"The Cognitive Revolution"
00:58:30 · Nathan Labenz
[00:58:30] S0: Come back to the more extreme scenarios again in a second, but just in terms of the sort of scale of the realignment, if you will, you know, maybe euphemistically of the markets that you're entering. If I had to put a number on it, I would be somewhere in the, like, 10 to 20% of companies that currently are out there, you know, operating as traditional local services firms might get over the hump to join one of these compounders. And then for everybody else, it's like, why bother? Right? Like, your leadership's not that great. The pull factor's not that strong. You know, you're kinda got your head in the sand or whatever. Maybe we'll just, like, take your customers. Maybe we'll hire some of your best people. But I guess my expectation is something, you know, the other 80 to 90% of those firms, I think, just not gonna make it. Is that too... And I don't know. You've been... You're striking a a tricky balance here on the on the communication front, but, like, to some degree, you might wanna be kind of... It's in in some ways in your interest to be clear about that if if it is what you believe because it would be, like, quite favorable to your deal terms or, you know, ability to, like, get people to move fast if they feel like they wanna be in that 10 to 20% and not Yeah. Not standing without a chair when the music stops.
00:59:47 · Marc Bhargava
[00:59:47] S1: Maybe that'll be good for deal terms, but I think the reality is, a majority of firms could join these sort of AI enabled roll ups because the tools we are building should be super intuitive. Like this is very different to your traditional software model where you have to go in and you gotta learn a system like SAP or Jira or even Salesforce and, you know, it's difficult to do. The way we're actually building these AI native toolings, especially agents is so much so that you can put it in your own workflows. And so it should be easy enough for most companies to use is kind of the first point. And then the second point is there is a lot of churn going on in the workforce. You have a lot of baby boomers retiring and you have a new generation joining. That new generation is already fluent with ChatGPT, with using a lot of kind of online tools, certainly with email and Slack and other things that we integrate really deeply with for our agentic workforce, etcetera. And so I think, know, one, the tools being built are actually very similar to existing workflows and most firms can use it. And number two, while there are of course some extremely old school firms that are still using facts and other things like that, we absolutely have seen that as well. Part of that is also just a generational shift, right, where that generation is kind of retiring in the next ten years or so. And the folks coming out of high schools and colleges today, many of them use ChatGPT as like an operating system, not just a search piece where they're getting life advice and in some ways they're even more AI native. And the engineers today are using Cursor and Windsurf and so I overall think a majority of firms even in the services space will be able to participate in this if they want. There are other alternatives too though, you know, folks especially on the leadership side might feel like we want a 90% cash out, we wanna sell to private equity and we wanna take the money to a beach and it's... That's kind of how capitalism works if they wanna sell their company that way. But we're... We have a very different pitch which is, you know, take a second bite of the apple here. Transform what you've built for the last thirty years, you and your family. Transform it with AI. Make it way more effective. Grow the business.
01:01:45 · Marc Bhargava, Nathan Labenz
Roll over a significant amount and be part of an alternative to that sort of PE consolidation. And we think that really resonates. Honestly, I think it can resonate for not just 10 or 20%, but for a majority firms. And certainly, every year, we're seeing it resonate for more and more. [01:02:00] S0: Okay. So here, I'm gonna push you on the... Just how crazy does this all get. But maybe we can start with... You went through 70 industries, you know, winnered it to 10 based on where you could see a path to 30% automation. What are the things that can't be automated and, like, what are the barriers? I mean, to some degree, obviously, like, operating in the physical world, like, we don't have robots yet. We do have, you know, quite a few humanoid companies that are, I think, on track to maybe change that in the not too distant future, but clearly, it's not here yet. Then we have this notion just from the AI companies that there is gonna be the drop in knowledge worker, and it seems there that one of the big barriers is context, like lack of context or lack of ability to handle enough context, etcetera. How do you taxonomize what can't be done? And and do you have a map for, like, what the AIs specifically can't do that makes those things not yet accessible?
01:03:02 · Marc Bhargava
[01:03:02] S1: There are kind of two bigger buckets here. So one is what you already alluded to where, you know, a lot of the automation today is more in these continuous tasks that I spoke about, like data entry, analyzation, creation of presentations, those sort of things. It's not in, for example, you know, maybe plumbing and roofing and HVAC and a lot of like in person, work, firefighting, etcetera. And so there is a lot that still happens in the physical world where there might be some automation on maybe doing routing, scheduling, payments, all of that, but it won't meet our 30% criteria of like, look, this automation will really transform how you are a firefighter, for example, at least not right now. So one bucket is that. A second bucket is we don't want to go and buy up firms that are have high churn. So you know, when we come in and we do AI automation, if you think of something like the digital ad agency or PR agencies, lots of folks use multiple ad agencies and multiple PR agencies. So if we were to go and buy one and start transforming it with AI, if there are any hiccups along the way, they might just ditch us because it's a very kind of using multiple providers and it's very high churn. And so we also... Another big criteria is we're only doing this in industries where there are really good business dynamics, where the customers have sticky contracts, maybe they're multi year, there's very low churn. So when we come in and we start doing AI automation, it's not always a 100% smooth. And so we have to have the benefit of at least six months or a year to kind of implement these things for our base workers and for the end clients as well. So those are two things that really have struck out a lot of different industries where either there's a big real world component or business economics around churn are are kind of dangerous. And so those have been two areas at least recently that have sort of flagged it so that it's difficult to go in that industry. And then a third of course is looking at how good is the AI as well. And so, you know, two years ago you wouldn't be able to use AI to automate a lot of what we're looking at today like in insurance and even looking at insurance underwriting like that was just AI totally wasn't there.
01:05:07 · Marc Bhargava
So there are also other industries where, oh, maybe one day AI could do those tasks, but the current models are worse than humans doing it. So you're not adding any real value there.
01:05:17 · Nathan Labenz
[01:05:17] S0: So do you not expect to see this drop in worker? Because, I mean, it does strike me that there's, like, several data points that I see pointing to big tech takes all. A friend of mine coined the term the big tech singularity. And I think that is basically my mental model of what's gonna happen. Not necessarily, of course, like, that they'll own every customer relationship or whatever. You know, when you... With Google and Facebook just on the ad platform, of course, they had, like, all these, you know, sort of local agencies and sellers and people, you know, kind of translating the platform value prop to the local business. But talk about a business that's had a lot of margin compression, you know, those facilitators of, oh, I can do Facebook ads for you, mister local business owner, that's been a really tough spot to be in. And, you know, in medical, for example, we've got, like, multiple studies that have shown that the AIs can diagnose better than the doctor and can even like prescribe better than general practitioners at least these days. There's been some that have shown that like the hybrid, you know, there's always this like refuge that people want to take and well, it'll be the doctor and the AI that'll work together, but there's been some suggestive evidence at least that like the AI is actually performing the best, then comes the hybrid, and then the doctor alone is worse. I just also saw a data point from Harvey the other day where they put out a a stack ranked leaderboard of... On their own, like, big law bench... Benchmark that their own fine tuned model has kind of fallen behind, like, eight other foundation models that just seem to be winning on the bitter lesson and generally, like, scale continuing to pay off. There is still this issue of like the drop in knowledge worker doesn't quite exist because it's hard for them to absorb all the context, but that to me seems like something that probably gets solved. I guess I wonder like, do you think that just never gets solved? Or if it if it does get solved, how do we not end up in a situation where it's like, okay. Now we're just dropping in these AI knowledge workers into this environment. And, you know, again, you sort of have a... Now you have a very literal complement versus substitute dynamic going on.