Family Office Capital Allocation Strategy | Investor Insights & Deal Flow

Arthur (0:02): Welcome everybody to another episode of Arthur's Roundtable. Super excited to have Michael Schatzmann with us today and talk about his history and the venture fund. And big shout out to Colton Rantz, who's kindly made this introduction. And so we're grateful that we're able to have this chat today with Mike. So Mike, let's start, if it's okay with you, with your sort of origin story, your history, and how this all got started, and then where you're at today.

Michael Schatzmann (0:30): Yeah. Thanks so much for having me, Arthur. It's been, great to be a part of your network and also spending time with Colton, who who you work with and introduce to us. But yeah. So my history is I'm an IU grad.

Michael Schatzmann (0:44): Go Hoosiers. National football champions, if you can believe that. But I was started out originally from the Northern Suburbs Of Chicago. I was a marketing consultant by trade out of school, lived in New York City for about seven years, and then moved back to Chicago, spent time working for Visa and their co branded credit card group, and then was there pre IPO, spent a lot of time traveling with them out in San Francisco, Silicon Valley area in its early days. And then, you know, started out, built my own businesses.

Michael Schatzmann (1:20): It's kind of a longer story, but started a whole group of restaurants from scratch, the ground up, three independent restaurants that were under a corporate umbrella that I established, and then had successful exits in those, became a early stage investor in various companies, also looked at different asset classes from private credit many years ago when it was more in its infancy. Obviously, digital assets and every major asset class that's out there. And then through that whole process, kind of marriage investing and entrepreneurship together where we built a fund focused on early stage investments. And this was sort of pre CHEC GPT. Our investment thesis was a little bit different.

Michael Schatzmann (2:11): Just given my background, we were focused at that time coming out of the, you know, all asset bubble in 2021 post COVID. We, had a strong philosophy that, you know, a strong belief that interest rates were gonna go higher for longer. So we were looking for really sound businesses, really strong founders that, were building business models that, would be resilient in a higher interest rate environment. And then as we started to tap that network, I also had a strong network of repeat founders with previous exits through various investor groups I'm part of. Post that GPT, we started to see a lot of AI deals come to us.

Michael Schatzmann (2:53): And these AI deals were very interesting because they were from some really well regarded networks where in order to be admitted, you have to be a founder with exits, where you built a company from the ground up. And that was me multiple times. So being a part of these networks, we started to see these entrepreneurs that had exits in spaces where they had domain expertise, use it utilizing these AI technologies to go back and solve for workflow issues. Right? So they knew where, you know, all the bottlenecks were, where all the plumbing wasn't right.

Michael Schatzmann (3:30): But they knew these spaces well. They had means of distribution, and they had domain expertise. So our next kind of set of investments, we didn't do this intentionally, but we looked at, you know, we made three investments that we really liked, and we looked at the characteristics of those investments. Right? And you look at pattern recognition.

Michael Schatzmann (3:51): And all those were repeat founders with exits, building an applied AI business, right, a vertical or horizontal technology. Most of the technology was vertical, which then, as you you really expand in a vertical, you can, your technology can be applied into other spaces, which then it becomes a horizontal technology. So we kind of were at the forefront of vertical AI before it became a thing, which is really, you know, under the umbrella of applied AI. And so we took a pause and saw, you know, really started to really think about that thesis and basically doubled down on our funds thesis. And that's where we started to just focus on Applied AI businesses from repeat founders with proven exits, and and the rest is kinda history.

Michael Schatzmann (4:35): And so

Arthur (4:37): How long has it been since you decided to focus on on that? Was it just after COVID?

Michael Schatzmann (4:44): Well, our fund we seeded our fund in the 2022, but obviously, we were working on it beforehand. You know, I can't remember the exact date that CHET GPT came around, but it was shortly thereafter. And so, you know, we had a bunch of investments lined up because we were doing, you know, a lot of deals beforehand where we were doing individual deals and then bringing in co investors. So we started the fund with, you know, some attractive investments that we wanted to seed right away. But I would say it was about, maybe about a year after until we really doubled.

Michael Schatzmann (5:22): You know? But one year after we seeded the fund was was when we, you know, recognized this and and doubled down on on the strategy.

Arthur (5:31): And things are moving really fast. I mean, that's not like that's a brilliant statement, but what what do you see now? Know, aside from the characteristics of the founder, multiple exits, you know, passionate about what they're doing, focus on getting things done as a founder and demonstrating that they can build businesses. What's the, what do you see? Because things are moving so fast.

Arthur (6:02): You're, when you say applied AI or in vertical and horizontal markets, Can you just, you don't even have to disclose the company, but, you know, give us an example of what, where you think things are going by way of example of a company.

Michael Schatzmann (6:19): Yeah, let me speak to that. So let me just take the comment. Yes, things aren't moving really fast. They're moving insanely fast. So a lot of outside, you know, people that are embracing AI, they're using it personally.

Michael Schatzmann (6:32): But a majority of people are they're they can't keep up. Right? And so with the way the pace of AI is moving, it's just, like, given some people pause, like, I I just can't keep up. And so Right. You know, there are some people that are can be more of a wait and see mode because they can't keep up with the cadence of AI, which, you know, is happening a lot more in in a lot of these larger enterprises where, you know, if they choose to adopt an AI technology today, is a better one gonna come, you know In two weeks.

