The Advantage of Scale with Robert F. Smith, Founder & CEO of Vista Equity Partners

Episode Transcript

SARAH ELK: Robert Smith is the founder of Vista Equity Partners, a global investment firm that focuses on enterprise software and tech-enabled companies.

ANDREW NG: And through his vantage point, he uniquely has a view on what many businesses are doing on AI. And so I'm really looking forward to learning and hearing about this broad view and what lessons apply to all of our businesses. Thank you, Robert, for joining us.

SARAH ELK: I'm Sarah Elk with Andrew Ng, and this is Winning with AI.

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SARAH ELK: Welcome, Robert. Thank you so much for spending time with us today.

ROBERT SMITH: My pleasure. Thanks for inviting me. Good to see you both.

SARAH ELK: I would love to start with just a very open question. When did your AI journey begin?

ROBERT SMITH: Interesting. So our AI journey actually began over a dozen years ago in terms of how we were utilizing it for certain of our businesses to do things—like in our sports business, for instance. How do we now take and strip what I'll call data and information effectively from what happens actually on a field to putting it into a data set can then be repurposed for customer sets?

And that evolved quite naturally as we started to have the introduction of, call it the transformer papers, which has then led to asking, okay, how does this now lead to a generative AI environment? And we were fortunate that we had relationships, of course, with some of the large hyperscalers and Sam and with Dario that gave us access to platforms to test and train. I think they realized that because of the breadth of our portfolio, we provided an interesting set of use cases for this technology. And that's really where things started to evolve over the last almost, I guess a little over three years.

SARAH ELK: Amazing.

ANDREW NG: One of the things I was fascinated by was the agentic AI factory. I think I'm the guy that coined the term agentic, and when I came for the term, I was expecting it to take off like that. But when I hear about luminaries, like you talk about the agentic AI factory, sometimes I wonder did I overdo it? But it's clearly been very beneficial and successful for Vista. We would love to hear more about your experience rolling that out.

ROBERT SMITH: Yeah, thank you again, Andrew, for coining the term because it gave us something to coalesce around. As you know, when you're leading through transformation, you need things to coalesce around to bring ideas forth in ways that can progress the intent. For us, one of the things we did well over a decade ago was, there's an introduction of this hosted environment for software. In the early days we were [went from] client server to on-prem, and then prem to this thing called hosted, which ultimately became the cloud.

And over 12 years ago, I had a relationship with a young man that nobody knew much about by the name of Andy Jassy. And he was building out some capacity to support one of the large businesses that enabled him to really build out a compute infrastructure. And I said, “Hey, one of the things we want to do is migrate our businesses from on-prem to cloud.”

And we had all sorts of people calling us, “Hey, we'll build this for you and build compute.” But he had compute. And I said, “Well, listen, I want to build a factory that converts on-prem software companies to cloud, but I need compute.” And so we struck a deal way back when that we could now drive our companies into their cloud infrastructure.

Of course, now we have Microsoft with Azure and others to support that. But the whole concept again of a factory to actually take these enterprise software companies and convert them into a different form factor. In that case, being hosted or cloud was something that we pioneered well over a dozen years ago. So now you have an introduction of a new technology. This whole generative AI technology.

And so we said, “Well, listen, let's use the same methodology. Let's build a factory.” And so we started contacting some of our partners in relationships about how to do it. And Satya actually called and said, “Hey, listen, I hear you're building this factory. We'd like to provide the foundry tools for your factory. We'll be the foundry to your factory.” And I said, “Sounds like a good idea. Let's see if this works.” And so we of course sent teams up to Seattle, and part of it was with a couple of our companies. I think you and I chatted a little bit about kind of our customer success business. Because we thought that was kind of the most factory ready.

And then some other people who could actually help us architect what a factory should look like for the rest of the portfolio company. So that's the narrative. Again, history, as I say, doesn't repeat itself, but it rhymes. And so what we're looking to do is rhyme that same capacity and now with 92 software companies to date.

We have over 30 that have gone through our agentic factory, and that's basically enabling these enterprise workflows to embrace agentic technologies, i.e., agents who are actually working and navigating through these workflows to access very specific content in context and managing dynamic data repositories to deliver, ultimately, in many of these cases, deterministic outcomes using some of the probabilistic inputs that come from utilizing this technology. So that's really the journey that we've been on. It's the second factory we've built, and now it's continuing to go through a moment of scale.

