces, and other high-volume internet transactional businesses. We invest in a small number of founder-owned, capital-efficient businesses that aspire to lead their markets.
With a stellar academic background as the top business student at Providence College, where he earned his BS in Finance, Jim brings both expertise and passion to his role. His investment portfolio boasts successful ventures such as Aditude, Doing Things, Rounds, ButterflyMX, Automatiq, Revi, Grove Collaborative (NYSE:GROV), Connatix, and JazzHR.

Jim’s Links

Contact Jim at jim@VolitionCapital.com.

LinkedIn: https://www.linkedin.com/in/jim-ferry-91b33375/

Company Website: https://www.volitioncapital.com/

SUMMARY:

This episode reviewed recent reporting that ChatGPT’s market share is slipping as competitors accelerate distribution and integrations, and framed the current phase as a market-structure story where early leaders prove demand, capital floods in, competitors close gaps, and the window to dominate narrows. Participants contrasted consumer-facing and enterprise-facing AI, noting Claude’s rapid enterprise traction and higher monetization per user versus ChatGPT’s larger consumer base. Jim Ferry emphasized that releases like Claude Cowork—capable of reading CRMs, drafting messages, and building live dashboards—are shifting AI from occasional use to daily embedded workflows. The group warned against non-durable “wrapper” businesses built on third-party LLMs and urged focus on durability through proprietary data, unique integrations, and defensibility, while comparing this transition to past platform shifts such as SaaS versus on‑prem.

Discussion then turned to investment opportunities. Jim, speaking as a Series A/B investor, argued that AI will materially disrupt labor‑heavy services businesses, increasing efficiency so one person can serve many more clients and enabling roll-ups that convert low‑multiple services firms into higher‑multiple tech‑like assets; examples included fractional CFOs, accounting firms, and design services. The meeting ended with practical next steps: Jim shared VolitionCapital.com and his Twitter and invited outreach.

SHOW NOTES:

Welcome back everybody to DIY Cyber Guy.

HOF: 3 out of 5

For Users and Investors in the AI space.

On February 5th, Fortune published a piece called:

ChatGPT’s market share is slipping as Google and rivals close the gap, app-tracker data shows

Even with its massive head start, OpenAI’s ChatGPT is already feeling the pressure. The article makes it clear: “ChatGPT’s early dominance is beginning to slip as rivals rapidly iterate and capture user share,” with Google and others accelerating fast—through distribution, integrations, and enterprise penetration.

SOURCE: https://fortune.com/2026/02/05/chatgpt-openai-market-share-app-slip-google-rivals-close-the-gap/

This is not just an AI story. This is a market structure story.

We are watching the compression of competitive advantage happen in real time. One company proves demand, defines the category, and creates urgency. Then capital floods in. Competitors close feature gaps. Distribution scales. And the window to dominate shrinks faster than most teams are prepared for.

At that point, innovation is no longer enough. Execution and differentiation become everything.

And that exact moment—post product-market fit, pre market leadership—is where opportunity exists for all users – from enterprise to individuals.  The promise is better products, specialized services, and constantly improving results from your AI tools.

To unpack all of this, I am joined by Jim Ferry.

Jim is a Series A & Series B growth equity investor at Volition Capital, where he works closely with high-growth software and technology companies on critical items like scaling operations, and go-to-market execution.

Welcome Jim!

TRANSCRIPT

0:00 – David W. Schropfer
Welcome back everybody to DIY Cyber Guy. 0:00 – David W. Schropfer
Good.

0:03 – Unidentified Speaker
Welcome back, everybody, to DIY Cyber Guide. This is episode 97. As ChatGPT’s market share drops, what’s in it for you?

