Recall Sessions: Most SaaS Companies Won't Survive This - Jake Saper (Emergence)

The absolute worst thing you can do right now is say, I grew 3x last year and they're far more safe. We are in this foggy phase where it's like, what is this new business model? Is it even a thing? And if it is a thing, how do you build it? AI Native Services is going to be the next big emerging business model, and we will be the emerging experts to understand and teach the industry how to build these companies. And also with great power comes great responsibility. We have to help figure out ways to make society shift in a way that is more, you know, that is going to survive in this era. My guest today is Jake Saber, General Partner and Emergence Capital. Emergence was the first institutional investor in Zoom. They were early in Salesforce, Viva, build.com, and together.ai. Companies now worth over $450 billion combined. Jake has been at the firm for over a decade, leading investments and assembled, Unify, ironclad, and others. He sits on boards, works closely with founders through their early Gordon Market Grind, and has developed Emergence's thesis on AI Native Services, what they call Ains. And why they believe this is the most important structural shift in enterprise software since the move in the cloud. Before venture, Jake worked in management consulting and spent time at Clienter Perkins. He grew up raised by serial founders, his parents are co-founders, so he saw the messy reality of building companies long before he started backing them. We're going to talk about what actually changes when AI can do the work. Why Jake thinks the line between software and services collapsing, what it takes to build a company that wins in that world, and where he sees the biggest opportunities and the biggest mistakes playing out right now. Let's get into it. - Jake, I'm known for a long time, probably one of the first people I think about, one I think of who's the best person child with an application software. But the world is fucking changing. And I want to start in a place that is just deeply troubling about what is happening with SaaS. Maybe we can start there as like, all these companies pre-AI, what is going to happen all of them? - It's a tough time. Is the TLDR. There will be a number of them, probably a small number of them, that make the shifts to this AI era, and most of them won't. - What does it mean to make the shift? Like what does that really mean in practice? - SaaS businesses have been built to sell a tool. In the AI era, they have to shift to selling outcomes. And that is a fundamental DNA shift for our company. If you have built your entire organization around the idea that we are building this widget to sell to someone in a per seat basis and help them do their job, and you have to shift to a world where you are building something that does the job. It has huge implications on the product development, it has huge implications on go to market, certainly on pricing, and it's very difficult for a business that has gotten to itself to a certain amount of scale to be willing to make that shift. Not just from a, we're going to jeopardize our growth, jeopardize our margins perspective, but also just from a cultural perspective. Like it's really, really hard, even if CEOs have good intentions to make those changes. It is like this is a classic classic innovative so I'm a moment for the entire industry. And in any of these moments, some companies make it and some companies don't. You know, our firm was founded as software was moving from on-prem to cloud. There were a lot of on-prem software companies that existed, many were thriving. There was a nuclear explosion of a new technology that was the cloud, and the vast majority of the companies in that previous area did not survive. But then you had even bigger companies like Salesforce that got built on top of the ashes. And if you companies like Adobe managed to make that shift. Is pricing the primary, I mean, obviously product has to be very, I mean, I know if you talk to CEOs today of SaaS companies, they're like, we've always cared about outcomes. We just, we just packed it up and we sold it as seeds. And that was the whole thing. Now, I think the way that SaaS leaders thought about outcomes historically was, did my customer renew? I think in the future, the outcome has to be, did we create dollar value? It's a totally different-- >> Yeah, but I mean, just to challenge that, I mean, most of these SaaS CEOs are gonna say, oh, we've always focused on ROI and there's some value-based narrative that existed. And so it's like, we've always cared about outcomes. I understand that it's a, you know, look at customer support as an example. You know, it's like, hey, we're the pricing of all of the service software companies before it was all like how many CX people do you have. It's very different now. But I feel like they would all challenge this right now. >> Yeah, the product that they have sold historically has been a derivative of value creation. It hasn't been value creating. So what I mean by that is like, you were selling a tool to arm someone to go do something, but you were a derivative. In this new world, they have to go do the thing. So it's not, this is not just a pricing change. Yes, pricing has to change, but the fundamental value you deliver has to change. The way I have a friend, Madhavan, who used to run this consulting from the did pricing stuff, and he has this two by two around how to think about getting to outcomes-based pricing. And I think it's really telling because to get there, it's not just a function of like, can you change your pricing model, it's actually, can you change what you sell? And in his mind, you have to both deliver a product that has an autonomy level where it's able to do something without, you know, a lot of human intervention and that you can attribute the outcome to it. So it has to be high attribution and high autonomy. And if you think about like, what SaaS vendors are selling today, in most cases, you cannot do that. It doesn't matter if you try to change the pricing model. You can't say to me, if you sold me some productivity tool that's price-per-seat, that like you, the software vendor, with the reason that some business outcome happened, and that it happened autonomously without the end user involved. So the hard thing is this shift for SaaS leaders is not just one of pricing and packaging. It's not just one of like, I need to get all of my employees to become AI native and how they work. It's the thing you sell has to change. It's a fundamental shift. In fact, much more fundamental than the on-premise cloud shift. So what are you telling your SaaS CEOs? Like, is there a roadmap that exists to like, hey, first you do this, then you do this? Like, because a lot of people are like, you know, hey, I have a certain product that's making certain error. I got to show growth. Like, do I just like, just accept, pull the plug? Like, what do people do? I think it depends on the situation you're in. So if you are a small SaaS business, you have a lot more room to know which is to find a small SaaS in the sky. Well, like companies that have like 30 million revenue in below. Like in that world, you obviously have existing shareholders that have to weigh in. I think the most on top of it shareholders are saying, look, the old world doesn't matter anymore. We have to reinvent ourselves. And so we're willing to part without revenue, we're willing to part with that margin to ensure that we have a shot at playing in the old world. So I think like private companies, you know, middle and smaller companies should have capital structures and hopefully investors that are willing to encourage them to take a leap. Public companies are a harder situation. Right, because they have to get, they might get destroyed by the market if they decide to say, hey, we're going to stop selling the thing we were selling altogether or we're going to completely change. Are there any examples of that right now on the public side that you're, I mean, I understand it's private, it's happening kind of, private it's happening all over the place. And the public side of things, I don't think anyone has taken the full leap to say, we're scrapping what we sold before and we're going to take the best parts of it to rebuild completely. I think it's a really hard thing to do. I had a conversation, we've been hosting these AI pricing workshops in our office. The one we had a couple weeks ago, there was a CFO of a public SaaS company, who I won't name. And she came to me and said, I am stuck because I want us to push more AI usage in our product. But I know that in so doing, I will lower my gross margin. And if I lower my gross margin, the board and the market will punish me. But if I don't do it, I'm not actually moving to the next era. So I'm stuck. I don't know what to do. And the reality is, like, she would have to figure out a way to say to her shareholders and to the board, we have to do this or we're not going to survive. And that's a really hard message to deliver, particularly given the power of dynamic. So I think there's kind of embedded structures that make it really hard to make this shift. And so I think in some ways, the public market companies are in a worse spot than the private market companies. Let's say you're like a few millionaire are in that sort of spectrum. And growth is like, OK, even folks that have a 3X growth, like what do you say to those founders that are like, hey, I had something, people bought it. Do you-- would you take a more aggressive strategy there? For sure. Yeah, I worked with a company that grew four and a half X last year. And over the past two months, we've been thinking about how we completely change what we sell. So this is a business that is not in trouble. The business has capital. The business is growing really quickly. And we-- and the CEO's credit, like he has been spearheading a lot of this, have said, look, the