Family Office Capital Allocation Strategy | Investor Insights & Deal Flow

Arthur Andrew Bavelas (00:02)
Welcome everybody to another episode of Arthur's Round Table. Super excited to have Michael Schatzman 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.

Mike Schatzman (00:31)
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 you work with and introduced us. But yeah, so my history is I'm an IU grad, Go Hoosiers, ⁓ national football champions, if you can believe that. 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. ⁓ It's kind of a longer story, but started a whole group of restaurants from scratch from the ground up, three independent restaurants that were under a...

corporate umbrella that I established and then had successful exits and 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-Chatch EPT or investment thesis was a little bit different. Just given my background, we were focused at that time coming out of the, know, all asset bubble in 2021 post COVID. We...

had a strong philosophy that, you know, strong belief that interest rates were going to 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-Gap GPT.

we started to see a lot of AI deals come to us. 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. 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 sell for workflow issues, right? So they knew where, you know, all the bottlenecks were, where all the plumbing wasn't right. 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, 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 and all those were repeat founders with exits building and applied AI business, right? A vertical or horizontal technology. Most of the technology was vertical, which then as you really expand in a vertical, 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, the rest is kind of history. And so, ⁓

Arthur Andrew Bavelas (04:37)
How long

has it been since you decided to focus on that? Was it just after COVID?

Mike Schatzman (04:44)
Well, our fund, we seeded our fund in the fall of 2022, but obviously we were working on it beforehand. You know, I can't remember the exact date that CHAT 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. But one year after we seeded the fund was when we recognized this and doubled down on the strategy.

Arthur Andrew Bavelas (05:31)
And things are moving really fast. mean, it's not like that's a brilliant statement, what do you see now, aside from the characteristics of the founder, multiple exits, 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. When you say applied AI or in vertical and horizontal markets, you don't even have to disclose the company, but give us an example of where you think things are going by way of example of a company.

Mike Schatzman (06:19)
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. And so a lot of outside, you know, people that are embracing AI, they're using it personally, but a majority of people are there. 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 just can't keep up. And so, 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 is happening a lot more in a lot of these larger enterprises where if they choose to adopt an AI technology today, is a better one gonna come? And so that, yeah.

Arthur Andrew Bavelas (07:08)
Two weeks. Just like, just like

my, I'm sorry to interrupt, but it was like, to me, was wild. You saw open claw come out and everybody shifted from wherever they were to open claw. You know, the people that were digging in deep, right? And then the guy leaves, it keeps open claw open source. And then he goes to work for ChatGDP, you know, and then another guy decides to write.

Nano claw, 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, it's kind of crazy, right?

Mike Schatzman (07:48)
So,

yeah, so more of that's going to happen. like people try to draw parallels and, I'll get back to the original question with an example in a minute, but just to kind of piggyback off that, lot of people draw parallels from this AI era to the dot com ⁓ era, 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 dot com era, there was no revenue growth.

Arthur Andrew Bavelas (08:16)
No

revenue, right?

Mike Schatzman (08:18)
So it's actually the complete opposite, right? And so what will be interesting here is that like, you know, are 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, you know, 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 got to do your homework when making these investments because when companies have experimental budgets, they're using everything, right? And then eventually they're going to decide like where they're going to really go, go deep with or embed that technology within their company. So that's something that you have to be a 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, chat GPT, figure AI, mean, they're raising record fundraising rounds. 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, 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. 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 you replacing your windows at your house, right? If you think about what that process 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. 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. 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 re measure because it probably wasn't entirely accurate, right? Because now they need to produce a 3d CAD drawing based off that. so it needs to be a hundred percent accurate. Right. And then that all happens. You sign the paperwork, 3d CAD drawing gets created, then, you know, the window gets made and, and then, um, it gets, it gets shipped out to installed. Right. If you think about that process, that's a, it's a very long timeline, right?

Arthur Andrew Bavelas (11:11)
Right.

It's become real.

Mike Schatzman (11:37)
Well now imagine a company that has the technology, right? This is custom built technology, not, you know, is they call it AI rep. There's a lot of tech that's built around chat GPT and, uh, you know, in our space, they call it rapper 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? From that window, it could produce a 3D drawing where you can potentially see what do windows look like in my space, right? And then you decide on your window. And then that's that technology can also produce, you know, the 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,

Arthur Andrew Bavelas (12:07)
Physically measuring it. Yeah.

while

Mike Schatzman (12:35)
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? So that's where this vertical piece becomes horizontal where they've built. And this is no different than any other business. 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, customers, you know, around relentless focus on the business model of just selling books and then look what they expanded to. 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. Sure, can that work in some circumstances? Yes. But more than not, that approach tends to be challenged. 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 Andrew Bavelas (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. I mean, there's lots of, lots of, you know, you, uh, time wasted in all that, right?