ANDREW NG: I'm glad you mentioned Andy Jassy. I think as respected as he is, not everyone still remembers how he changed the face of computing. But you were there in the early days. It sounds like you know what he did.

ROBERT SMITH: He is a brilliant pioneer. He gets nowhere near the credit he should, but he will actually go down as one of the great leaders and luminaries in our industry. And people, hopefully, will take some of his lessons of leadership and apply them to their businesses.

ANDREW NG: Yeah. Very well said. Of the agentic factory you mentioned just now, the customer success agent—that was actually one of my favorite examples of a sophisticated agentic AI workflow because a lot of people talk about cost savings. There's something that people used to do. Let's automate it, get cost savings, that's fine. That's okay. But I think one of the reasons I thought what you built for the success agent was remarkable was because it allows you to not just take costs out but serve a lot more customers and therefore drive business growth. Did I get that right? I'd love to hear more about that.

ROBERT SMITH: Yeah, sure. I mean, so if you think about knowledge workers generally and customer success agents specifically, they often have a wide number of tasks that they have to execute on behalf of a specific customer. And some have a number of customers in the same set of tasks for those customers.

And in some cases, you need access and understanding into various parts of the relationship. It might be what trouble tickets are outstanding,on the one hand, or what deployment might be in certain divisions or departments or across different institutions. And so an individual who is managing large customers often has to have access to multiple databases and multiple workflows to actually provide a comprehensive view, or in some cases a very narrow perspective on what is actually happening to make a customer relationship successful. And so the agentic deployment for us means, okay, what are the tasks that they are involved in every day? And can you take those tasks and create agents that perform those tasks either more efficiently or more effectively?

And so then you have a series of agents that are now performing groups of tasks and then you can orchestrate them. And in the enterprise, importantly, often you have to also record what they do so that you can actually go back and evaluate either what went right or what went wrong. In some cases you need it for compliance or regulatory requirements.

And so now you have to build out a whole different set of, I call them administrative agents. So you have task agents, orchestration agents, administrative agents, and then some of the administrative agents actually have to provide telemetry, right? Report back what happened, record the utilization of tokens in that environment. How efficient was it? Is there a better way to do it going forward? So that is, again, I call it a complex workflow. We have now 90 companies going through again, and 30 of them have already progressed through the factory. Come up with kind of four archetypes that do this sort of work.

The one I just explained—they call it the smart sidekick—actually is able to evaluate various workflows, and then bring them forward to aid the worker in being more effective in delivering what it is that the customer's expecting and hopefully delighting that customer with that work.

A couple other architects, we call it kind of the “always-on,” right? So these are agents that are constantly monitoring broad-scale implementations. Some are orchestration agents. We can call those the conductors.

Like managing a process that might be occurring in a financial institution where there's some regularity, the way things are done. And in the course, things that are, I call them a workhorse, which is saying managing broad deployment. You think about in government, how do you deal with a government entity that has to deal with everything from potholes to DMV, right?

So there's different things, and they may not be that deep on the one hand, but they're broad, and can be called upon by, in some cases, millions of people at the same time or whatever it might be. So, coming through our factory, we've determined that there are certain agentic archetypes that require different forms of either configuration or delivery of systems, and some require a shorter latency than others. So that's part of what I call the outputs that come from having a factory approach across a broad number of companies.

SARAH ELK: Robert, with the agentic factory approach, I'm curious with the world changing as fast as it is—and you mentioned complex workflows, more agent orchestration—how has your factory approach changed over time? With 30 companies coming in and go, having gone through it, I imagine the capabilities in the factory, how you're approaching that has changed as well.

ROBERT SMITH: Yeah. It will, It has to evolve. Our teams, our company, our philosophy—especially in if you invest in technology, if you're not building the design point around evolution, you've got a problem, right? Because our technology changes constantly.

And so we have to have organizational design that constantly evolves, and it's important because as later and later tools—in this case, LLMs and models—are delivered, they have enhanced capabilities. So things you had to do in the past you can potentially do less of in the future, right?

So now you have to evolve the way that you’re writing and the way that your agents are doing discovery and evaluation of the environment so that you can become more efficient.