Unknown Speaker (7:09): Right. Just like that

Arthur (7:12): Just like, I'm sorry to interrupt, but it was like, to me, it was wild. You saw Open Claw come out and everybody shifted from wherever they were at to Open Claw, you know, the people that were digging in deep. Right? And then the guy leaves and keeps Open Claw open source, and then he goes to work for ChatGDP. Yep.

Arthur (7:34): You know? And then another guy decides to write NanoClaw, which has, you know, this much code instead of this much code, and then everybody shifts to that, right? Everybody's exaggeration, but you get my point. It that's kinda crazy. Right?

Michael Schatzmann (7:50): Yeah. So more of that's gonna happen. And, like, people try to draw parallels. And, you know, I'll get back to the original question with an example in a minute. But just to kinda piggyback off that, a lot of people draw parallels from this AI era to the .com, era.

Michael Schatzmann (8:06): But it's kind of the exact opposite. Yeah, some of these valuations are very high. But the pace of revenue growth is insane. Where if you look at the .com era, there was no revenue growth.

Unknown Speaker (8:17): No revenue, right. So

Michael Schatzmann (8:19): it's actually the complete opposite, right? And so what'll be interesting here is that, you know, we, is there going to be a great churn moment, right, where all this revenue growth like, some of these companies are going to continue to accelerate, no question. But there'll be a bunch of companies where the revenue growth starts to decelerate. How many, you know, a lot of companies, there's a lot of experiments that are going on there. So you've got to do your homework when making these investments because when companies have experimental budgets, they're using everything, right?

Michael Schatzmann (8:52): And then eventually, they're going to decide, like, where they're going to really go deep with or embed that technology within their company. So that's something that you have to be very, very careful with. And also, like some of these and there's so many different ways to invest in AI. And that's what people don't understand because a lot of people are driven by the headline companies, ChatGPT, Figure AI. I mean, they're raising record fundraising rounds.

Michael Schatzmann (9:21): Obviously, they're burning through tons of cash. So there's a huge upfront commitment with CapEx dollars. Right? So, yes, some of that stuff can work out great. Some of it's worked out great for guys that have got in there from the beginning.

Michael Schatzmann (9:36): But our philosophy is kind of the exact opposite. We're looking for niche vertical technologies that are being built to establish inefficient workflows because we think once those get working really well and prove itself, and then that technology then can have another application, we think those companies are right for being acquired because they're proven in a space, right? So somebody that's bringing that on into their organization, it's going to be an immediate accelerant. Right? It's a proven technology.

Michael Schatzmann (10:13): And so getting back to your original question, which is an example, we have many companies in our fund one portfolio. But I'll give you a good example just because it's relevant to most people is that the process of of you replacing your windows at your house. Right? If you think about what that process look like looks like right now, you have to call a company. Let's say it's Pella Windows and schedule someone to come out to your house to measure, which could be two, three, four weeks.

Michael Schatzmann (10:40): Heck, it could even be a month. Right? Someone comes out to your house. They're in a hurry. They have to take the measurements because their job is to hit as many houses as they can.

Michael Schatzmann (10:51): They take their measurements. You go back to the company and, you know, see what type of windows you want. They'll give you some sort of quote. You're trying to figure out how does this window look in my place. And then once you come to an agreement on the price and you're about to sign the documentation, then usually 50% of the time that person has to come out and remeasure because it probably wasn't entirely accurate.

Michael Schatzmann (11:13): Right? Because now they need to produce a three d CAD drawing based off that. So

Unknown Speaker (11:18): It's become real, right.

Michael Schatzmann (11:19): 100% accurate, right? And then that all happens. You sign the paperwork, three d CAD drawing gets created, then, you know, the window gets made, and then it gets shipped out to install, right? If you think about that process, it's a very long timeline, right? Well, now, imagine a company that has the technology, right?

Michael Schatzmann (11:41): This is custom built technology, you know, is they call it AI rep. There's a lot of tech that's built around ChatGPT. And, you know, in our space, they call it wrapper technology. So this is purpose built AI on your phone where either whether it's you or the sales rep can come over and you can take a picture of your window, and it's more accurate than that person coming to your to your house. Right?

Unknown Speaker (12:07): Physically measuring it.

Michael Schatzmann (12:08): Yeah. From that window, it could produce a three d drawing where you can potentially see what do windows look like in my space, right?

Unknown Speaker (12:14): Yeah.

Michael Schatzmann (12:15): And then you decide on your window, and then that technology can also produce, you know, the CAD models, which then get sent to production. Like, you're talking about, like, almost 60 to 70% minimum time savings right there and more accuracy. And so, you know, think about how that can accelerate some of these companies' businesses, where they're not just reliant on someone having to come into your house to measure. They can expand into new markets. And then if that can be done for windows, why can't it be done for doors, right?

Michael Schatzmann (12:51): So that's where, like, this vertical piece becomes horizontal, where they've built and this is no different than any other business. And, you know, people kind of or I try to break these explanations down simply. But if you just go to a classic example that everyone understands, look at Amazon. Their wedge was selling books. And then they sort of built that, you know, customer's relentless focus on the business model of just selling books.