0:11 – David W. Schropfer
Now, this is a hair on fire three out of five for anybody that uses AI, which I have to believe is everybody that is listening to this podcast right now, but also investors in the AI space or even the technology space more generally. And here’s the issue. So on February 5th, magazine published a piece called ChatGPT’s market share is slipping as Google and rivals close the gap. So basically what they’re saying is, even though OpenAI’s ChatGPT had a massive, massive head start, they are already feeling the pressure from competitors after just a year or two. The article makes it clear that, I’m quoting now, ChatGPT’s early dominance is beginning to slip as rivals rapidly iterate and cash user share, and with Google and others accelerating faster distribution, integrations, and enterprise penetration. And as always, if you go to DIY Cyber Guy and search for Episode 97, you’ll see the source for this article right in the show notes. So this is not just an AI story. This is a market structure story. We’re watching the compression of competitive advantage happen in real time. One company proves demand, defines a category, the urgency, and then the capital floods in. Then competitors start to close the gaps, distribution scales, and the window to dominate shrinks faster than most teams are prepared for, which means everybody has to hustle to catch up and keep their product relevant. So at that point, innovation is no longer enough. Execution and differentiation become everything in the market. So at this exact moment, The post-production market fit has been established with AI. We’re all aware of it. We’re all using it. Pre-market leadership has been established. The opportunity exists for all users, even enterprise and individuals, to start to change their habits and their work structure in a world where AI is a major tool to make you more efficient and more productive. So the promise of all this happening now is better products, specialized services, and constantly improving results that you get from using the AI tools that you use every day to do your jobs, to do your work, or to live your lives. So to unpack all of this, I’m joined by Jim Jim Ferry. Jim is a Series A and Series B growth equity investor at Flowition Capital, where he works closely with high growth software and technology companies on critical items like scaling operations and go-to-market execution. Welcome, Jim.

2:51 – Jim Ferry
David, thanks for having me. Absolutely. Thank you for being here.

2:55 – David W. Schropfer
So let’s start with the basics. ChatGPT’s market share is slipping. Other competitors are coming up. From 30,000 feet, what’s in it for the end user? What’s in it for the customer?

3:07 – Jim Ferry
Yeah, well, I think it’s interesting, you know, that everything’s moving so fast in this AI world that there were a lot of stats in that article. They’re probably all outdated because it was 50 days old because things are changing on a day to day and week to week basis. I think the sentiment of the article holds true. And in the closing paragraph, someone likened these AI wars to the streaming wars. And if you think about the streaming services like Netflix, HBO, Hulu, Peacock, however you want to, I’m sure everyone that’s listening subscribes to some, if not all of those. And the reason why is because they’ve all carved out their own niche. Even when I think about some of the powerhouses of content, Like Netflix, I tend to view as quantity. They push a lot of content out in, you know, a pretty fast manner where HBO is much more curated content. And they’ve had a quality over quantity view, I think. And you think about some of the biggest shows of last decade or so, or even longer, like Sopranos, Game of Thrones, like those have all been HBO shows. And I think that there’s a lot of stuff on Netflix that people binge and might even forget I forgot if they watched it.

4:18 – David W. Schropfer
Two separate models, both can be successful as we’ve seen in that category. How do you draw the parallels between the quality quantity example in your streaming video or streaming services versus AI, which is just trying to make everybody that’s using it more efficient, more effective at what they’re doing?

4:38 – Jim Ferry
Yeah, so I don’t think that the parallel in AI is quality and quantity. Because they all need to have quality. I think what’s happening is you’re seeing a distinction between consumer-facing AI tools and enterprise-facing AI tools. So when I think about the consumer side, the two category leaders there, in my mind, are OpenAI’s product, ChatGPT, and then Google’s product, Gemini. On the enterprise side, I think about Anthropic’s product, Claude.

5:10 – Jim Ferry
They’re almost different business models in a way. You know, Claude has a fraction, almost a rounding error number of users that ChatGPT has. I think they only have 19 million consumer MAUs, but they’re monetizing at roughly 8x that of a user on ChatGPT because Claude tends to be the enterprise solution. Even at Volition Capital, all my portfolio companies, everyone’s using Claude. If you rewind six months ago, that was not the case. I think everybody’s using ChatGPT and they were more using it as a discovery tool. Hey, help me write this email. And I think that someone had a line that prior to Claude’s recent update with Cowork, they were visiting AI and now they’re using it. And I kind of feel that as well. So Claude had a big release on Cowork and that can kind of access files locally on your computer, browse the internet for you. So the amount of tasks that you can do has multiplied by an order of magnitude, I’d say. And because of that, it feels like they’re becoming the winner on the enterprise side, where the monetization is through corporate credit cards. People care less about what that expense is, because it’s someone else’s money in their mind, even though it’s their company. Where you think about ChatGPT, they have, I don’t know what the number is, something like 10x, probably more than that, the number of users as Claude, but only 5% them, they’re monetizing. And when you think about what goes into chatting with any of these AI search engines or bots, however you want to call it, there’s a lot of compute power that’s expensive. That is why ChatGPT is burning $17 billion per year, I think. Every time that someone logs in and asks it a question and they have to have a response, cost them money and 95% of their consumers are not spending, don’t subscribe to a subscription. The only lifeline out of that is advertising.