So it's part of the process of innovation. And the good news is because we have 90 companies across 70 different industries, we can do a series of designed experiments that we can say, oh, well this is effective to this environment, so it should apply to these others and gain some economies of scope that way.

SARAH ELK: That's great.

ANDREW NG: Most CEOs run only one company and don't have the luxury of running 80-plus things the way that you do and being able to spot patterns across so many different businesses. What patterns do you see in terms of what works and what doesn't work in terms of AI adoption? And what lessons would you share with business executives that run only one company at a time?

ROBERT SMITH: The thing that I tell my teams all the time is you have to take advantage of the resources that you have. One resource we have are 90 companies, so let's take advantage of that, which means try various combinations and permutations that yield outcomes.

So like all these things in innovative environments, you want to fail fast, and then adopt quickly, right? And adapt quickly based on those failures. So when you ask the question of what recommendation do I have for executives? It's the same one we have to each individual CEO of our portfolio companies, which is in some environments we're saying, “You need a scrum team where you carve them completely away from the rest of the organization. In some you go to—and I like one of my CEOs had a really great approach, and she said, “Listen, let's start with a kind of zero-based planning of the company.”

Because the size and scope and scale of that company is: We can just go AI-native on this, but we have something unique. We have context, we have data, we have workflows that no one else has. Let's just rebuild from the bottom up. So that applies in that case. And so then as we look at another business, it may be one of those, or it could be a different approach, but what we're encouraging to do is to take some risk in this because the economic benefit of what we are seeing is orders of magnitude higher than the economic benefit that we saw going from on-prem to cloud, which was honestly two and a half to three times economic rent pickup. So it's worth taking that risk and you have to encourage them. And then you also have to, to the extent you can, point to successes.

We just had a CEO summit, so I had, I think it was 72 of our 90 CEOs all in one place, two days. Which is a lot, but they get a chance to not only learn more about the capabilities of our agentic factory—but the point is they also demonstrate to each other what worked in their organizations and what didn't.

Finding the right leaders who can embrace the change, ensuring that those leaders have the resources. But one of the most important is mindset. Believe it or not, it's not the technology, it's the mindset. And the best way to move a mindset is to show people. And so we bring our people together to show them the results. And they show each other. And so CEO to CEO says, “Here's why this worked. Here's what I did, and here's why this is effective.” As opposed to us kind of preaching to them, they get a chance to share with each other. It's a different, different efficacy in my mind.

ANDREW NG: Yeah. What I’m curious about is why is this so hard? So, I remember for many teams I led over the years, like when I was running the Google Brain team, which is a team that wrote the transformer paper you mentioned some years.

ROBERT SMITH: Well written by the way.

ANDREW NG: I wasn't personally involved in that paper, but the team did a good job. It was that same corporate change management that I was doing at Google. I was finding successes, highlighting the leaders, letting each other show each other the results, creating stages, the successful projects to be highlighted, supporting others get promotions and get pay raises, and using that to encourage more people at Google at the time to adopt modern AI.

But the thing that always surprises me, and when my team at AI Aspire when we work with businesses is, even though this is the standard corporate change management playbook to do all of these things, they're all completely sensible. It is just so hard for businesses to do this. I'm asking you this part because I know you've written this book on leadership inspired by the writings of MLK, but why is this so hard for people to do?

ROBERT SMITH: Yeah. I mean, all know that when you introduce change, those who've been doing it a certain way are reluctant participants and those who will benefit from that change aren't necessarily the hesitant adopters. Right. Change is hard for some people.

I like to think about organization design. I actually got this from a friend of mine, an 80/18/2 rule. 80% of the people liked things the same way every day. About 18% like incremental change. And it's like 2% who want to change everything every day. Right? And the combination of those, as a senior leader, you need to know who your 80s are, who your 18s are, and who your 2s are, and how they affect each other. And part of what our job as senior executives—and I'm assuming again, the audience here is senior executives—is to identify the 2s in a way that they can get the proof points to convince the 18s and the 80s. And often it is we all--all logical, rational, people—like to see proof points.

Markets like to see proof points. And if they don't see proof points, they have a healthy degree of skepticism. And the thing about our market, which is interesting: 96% of software companies are private. Enterprise software companies are private, and so the proof points aren't delivered quarterly in a way the general investing population understands the dynamic of change and how rapidly it's coming.