Mike Schatzman (14:18)
Most of them.

Yeah. I mean, look, some of them are sales guys when they're short staff. Right. And so like just AI is creating inefficiencies and you know, the first part of AI is just, it eliminates all the BS. Anyone that's smart and using AI, if you're the way that I think about it is look, this there's always good and bad with technologies. Right. And so now 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. if you personally, I'm talking about a personal use case, but then it applies to business. But if you can automate, you know, how you see email, 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, you know, sales, business development, like the things that you do that make the most impact your business. Right. And if, and you can just, if everyone can just think about that, then it helps unlock how they can use ⁓ AI to, to really just be more efficient, not only in their business, but just everyday life.

Arthur Andrew Bavelas (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, there ⁓ 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 chat GDP 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 next, right?

Mike Schatzman (16:30)
Yeah, yeah jobs are shifting with that and 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, know You know from from social media to b2b anytime these things come about the speed of business just moves quicker and quicker and this is at a speed that's ⁓ that that could be frightening to people right because

you're adding this productivity element before, like, you you look at B2B SaaS and, 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, and when you got the technology, then you needed to call the company and they would send you a potential consultant or card you for a consultant for you to learn how to do this. Right. And this whole per seat, like,

This is a, this is a heightened element of proctive productivity, which becomes very interesting because obviously when it's productivity, it's another employee, right? So this is a very cost efficient employee. 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. 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 they'll be some you know new opportunities that are on the table.

Arthur Andrew Bavelas (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 very pedestrian example, but it spits something out and it makes mistakes. So you need a human to go in and give the sniff test and close the loop on the, it actually work? And that often requires somebody that has the skill.

Mike Schatzman (18:31)
Yeah.

Arthur Andrew Bavelas (18:43)
to not only just understand the business, but understand whether the AI actually produced something that's gonna work.

Mike Schatzman (18:51)
That's right. And so also think about it from a company's perspective. If no, there's a huge trust factor, right? I mean, embedding this to automate some businesses and have it fully run, like, you know, some company is going to be very uncomfortable. That's why, like just from our standpoint, we, love, um, we, we love to see something starting in a niche vertical.

Arthur Andrew Bavelas (18:59)
Great.

Mike Schatzman (19:17)
where with domain expertise where it's proven to do one thing, right? Because then think about it, it's less risky if you've bed that one thing into the organization and okay, there's an issue, 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.

Arthur Andrew Bavelas (19:41)
Yeah, everything comes

to a grinding halt till you fix

Mike Schatzman (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 Andrew Bavelas (19:55)
Yeah, there was a, uh, uh, one of the co-founders of Reddit was on the program and he made a really interesting observation having built, like he was in the weeds building that whole program. 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, if you have stuff that hasn't been tried and true and tested, it's really, uh, you know, can blow up a whole organization.

Mike Schatzman (20:43)
That's right.

Yeah, no, that's right. And so, but yeah, so mean, look, at the end of the day, now I've been out ⁓ and I'm fortunate enough to have been, you know, asked to speak at a lot of different conferences and, know, people always ask me a ton of questions and, know, for the growing organizations, like, you know, lot of these companies are going to have chief AI officers, right? And that person is really going to be in charge where whether the CTO becomes a chief AI officer. mean, look, there's

going to be a combination of the two, but that person is 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, they're, they're 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 still set too. So there'll be.

Organizations that have teams of people with technical skill sets like this, maybe less of them, but as I like to say, you need to be able to go under the hood, right? And so to go under to the hood to see like, what's really there? Is this a rapper? Is this, 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 problems right away. So, ⁓

Arthur Andrew Bavelas (22:13)
If you know what you're looking for too, right?

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

Arthur Andrew Bavelas (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 them, 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 idiosyncratic use case of your company. So they don't use your data to teach their models.

Mike Schatzman (23:02)
Yeah. Well, I mean, look, data is kind of the new, like that's really when you look at AI and what's the mode, right? You know, it's, all going to be about the data. Right. And so that's really 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, 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 all about the data.

Arthur Andrew Bavelas (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.