7:14 – David W. Schropfer
And they are young when it comes to advertising.

7:16 – Jim Ferry
So for many reasons, I think that Google’s better positioned to capitalize on that. But roundabout way of answering your question is I think it’s really bifurcating between enterprise and consumer focused AI.

7:32 – David W. Schropfer
So that’s a great example. And the bifurcation between enterprise and personal tools. Got a couple of follow-up questions there. So one, do you see it bifurcating again? Or do you see more sectors coming out other than just enterprise and personal? Is it going to split again within, say, the enterprise segment, HR uses versus financial uses? I don’t know.

7:56 – Jim Ferry
I don’t know if it’ll be the actual LLM or kind of the platforms that we’re talking about, but I think that we’re already seeing that play out. And that’s the opportunity for me as a Series A and Series B investor is there’s basically every single category where there was a traditional incumbent on the software side, there’s going to be an agentic solution that’s built on top of these LLMs. So I think that’s where you’re going to see like the next split when it comes to bifurcation.

8:24 – David W. Schropfer
Okay, good. And when thinking about cloud, Claude versus ChatGPT, a lot of people were exposed to AI using ChatGPT. It was really the first one out there that people got to experiment with. How would you describe the change? I liked your quote of somebody that said, it’s the difference between visiting AI and using AI. So when you say that most of your portfolio companies are using Claude, that’s differently from visiting ChatGPT. What is that difference? And more importantly, what kind of competitive advantages are they experiencing because they’re using cloud and based on the way that they’re using it?

9:06 – Unidentified Speaker
Yeah.

9:07 – Jim Ferry
And like I said, things are moving so fast that this is almost new. Like two quarters ago, I think most people are using chat GPT and opening eyes.

9:14 – David W. Schropfer
So we’re talking a point of time of who has the leadership.

9:18 – Jim Ferry
And I think that we’re starting to establish specific swim lanes.

9:25 – Jim Ferry
And as I mentioned, Claude has kind of become the winner, despite the fact that I think chat GPT with their newest update has a lot of the same functionality. But it’s just how people kind of view them. And in a moment in time, you know, Claude had really good marketing and simple kind of messaging about and they released a lot of new products and functionality. So the example that I give of visiting is my six months ago, or, you know, nine months ago, whenever it was my, my usage for chat GPT is more likened to help me craft this email better, you know, really around like communication and hey, how do I communicate this difficult topic to a coworker of mine or something like that. And they’re kind of giving you, you know, some suggestions. But it was also a little bit on the consumer side where I’m using it for research for certain things. If I want to buy a product, it can help me find something or, you know, fixing something in my house. That’s a good use case.

10:25 – David W. Schropfer
And to me, like, that’s just a fancier version of a search engine in a way, if you’re using it that way.

10:32 – Jim Ferry
Whereas today, the way that I’m using cloud is very different. Co-work, for example, can read our CRM, see the 20 companies that I have a task to reach out to. It can click into the CRM record and understand the context of when was my last contact? Or am I still, have I never reached out to this person? Are we friends, et cetera, based on all the data that’s already in there. And it can craft a custom message or it can reach out on LinkedIn for me. So it’s doing that autonomously, where before I was copy and pasting something and every time kind of going back to chat GPT. So now I can have, you know, 50 tasks and say, hey, roll through all my tasks. And for compliance reasons, I don’t let it send anything, but everything is drafted and ready to go. And all I need to do is quickly review and hit send. That’s a great use case. Another use case that just happened today is I had a CFO show me a brand new dashboard that they created using Claude where it syncs up with all of their financial information. And it’s basically a live dashboard in real time. We can click through and see all the metrics that we care about in the business. Prior to that, I’ve had portfolio companies that are spending, you know, 50 grand on Looker or some data tool and hooking up into all of their different systems. And it’s a, you know, three to six month project to have everything come out. This is somewhat a CFO who has no coding background, no and they’re able to code a pretty useful dashboard for us. So those are a few examples of what I think using AI is versus visiting it, when you’re quickly asking a question, getting your answer, and jumping out of it, as opposed to living in it as a core workflow for your day-to-day. Excellent.

12:20 – David W. Schropfer
So as we move toward that core workflow, God, I almost used the word paradigm. Sorry about that. As we move toward more workflow, workers using it as a much more sophisticated tool, including, your example is perfect, of actually what would have been a coding project not very long ago, even six months ago, that really would have been a development project that would have needed a team of developers and the usual development workflow to make a product or make the dashboard, make the app, pull in all the information, et cetera, a six-month project, like you said. And now it’s just a number of… Or Claude is really writing the API bridges to the extent that they’re needed to pull in whatever data is necessary to make the AI function like the CFO wanted to do. I think that’s a brilliant example.