value that we create needs to change. The people that we sell to are changing. Many SaaS businesses are selling to seats that will no longer exist. It doesn't matter how good your product is if your buyer does have a job. You have to completely change the value you're creating. And that is a really, really hard shift to make. It's really scary to-- even for this business, to walk away from the growth and the revenue it's had and figure out a way to sell something different, to perhaps a different persona. And in so doing, take on more of the job to be done. Most folks have never done what you're describing. Is it a, let's go back to the pizza roll kind of, let's be thoughtful? And I know a lot of CEOs are like, let me protect my revenue versus-- I don't really care about the revenue we have. I'm going to have to make tough calls. I'll deliver the message to our customers that, like, hey, we're going to keep this thing going for XYZ, but we're not going to longer service it. We're going to be working something new. How do you operationalize this? Like, what are you discussing in those boardrooms where those conversations are happening? I think the first thing to understand is. what is the unique insight or value you have in this new world? And the reality is like many of these SaaS businesses do have, they should have something like that. They've been serving this product for years. So they should have some insight in terms of the job that the product is doing that the rest of the market doesn't have. They might have some proprietary data that they could use. The first step is to understand, what do I know, what do I have that no one else has? And then step two is, okay, how do I operationalize that? What could a product or a service look like in terms of what I sell going forward? Using the unfair knowledge and advantage I have before? I think like, those are the critical steps. Then you have to figure out, okay, how do I rally my whole team around this? And that's a hard thing to do, right? Because you have people that were hired to build and sell something different than you are now asking them to do. And so your first job is to rally the troops and communicate this clearly and get people all bought in. And then the second harder thing to do is to say, like these people likely aren't great fits for this next era. Either because they're not bought in, or because the skills that they have isn't relevant to the product that we are now selling. And it could be the case that like, the product or service you're now selling needs a completely new skillset, which could mean that you are hiring totally different people. You are partnering with some services firm. There's lots of different ways you have to think about reinventing your DNA. But the absolute worst thing you can do right now is say, I grew three X last year and they were form safe. Actually, those businesses are almost in a worse spot than the business that grew 30% last year. Because this is like 30% last year. You don't have enough, I don't have enough to begin with. And so like I've got to take, in some ways like this is their moment, right? Because like they have the opportunity to say, like I'm going to reinvent it all. And hopefully they've got the capital partners who are like, I'm right behind you, I'm here to help you help you do it. But the ones that were like on a really good trajectory in this ass era, I think are the ones that are going to have the toughest time taking a look in the mirror, but are probably the most important ones to do. Is there any examples of folks of companies that you feel like are either in transition or transitioning or like have already made the leap? And it's their. - Yeah, I think the one that's been most popular as far as Owen and Orcom. - Right, with Finn. - With Finn. And that took a pretty dramatic thing of like founder, leaving the company and then coming back, firing a bunch of people, completely changing everything. And he had to grab a toss to be able to say, look, I built this and I'm willing to tear it down. - Right. - And I've had really frank conversations with some CEOs that say like, I just don't have the energy to tear down the thing I built. - And is that just M&A is like, is it just like, okay, let's go explore? - I think you have two options there. It's either M&A or you find a new leader. And I think that the best CEOs right now are operating with a level of self-awareness to understand which of those people they are. Because the reality is like, - Do you judge them? I mean, you know, it's like a. - No. - Because like a God, I mean think about it. Like someone who's been building something for 10, 12, 15 years and they've been through so much, like the way I think about this is almost like a video game. So like, if you think about it, found who started a business in 2017 and they had to figure out all the terrible stuff to get to product market fit. They find product market fit. They raise around, they start growing. And then things feel really good for three years then COVID hits. Everyone thinks the world is ending. The business collapses for three to four months, interest rates drop, all of this in the business takes off. So all the people they fire, they rehire. And they're scaling, trying to serve demand in 2021. And then obviously interest rates, you know, skyrocket. And the businesses then, you know, all fall off and raising capital's hard. They have to fire a bunch of people and then rebuild and kind of crawl their way back up into something relevant. Then 2024 happens, they start playing with OpenAI and chat you're saying, "Oh, this is making me a little more effective." And it's kind of exciting business starts to go again. And then all of a sudden, Claude drops and it's like, "Oh wow, like the Opus 4.6 can do a lot of what my product used to be able to do." And it's, they didn't do any wrong, right? They built a business that was adding a lot of value. And the reality is, the value that they were adding is not as valuable in the new era. Either because the people that they were selling the product to don't have jobs anymore, the function is being replaced by AI or because the value they were creating can be done by these foundational models. There's lots of reasons why that's the case. But I don't judge them. I feel, I feel for them. And I think it takes a very rare type of personality to say, "I've been through 10 years of this and I'm willing to tear it all down and be energized to rebuild this new era." The flip side of it is like, this is arguably the most exciting time to ever build. It is just insane how much you can build with so few resources. And if you're doing it not from a cold start place of a new company but you're doing it from the place of, I've already got this asset and this data and these customers and distribution and whatever, you do have a real advantage. But God, you have to do some real looking at the mirror. As I look at, Emergence says, like last few decades of companies you invested in, it just seems now just application software is just a really, really tough category to underwrite. And either you're like, "Oh, the labs can do it," or like, "I can vibe code something," or I can, "Oh, maybe it's just easy to build because, you know, cloud code is just so easy to kind of go from zero to one." Like, what is your perspective of what is happening in application software? - For sure. - There are software modes in this new era that are going away and there are software modes that are rising. The ones that are going away are some of the modes that were the strongest to bank on before. You could argue that one of the strongest modes that a software company had before was workflow. If you get thousands, millions of people using your software every day, even if there is better software that comes along, it's the pain in the ass to rip it out and retrain people on how to use it, et cetera. In a world where the agents are doing a lot of the actual workflow, that's no longer a mode. Relatedly, it used to be the case that integrations was a huge mode and it was never like, trying to rip things out and re-plug in the API, whatever, that's no longer a great mode in a world where CLI exists, MCP exists. There's just lots of ways in which agents can do the integration and talk to each other. So those modes are no longer, I think, interesting. But on the other hand, you've got some modes that I think are rising in this era. In one mode that I think is increasingly important, is being a system of action in a mission-critical context. So one example of that would be our mutually beloved company, Gusto. I think it's very unlikely in any near or medium to a world that companies are going to to vibe code payroll. It is just too important, it is regulated, you cannot mess it up. And so having a vendor that does the action-- >> That is supposed to put in a J-sensee, like lattice or something like that. >> I think lattice isn't a tough spot. >> Yeah. >> A super tough spot. That's not a system of action. System of action is like, I pay you. Latis is a workflow tool. Latis is a tool that allows you to aggregate feedback from someone and then give it to someone. >> What do you feel like at large software categories that you guys were early investors in Salesforce, CRM? Like, do you think would you invest another CRM company? >> Or what would need to be true for-- >> Yeah. >> Because as you describe workflow, integration, those were the modes. >> The thing that I'd want to see for any of those types of like for CMP-- >> ARP is an example of a sort of known category. >> I think that there are two other modes that I think would be important that apply to this question. The first is brand and trust. Like in an era of agents, the role of trusting your vendor becomes almost more important. Like if agents are doing lots of things, it's really important. Like a big part of the value of the vendor becomes like the throat to choke. Like I am here and you can trust