Michael Schatzmann (13:19): And then look what they expanded to. Yeah. And so just from an investment standpoint, I think we're getting back to that point of time of, like, where a heightened sense of focus on technologies that are purpose built that can then expand. The I want to be everything type approach from the beginning, know, sure, can that work in some circumstances? Yes.

Michael Schatzmann (13:42): But more than not, that approach tends to be challenged. So I think that's always a relevant example that I give, and then people kind of get a better understanding of what do I mean with vertical, and what does it mean when something starts off vertically and then moves to be horizontal?

Arthur (14:01): Yeah, totally makes sense. And the guy that's running out doing the appraisals is, I don't know, you know, different companies have different ways to do this, but is he the sales guy or is he just the detail guy and then the salesman comes in?

Unknown Speaker (14:19): Most of mean, lots of,

Arthur (14:20): you know, time wasted and all that. Right?

Michael Schatzmann (14:25): Yeah. I mean, look, some of them are sales guys when they're short staffed. Right? And so, like, just AI is creating inefficiencies. And, you know, the first part of AI is just it eliminates all the BS.

Michael Schatzmann (14:37): Anyone that's smart in using AI, if you're The way that I think about it is, look, there's always good and bad with technologies. Right? And so, obviously, there's some challenging things that are going to happen with AI, as with social media and all this stuff. But from a sense of how you can be more productive, and everybody always complains, pretty much everyone, that they get bogged down in all this BS and administrative stuff and all these things. But if you personally, I'm talking about a personal use case, then it applies to business.

Michael Schatzmann (15:08): But if you can automate, you know, how you see emails, some just certain daily tasks of how you take notes via these note taking apps and everything, and, you know, think about how people used to just take notes and spend all day, you know, organizing their notes and everything. Then you can focus on the high value touch point of, sales, business development, the things that you do that make the most impact to your business. If everyone can just think about that, then it helps unlock how they can use AI to really just be more efficient, not only in their business, but just everyday life.

Arthur (15:49): Yeah, it really is a great assistant to prioritize things without you manually having to do it. It's really pretty incredible. In fact, it may not be a good commercial use case, but on a personal level, I'm often thinking about an idea or a strategy, and rather than sending out the research assistant to go do all the research, you just drop it in to Perplexity or ChatGDP or whatever, and you say, Okay, what about this? And then it comes back with some, you know, 80% of the work done. So you can say, that was a bad idea.

Arthur (16:29): Next, right?

Michael Schatzmann (16:30): Yeah. Yeah, jobs are shifting with that, and it makes things more efficient. But it's just going to speed up the pace of business, right? If you look at the pace of where businesses come from each, you know, from social media to B2B, any time these things come about, the speed of business just moves quicker and quicker. And this is at a speed that could be frightening to people, right?

Michael Schatzmann (16:56): Because you're adding this productivity element before. Like, you know, you look at B2B SaaS and what that did, and obviously that put things in the cloud. But at the same time, you still needed a lot of employees to work with those technologies, right? And when you got the technology, then you needed to call the company, and they would send you a potential consultant or charge you for a consultant you to learn how to do this. Right?

Michael Schatzmann (17:23): And this whole per seat, like, this is a heightened element of productivity, which becomes very interesting because, obviously, when it's productivity, it's another employee. Right? So this is a very cost efficient employee. And so, yeah, of course, there's no doubt that this is going to take away jobs and make things more efficient. But I don't prescribe to that doomsday approach that this is going to gut, like, every job that's out there.

Michael Schatzmann (17:53): I think there's just going to be structural shifts in jobs. And sure, like, could this spike employment rates in certain things? Yes. But I think eventually, like, as more of these AI businesses are being created, like, there'll be some, you know, new opportunities that are on the table.

Arthur (18:12): Yeah, it's already clear that being a good prompt writer is a valuable skill, right? And then I call it, you know, AI quality control. Like the AI, and this is a very pedestrian example, but it spits something out and it makes mistakes. You need a human to go in and give it the sniff test and, you know, close the loop on the, does it actually work? And that often requires somebody that has the skill to not only just understand the business, but understand whether the AI actually produced something that's going to work.

Michael Schatzmann (18:51): That's right. And so also think about it from a company's perspective. If, you know, there's a huge trust factor, right? I mean Right. Embedding this to automate some businesses and have it fully run, like, you know, some companies are going to be very uncomfortable with.

Michael Schatzmann (19:06): That's why, like, just from our standpoint, we love to see something starting in a niche vertical where with domain expertise where it's proven to do one thing, right? Because then, think about it, it's less risky if you bed that one thing into the organization and, okay, there's an issue, it doesn't work. All right, just one thing went wrong, we can fix that. But if it's embedded in like every, all of your business units and something goes astray, that's a huge problem, right? And so

Unknown Speaker (19:41): Yeah, everything comes to a grinding halt.

Michael Schatzmann (19:43): I think the market will come around to that eventually where they'll start, you know, just embedding these things one vertical at a time because there's much less risk in doing so.

Arthur (19:55): Yeah. One of the co founders of Reddit was on the program, and he made a really interesting observation having built, like he was in weeds building that whole program. He said, What often happens is that when you build something to go at scale and you don't use household items that have been, used historically and are more or less bulletproof, and if something goes wrong, you can find where the gremlin is because everybody uses those tools. When you build the new tool, you don't know where the gremlin is, right? And so it's really hard to scale if you have stuff that hasn't been tried and true and tested.