13:11 – David W. Schropfer
You also mentioned that a lot of different AI products have a similar ability. So if that same request was made of another product, was made of Gemini, it might’ve been a slightly different process to make that dashboard, but Gemini could have made it. So is this a marketing race? Is this just the fashion marketing?

13:36 – David W. Schropfer#+#Jim Ferry
Yeah, I think so. Yeah, I think in that example, it’s funny.

13:43 – Jim Ferry
If someone was going to try to build that, I would tell them to use Anthropics product Cloud. Right.

13:52 – David W. Schropfer
I don’t think that they could go wrong with ChatGPT either.

13:55 – Jim Ferry
I’m sure you can do the same thing just based on the recent update. But it’s funny, I don’t even think about Gemini as having that capacity, and I’m sure they do. But like I said, I tend to think about them more as a consumer-facing product, and it’s interesting. I tend to view them going up more against ChatGPT on the consumer side today. Now, Gemini has the benefit of being a Google product, and Google has almost playing a different game where Google released Gemini into its workspace for business and enterprise products. So overnight, they have 27 million users or something like that. So it’s showing up in people’s Gmails, the docs and so forth. But the real beneficiary of that is Google Cloud, where, you know, that I think grew 34% annually, it’s, you know, 50 billion plus in revenue. And given all the compute power Google Cloud is the beneficiary of that. So, you know, I think from a business perspective, Google’s taking a little bit of a different strategy where it’s, hey, we already have all these business users on Google. On the consumer side, it’s interesting because I talked about ChatGPT only monetizing 5% of their users. So now they’re testing ads to, you know, to go after the other 95%. If Google, on the other hand, already has one of the largest ad ecosystems They have the largest ad ecosystem in the world built out already that they can leverage for this, which they are doing already and they’re going to. They also have the number one browser, the number one search engine, the number one mobile operating system in the world. So I think that they’re really well positioned and probably the most historical data. So they’re really well positioned, I think, to go after the consumer. But it’s a classic innovators dilemma where they need to disrupt their own business model a little bit in order to do that. Always been in this AI race, a little bit of a fast follower. I don’t think that they’ve been the innovator, but they are really well positioned. And when you go to Google today, depending on what you search, a lot of times you’re getting an AI result, which is Gemini, basically in the traditional search bar above the results. I think that’s going to continue to evolve, where depending on what you search for, for example, if you type in Nike shoes. It might look similar to what we’re seeing today, where you have a scroll on the shopping side of a couple of different Nike shoes. But if you type in the Greek goddess Nike, it might look more similar to how people vision like a chat GPT answer. So Google search is continuing to go up year over year and growing. And I think people don’t tend to view that as an AI LLM or chatbot. But I think that’s where they’re going is it’s ultimately just going to become more and more of a chatbot because people are already using it. They don’t really need to change their behavior. And they already have the infrastructure set up from an advertising perspective. Oh, and by the way, they can subsidize all their AI compute power based on their crazy profitable cloud business. So they’re in a really good spot to ultimately win the end consumer, I think.

17:10 – Unidentified Speaker
Right.

17:11 – David W. Schropfer
You’re an investor, and I know with investors, it’s hard to bring up this thing, if you recall, the dot-com boom, because there were a lot of horror stories. There was a lot of wealth created and a lot more wealth wiped out during that period of time. But I think we’re both old enough to remember some of the arguments, which is how could this upstart Amazon thing actually compete against Barnes and Noble dot-com or these heavily established brick and mortar retail companies that all they have to do is put up a website. They’ve got the distribution center. All they have to do is ship a product to a person as opposed to shipping it in bulk to a store. And they can’t possibly have competitors that are just an online presence because how can you possibly build the brand name? How can you create enough flash to create enough attention and get enough customers and get enough traction to actually win? But that’s exactly what happened, right? Are there any lessons to be learned? And I get it ago 25 is, you know, another universe compared to where we are now from a technology standpoint. But are there lessons that we can learn from some of the assumptions that were made before, during and after the bubble of the dotcom boom versus what’s happening now with the growth of AI?

18:25 – Jim Ferry
Yeah, well, I think it is relevant. History tends to repeat itself. I think that there, I mean, the dot-com bust happening and there being a lot of wealth, but a lot of dollars lost as well. I think we can all agree the internet was a success.