me and I will guarantee the outcome gets done. If you take, this is a very extreme statement and I don't know if it will actually happen. But if you take my argument that ultimately software is moving the direction of selling outcomes to its logical extreme. And let's say you believe in a world where a cloud can commoditize code. Where my code is the same as your code and there's no better code because cloud can do it all. The role of the software vendor or the technology vendor becomes an insurance carrier. >> Like what do you think about companies like cursor? >> I don't think cursor is an outcomes based company. Right? I think cursor is a workflow tool that helps people code autonomously. And as a result, I think it's going to feel pressure. It's already feeling pressure. I think that to complete the insurance carrier analogy, the value of a vendor going forward is to say like, I guarantee that this thing you were trying to do gets done. And if it doesn't, there's some financial outcome. There's some like, I pay you something, there's some remuneration, et cetera. So my view is that like the trust of the brands, particularly mission critical workflow becomes even more important. And if the thing you are doing is I'm a tool that helps people get something done, I think that's going to be a really tough thing to do regardless. The last thing I think is really important that is not been talked about enough in this new era, but has been important throughout technology history is network effects. And it's nuance because there are some network effects that become less important in this era, and there are some that become more important. I'd argue that the ones that become perhaps less important are workflow based network effects. Unfortunately, things like Figma, where part of the network effect was everyone comes here to do design together in a world where agents are doing more of the design, the model that Figma had does not have as much dickingness. Now, obviously Dylan is very smart and is moving their model in directions that I think will capitalize on the new world. But that type of network effect that's workflow based I think becomes less important. But I think actually data based network effects become more important and trust based network effects. So data networks effects are fairly straightforward, where as the product does some job and has the full understanding of the outcome, the data it's gathering about that closed loop can be piped back into the product and makes the product better and better. There's also the concept of trust based network, which I think becomes arguably even more important in the AI era, where we don't know how to trust the agent versus anyone else, which is why I'm very long linked in, which is crazy because this is a product you could argue has not been innovated upon enough over the past couple decades, but it is still a place where people share their trusted, verified or self-verified information about their careers. And even in a world if where agents are the recruiters on the platform that are doing all the outreach and everything else, it is still the gathering place where people are sharing their trusted information, keeping up to date, etc. And so I think it actually becomes more important. The struggle that I feel founders that are having that are early in their journey is like they buy into what you're saying. It just takes a lot of time. How do you accelerate trust? How do you prove that the data outcome feedback loop is actually defensible because everybody is like, hey, I got a few hundred K, I've achieved some outcomes, but you're like, okay, so what? It's a really good question. I was just having that conversation with the founder this morning. He was arguing that her proprietary data makes her product better. And I was like, show me, just show me what your thing can do versus like if I were to code up on cloud without the proprietary data. I just want to see a comparison. So it's easy to feel like it's like, you know, whether it's in the family or you know, someone that you are on the outside that you have respect for. Well, I think that the, like, so here's an example, we have an investment in company called Harper, which is an AI native insurance broker. So they actually like help companies find insurance. If you are in that position and you are doing thousands of brokerage interactions every day to understand, okay, this day care in this market is looking for this type of coverage. And you have an AI system that's out reaching to all the carriers and figuring out who is covering that type of risk and what they're charging for it, et cetera. Every time you do an interaction, the your ability to do a better job brokering goes up, goes higher and higher because you have a good sense of the market right now for what's happening. And so that's a business where it you can actually like quantifiably see that like as they do more business, they're able to, you know, close the deals more quickly for their, their customers because they just have this this proprietary data network effect. So I think anything where there's a really clear closed loop outcome and when there's some sort of like quantitative, you know, speed to close or likelihood to close or whatever, I think that like in that world, it becomes more visible. But it's incumbent upon the entrepreneur to demonstrate that, to say like, look, here are the ways in which having this proprietary data actually improve these three metrics we care about. And we did an A/B test and we ran it without the proprietary data. And here's what happened. I think we're now in an area where the CEO has to go from telling the story to conceptual level to telling the story quantitatively. I know that you've been talking a lot about AINATIVE services. Tell me about the thesis that has led you to kind of go deep in this area. It seems like everyone's talking about it, you know, and it seems like maybe we can start there. Like how did you land on this area of opportunity and what's interesting to you about it? So back in 2023, I met a guy named Rob Me, who had started a company called Pivotal Labs, which was the premier to kind of tech consulting firm in the valley in the 2010s. They would work for companies like Twitter and Google and do their hardest projects there with the outsourced crack team. I know this because I was on the board of a company called Drone Deploy and we hired them years ago and I'm really looking at the bill and being like, this is insane. And they were like, yeah, these guys are really good. I mean, some of the best engineers I know worked at Pivotal. It was, and Rob was the CEO and founder just had this incredible ability to recruit just the most crack engineers and figure out how to do pair programming everything else. Rob started a company during COVID called Mechanical Orchard. And what Mechanical Orchard does is an AI native service that does mainframe modernization. So they go to really big enterprises, Fortune 500, 100 companies, where the mission critical workloads or workflows are still written in cobalt and housed on an IBM mainframe, which is nuts, but which is nuts, 75% of Fortune 500 companies are still running their mission critical applications in a mainframe. We think that the cloud is dominant because like CRM, ER, whatever. The reality is like those, the easy things were the ones that got to the cloud. The inventory management system that you built in 1995 that powers everything into the retailer. You are so scared to move that in the cloud. It is so hard. That's millions of lines of code. The people who wrote it are retired or dead. You've got to figure out a way to get in the cloud. Historically, you've hired, you know, consulting firms who have spent years and tens of millions of dollars trying 50% success rate. AI does coding really well. Now, the foundational models don't have all the access to the cobalt data that they would need to to be able to do this fully out of the box because by definition that cobalt data, what's on mainframes, it's not cloud data they can scrape. So Rob's insight was like, I will use the foundation models and pair it with the data I'm gathering from talking, working directly with these cobalt mainframes to basically build, you know, cursor for cobalt for lack of a better term, but to sell it as a service. So he's not selling software product that says, you know, hey, Target, you figure out how to do this yourself. It is, no, I'm going to do the entire service for you. And what is it? What is the service? Service is moving your application into the cloud. So like rewriting it. Is that like a one time thing? Or are they like, you know, it's like, how do you price and package? Yeah, it's a great question. Like it's recurring. Because it sounds like a one time event. What's interesting, and this is surprised me a lot, is that once you get into some of these organizations, it's not just one application that is in the mainframe. You do it, you spend six months moving their core application, then you realize, oh, this other one was tied to it. And so now I'm doing this other one. I'm doing this other one. So so far, we have found that when you tap these big organizations, the work just continues because there's so much code that's been written over the years in this language. Now over time, there's all sorts of software that you can sell to support that. So observability tooling is really important. So you rewrite there, you are the author of their core software application. And you generally also write some sort of observability tool to understand, like how is it performing? What's the uptime, etc. That's a product you can sell as a recurring revenue basis thing. So anyway, to answer your question about how I got to an innovative software, I made this investment. And I started to realize that this concept of selling a service and not selling the software was more than just one company that this was the new business model. It emerged in