Unknown Speaker (20:43): That's right.

Arthur (20:44): It's really, you know, can blow up a whole organization.

Michael Schatzmann (20:49): Yeah. No, that's right. And so, but yeah, so I mean, look, at the end of the day, now I've been out, and I'm fortunate enough to have been asked to speak at a lot of different conferences. And, you know, people always ask me a ton of questions. And, you know, for the growing organizations, like, you know, a lot of these companies are going to have chief AI officers, right?

Michael Schatzmann (21:12): And that person is really going to be in charge where whether the CTO becomes a chief AI officer, I mean, look, there's going to be a combination of the two. But that person's going to need to have their finger on the pulse of all these technologies and how to implement them across the whole organization. Because if you don't have someone in that role, like, you know, not only could they miss opportunities, but you have to really go deep with some of this stuff, before you can give it the stamp of approval. And that person has to have a technical skill set, too. So there'll be organizations that have teams of people with technical skill sets like this, maybe less of them.

Michael Schatzmann (21:54): But as I like to say, you need to be able to go under the hood, right? And so to go under the hood to see, like, what's really there. Is this a wrapper? Is this, you know, it may look good from the outside and sounds good, but when you open up the trunk of the hood of a car, you can discover a lot of

Unknown Speaker (22:11): problems right away. If you know what you're looking for too, right?

Michael Schatzmann (22:15): I think that's going to be something that you start to see a lot in the marketplace.

Arthur (22:20): What, you know, there was a, at the beginning of all this AI stuff, especially with ChatGPT and others, and I'm not trying to pick on that, I'm just, is that people were concerned that they were building their LLMs on the queries of anybody that would use it. And that, is there a trend now to have your own LLM and have it learn, you know, slowly as it relates to any idiosyncratic use case of your company. So they don't use your data to, teach their models.

Michael Schatzmann (23:02): Yeah. Well, mean, look, data is kind of the new like, that's really when you look at AI and what's the moat, right, you know, it's it's all gonna be about the the data. Right? And so that's really the the next front frontier here when you're looking at some of these companies and who owns the data. You know, I think there's a lot that's going to play out, in that space, right, with and so, yeah, I don't have a clear lens on how that's going to play out, but what I do know is that is really going to be the piece that everyone's going to be looking towards, especially when making investments of, like, you know, it's really going to be all about the data.

Arthur (23:46): So talk a little bit about the fund, what type of investors you're looking for, what type of companies. You've described the companies, but to the extent that you want to describe that further.

Michael Schatzmann (23:58): Yeah, our strategy is kind of twofold. There's two things that are sort of table stakes for us. The first is we will only invest in a repeat entrepreneur with previous exits. And so what that does and, you know, I support a lot of first time entrepreneurs. I'm on advisory boards and do things a lot personally.

Michael Schatzmann (24:19): But it plays into our applied AI strategy. So it has to be an applied AI technology, whether it's vertical or horizontal, that's solving for a workflow problem. And one of the founders has to have been a previous or a founder with a previous exit. Right? And so the reason why we put that lens on it is because a lot of these founders are going back and rebuilding in spaces they know.

Michael Schatzmann (24:42): Right? Or they discovered these and so and they can keep up with the cadence and the speed. And so it is going to be more about domain expertise, but also about distribution. If you think about where AI is going and, you know, where is the next opportunity for someone that's coming out of school, Well, I think the market's told you that, you know, there's not going to be an abundance of engineers coming out of school that can get $300.400 to $500,000 jobs on teams of, you know, 100 people where

Unknown Speaker (25:15): Just because they could code, right?

Michael Schatzmann (25:16): Millions of dollars to code. Because if you think about that with B2B SaaS, that was the real competitive advantage. Whoever got the best developers to develop the product had the lead, and sales were relatively easy then. Right? Now the exact opposite's happened.

Michael Schatzmann (25:32): So you can use AI to build these technologies. Right? You can do things and build things that used to take months, sometimes if not years. And the cost to do those things is, like, in some cases, can be 95% to 99%

Unknown Speaker (25:48): fraction of what it was.

Michael Schatzmann (25:49): Yeah. What's going to happen then when you look at this? Well, obviously, there's going to be a lot more technologies that are come up gonna come out to play. Right? Because if the barrier to entry is that low, the marketplace is just gonna be filled.

Michael Schatzmann (26:03): And that's what's frightening people now because things are happening left and right, and it's only gonna continue to happen because you can go home tonight and make your own CRM. Now, it could work for you, how you go about that and building it to a company. So, you know, this next phase of this younger generation of entrepreneurship, like, could be insane Because everyone's going to try to create a potential company based on using AI to develop something. On the flip side, though, it's all going to be about sales and distribution, right? Because you can build all this stuff, but if it can't be sold in and it's not generating revenue, then you don't really have a business.

Michael Schatzmann (26:43): So that's what we look for, and that's why we like the repeat founders with exits because you need a path to accelerate sales. And I give an old adage. We we used to see a lot of health care tech deals. And one of my partners, you know, knows the space very well. He used to run a hospital before becoming a fractional CFO.

