A (3:53)

Thank you. And when you look at sort of the impact of AI and artificial intelligence, you've been somebody who's been in technology almost as long as I remember. And so you've got a different mindset than most people do. You're much more native to it than the rest of us. Where are you seeing AI having the biggest impact, making results? And as you, you as an investor, how do you look at how people use technology and in artificial intelligence? Yeah.

B (4:19)

You know, our investment thesis comes from something that I learned about 15 years ago when I was in Africa of all places. I'm out in the middle of nowhere, three hours off the nearest paved road, two hours off the dirt road. But I've got, you know, no running water, I've got no flush toilets, I've got no electricity, but I have four bars on my cell phone. Because what they did is they dotted the entire Serengeti with cell towers because they didn't have the typical infrastructure, you know, AT&T and Ameritech, that we had to overcome. And I was able to transfer a million dollars of payroll, you know, sitting on a log in the middle of the desert. They were doing Internet banking over cell phones. Not even smartphones, just cell phones. It was, it was a product and it's still probably called M Pesa. And what I learned was the, the infrastructure is often an impediment to the advancement of different things. And technology is a huge piece of that. When the Internet came around, everybody was suspect. You know, people wouldn't even put their credit cards online now. I mean, nobody wants to go to the store anymore. So there's a typical roadmap for how things evolve in this world, in business and in technology in particular. And when we look at these things, we look at how nascent the industry is and how transformative the technology is and the ability for those to intersect. So we. I was an early stage tech with a firm called OCA Ventures here in Chicago for a number of years. I'm still a limited partner. And they have what's called the Edge Fund, which is sort of a feeder fund that allows us to get on the cap table so that when the Series A comes around, they. They have a right of first refusal to get on. You know, in Series A, when you're competing with Silicon Valley, those early stage companies have had a significant impact in my investment thesis, because you're not constrained by all of the complexities and infrastructures that, you know, we have now, for example, at abstract tech with 180 employees and the agility of founders and investors to be able to take that technology and move fast with it and not be bogged down by all those incumbencies. You know, that's an area where we've really focused on. And how can you really upend the markets much in the same way that Uber and Airbnb came in and were transformative in their respective industries. There's a lot of technology and there's a lot of, as our friend Alan Greenspan once said, irrational exuberance around things like AI and even when the Internet came out. But really drilling down on what can be effective based on the needs that the marketplace has and the passion around the founders and their capabilities to be able to deliver those things, Those are sort of the things that we look at.

A (7:34)

And let me ask you a question about that, because everybody's trying to figure out where AI will apply. Well, where it won't apply. Well, where there's, as you said, Alan Greenspan, irrational exuberance. And where there's not. Does a lot of it come down to founders that are very plugged in and that could think and move fast and try things and try and work through things and stay dedicated to getting better at. Better at it. Is that as much of the secret as anything? Then obviously they have to be bright enough to work with the right technology people, the right AI people, the right technologies. But. But there's a lot of it just around having founders that are really at it and engaged in trying to work the problem. Forget where they can apply things.

B (8:15)

Yeah, I mean, yes, absolutely. The answer is yes. Founders that are passionate, that are flexible, that coachable. I've never had an exit that was a straight line. I mean, we've never gotten to the finish line without pivoting, you know, two or three times. Your ability to be able to take things to market based on what you perceive As a market need is difficult. The, the market and the feedback loop have a tendency to upend the things that you think are, you know, the customer's willingness to pay and so the passion to continue moving forward, but the flexibility to be able to focus on delivering what the feedback loop tells you and being coachable to be able to do that, you know, that's really critical in the startup world. You've got to be tenacious. You know, one out of every ten startups actually gets to an exit. Right. And those founders are the ones that possess the fortitude that, you know, that we just discussed.

A (9:24)

Right. And how much of it is about just fortitude, tenacious to stick it with it, keep on trying to figure it out versus natural intelligence or some mix of both. What do you see them founders that make it from point A to point to exit?

B (9:36)

Yeah, I mean, I think in the beginning it's 90. I'd much rather have a rock star team with a mediocre idea than a rock star idea with a mediocre team. I think as the company progresses and I think, you know, case in point, what we're seeing now in Abstracts Tech, the fortitude and the, the tenaciousness of the founders, I don't want to say it becomes less important, but the governance and the other aspects of the business, financial reporting and things that tend to be overlooked in the early stages become more important. So I think they're both critical to getting to an exit. But I don't think the startups ever get to a point where those things matter if they don't have the tenacity and, you know, the team members don't have the drive to be able to continue moving forward in the face of failure over and over again. Then they finally get the luxury of being able to look at the infrastructure issues that are going to get them to an exit.