history of the firm is we have aspired to be early experts in emerging business models. When mainframes when on-prem went to the cloud, the emerging business model that got created was SAS. We were the first experts to understand how to build those companies. I think we're in a similar moment right now, where AI is a trans, trans, you know, crazy, you know, groundbreaking technology shift. And there are emerging business models that are being enabled by this for the first time. And no one knows how to build them. Is it even a thing? And so what I and we have chosen to do is to say, AI native services is going to be the next big emerging business model. And we will be the emerging experts to understand and teach the industry how to build these companies. Because the way you build the software, the way you think about going to market, the way you hire for the team, the way you price, all these things look very different than software. Let's use like when I think of services, I'll start with it like consulting firms. Like, are you saying that there's a world where there's a new type of consulting firm? Yeah. But the consulting firms own the outcome. So it's not just like, I'm going to tell you how to do something. It's like, I'm going to do it for you. So it's, I think the more compelling way to think about it is accounting firms will become AI native accounting firms. Law firms become AI native law firms. Insurance brokerages become AI native insurance brokerages. Claims processing companies become insurance, AI native claims processors. Customs brokers become AI native. All there are trillions and trillions of dollars just in the US economy spent on these kind of professional services types of activities that are staffed entirely by people and not by technology. And the reality is there's an opportunity to create an entire new industry that is AI wrapped around by humans who provide the throat to choke and the expertise to deliver the service. Is the, I mean, historically, putting the, you know, prior iteration of this prior to the AI kind of world, they would have said, oh, services based businesses are not venture outcomes. Yeah, they saw. What is the, what is the counter to that right now? The biggest reason why services business was not venture back old before was margins was that by definition it grows linearly. The reason why tech has been such an attractive asset class for so many years is that it grows non-linearly with cost. So if you're building Facebook and, you know, you've got a bunch of users that started to use it and you get all the advertising dollars that come with it, your cost to support that is not scaling linearly with the advertising dollars. And so these businesses look really, really good. Historically, in services, it's been linear, right? You close a new deal, you need to hire three more people to deliver a con on that project. So yes, revenue goes up, but margins don't go up. So you have these lower gross margin businesses, 10%, 20%, 30% at the max. It is now possible if you have AI that performs a lot of the core services with the human layer on top to deliver these services at 50% and 60% gross margins. And what's interesting is that the addressable market for these companies is much larger than software ever was because they're not selling a tool. They're selling the outcome. When you look at this, there's a lot of ways to go about it. One is to say I could go build technology and deliver it to the services firm. I'm going to create some efficiency and means there's some unique business model. The other is I will become the thing. I know you have some investments that are like this that you can talk about. What are the different approaches to building it? When you say AI native services, the first is a ladder or is there something completely different? It's definitely not the first. The first is a software vendor. You're selling software to a service vendor. Well, maybe there's a business model where you're like, hey, I'll get a percent of the outcome and I'll service you and you're kind of like the distribution so arm of it. I think like healthcare, this kind of happening in healthcare historically. It's like, hey, there's all these builders that are out there that are trying to recover some money. And you could sell to them or you could become the builder. I think that there will be hybrid models. I work with a company called Prosper AI, which is in the healthcare building. It's really in the healthcare benefits verification and prior authorization space. Historically, this is a job that has been done either by BPO's or it's been done by the hospitals and clinics that call the insurance care and say, hey, it can Chumrod get his X-ray is not approved, whatever. It's incredibly human. It's crazy that I've been listening to this conversation. It's a number of humans that sit on a line and exchange information back and forth to say, yes, you can get the X-ray. AI obviously can do this in a way better. So this company started with an AI voice agent. Now it has a bunch of other agents that do this. And what's interesting is they started by selling to the BPO's because the BPO's needed this one. Imagine this also makes a distribution though, like, hey, I don't-- I mean, less the founder had like, you know, a bunch of relationships. So in his case, yes. And he got some of the largest BPO's to start, which gave him huge credibility in the whole industry and particularly with direct customers. So now he's got that business model. And then he also has a direct business model where he's selling into clinics that were too small or weren't working with BPO's yet. And he's just going direct and saying, hey, look, if I can do it for these guys, I can definitely do it for you. And he has this kind of partnership model with some BPO's where they jointly go to some customers and say, we're going to jointly market our offering to both of you. So to your point, there are going to be examples of this that are kind of hybrid-y. The thing to keep in mind is that an AI native service business is owning the outcome. And that is the core insight of the core nor star, I should say, about these businesses. So if you are a software vendor that is selling software to a service provider, but you are not also capable of owning the outcome that the service provider provides, you are not an AI native service business. You are a software company. If you're just selling a technology and saying, hey, you can use it. You can use to help you do accounting better. If you aren't capable of doing the accounting yourself, you are not an AI native services business. But the cool thing is there are not a bunch of companies that are doing the accounting themselves. I work with a company called Hanover Park, which is a fund administrator. Fund administration for the non-VC listeners out there. I definitely know a lot about fund admins. Every time I talk to someone who's an investor, that's their reaction. Everyone knows how painful this is. So for those folks who are not investors, fund administration is like a vertical accounting firm. It is a vertical accounting firm focused on private equity and venture capital funds. The way we do accounting is very bespoke. And there are some legacy services firms that do this. They are not well-loved. They don't have great margins, but they're very large businesses because it's a really big industry. Hanover Park decided to do this from the ground up. And they did something to start with that I thought was really bold. They built their own custom ERP just for this use case. So they built the core system of record themselves. But they chose not to sell that ERP to existing fund admins. That would be a software company. They said, I'm going to take this ERP I built, and I will become the fund admin. And I have the unique ability to deliver better fund administration because I literally built the core tool that I need the agents to come out of. Whereas even if you took an existing fund admin company and said, I'm going to make it all AI native, but if the core system they're working on is some legacy SaaS system, you have to figure out how to get your interest interact with. It's never going to be as good. So this company built the technology and then is doing the services on top of it. And so they're able to do it way faster. If you want to have all-- You believe that all services markets will have an AI native venture backable opportunity? Or do you feel like some-- Yeah. I mean, healthcare is so big. We can get the number of people. They will be a bunch of healthcare. They'll be a bunch of healthcare. But are all markets considered-- is there an opportunity from a venture perspective? Because I struggle with this. Yeah. Even in healthcare, if someone might say, oh, I'm going to be going after a specific sub specialty area. And it's like, is this sizeable enough to become an independent company? Or how do you think about that? Well, let's compare it to vertical SaaS. Because the argument would be the same. In vertical SaaS, was vertical SaaS ever big enough to build large companies? And the reality is, when we invested in Viva in the mid-20, was a 2008, 2009, the address market for a CRM in pharmaceuticals was $400 million. Like, if you read our investment memo, it was like, that's the market size. Right, well. So that was kind of a crazy bet. The thesis we had was that the market would expand over time. And that the founder, Peter, would find ways to sell more stuff into that market. And the current market gap is, but it's probably $35 to $40 billion. So obviously, the market size grew a lot and Peter figured out way to lay out the cake. So we've learned a lesson from vertical SaaS that if you are selling something that is very valuable to an industry that has a lot of money, and you're a great leader, you can find a way to expand it. But the difference between vertical SaaS and AI native services is that the dollar budget you're going after is much larger