Michael Schatzmann (27:06): And in healthcare right now, you see some amazing technologies. I mean, unbelievable technologies. But depending on who their audience is, if that healthcare tech stack needs to be sold to doctors, good luck selling it to doctors when it comes

Unknown Speaker (27:23): to the

Michael Schatzmann (27:23): face with a network. I mean, so that's what's going to happen. You're going to see a lot of incredible technologies that are being built. And but if You build it, and they won't come. Right?

Michael Schatzmann (27:35): Yeah. It's like and and obviously have a means of distribution, they're they're gonna be significantly they're gonna be significantly challenged. So that's that's how we that's kind of why our strategy is in place, because we think our strategy lends ourselves to having a much quicker means of distribution with the repeat founders.

Arthur (27:59): And are you finding that the repeat founders are building in, you know, back to the age old, you know, do what you know type thing? So they may have exited a company in the same domain, and now they're going back to that similar domain with a different use A

Michael Schatzmann (28:21): 100%. Look, the sky's the limit right now. Like, if you're someone, you know, the people now, when they say like AI's, I think a lot of people hear this phrase, AI's remaking every industry. And most people have trouble understanding, like, what does that mean? Like, is, like, AI going to take over this fat like, what it means is that there's going to be different ways of establishing efficient some businesses are going to be able to be more efficient with workflows, right?

Michael Schatzmann (28:50): And then in other businesses, like, there's going to be more automation in manufacturing facilities, maybe with robotics, right? So every sort of sector is going to look a little bit different, right? It's not like this one thing is going to be able to do everything. And so what that gives someone, like the whole lay of the landscape is changing. So if you have expertise in the space right now, and that's what we you know, that's why we got behind our thesis.

Michael Schatzmann (29:19): Some of these guys are licking their chops, saying, I know all the problems in this space. I can use this technology, and I'm going to go, you know, I'm going to start in one area and start to build a business around it, right? Because it's relatively easy for them to come right from the space. So that's our whole investment thesis in a nutshell there. So then, of course, like, you have everyone gravitating towards that, but then you're going to have, obviously, you know, some industries.

Michael Schatzmann (29:46): Like, you know, there's some automation coming in landscaping, where you'll see some robotics things happen with, you know, lawnmowers and stuff. But, you know, plumbers, everyone's talking about like plumbers, electricians. And if you think like in life in anything, right, everything moves too far in one direction and then comes back a little bit to reality. So, yeah. We moving

Arthur (30:07): Version to the mean. Right.

Michael Schatzmann (30:08): A reversion of the mean happening with, you know, with everyone, like you trying to call for your electrician or a plumber or someone to come out. Those guys are on insane backlogs, right? And so there'll be opportunities that open up that, you know, AI can't, you know, sure, it can have an impact on scheduling certain things to make their business more efficient, but the physical labor part of some of those professions aren't going to change. And also there's a shortage of those people right now because everyone wants to move into tech. The younger generation just wants to be with tech.

Michael Schatzmann (30:42): They're growing up with iPads and all this stuff, and that's all they know, right? And so,

Arthur (30:47): it was between tech and crypto. People were saying, why do I need to work hard? Like, it might be hard work to figure all that out, tech and crypto. But, you know, between that and deciding to be a plumber, it was really interesting that you go to any sort of tertiary town or even rural town, and the guy with the nicest office building is the electrician. Yeah.

Arthur (31:13): Right?

Unknown Speaker (31:14): That's right.

Unknown Speaker (31:15): It's always been that way, right?

Michael Schatzmann (31:17): Yeah. And so, like, you know, there's obviously when everybody gets excited, you know, like when, you know, I'm saying that we're in a bubble by any means. You know, there may be some pockets of excess. But when you look at that, it's just excitement, right? Everybody is excited about this stuff.

Michael Schatzmann (31:34): And so that's where the enthusiasm comes in and investment comes in, overinvestment, all this type of stuff. And you know, you just have to be very careful. All these technical, you know, in every sort of technical revolution, the same things seem to happen.

Arthur (31:55): Yeah. What do you think of the, you know, you often have to ignore headlines, but what do you think of all this talk about, you know, SaaS is dead, you know, companies like Salesforce are gonna suffer not because they don't have a good business model, it's just that software's gonna sort of not be the holy grail that it once was.

Michael Schatzmann (32:24): Yeah, so look, You know, there's an argument to make. Yeah. So, you know, parts yeah. Some b to b SaaS companies are dead. You know?

Michael Schatzmann (32:35): And so the the thing right now with these b to b SaaS businesses is they need to make a decision. Their business is at risk of going away if they don't, you know, bring in these AI build these AI models or or or buy them. Right? And so that was kind of our whole working thesis, too, because we thought if you get involved with the right companies, we think that a lot of these larger companies are going to be forced to buy. They'd rather buy, not build because They they'll have a balance sheet.

Michael Schatzmann (33:08): They'll also overpay for something that's working because if their business is at risk of potentially being extinct, they'll take all measures, right, to correct that quickly. But so, yeah, mean, pricing is going to change per seat versus productivity. So the business model is changing. And so, like, all SaaS companies aren't going to die per se, but a lot of them are going to be at risk of being extinct if they don't alter their business models and embrace it. And, you know, there's a lot of those conversations that happening behind the scene.