A (10:35)

Right. You need it to nations driven, bright founder, gifted in the founding team. And the hope is that you build a big enough business where you're still very reliant on that, that but not quite as much so and where you're building systems in teams and really an institution, not just a gritty, smart startup. So you sort of have both over time, I think, fascinating perspective. Do you have thoughts on where artificial intelligence will have the biggest impact over the next several years? Do you look at it globally like that or more just, you know, in specific businesses or how do you think about it? You've already given us some indication of that. As you talked about how the Internet grew into being all Pervasive. Where do you say AI over a period of time?

B (11:15)

Yeah, I think it's going to have a similar trajectory, but I fully intend to be on a beach somewhere before that materializes in full. I think over the next few years. One of the things about AI, and you know, I was fortunate, sometimes it's better to be lucky than good, right? As the saying goes, it was fortunate. Early on in tech, everybody was about data, data, data, data, data, data. Figuring out how to monetize data was really elusive. And even in the last decade there's still been a lot of difficulty understanding how to monetize data. One of the things that people don't understand about AI is AI is only worth the data that it represents in order to build on top of. And a lot of the data that was collected over the years was done sort of in a vacuum, blind. It doesn't have the right provenance, it doesn't have the right permissions, it doesn't have the right categorizations, the settings. One of the things that we've done at Abstracts is about a year ago we had the foresight to build a data lake. And that data lake allows us to ingest all of our first party data along with other third party data into a unified infrastructure that tags the data, stores the data and creates the opportunity for that data to be used down the road. What people don't understand is that the data that's really going to advance AI in the next decade is, is in large part still being accumulated. And I'm saying that that's absolute. Right. A lot of the larger companies had data scientists that were smart enough to be able to, you know, tag and capture their data. But a lot of the data that's out there right now is just not solid enough to really build on top of. And so, you know, we've got a saying that, that I love that, you know, we like to try to eat the cow one steak at a time instead of whole. And where we really see AI being impactful over the next two to three years, which is what, you know, the chunks of time that we like to think in is, is around agency and you know, the ability to use agents to process information in real time with more accuracy and in more capacity than human being. Right. So we've got a goal, for example right now of taking the company from $300,000 in, in revenue annually per employee to a million dollars in revenue. It's a pretty lofty goal. Most of that will come through growth and the ability for us to Use agentic AI to back up the customer support teams and project management teams and the, the, the stuff that we do on a day to day basis that requires human recall that machines are just much better at doing. That's where we're seeing the biggest immediate impact with respect to AI longer term. For example, we've built an AI digital flavorist so we can feed information into the agent and have the agent kick back to us the ingredients that we want in order to be able to create a flavor that is going to smell or taste a certain way. There's longer term objectives with respect to the latter. I still think it'll be effective in my lifetime with the company, you know, but the shorter term objectives are where the immediate short term wins are, where AI is going to help companies in, you know, elevating them in the near future.

A (14:42)

Thank you very much. You already spoke this a little bit, but what advice would you give to founders, CEOs trying to bring AI into the business and make better use of it? How do you think about that? What advice would you give?

B (14:55)

Oh yeah, do your homework. Understand what the data modeling is going to look like in order for your application to bring value to your customers. One of the things that we started doing, there's a concept in software development called dog fooding. Basically dog just means eating your own food. So what we started doing is polling internally our teams and asking them what are the biggest problems that they have to solve. And what we were able to determine is if we could solve the problems that our teams had internally. Chances are we were going to solve a problem that had commercial viability. We were able to accelerate customer feedback loop in a way that was very unique. It was something that I didn't realize until a few years ago, as after years and years of investing in technology, a lot of founders are investing from the outside in. If you can find a way to invest from the inside out. If you can get partnered with a company that says, hey, can you solve this problem for me? And then you can take that problem and commercialize that, that's a bigger win percentage in my mind when it comes to things like AI, where everybody and their brothers, you know, just out there going, hey, if I can solve this problem, a million people are going to pay me for it. Try to find someone who's willing to pay you for it before you go out and invest your time and money in solving a problem that you think somebody has but you don't know for sure.

A (16:22)

No, I absolutely love that advice. It's almost like the concept if you don't build a building until you've got tenants for it. The best investors I know have always said we're not building a new startup until we at least have a customer for it, that we know somebody who wants to buy it. It's just not an idea. So you've got close to what's a custom product market fit. I just absolutely love that. David Friedman, what an absolute pleasure to visit with you today. David, I've known for a long time, brilliant, brilliant thinker and investor. Thank you for joining us on the Becker Private Equity and the Becker Business Podcast. A total pleasure to visit with you. Thank you.

B (16:53)

Yeah, my pleasure. Scott. Great to catch up.