in AI native services because you're going after labor spend. Let's take Pharma, for example, if you were to build an AI native Pharma sales agency, there's way more money spent by the sales reps going out there trying to sell these drugs and there is on the technology to underpinning that. And I don't know if it's even possible to build an AI native Pharma sales rep thing. I mean, that's not possible. But the size of the budget is actually much larger for labor. So I'm actually even more bullish that there can be venture backable niche outcomes in ains, a native services, and I am in vertical SaaS. What do you think about-- so I meet founders that are pitching this in two different ways. One is building independent brands. I want to acquire customers in the case of the example of going direct and so forth. Others say, hey, I want to go and acquire-- I want to go do this PE. What do you think about these different strategies? Is there natural opportunities to lean towards one or the other? Do you have a perspective of what other one is better than the other? I do. In fact, that's why we named it AI native services. To be because we're trying to distinguish it from raw ups, AI raw ups. Native-- the work the word native there is doing is that the company was started in the AI era to be an AI native services vendor, not an AI. Well, you can still start a native services company, but the way you go about it is to acquire-- I don't think that's a native service company because you're acquiring a legacy services business. That's why-- But you can kind of like-- So this is the point. The you know thing that everyone's saying, there's a lot of work being done by the you know thing. If you buy a five services business that's been around since 1985, and you try to slam them together, and you have all these legacy people that were definitely on AI native people, and you say, OK, now everyone use AI. Do the thing but do with AI. I think it's really going to work. Well, OK, just to play-- I mean, that I've done this before. But like the what has been positioned is a lot of these folks have existing client bases. They're x-shirts in their workflow. We can kind of study the workflow. Then we're going to build the software around that workflow. And then we'll sort of like kind of figure out what's our true native capacity there. We will downsize. And that's how we'll do it again. Yeah. So it is definitely true that there is an advantage from a go-to-market perspective by buying an existing book of business. That's obviously true. And there may be an advantage on the data side, although I think that's overblown. Because I think people assume that these legacy services businesses have lots of data, and it's structured in a way that you can make use of by building an AI tool. And the reality is most of them probably don't. So I think that that is probably-- there might be something there, but I think in many cases, it's overblown. The go-to-market motion or having buying customers-- I think there's some value in it, but I would argue that should be step two, not step one. Step one is build an AI product. Find a way to-- without any legacy, gorpi, stuff that you have to keep managing, find a way to build it truly from the ground up, build your ERP for fund administration, whatever the service you choose, get some customers organically. And the reality is, I've seen this now firsthand. If you are selling an existing service and you're selling it either faster, better, and or cheaper, demand is not the constraint. To use the handover park example, he has so much demand that in Q4, he stopped selling completely. He said, I'm not going to take a single new customer because the challenge in this business is actually delivering and deploying. And I just had a call with him an hour ago, and he's threatening to do the same in Q2. The challenge of these businesses isn't actually-- people think it's good to market. I think for the right CEOs and you choose the right market, if you know there's existing pull because there's a massive services in Q4. So it's not a question of if I build this, what people like it. It's like, if I am selling something either faster, better, cheaper than my competitors, people are going to buy your thing. The challenge, the biggest challenge in AI native services business is being an AI native service. The biggest risk in these businesses is being a service, right? The biggest risk, and this is why I think buying, you know, doing the roll up thing from day one is really risky because by definition, you are starting as a service and you're hoping to over time migrate to becoming AI native. I think it's much higher likelihood for success. If you start with an AI tool and you figure out a way to build that to be something that can deliver a lot of the value with AI, and over time, as you do more work, and you build the systems in a way that there's a closed loop, more and more of that work will be done by AI. And then you can figure out ways to scale, go to market from there. I think organic is working really well in a lot of the businesses I work with. I'm seeing these partnerships model work really well. There's this really interesting frenemy dynamic for a lot of these businesses where like these existing, the legacy service providers are like, should I need some help? And so they're willing to do these pretty favorable deals with these AI native service providers to say, we'll go to market jointly and we'll split the revenue 50, 50, and whatever. And then you get a lot of this go to market benefit without the headache of the acquisition stuff. Now this isn't to say that over time, there's not a role for, okay, I've gotten to some meaningful scale where I've solidified my culture, I've solidified my product. Now I can do a tuck-in acquisition to get exposure to the Northeast marketer, to the Canadian market, or whatever. That I think makes sense. I think what I don't fully understand is the idea of trying to do that to NOVO. I'm always curious about, is this sort of tension between outsourcing a service to a services firm that might have a better business model to serve the client versus saying, some of that value is gonna go back in-house. There's a lot of examples of this accounting, you can say, oh well, people have worked with accounting firms at the mid market, well, if all of a sudden you are half these capabilities, why can't you just, not work with the services firm and just-- - Do you own accounting? - And do you own accounting, right, using the same AI, and maybe there's a company that's selling directly to the client. How do you determine like whether there is a real market shift towards, there are all services based businesses to survive in the next 10 years? - It's a great question. I think that the businesses that are most likely to survive in the services realm are those that have really high trust need. So if you are performing a service that has some regulatory oversight, certainly again, any sort of legal oversight, if there's some sort of like sensitive healthcare angle to it. Anything where it's like, if you mess this up, it's really, really bad. It's probably something that you're gonna want to throw out to choke. You're gonna want a third party who's an expert who stays on top of the technology and is willing to take on that, as I said, that kind of insurance-like responsibility. On the flip side, if it's a service that maybe everyone doesn't die if it fails kind of thing, it may be the case that you just build your own AI to do it. I think about marketing agencies, for example. And there will probably be some marketing agencies that survive and thrive in the new era, but I think a lot of people are realizing, oh, actually, I don't need to outsource that anymore. I can just use Clarence. - Are you saying like, you know, publicists, which is like, you know, tens of billions of dollars and on the common, you know, WPP, these are like massive agencies. Do you think some of those, some of those, there's gonna be a shift of rather than paying an agency to like bring it in house? I think the role, and I'm not an expert in this space, but I think a lot of the role those folks play is like ads. There's like a network element to it, so I think they'll probably survive because there's still this kind of like, I'm in the middle of the ad flow thing. I'm thinking more like the web design agencies. Like if you're a web design agency and like you made a lot of money that way, like you should use Boll to use one of these companies and just do it for you. - Well, let's talk about a category that I know you have deeper familiar with, like law. - Legal. - Right. You know, I've been wondering about this because there's one model which is like the ultimate value, who has the budget comes from the client, the general counsel legal teams that are paying the outsourced legal firms. You know, there's a bunch of them. And I'm like, well, isn't most of those dollars gonna be wanting to come back in house and just saying, hey, we'd have a smaller team? Like, I kind of wonder whether law firms in general, you know, and there's a lot of them which should even exist. - Yeah, sure. - And yet there are AI native legal firms that are getting created. There's more and more. - Yeah. - I don't think it's an either or thing. I think it is true that GCs will look to realize, like, oh, I can do more of the stuff I used to outsource myself internally with tools. And I think that there's still a role for the external law firm back to the same point I mean before which is like, partly as you hire law firm is a C-O-I-A tool. It's like, I had someone who was, you know, past the bar, say this is Blastin's kosher and so we can do it. So I think there's still gonna be a role for those folks, but I'm on the board at Ironclad. We sell to general councils and we had a record you for an outperformed last year. So like the business is doing well, I think in part because like GCs are realizing I'm gonna, I think tech spend by GCs is gonna continue to increase. - Yeah, I mean, I have not made a lot of investments in legal because I don't know where the puck's gonna go. But I do think there are categories like accounting and healthcare. I think it's hard right now for VCs to like figure out what makes this team kind of unique because they all kind of like, how do you determine, there's all five companies coming to you and they all kind of say, I'm gonna create a new AI native XYZ services business. How do you distinguish between is this the one? Because they're all saying the same thing. - I think that it all sound great. - In an AI native service business, I would argue that having some domain expertise in the team is even more important than a software company. 