Michael Schatzmann (33:44): And so that's what's happening right now because if you look at the market, people, you know, of course, things always get overdone too, right? So these could be attractive opportunities for the right SaaS based businesses that alter their business model and then have growing revenue. But if you look at the ARR, the market's basically saying we don't have certainty that ARR growth's going to continue at this pace.

Unknown Speaker (34:06): Totally. Yeah.

Michael Schatzmann (34:07): And then you're assigning larger multiples to the faster growing AI businesses. Right? So these these SaaS based businesses are, you know, are just they're they were they were at, you know, some high multiples. Right? So this is just multiple contraction that's happening right now until the market sees them accelerate or embed the AI business models.

Michael Schatzmann (34:33): You know, it can continue to go down a little bit more.

Arthur (34:37): What's the risk, that you see, for example, with the founders that you know that have built things and sold them and building something new, when something like, you know, Open Claw comes out and they built it all on Anthropic and they go, Holy crap, what do I need to do now? Do I need to switch to that? And then within a matter of weeks, Nano Claw comes out, is is, you know, normally that infrastructure that you built becomes a legacy system in the old parlance. Right? And you can't extract yourself from it.

Arthur (35:18): Is that is it easy to extract yourself when you build it on some LLM and then something cooler and better comes out more efficient? Is that an easy transition or easier than it once was?

Michael Schatzmann (35:31): Yeah. I mean, look, it's easier. The the way I explain this is it's what was I gonna say? It's a lot easier for smaller to medium sized businesses. Smaller to medium sized businesses right now have a huge opportunity because they switch out this technology and stuff overnight.

Michael Schatzmann (35:52): Right? So that's incredible. The larger enterprise ones are stuck because, like I was alluding to earlier, once they place their bet on something, even to unwind it, to get it integrated I mean, we've all been a part of large enterprises. You move with a snail's pace. And so once you know, it can take them like six months to integrate something, right?

Michael Schatzmann (36:12): And so there's a huge opportunity for small to medium sized businesses to embrace these technologies, play with them, and move them in and out. And so people have to I think it becomes challenging for the larger enterprises. They really need to think through that, right? So that's kind of how we, you our lens on these things at the early stages. This comes out, then that comes out.

Michael Schatzmann (36:43): You're a two or three man team. It's pretty easy. You just switch the subscription, you know, maybe fix a couple things internally, and off you go.

Arthur (36:53): So there was a time when you alluded to it earlier, when you decided to adopt as a big enterprise, right? It's decided to adopt a technology, and then you had to go hire PWC or whatever to do the integration. Is that, those companies going to suffer because you don't need a team of, you know, PwC technicians to help you integrate a new technology?

Michael Schatzmann (37:24): Yeah, I mean, look, there'll still be, you know, it's interesting with AI, because with all this stuff, it's actually been a bit of a boost for some of those outside consultants, because there really is a shortage of people that understand AI and the technology, Right? And then a lot of these CEOs and, you know, some of these guys that, you know, aren't as technical as others, you know, there's a huge need for consultants right now to come in these enterprises and help fix stuff up. So it's actually been a boost for them. Over time, I think that will dissipate a bit as the skill set catches up. Right?

Michael Schatzmann (38:05): But with this new skill set, everyone's paying you know, I've known consultants that are making hundreds of thousands of dollars to come in and scope out how to implement this stuff. And then they write up a huge report and all this stuff, and it just goes by the wayside, right? So there's a lot of there's actually a ton of capital being overspent on some of that stuff right now, because everyone's panicking. Boards, you know, directors of boards are coming down and saying, We need an AI strategy. And then they call these guys, right?

Michael Schatzmann (38:33): So, and you've seen some of these reports where, you know, you know, some of these companies can pay a consultant, and the consultant is using AI to do these reports. Right. So they're producing these reports for, you know, a significant amount of money. And then their their profit margins are are substantial because they have less people doing them. So in the short term, it's actually a boost for those type of people, I I think.

Michael Schatzmann (39:00): But it it may take a while. This this could keep going on and on. The more you introduce all these models and everything, like, you need these you need expertise, which is in short supply, to get in there and understand, like, all these different language models, what's they do, what's the pro and con. Am I using Claude? Am I using Gemini?

Michael Schatzmann (39:19): Like, what do I use for what? And then how do we teach the employees how to do this? How do we have a heightened level of consistency across our organization? It's a It's exhausting. It's off, but advantage to the startups here that can integrate this and master it.

Michael Schatzmann (39:35): Right? Because that whole new wave of companies that are embracing it, you'll really start you mean you're starting to see revenue accelerate them with with them now. And I think that's only gonna continue.

Arthur (39:49): So that suggests that, you know, where are we with the talent pool? For example, you've got people who you can't compete with the checkbook for Facebook and Google or Alphabet and just go down the list, OpenAI. You know, how do these small founders attract the talent that would otherwise just get a million and a half bucks from Google and go sit and do their work?

Michael Schatzmann (40:26): Yeah, so that's the hard part, right? And so if you look at, like, there's distinct advantages to being in a virtual world right now, right? And so the good news is you can source talent from anywhere in virtual world, right? So the, I guess, the challenge is how do you build culture? It's a little easier when you're a two or three person start up and everyone's working, one person East Coast, West Coast, but you all you guys are everyone's

Unknown Speaker (40:53): On the same page. Right. Yeah.