And then of course, the media sometimes says, oh wow, look what just happened. Well, it's been happening for 12 years or six years, or that sort of a thing. And so it's those incremental things that are often hidden. From the view of the broader public markets. But again, most people aren't comfortable with the way things are. Even though logically things are always changing. And it's just a matter of at what point in time do you actually realize that you've actually been changing and evolving? And that it's important to do that, to progress, frankly, as a society. So those are all kind of the elements that we see.

And there's certain teachings like in Martin Luther King that talk about the importance of looking at facts and then enabling people to make change and enabling the human spirit to be elevated and lifted by that change, which actually makes us all more productive in so many different ways.

SARAH ELK: Yeah, I think that's so consistent with the principle of scaling bright spots. So how do you take the 2%, prove that the new way can work and that it's the more compelling future versus where you are right now? I'm curious in how you've designed the collaboration across your companies.

It sounds like you just brought your CEOs together as one example. Are there ways that you've been thoughtful about how to get that change to scale faster or how to scale those bright spots from the 2%?

ROBERT SMITH: Yeah. We have a well established process called a BPSS—best Practice Sharing Summit. And the CEO summits are part of that. We also have a CXO summit twice a year. We also have a BPSS for all the chief marketing people, one for the salespeople, one for R&D, et cetera.

And so as a result of that, each one of those departmental—and again this across all the portfolio companies, so we may at any point in time have 450 people sitting in. I like to find hotels that are reasonably priced. So they'll be sitting in Utah in September.

SARAH ELK: Yeah.

ROBERT SMITH: And in doing so, they will then present and teach and train with each other for three days different best practices to make marketing organizations more effective or development organizations more effective or, or sales organization more effective. And it's that same, it's that same motion. So again, designing an organization to embrace the evolution of change is how Vista is designed.

We are designed to evolve and to enable our companies to evolve. So, as a chemical engineer, I don't like instances of success—I like processes that lead to success consistently. And so that's the way that we approach value creation across our platforms.

SARAH ELK: Yeah, it's interesting. There's a discussion that's been happening amongst CEOs that the winning capability actually, like the idea that you can innovate and scale and do that at pace. Does that sort of become the competitive advantage that the process itself of being able to drive that reinvention is as important as choices you make in customer offering because it's that always-on process. You're describing where the technology's changing, the organization's changing, and the ability to harness that is the winning factor.

ROBERT SMITH: In my business, I believe so, because we are in, I call it a continuous process business. We are continuously investing capital. Creating value and returning capital, and that's happening kind of all the time. What often happens is people will think about life, in instance, what is the average life of a CEO of a company, and are they just looking to optimize for the period of time that they are the CEO?

And that creates a whole different set of decisions, which creates a different set of outcomes, right? Because they're not necessarily building that business for the long term. They may be building it for just an exit, and astute buyers will figure that out. And I've always been able to view that. Build durable companies that have the capacity you build in these systems. So it's not just a function of the work you did with them, but you built in some infrastructure. In those businesses so they can sustain their growth, sustain the profitability long after you've either been an investor or been a steward of that business.

And so that's the approach that we take, because I'm of the view that build companies that buyers, when they're evaluating, say, oh, this is sustainable with or without Vista's participation and therefore it's worth paying a premium for them.

SARAH ELK: Yeah, there's certainly a lot of perspectives on the durability of the software market these days.

ROBERT SMITH: Yeah. And look, I think some of that perspective comes from…again, we talked about people's unwillingness to change because there's a narrative out there that says, oh, ARR. Right. Should last forever. Okay. And I say, oh, well, okay, you got this. The terminal value of these software companies is assured because people need this software forever.

And this whole dynamic of recurring revenue, which is how we price. I mean, we went from on-prem to cloud, which led to a different business model that went from license and maintenance to subscription, right? There's a couple things that happened there.

There's a technical change. From the way that the software was delivered. And there was also a business model change. People kind of conflate the two as one, but it's actually two different things that that happened. And as a result of that, so people say, oh, well what's the terminal value of that business?