18:47 – David W. Schropfer
I think that’s going to happen here in this AI world as well.

18:53 – Jim Ferry
You’ve probably heard a lot of people talk about this from an investor perspective. There’s been a lot of venture dollars flowing into what I would consider non-durable AI businesses. So businesses that are really just a wrapper. So like sitting on top of someone else’s technology. And that’s kind of become like a dirty word if you’re, you know, or you’re just a wrapper on top of someone else’s LLMs. And what people really mean by that is there’s no defensibility. Coding is no longer a barrier to entry like it used to be for software products. And we talked about that CFO of mine who kind of created their own dashboard. A great example where if you’re a data visualization tool, that’s got to be pretty scary for you, right? So I think if you don’t, if you have a product that someone can easily replicate, there’s going to be a race at the bottom on pricing, because there’s going to be a ton of competitors. So we’re focused a lot, and I think a lot of investors now are focused on durability. And that comes in a lot of different forms. That can be proprietary first party data, that can be distribution points, that can be integrations that are not open APIs or public, that gives you an advantage, and so on and so on. So that’s ultimately what I think we’re asking ourselves. So I think that there’s probably a lot of AI businesses that were extremely overvalued, grew like crazy, because there’s been a lot of demo users, because the pricing model is a little different. If you want to go buy Salesforce, it’s going to be, you know, for your startup, it’s going to be $100,000 or whatever. And that’s a big enterprise decision. A lot of the pricing models for AI are per seat, and someone can just drive a credit card for 50 bucks a month or something like that. So we’ve seen a lot of businesses evolution, especially if they’re consumer-facing on the AI side, that scale rapidly, like I’ve never seen businesses scale before, you know, zero to 15.

20:46 – David W. Schropfer
Sorry to interrupt, but the Salesforce example, they were going up against Oracle at the time, which was a, you know, $30 million installation of a massive CRM enterprise product that took two floors of your downtown Manhattan office complex, right, to run.

21:04 – David W. Schropfer#+#Jim Ferry
I’m exaggerating a little bit of that. And they were software as a service, which is much less expensive.

21:09 – David W. Schropfer
They were month-to-month at the time. And it’s a brilliant analogy to where they are now, which is they are the Oracle of the day compared to the 50% per user.

21:18 – Jim Ferry
Yeah, for sure. Yep. And they’re trying to shift more to AI as well. But yeah, just because of the new pricing model, we’ve seen a lot of companies go like zero to 15 million of revenue in the first year, or maybe we’ve seen zero to the 30 first year. A lot of those at some point experience a mass churn event because everyone’s testing it and they have this virality to it. A lot of people wind up turning off because maybe it wasn’t as game changing as they thought or they didn’t need it. It was just kind of a fun tool and it’s cheap enough where they can test it. I think that there’s that as well. Ultimately, because the businesses are growing so fast, you don’t have it. If you’re a growth equity investor like Volitia, we love to see a couple of years of history so we can kind of do our typical analysis and then use all of that data to help us predict what the future looks like, If a company goes zero to 50 million run rate, they may be raising in three or four months. So we don’t have the historical data. So I think that’s where like a lot of money has been thrown at stuff that may not be as durable as you think in the long run, because you don’t have people that are up for renewal cycles yet or anything.

22:24 – Jim Ferry
So we’re talking about the negative. I think there’s also going to be a mass wealth creation And like for me as an investor, like there’s, you know, the Oracle to Salesforce was the transition from license and maintenance software, which is kind of on-prem hosted. So people have their own servers to the cloud and the cloud created the SaaS category. And there was a huge wealth creation event.

22:49 – David W. Schropfer
And over the last years on that, we are now experiencing the next wave of that.

22:53 – Jim Ferry
So I’m excited because I think that this is a, unbelievable opportunity for me as an investor to invest in AI businesses.

23:02 – David W. Schropfer
And I wouldn’t be serving my listeners if I didn’t ask you the obvious question. Since you have a portfolio of companies, you work with early stage or rather Series A, Series B stage companies that are in a growth phase. What are you seeing out there that is your best bet as as to where the market’s going to go. And from, man, I wanna ask that question more specifically, but at the same time, I don’t. I’d rather ask the macro.

23:34 – Jim Ferry
What do you think is the sweet spot with AI that may or may not have been exploited yet?

23:39 – David W. Schropfer#+#Jim Ferry
And yes, this is a chance for you to pitch one of your portfolio companies too.