Michael Schatzmann (40:54): With you know, on the same page with each other. You're having calls each day. But what nobody's really thinking about now is, okay, well, if we're growing the organization, like, what's our strategy? Because virtual employees, while it's great, you know, to offer that type of flexibility, How do you build a culture? And how do these people you know, so there's a lot of you know, the word fractional is, like, commonly used now.

Michael Schatzmann (41:22): Fractional marketing, fractional CFO, right? All that type of stuff. And so are we moving to a fractional society? We're moving to a place right now where it's, you know, it's not uncommon to see someone that's had four or five different jobs over the past five years. Right?

Michael Schatzmann (41:42): And, when I went to school, like when you were looking at resumes, I mean, coming out of college, people that like, if you weren't in a company for at least like three years, that was a red flag.

Unknown Speaker (41:53): It was a total red flag, yeah.

Michael Schatzmann (41:55): Something's wrong. So those dynamics are going to be interesting because you can grow revenue and do all that, but how do you build culture? How do you keep people? That's not easy. And so a lot of these startups will be challenged in that nature because they grew up in this virtual world.

Michael Schatzmann (42:17): Some of them have been more in isolation mode. They're behind the screen. They're not at some of these, you know, networking events, less in person. So I think a lot of that will come back a a little bit. Right?

Michael Schatzmann (42:31): As we talked about everything moves in extremes. But a lot of these founders that we work with really have to you have to think about that. If you're in the business of starting, you know, you're an entrepreneur, like, you got to think big. So you have to think in your mind, like, okay, when this starts working, what's, Where am I gonna get the talent? Yeah.

Michael Schatzmann (42:52): And that's why, you know, trusted networks are very important. And and also, there's heightened competition for people with certain skill sets as well. Yeah. It makes it easier to find people. But how do you know, is this person real?

Michael Schatzmann (43:09): How do they work? Like, you gotta do a lot of diligence. So it's easier to see people now find them from all over the place, but the trust factor is high. And so that's the hardest part when you're trying to, bring on new employees and build an organization.

Arthur (43:25): Yeah. The upworks of the world have been a godsend to many. But when somebody's sitting in, and I'm just going to pick on Bangladesh, like, how do you know? Like, do you really know whether they can deliver, right?

Michael Schatzmann (43:42): Yep. That's right. And so trusted circles are very important. This ties back, you know, I'll give you a great example that's relevant to your space. Like, you know, all these family offices now, right?

Michael Schatzmann (43:53): So they're getting bombarded left and right. You know, this next generation of wealth that's being passed down. Like, you know, there's a huge, you know, family office boom where these families have their structured capital, want to make investments together, or they have their businesses under one roof, and then they have their investment arms, right? And so look at that example that's happening now. Look at all these, you know, groups, all trusted circles.

Michael Schatzmann (44:22): They all want to talk with each other, do due diligence together. It's very hard for, you know, a new whether it's a manager or someone that has a new product to break through in those circles. Some of them won't even entertain a new idea or a new product unless it comes from someone they trust, right? 99.9% of the time that happens. So that's a relevant example in your world that's transpiring right now.

Michael Schatzmann (44:49): And AI only makes that worse. And so, like, if you talk about, like, a little bit, there's tons, you know, of things that with AI that are concerning. But the one thing is if you think about, like, look at the memes online, social media, right? And so the thing is, is like once you start to make someone question, is this real or not, right, they're going to carry that thought process with them through everything. Investments, life.

Michael Schatzmann (45:18): And I think that's a negative consequence that a lot of people don't talk about enough in AI because it's going to continue to happen. And so if people start to have that mentality, they're just going to go back to the people they trust. And if you look at what's happening in the investment landscape right now, you can make an argument that that's already transpiring because if you look at just I'm just using funds as an example because that's the world that I that I live in, but we could talk about other investment asset classes as well. But, you know, Andreessen Horowitz, the Sequoias, all these guys, obviously very reputable, amazing firms. But, you know, 55, almost like over half of the capital raised last year in the private markets went to, like, a handful of firms.

Michael Schatzmann (46:07): I think it was three, four and five, right? So if that doesn't, if that's not a key indicator, I don't know what is.

Arthur (46:14): Flight, see the old thing when 2008 flight to quality, that sort of thing, and it's true that, you're right, Mike, the thing that I hear the most from our members, which are largely single family offices, is that they want to meet other single family offices. And totally makes sense. And I agree with you that the trend is to pull back and trust and go back to further embracing those relationships, because you're right, it does something to the psyche, because whenever you look at something, you're immediately doubting it, right? You're immediately, and it's the memes, it's the feeds on all the social media. Forget about the legacy media.

Arthur (47:08): You can't believe anything they say. Right? In fact, you can start with saying, well, that's not true. Right.

Michael Schatzmann (47:14): Right. And so it's like looking at the glass half full or empty. And, you know, one of the quotes Jeff Bezos has, which is amazing, is people always, like, overestimate downside risk and underestimate upside risk. Right? Because everyone's just paying too much attention to the negative.

Michael Schatzmann (47:32): And look, it's important to have that perspective, but I think balance is important. And so, yeah, the trusted circle thing is big. It's just going to continue to happen. Like, I don't think I don't see that trend stopping anytime soon in this day of age of AI, which so, people have to be well networked. And then we're coming into this age where the younger generation is, like, a bit more antisocial, right?