'Cause in a software company, you're selling a product. In Ains business, you're selling yourself. You are a service. You are saying I'm going to do this for you. You're not selling them some tool. And so you, whoever the you is, you yourself the founder or you the team that you're representing, becomes incredibly important. And so one easy way to do it is say like, do you have DNA that's relevant to the service? And that's relevant both in terms of like figuring out how to build a product, although sometimes having too much like a CDNIC and actually, you know, hinder you from building the new innovative product. But it's more important from a go-to-market perspective because your customer is gonna wanna say, is you wanna see like, oh, yes, this is a startup, but like they have this woman who like, ran fund admin for this thing for a long time. So like I trust them because like I know her, I know her brand or where she came from, et cetera. So some of the best AI native services founders come from the space. I mean Rob is a great example. Like Rob is like the king of the nerds in terms of engineer hiring. Like he was a pretty logical person to start this business. But in the case of Chris who runs Handover Park, he was not a fund admin. But what he did, I mean, he went, I was skeptical when I first met him 'cause I was like, how do you know about this space, which is so bespoke and random. And he was like, I've had 115 conversations with CFOs, Adventure Firms and Private Equity Firms, ask me any question you possibly could about the way Fundatme gets done. And he just like became the savant in it. And then he hired a bunch of people from legacy firms that all have recognizable brands. And so when he went to customers, he was like, look, it's AI. But I have these people who you know and trust are the human wrapper on top of it. So I think to answer your question in one way, like understand what the team's DNA is. And I think that you can't just be like some hot shut kid at a Stanford without domain expertise to sell the service because ultimately the buyer doesn't care how smart you are, the buyer cares like, do you have relevance and why trust you? And so imagine there's a listener out there that's building an AI native services firm business. What does traction look like? They raise a pre-seed round and they want to prove a story to the world. What do they have to show to you as an example to be like, they got the right team and now they're executing? - So it's totally different in software. In software, if you raise a seat or pre-seed and you go out and raise a series A, what the series A investors looking for is are you growing quickly? Like is there an incredible poll for what you're selling? And do you have good customer attention? Now you could argue that like in the past few years, the series A investor hasn't been able to ascertain the second because founders are raising so quickly so you don't know if they're gonna be customers or renew. But let's just assume a world where customers are renewing. Generally speaking, in SaaS, that's product market fit. If you're growing quickly, your customers are renewing, like that's a good project for me. - It's just an EMI. - It's even better. - Exactly. That is not the case in Aynes. In AI native services, I think one of the biggest risk is something I'm calling mirage product market fit. And that's a world where you are growing quickly and your customers are renewing. You've got good NDR, but you don't actually have product market fit because the service you're providing is not being done by AI. It is being done by people. And in that case, you are just a worse services business. It's taken a worse financing model. And so I think that's the head fake that's happening or will happen. I still think this AI native services thing is still quite nascent. Well, maybe it seems sort of buzzy because I and some others have been talking about it more recently. It is still definitely the minority of companies that are being started this way. This is still weird. At the very, very early stages, we're still trying to figure this stuff out. I wrote this thing called the Aynet of Services Playbook in part to kind of track the way this is growing over time and be a resource for founders. So I'm still obviously learning myself. But I think that there's this mirage product market fit thing. I think people are going to go try to raise and they're going to show good growth numbers. And when you double click and see how much of the service is actually being provided by the AI versus by the humans, you're going to see that it's still majority human. But are we, I mean, is there a metric that you're looking for there because in some ways, I'm like, there's AI everywhere. But is it really meaningful? Yes. So say, hey, we're actually moving costs or improving top line. And it takes time to show this. I mean, I'd sell founders, they got to show it. And I'm like, well, hum, I mean, that's not easy to go do. For sure. So a bunch of thoughts. So let's start with metrics. And then I'll talk about strategies to actually achieve it. So on metrics, there are input metrics and there are output metrics to understand if an Aynet of Services Business is working. Input metrics, the most important thing you need to do as an Aynet of Services CEO is figure out what's your product north star is. How do you know that the product you have built, the AI platform you have built, is delivering real value and the values compounding over time? And the reality is that metric is going to look different based upon the business that you're actually, the service that you're actually providing. There's no universalizable metric for that. In the case of Ryan at Crosby, which is an Aynet of Legal firm, he tracks this thing called Hurt or Human Review Time. And it's, you know, how long does it take for a human to review one of their contracts? And then he pairs it with some quality metric to make sure that it's above a certain bar. And over time, like if Hurt is going down, then theoretically, you know, that should be a good input metric. But every one of these Aynet of Services businesses needs to figure out like what is the north star product metric that is the most important thing for me to track? So that's the input. And the output to know if it's working, there's kind of intermediate outputs and there's like one most important output. So the intermediate output are things like revenue per employee, like how efficient are you as a business, which is something that becomes really important to the services business. So revenue per employee and a legacy services business is by definition going to look much worse than revenue per employee in an Aynet of Services business. It may be the case that as you start out, your metrics don't look that good there because you still have a lot of people as the AI is getting smarter, et cetera. But as you start to go through your growth curve, you should see leverage there. So that's something that you and the VC should be tracking. And then of course, the most important output metric is growth margin. So are you at a 20% growth margin? Are you just 60% growth margin? It's a completely different story there. I do think that there's a lot of fudging going on in the growth margin calculation right now. And I don't think it's necessarily ill-intended. I think it's just that founders don't know. We're still learning. You're still brand new in this. But if you're cocked and clogs as an Aynet of Service, you need to include the human labor required to do in the service. That's obvious. But some people are putting an R&D and I'm like, no, no. I know, not this, not this. This needs to be there. that's COGS. Obviously, you know, the to spend the, figure out how to allocate token spend. >> Right, yeah. >> And this gets a little tricky because like some of the token spend is R&D. Like if you're actually developing the core platform, but some of the token spend where you're actually using the platform to deliver the service, that's gotta be COGS. And so if you have an honest look on what is COGS and it's approaching 50, 60%, then like you probably have a pretty good I need a services business and I would like to talk to you. >> The thing that I wonder though is like folks that are raising kind of rounds today. Like there's this like, I'll raise a pre-C and I'll raise like a million or two. It feels like it'll take a long time to prove what you're just describing. >> Yeah, maybe and maybe in like, I mean especially the gross margin thing, like let's put that out because like that's, that's you know, you can calculate and it just looks really bad in the beginning. Like, so here's my preference, which is a, I think an unpopular thing to say as a VC. I would rather see a business and Ayn's business I invest in grow more slowly. But really perfect the AI product such that those leading and lagging indicators are showing up into the right, then grow super quickly and figure out the AI later. I think the gross super quickly and figure out the AI later thing is a, we had some of these issues in previous tech cycles where it's like I'm gonna sell a dollar $0.50 and it's gonna work. Like I just like, I would much, I believe