Mike Schatzman (23:58)
Yeah, so we,

⁓ 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, with previous exits. And so that, ⁓ what that does, and, know, I support a lot of first time entrepreneurs. I'm on advisory boards and do things a lot personally, but it plays into our applied AI strategy. So it has to be.

and applied AI technology, whether it's vertical or horizontal, that's solving for a work full problem. And one of the founders has to 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, right. Or they discovered these and so, um, 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 markets told you that, you know, there's not going to be an abundance of engineers coming out of school that can get three to four to $500,000 jobs on teams of, you know, a hundred people where there's millions of dollars to code. Because if you think about that with B2B SaaS, that was the real competitive advantage.

Arthur Andrew Bavelas (25:15)
just because they could code, right?

Mike Schatzman (25:23)
Whoever got the best developers to develop the product had the lead and sales were relatively easy then, right? Now the exact opposites happen. So you can use AI to build these technologies, right? You can do things and build things and 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 % less.

Arthur Andrew Bavelas (25:47)
Yeah, it's a fraction

of what it was,

Mike Schatzman (25:50)
So 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, going to come out to play, right? Because if the barrier to entry is that low, the marketplace is just going to be filled. And that's what's frightening people now because things are happening left and right. And it's only going to 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

Arthur Andrew Bavelas (26:13)
Yes.

Mike Schatzman (26:18)
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. So

Arthur Andrew Bavelas (26:35)
Yeah.

Mike Schatzman (26:45)
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 outage. We used to see a lot of healthcare tech deals and one of my, ⁓ partners, you know, knows the space very well. He used to run a hospital before I'm becoming a fractional CFO and in healthcare right now, you see some amazing technologies. 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, you don't come to the space with a network. mean, so that's what's gonna happen. You're gonna see a lot of incredible technologies that are being built. But if they're on equal scale, and obviously have a means of distribution, they're gonna be significantly challenged.

Arthur Andrew Bavelas (27:22)
Good luck, Ray.

He built it and they won't come.

Mike Schatzman (27:43)
⁓ So 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 Andrew Bavelas (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 case.

Mike Schatzman (28:20)
Yeah.

A hundred percent. Look, the sky's the limit right now. Like if you're someone, you know, the people now, when they say like AIs, I think a lot of people hear this phrase, AIs 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? And then in other businesses, like there's going to be more automation and 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, the whole layer of the landscape is changing. So...

If you have expertise in a space right now, and that's what we, you know, that's why we got behind our thesis. Some of these guys are licking their chops, saying, I know all the problems in the space. I can use this technology and I'm going to go, you know, I'm going to start in one, one area and start to build a business around it. Right. Because it's relatively easy for them become, they come right from the space. So that's, that's our whole investment thesis in a nutshell there. So then of course, like you have

everyone gravitating towards that, then you're going to have obviously, you know, some industries like, there's some automation coming in landscape and where you'll see some robotics, things happen with, you know, lawnmowers and stuff, you know, plumbers, everyone's talking about like plumbers, electricians. And if you think like in life and anything, right, everything moves too far in one direction and then comes back a little bit to reality. So yeah, are we moving? ⁓

Arthur Andrew Bavelas (30:05)
Reversing to the mean.

Mike Schatzman (30:09)
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. also there's a shortage of those people right now because everyone wants to move into tech. younger generation just wants to be with tech. They're growing up with iPads and all this stuff and that's all they know, right? And so, ⁓

Arthur Andrew Bavelas (30:48)
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. It's always been that way.

Mike Schatzman (31:01)
Yeah.

Yeah, that's Yeah.

so like, you know, there's ⁓ obviously when everybody gets excited, you know, like when, you know, I'm I'm not 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. And so that's where the enthusiasm comes in and investment comes in. ⁓

over investment, all this type of stuff. And so, you 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 Andrew Bavelas (31:55)
Yeah. What do you think of the, you you, often have to ignore headlines, but what do you think of all this talk about, you know, SAS is dead, you know, you know, people, companies like Salesforce are going to suffer not because they don't have a good business model. It's just that software is going to sort of not be the, the, the, ⁓ holy grail that it once was.

Mike Schatzman (32:24)
Yeah. So look, ⁓ you know, there's an argument to make. Yeah. So, ⁓ you know, parts, yeah, some B2B SaaS companies are dead, you know? And so the, the thing right now with these B2B 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,

Arthur Andrew Bavelas (32:31)
Yeah.