23:44 – Jim Ferry
So are you just talking about where do I think there’s opportunities for AI?

23:49 – David W. Schropfer
I’m asking where the biggest one is. Where that one category is that may not be getting the attention that it will be getting in a year or two. And I can edit some of this out too.

24:04 – Jim Ferry
No, no, you’re good. Yeah, so I think that one interesting area is a little bit contrarian, but it’s services businesses.

24:11 – David W. Schropfer#+#Jim Ferry
I think that services businesses are now gonna be completely disrupted by AI because you think about them, they need a lot of people today and AI is replacing a lot of the workflows on the cost structure of a lot of these services businesses.

24:30 – Jim Ferry
And there’s already some private equity funds that are throwing a lot of dollars to do a roll up of services type businesses and layer AI on top. So you’re going to get a multiple arbitrage because you’re going to buy it low like a services business and you’re going to sell it like a tech business. But, you know, these services businesses by nature, there’s no technology. So it isn’t like there’s a, you know, a ton of equity value creation. So you need to be profitable. So they all tend to be profitable already. Ultimately is going to make them more profitable. So some examples of that would be like if you’re a fractional CFO firm or an accounting firm, so people heavy, like, you know, it’s a lot of manual labor that I think AI AI can easily make more efficient and do a lot of the busy work day to day where maybe you needed one person for every 10 clients. Now you can have one person for every 50 clients or something like that. So I think that’s kind of a non-obvious one that people aren’t thinking about because they tend to think about displacing traditional incumbent software solutions. But I think we’re going to see a lot of role of services, small services businesses into one kind of large conglomerate.

25:51 – David W. Schropfer
I’ve got a close colleague who is a design expert. He can, you know, if Nike had a new store concept that they wanted to launch, they would come to his firm and and they would build it out. And what he was telling me is seems to be seems to track perfectly with what you’re saying. He said his value proposition is basically he has downsized the firm to basically only the senior partners and a minimal support staff remain. And his pitch to his clients is that he personally and the other senior executives who’ve got real experience in this area will personally do the work and not have legions of people coming up with mock-ups and models and three-dimensional. He can do all of that with the help of AI. So his team is more productive and about 80% percent smaller than it was just three years ago. Is that that’s the idea you’re talking about?

26:46 – Jim Ferry
100 percent. And I think less is more sometimes. And I think that’s a great example where if he’s a you know, him and the people that he kept are more senior level employees who have seen, you know, what’s good and they know what they’re doing. You’re probably going to get a lot more quality or better quality out of them than maybe some B level employees that you had to hire because you just need needed to fill a couple roles. And, you know, I always laugh at, like, the big tech companies when they do a big layoff and they allow 10 percent of people and it’s, you know, tens of thousands of jobs and the companies don’t miss a beat. And I’m like, well, what were those people doing?

27:23 – David W. Schropfer#+#Jim Ferry
I think in all these big businesses, at some point you get large enough where a lot of people are hiding and they’re not really contributors at the end of the day.

27:31 – Jim Ferry
But I think that, you know, can play out a little bit in startups as well. Excellent.

27:38 – David W. Schropfer
Excellent. Jim, it’s been absolutely great having you on the show and getting your perspective. Where can people find out more about what you do?

27:46 – Unidentified Speaker
Yeah.

27:47 – Jim Ferry
So feel free to check us out at VolitionCapital.com. And we have a good website that kind of says what we do. But Series A, Series B investor and high growth tech startups tend to be $5 million plus in revenue, scaling well, really anywhere upwards of kind of $50 million of revenue. And we invest $15 $60 million in these businesses and try to help them achieve their aspirations. My Twitter handle is also at jimferryvc, if anyone wants to follow. I’m starting to tweet a little bit more. And a lot of it has to do with some of this AI stuff that we’ve been talking about today.

28:26 – David W. Schropfer
And for the rabid startup CEOs out there who aren’t sure they just heard how to contact you, is that something you want to put out there or just follow you?

28:35 – Jim Ferry
No, feel free. I’m always willing to chat and talk about what people are building and get my perspective. My email is Jim at VolitionCapital.com.

28:44 – Jim Ferry
So it’s simple. If anyone wants to reach out, I’d love to hear from you. Okay, wonderful.

28:48 – David W. Schropfer
And for those of you who are listening from your cars or something, just go to DIYCyberguide.com, search for episode 9797, and you’ll see all the links that Jim just said. Jim, thanks again for being here.

29:00 – Jim Ferry
Thank you, David. Appreciate it.