because I've now seen it in a bunch of the business I'm involved with that like an AI service business should not struggle for go to market. Like ultimately if you're selling something that has existing demand and you're selling it. - Well this is an existing where people are already buying these services. - Exactly, and that's the thing people don't understand. In tech, like in software, you invent some new thing to solve some new problem. You still don't know if like people actually want to buy this and so you've got all these things you got to prove on a product market fit. If you're selling accounting, everyone needs it, everyone's gonna buy it. If you can go to me and say, I'll do your accounting, it'll be more accurate, it'll be cheaper, it'll be faster. And you can show me evidence that the six other people that look like me that you served it happened for, of course I'm gonna buy you. So a great AINNative Services business, the issue isn't gonna market. As I said, Chris at Hanover said to me a couple hours ago, he's gonna pause sales again. The issue is making sure the AI is good enough to deliver the service in a high quality way. - Do you think this is universally true? Because I feel like once you're on the show, I've gotten two quarters to a million. I gotta keep on showing the thing. - I've had Frank a Frank conversation with one of the more high profile founders in this space about this very issue. Because once you get on the venture drug and your venture investors are saying, you gotta keep growing, you gotta keep growing, you're gonna feel the pressure to do it. My hope, I mean, A, if you're working with me, I'm not gonna do that. - That's right, that's refreshing. - B, my hope is that we're still in the early learning phases of this business model and VCs aren't stupid. So if they do this with three companies and they see that they all blow up or they all get to a place where they have terminal values and aren't that attracted because they're traded on low ebit DOM multiples because it's low gross margin, they're gonna learn the lesson and say, okay, I'm actually gonna do it the A, I need a version. Next time, I'm not gonna try to force the growth and move over the A, I need a thing. It's gonna take some time. This is why we're still on this like, you know, foggy era for this business model. But I think those of us who are like real experts in or who are dedicating ourselves to become experts understand this and we'll work with founders to help them understand as well. - The thing that I, you know, the humanity aspect and all of this is like, we're really investing in like, kind of this destruction of human labor across, literally, you know, dozens of industries have not hundreds. Like, this is millions of people that are like, you know, going, you know, day in and day out doing something that can be done through AI. Accounting is probably the one that is seeing a lot of disruption here. Healthcare obviously, you know, you mentioned the phone call picking the phone call, doing very basic things. There are millions of people working on this. Like, what is our responsibility in this like day and age? I know this is something that I know you think about it. Like, and I'm a little bit like nervous about it. Even though as a venture person thinks about, you know, financial like where is there opportunities of value creation, I'm excited about it. - This is the most important thing facing humanity. Like, I feel so passionate about figuring out a way to help society make this transition in a way that isn't horrible. And I do not think that we as an industry are paying enough attention to it. Dario who has tried it has been, you know, talking about this as have others. But I think most of us are kind of going along with, you know, we have the economic incentive to like to do this. And I think we should, we need to continue to follow this economic incentive because that is the way this model works. We have to help figure out ways to make society shift in a way that is more, you know, there's going to survive in this era. I'm spending, I don't have any answers to this, but I'm going to spend my time on it. So next weekend, I'm going to spend four days at a summit focused on this with other leaders in tech and finance and business. We're all going to New Mexico and the ideas, like we're just going to try, we're breaking into small groups and we're going to come up with like ideas to solve, how do you retrain, how do you, like, we're going to try to come up with some ideas and then see what we can do in the real world with them. I have no idea if this is going to work, right? It's probably not. But I think all of us have a responsibility to be investing our time and money in helping society make this shift. - I mean, you know, it's, have we seen evidence of this quite yet though? Because in some ways, you know, if you look at any sort of technology shift, you know, over the last, you know, century, there's always been this fear of like, someone gave an example of like, you know, NASCAR and how like the first time they built new technology for the NASCAR, there were like two people kind of in the, you know, in the pit working on the car. And now there's like 15 people. It's like clearly the technology co-almost created more jobs is are we like, how much of this is just, you know, fodder versus actually being real? - I think that it's back to my outcomes framing, which is I think in this world, the technology that we are building can do so much more of the outcome. And to use the NASCAR example, like, that it's not applicable there, right? And I was trying to come up with some of the questions here. - Yeah, yeah, no, I mean, like, like you could think about like the, the industrial revolution, which might be the best, you know, analogy here. And like, I think it's not well reported enough, but like there was this concept, and there was a group of people called the Luddites. This is where the term Luddite comes from, that there was a big bloody revolution where people were really upset with the rise of these, you know, industrialization things because people were at work. Now the reality is, the industrialization only did a little bit more of the outcome than what happened before. And so there was still a lot of jobs happening in the factory. I think what I fear in this world is that the AI is gonna do a lot more of the outcome, which is gonna mean that the need to do work goes down. Now there are, you know, there's all sorts of positive utopic implications of this, I'm a musician. And so like one of the things I think a lot about is like, what could this unlock if I or we all had time to create more and do things that feel more human? Like are there lots of like positive things for our kids and everything else? But I think like there's going to be a really rocky transition that we got to figure out. And sometimes I feel like when I'm talking to people that aren't so AI-pilled, that I'm a crazy man from the future, who's like, guys, a big thing is coming. And like no one, we're not taking this seriously enough. But it's starting to happen. Like I just got a text from one of my college friends who was not in tech today and the text was, he forwarded the mythos announcement from Claude. And he was like, I think working feels stupid now. So like I do think like it's starting to realize like the implications of all of this is becoming quite real. I'm kind of curious whether the-- obviously we think about the business model. We think about the economic leverage that can be created through AI and so forth. But when I think about my friends that are doctors in middle America, I don't know if they're thinking that way. I mean, maybe they are. And there's real pressure to be like, all right, we can automate our front office person. I think they actually care about-- I don't know. I do believe there's real technology shift and it's going to happen. I just don't know if it's going to happen as fast as we think it is. Yeah. I think that's the positive spin because the reality is if this happens more slowly, it's better in many ways. Because the society can adjust more quickly or adjust more effectively if it takes less time. But that company prosper I mentioned is selling to a lot of Midwest doctors. And if there was someone in the office whose job was just to call insurance cares all day long, and now you can do it to attempt the cost and higher accuracy, you're probably going to make that shift. Because doctors are very rational people. Let's take self-driving, for example. We always thought this was going to take forever. And there's so much more to spend on it. And now I got here in a Waymo. I'll leave here in a Waymo. My five year old was in the Waymo with me the other day. And completely non-plus by the fact that there's no driver. And here's the even crazier thing. At the end of the Waymo ride, it says, don't forget your keys and wallet. And she turns to me and goes, what are keys and wallet? She doesn't even know what those things are. And Waymo was going to roll out across the country but imminently, I invested in a company that's spun out that is from a Waymo founder, our Waymo executive called Bedrochrobatics, which is attempting to do Waymo for construction. So self-driving excavators and self-driving dump trucks and such, which would increase the speed of which we're able to build our country way faster because you could build it night, you could build more safely, et cetera. But also has huge implications on employment. And so I think that the people that are funding the stuff, the people that are building the stuff, have a responsibility to figure out how do we help mitigate the impacts of what we're doing. >> For listeners that are out there that want to be part of this conversation, what is the starting point of this? Whether you're a founder that are like, I'm just going to go and disrupt, you know, that's what we talked about all day, or VCs that are listening. Well, if you're