Unknown Speaker (48:00): They're behind the screens. They haven't built that muscle,

Unknown Speaker (48:03): right? Right.

Michael Schatzmann (48:04): So, like, everything, you know, like some I have some scenes, but I always say, like, behind the screen don't mean a thing. And, like, out of, you know, out of COVID, like, I call it know, there's people I call them Zoom Lemons. They're on Zoom, but they're wearing Lululemon, right

Unknown Speaker (48:19): below it.

Michael Schatzmann (48:20): And, like but there's people, like, if you look at a crazy example, if you look at, not to pick on him, but, you know, Kevin O'Leary, Mr. Wonderful, when he's on CNBC and he's on social media

Unknown Speaker (48:31): And his pajamas

Michael Schatzmann (48:32): in his underwear. Yeah. It's almost like saying to people, like, are you really authentic or this and what's happening? But, you know, there's a huge opportunity for people to get out there and hustle and build build relationships, because that's that's really where things are going right now. And so, yeah.

Arthur (48:55): And that's where the action is. We've been doing that for a long time. And I will tell you that most people would rather ask somebody in that trusted circle, like, what did you do about this? And listen to that from somebody that actually went through it, that's in that trusted circle, then go pay a consultant to say, What should I do about this? Right?

Michael Schatzmann (49:25): Yeah. And people are lazy now. And so like, if you want to break into family office groups and stuff, like, do some research on them, find out what's important to them, and come to the table, whether with an idea or some form of expertise, right? And so, you know, like, all this AI stuff gets old, and you see all the LinkedIn posts. Like, everyone, like, you know, have, you know, their automation set up, their sales scripts, like, people so, like, email, you know, like, eventually, email is gonna go away, and most people are done with it.

Michael Schatzmann (49:58): They're like, all I'm getting is junk. I don't know what's real or not. And then you have, you know, text messages, WhatsApp. It's you know, if they're not in my phone or I haven't met them somewhere, then I don't I don't wanna respond. Right?

Michael Schatzmann (50:12): So how people communicate is going to change as well, you know, under this new AI regime.

Arthur (50:20): It's already happening. Yeah, we see it all the time. And we're just no different than any other business in Family Office Insights, for example, and that the AI has helped us where we would manually, when somebody would come to us and say, We have this opportunity, then we'd have to take the time and manually figure out who that's appropriate for, if we're gonna get involved. And now we have a living, breathing scoring system.

Unknown Speaker (50:52): Yeah.

Arthur (50:52): Right? Where we can not bother people who aren't interested. Right?

Michael Schatzmann (50:57): Yeah. Right. So there's great so, yeah, there's the good there with makes those tap things, so much easier for you. Right? So, but, yeah, I like to focus on the good on this technology and hope that, you know, some of our, you know, worst thoughts don't necessarily, transpire.

Michael Schatzmann (51:15): But it becomes a level of responsibility for everyone as well, right? And so people have to be educated on this stuff. But, look, there's always bad actors with these things. Like you can't And will always be, yeah. Exactly.

Arthur (51:29): Yeah. Well, that's awesome, man. I really appreciate you doing this. Super appreciate your insights, and I'm sure the audience will find it valuable as well. If there's anything that the audience can do for you, what would that be?

Michael Schatzmann (51:44): Look, we're pro family office and firmly believe that for us, it's about education. So, you know, we'd love to, you know, if we have the opportunity, come to either some of your events and focus on the education of how to invest in AI, where to be looking. Mean, that's what we're all about. Right? You know, it's not just about our product, but it's about education to opening people up to, like, I didn't know I can invest in AI in these particular areas.

Michael Schatzmann (52:14): Like, I only thought I could do it through whether it's the public markets or these large, you know, funding rounds for, you know, the namesake companies. But I think there's a lot of opportunity. I'd welcome, you know, family offices could embrace us where we could help educate them on the areas to potentially look at in this space. Because I think it's only getting started, right? And so more and more is going to come.

Michael Schatzmann (52:43): And these family offices also have to have the right infrastructure set up, especially for venture in some of these alternative asset classes. In the private markets, it's just harder to do diligence, right? And that's why everybody gets comfortable in public markets. It's all readily available data. Yeah.

Michael Schatzmann (53:01): Private markets, I think, represent some of the best opportunities down the road. And I think we'll see more conversions with public and private markets. But how you get access to the information and know what's real or not and utilize your network and resources is extremely important when when you're looking at alternative assets.

Arthur (53:20): Yeah. We'll we'll be sharing this with the Family Office Insights community, so please feel free to reach out to Mike. Is that okay, Mike?

Michael Schatzmann (53:29): Yeah. That'd be great. So I'd welcome the introduction and and look forward to, you know, assisting you in any way, shape, form down the road.

Unknown Speaker (53:37): Appreciate that. And it's a great time to be alive. I'll tell you that. Amazing.

Michael Schatzmann (53:41): Yep. There's no show. I mean, it's, it's a fast paced world buckled up. Right?

Arthur (53:48): Well, you everybody for joining us today. Thank you again, Mike.

Unknown Speaker (53:51): Thank And

Arthur (53:52): we'll see you next time. Thank you.