Mike Schatzman (32:52)
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'll also go over pay for something that's working, because if their business is at risk of potentially being extinct, they'll take all measures to correct that quickly.

Arthur Andrew Bavelas (33:05)
So they have a balance sheet.

Mike Schatzman (33:19)
So yeah, mean, pricing is going to change per seat versus productivity. So the business model is changing. 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 are, that are happening ⁓ behind the scene. And so that's what's happening right now, because if you look at the market,

people, know, of course things always get overdone too, right? So these could be attractive opportunities for the right SAS 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 is going to continue at this pace. And then you're assigning larger multiples to the faster growing AI ⁓ businesses, right? So these SAS based businesses are

Arthur Andrew Bavelas (34:06)
Totally, yeah.

Mike Schatzman (34:18)
you know, are just there. 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. You know, it can continue to go down a little bit more.

Arthur Andrew Bavelas (34:38)
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 when in a matter of weeks, nano claw comes out is, know, normally that

⁓ infrastructure that you built becomes a legacy system in the old parlance, right? And you can't extract yourself from it. Is that 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?

Mike Schatzman (35:31)
⁓ yeah, I mean, look, it's easier. The way I explained this is, ⁓ it's, ⁓ what was it going to 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 can, they can switch out this technology and stuff overnight. 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 you've, all been a part of large enterprise. They move with a snail space. And so once, you know, it can take them like six months to integrate something. Right. And so, ⁓ there's a, ⁓ there's a huge opportunity for small to medium sized businesses to embrace these technologies, play with them and, and move them in and out. And so people have to, think,

Arthur Andrew Bavelas (36:05)
Yeah

Mike Schatzman (36:28)
it becomes challenging for the larger enterprises. They really need to think through that, right? So ⁓ that's kind of how we, ⁓ you know, our lens on these things at the early stages. This comes out, then that comes out, your 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 Andrew Bavelas (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, are those companies going to suffer because you don't need a team of, you know, PWC?

technicians to help you integrate a new technology.

Mike Schatzman (37:24)
Yeah, I mean, look, there'll still be, ⁓ you know, it's interesting with AI because, ⁓ with, with all this stuff, it's actually been a bit of a boost for some of those outside consultants because there's 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 aren't as technical as others, you know, there's

There's a huge need for consultants right now to come in these enterprises and help pick stuff up. So it's actually been a boost for them. Over time, I think that will dissipate a bit as the skillset catches up, right? But with this new skillset, 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. 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, know, directors of boards are coming down and saying, we need an AI strategy. And then they call these guys. Right. And so, and you've seen some of these reports where, know, you know, some of these companies can pay a consultant and the consultant is using AI to do these reports. so they're,

producing these reports for a significant amount of money and ⁓ then their profit margins 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 think. it may take a while. This could keep going on and on. The more you introduced all these models and everything, you need expertise, which is in short supply.

to get in there and understand like all these different language models, what's the do, what's the pro and con, am I using Claude, am I using Gemini, like what do I use for what? And then how do we teach the employees how to do this? How do we have a height and level of consistency across our organization? It's a lot. It's a lot, but advantage to the startups here that can integrate this and master it, right? Because that whole new wave of companies that are embracing it,

Arthur Andrew Bavelas (39:29)
It's exhausting.

Mike Schatzman (39:40)
You'll really start, you mean you're starting to see revenue accelerate them with them now. And I think that's only going to continue.

Arthur Andrew Bavelas (39:49)
So that suggests that 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, open AI. 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.

Mike Schatzman (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 a 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 startup and everyone's working one person East coast, West coast, but you all, you guys are, everyone's with, you know,

Arthur Andrew Bavelas (40:53)
On the same page, right? Yeah.

Mike Schatzman (40:56)
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, 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 and You know when I went to school like when you were looking at resumes I mean coming out of college but people that like if you weren't at a company for at least like three years that was a red flag like

Arthur Andrew Bavelas (41:53)
It was a total

red flag, yeah.

Mike Schatzman (41:55)
Something's wrong.

So those dynamics are going to be interesting because you can grow revenue and do all that. how do you, how do you build culture? How do you keep people? it that's, that's not easy. And so they'll, a lot of these startups will be challenged in, in that nature because they grew up in this virtual world. Some of them have been more in isolation mode. They, they're, 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 little bit right 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 You know what? And that's why

Arthur Andrew Bavelas (42:50)
Where am I gonna get the talent? Yeah, right.