a founder, like the best way to think about this is like, what business can I start to help address the change? Like if you think about it actually, like, an example, it seems very likely that white collar work will be disrupted before blue collar work. If that's the case, there's going to be some period of time where the demand for figuring out how to become trained in blue collar trades is going to be a lot higher. It's a lot of people who used to know how to code, who want to figure out how to be a plumber, which sounds kind of ridiculous, but actually probably not. In fact, I read an article on the FT last week that applications for plumbing schools in the UK are through the roof. So one business I think would be interesting to build and perhaps even fund would be, what does an AI native trade school look like? I don't know. I don't know if there's possible to build an interesting business that would be VC back able. But if you're a founder to answer your question, the best way to address this massive disruption is to start a business to figure out how to help people make the change. Yeah, another version of that is fine markets that have labor shortage to begin with. Yeah. Because there's probably opportunities to create more jobs. And construction actually is that. There are just not enough people to operate these excavators today. And so for some period of time, actually, this will benefit the industry, but over time, obviously, there are going to be people who need two fine new jobs. I'm really grateful for you to take the time and kind of talk through all this. I know that we're very early in this AI native services, but I know that you've been at the forefront of this going deep, deep into it. I appreciate the value around the playbooks and all the services. I know I definitely share it to all my founders that are working on this on this space. We can kind of close this out with some sort of rapid fire questions that I do. Deep tech, you mentioned you did bedrock robotics and AI native services. What do you think produces better venture outcomes over the next decade? I think that AI native services will be a better, like, adjusted, expected value situation. I think there's just going to be these businesses will be more likely to succeed by definition because they're less binary. Deep tech is generally pretty binary as a tech work or not. There's obviously going to market risk there as well. My read is that deep tech will have bigger outliers, but Ains is a category will be larger. Most overrated AI investment theme right now. I think if you are selling an AI co-pilot to a knowledge worker, it's going to be a tough ride for the next few years. What's an example of this? Well, like, if you are. Because like, ITSM is getting a lot of. ITSM is interesting. I mean, like, one thing actually on that topic, like, one thing I would be interested in funding would be, I'm interested in this, like, in the concept of an AI native MSP, which is in some ways doing some of the tasks of an ITSM for small organizations. There have been a few attempts at this some roll-ups, but I haven't seen enough yet. I'd be curious to fund. But as an example, like, if you are a tool that helps a marketer draft better copy, that feels like something that's going to be pressured over the coming years. What do you think is the most underrated? Obviously, the AI native services. Yeah, I know. That was a layoff. That was a layoff right there for you. It is a pre-LLM SaaS company that you think survives and thrives, and you can't mention Finn and Intercom because we are talking about without naming a portfolio company. Yeah. I mean, one I mentioned before, it's not a portfolio company, but I think I would be super long if I had the ability to invest in it directly, it would be LinkedIn. I just, I really believe in that network. I mean, maybe it's also. I've ramped up my communication on LinkedIn over the past couple years and have found it actually surprisingly valuable. Like, some of the people I've met, some of the insights I've gleaned, some of the intros that have been made have been really helpful. So, I'm wondering. And they've done a lot of AI stuff? No, but that's actually the point. That's actually like what's interesting. That's crazy. I don't know if they need to because they have this trust network. You already answered this, but I'm going to ask you again. One metric every AINZ founder should tattoo on their arm. There are three. The first is, what is your North Star product metric that indicates that your product is getting better with AI? The second is revenue per employee and the third is gross margin. True gross margin. And if you had to pick a vertical that produces the first $100 billion. Yeah, I need a services company. What would you pick? It's got to be a regulated vertical because I think those are going to have like so much pull and value. We have already made three investments in insurance for AI native services in different parts of the stack. And so I'm hoping it's going to be an insurance. Which one are the three verticals? So one is a BPO. One is a claims processing company and one is an insurance broker. Okay. Alright, so different aspects of the stack. So your insurance. Insurance would be my answer. Given patterns. Given what I'm looking at. Who do you think wins the Foundation Mall race? I don't know. I think obviously Anthropic is the darling at the moment and it's possible that they're now so far ahead that they'll stay ahead. Or is there even a race in the sense? I mean, you look at AWS, Google Cloud. Yeah. And the way I bet on this is that the most underrated player in the Foundation Model Ecosystem is just open source. Like I think that the open eyes and tropics, Google's of the world will continue to lean in and be a few months ahead. But I think over time we're going to realize that the vast, vast majority of use cases for AI doesn't need the model that's three months ahead. You can use the model that's three months behind. That's 80% cheaper. And so as a result, we are super long on the open source model ecosystem. We did the Series A at Together AI, which is indexed on that ecosystem and that company is now, I don't think I'm allowed to say, but it has got a retain revenue growth. My wife is a president of base 10, which is also very indexed to the rise of open source and I've also seen how fast they've grown. So I think my answer is not exactly one of those companies. It's actually the open source ecosystem. Makes sense. Just for my education, is there a book or an essay that really shapes how you thought about the aims kind of strategy? So the most obvious book is the innovator's dilemma like that because that is basically what is happening to all these both actually SaaS businesses as well as as well as legacy service providers. The other book that I just finished and I want to get the title right is called To Rescue the American Spirit by Brett Byer. And it is a book that came out recently that is a biography of Theodore Roosevelt, which is so fun because that guy is crazy and awesome. He obviously famously coined the concept of man in the arena. And the parallel I was thinking about, which was certainly not what Brett intended when he wrote this book, is that if you go from being a software vendor to an AI native service provider, you go from arming the man in the arena to being the man in the arena. You're actually delivering the outcome. And so in some ways, it's actually it's probably a harder business to pull off because you have to both build product and do services and client service and everything else. But tell you Roosevelt, like leaned into the heart. Love it. Last one, five years from now, what do you think you got most wrong about Ains today? I think what I will most have gotten wrong is a loose to the question you asked before, which is I think that there will be some services that exist today in our big industries that go away over time because the AI can just do all of it. Right, AI native services is a presupposed on the idea that there is a vendor that you want to have that delivers you the service. There will probably be some services where you don't need a vendor anymore and you can just have the AI do it directly. But believe that for the foreseeable future, there will be a number of industries where having a throat to choke, particularly in a regulated industry, having a third party validate something they're still going to evaluate that. But there will certainly be some services that we think about today that become in-house. Well, hey, Jake, I really appreciate you taking the time. This was a really fun conversation. We should probably do this in like six, nine months again. It's going to be totally different. Let's go like rehash what we just talked about and see if anything has changed. So I appreciate you, Jake, pre-dollar advice and listeners out there for folks that don't know emergence, what would you like to say? We aspire to be the early experts in emerging business models, business models like AI native services, physical AI with things like physical intelligence and bedrock, AI infrastructure like together AI, agentex software. But in general, we just want to be early in helping people figure out how to build these businesses in this foggy era. I guess I would end by saying I feel more personally and intellectually energized in this era than I have in my 12 years of investing because this isn't a function of like copy and pace. This is like we're all figuring it off from scratch. It's super exciting. Well, absolutely love it. Thanks, Jake. Appreciate your time. That's your matter. Hey, this is Ben Casinoca, co-founder of Village Global. Thanks so much for tuning into the Village Global Podcast where we go deep on all of the biggest topics in tech. If you enjoyed this conversation, please subscribe to our YouTube channel. You can check us out on Spotify, Apple, wherever you get your podcasts. We'd love to see you for the next one.