Well, it's going to be a function of the ARR, which is a function of the subscription, which is the function of the seats that are sold, and that's going to go on forever. And that's how the pricing's done. And no, they'll say you get the fast growing, high multiples, high valuations for terminal value.

Oh, wait a minute. Andrew and his team came with this new thing, right? This new technology that changes that because one seat is more productive than maybe 20 seats utilizing these tools. And so if you're still pricing on a per-seat model, that changes your term of value calculation if you're priced on a per-seat model.

And so now there's a new business model that says what is it based on value? Because if I can deliver a set of agents that in working with an individual delivers a capacity of a hundred people, I should be pricing that. I think our fair share is 50%. Some might argue differently. We should be pricing that at a much higher value, which is actually a multiple of the per-seat model when you actually do the terminal value analysis.

And once enough proof points kind of come out, people say, wow, these companies are actually worth work because their total addressable market is much bigger than what it was on a per-seat basis. But that's going to take some time to diffuse into the marketplace. The technology has to diffuse in a marketplace, so the productivity of it is realized, and then the business models have to diffuse in the marketplace where the realization of the revenues and the growth is more visible so people can point to it, say, ah, that's why these companies are worth more.

SARAH ELK: Yeah. What do you think, Andrew? 50%? Is that the right value share?

ANDREW NG: Yeah. No, I've never been able to get away with that, but it's respectable that you can.

SARAH ELK: I would love to know, you've been on this incredible journey and have taken bold action on your AI factory and other things that have been, I think, differentiated and unique relative to what we've seen from other players. What has been most surprising to you on that journey so far?

ROBERT SMITH: In this most recent journey, let's focus on that. There are certain individuals in our ecosystem who are intellectually curious and really want to see how this plays out and really want to get involved in that. And then there's certain who aren't. And I call it trying to believe that the world is what it was five years ago, eight years ago, 10 years ago.

That's a surprise to me in all frankness. And you see that play out in some respects, in some of the public market investing not really understanding the difference between enterprise software and consumer software, and the impact of things like context and trust and scale, and the importance of that in operating for businesses and companies.

I like to say, in the enterprise, close enough isn't good enough. You can't have probabilistic outcomes for a wire transfer, right? Where it's where my wire transfer is mostly. Right? Right.

SARAH ELK: Exactly.

ROBERT SMITH: Anyway, those are the things that are surprising. But, in some respects, it takes a while for not only the technology to diffuse, but the knowledge and the understanding and awareness. So I guess it's not too surprising, it just takes time to get through these, through these curves.

SARAH ELK: Yeah.

ANDREW NG: Just one last thing I'm curious about. What you did at Morehouse made the press. I think we all read about it. You are offering to pay off the student debt to the graduating students. You are clearly a champion proponent of education, higher education. What's your view on that in light of what everything tech and AI is doing to us?

ROBERT SMITH: Yeah, we still have the responsibility to liberate the human spirit. And these tools can do that. and removing certain burdens of access to opportunity, to education being one of them, I think is all of our responsibilities. I think this modern AI can play a big role in improving the quality of life. And one of the ways is a quality of education. Like one of my kids personally is now using a tool agent every day as part of his everyday learning experience. And I am fascinated, excited to see his progress. And now one of my other children is now going to start here in the next couple of months in that environment as well.

Then I've got a couple more. I mean, it's just to me, when you see the efficacy of it. And the ability to access it. And so part of what we have to do as an industry is make sure that we are enabling access to opportunity. And one of those is education so that people can actually liberate their creativity, liberate their problem-solving ability, liberate their capacity to make our planet, frankly, a better place to live for all of us. And we just have a responsibility to do that as effectively as we can in our sphere of influence and domain.

ANDREW NG: Yeah, so I think that's a great note to end on. There's a lot we could do through higher education, through other things to lift up everyone.

SARAH ELK: Absolutely.

ROBERT SMITH: let's do it.

SARAH ELK: Let's do it.

ROBERT SMITH: All right.

SARAH ELK: Thank you, Robert. Thank you so much for joining us. We really appreciate it.

ROBERT SMITH: Thank you. It was my pleasure. And I'll look forward to further updates later, after we deliver more of this.

SARAH ELK: Would love that to that. Would love to get the update.

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SARAH ELK: This was winning with AI. Thank you for listening. We'll be back with more episodes coming soon.