Mike Schatzman (42:53)
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? How do they work? Like you got to 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 Andrew Bavelas (43:25)
Yeah, the the upworks of the world have been a godsend to many. But when somebody sitting in, I'm just going to pick on Bangladesh, like, how do you know? Like, how do you really know whether they can deliver right?

Mike Schatzman (43:42)
Yep, that's right. so trusted circles are very important. And 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? 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, where these, these families have their structure 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 groups, all trusted circles. They all want to talk with each other, do diligence together. It's very hard for 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 new product unless it comes from someone they trust. Right.

percent of the time that happens. So that's a relevant example in your world that's transpiring right now in AI only makes that worse. And so like, if you talk about like a little bit, there's tons 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 gonna carry that thought process with them through everything. Investments, life. And I think that's a negative consequence that a lot of people don't talk about enough in AI, because it's gonna continue to happen. And so if people start to have that mentality, they're just gonna 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 live in but we could talk about other investment asset classes as well. know, the Andreessen Horowitz, the Sequoias, all these guys, obviously very reputable, amazing firms, you know, 55 almost like over half of the capital raised last year in the private markets went to like a handful of firms. I think it was three, four and five, right?

If that doesn't, if that's not a key indicator, I don't know what is.

Arthur Andrew Bavelas (46:14)
So flight, the old thing when 2008 flight to quality, that sort of thing. 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.

It's it totally makes sense. And I agree with you that the trend is to pull back and trust and and and further 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. You can't believe anything they say, right? In fact, you can start with saying, well, that's not true, right?

Mike Schatzman (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 and look, it's important to have that perspective, but I think balance is, is important. And so yeah, the trusted circle things 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 yeah, people have to be well networked. And then we're coming in this age where the younger generation is like a bit more anti-social, right? They're behind the screens.

Arthur Andrew Bavelas (48:01)
They haven't built that muscle, right? Yeah.

Mike Schatzman (48:03)
Right.

So like everything, you know, like some I have some scenes that I would say like behind the screen don't mean a thing. like out of, you know, out of covid, like I call it, you know, there's people I call them Zoom lemons. They're on they're on Zoom, but they're wearing Lululemon. Right below it. 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.

Arthur Andrew Bavelas (48:19)
Right.

His

pajamas on. Yeah. Yeah, right.

Mike Schatzman (48:32)
like in his underwear. And

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 ⁓ where things are going right now. And so yeah, I mean, you know,

Arthur Andrew Bavelas (48:55)
And that's what 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, should I do about this, right?

Mike Schatzman (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. 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 want to respond right so How people communicate it's gonna change as as well, you know under under this You know new AI regime Yeah

Arthur Andrew Bavelas (50:20)
It's already happening. Yeah, we

see it all the time. We've had to, ⁓ and we're just no different than any other business and 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 going to get involved. And now we...

have ⁓ a living breathing scoring system, right? Where we can not bother people who aren't interested, right?

Mike Schatzman (50:51)
Yeah.

Yeah, right. there's

great. So yeah, there's the good there with make those tapings 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, 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

Arthur Andrew Bavelas (51:26)
and

will always be. Yeah. Well, that's awesome. 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?

Mike Schatzman (51:27)
Exactly.

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 to come to either some of your events and focus on the education of how to invest in AI, where to be looking. I 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. 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 there, 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, in this space. Cause I think it's only getting started, right? And so

more and more is going to come. And these family offices also have to have the right infrastructure set up, especially for venture and 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. 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

Arthur Andrew Bavelas (53:04)
Yeah, no doubt.

Mike Schatzman (53:09)
how you get access to the information and know what's real or not and utilize your network and resources is extremely important ⁓ when you're looking at alternative assets.

Arthur Andrew Bavelas (53:20)
Yeah, we'll be sharing this with the. Office Insights Community, so ⁓ please feel free to reach out to Mike. Is that OK, Mike?

Mike Schatzman (53:29)
Yeah, that'd be great. So

I would welcome the introduction and look forward to, you know, assisting you in any way, or form down the road.

Arthur Andrew Bavelas (53:37)
Appreciate that. And it's a great time to be alive, I'll tell you that. Amazing.

Mike Schatzman (53:41)
Yeah,

there's no sure. mean, it's a fast paced world buckled up, right?

Arthur Andrew Bavelas (53:48)
Thank you everybody for joining us today. Thank you again, Mike. And we'll see you next time. Thank you.

Mike Schatzman (53:51)
Thank you.