The Exchanges

Q What do you think the biggest mistakes are that people make during the acquisition?

A The biggest mistake that people make during acquisitions is underestimate the intelligence of the people who built the business that you acquired. Because sometimes you take on the imperialistic attitude. I bought you, hence you must work for me. Our attitude is you kicked our ass. Come tell us what you did wrong. Come run this for us because you did well without our money, our resources, our scale. So you must have figured something out. So we spend our time trying to understand what they figured out. Find a way that we can make them part of our culture, make that, absorb that capability, and we let them run it. And that sometimes really makes it hard for my teams because they suddenly have a new boss in a category where they thought we were acquiring something. But it's just, as I said, you have to approach this as humility because there are people out there who are smarter, faster, better resources, more resourceful than you in certain categories. And if you can embrace them in the right way, it allows us to build a durable business.

AI assessment note: “The biggest mistake that people make during acquisitions is underestimate the intelligence”

Q I was curious. So, as we think about the next 12 months, I know you think a little, like, you think two years out or so. Do you think, one, do you think that will compress? Has that compressed over time?

A You're going to think two to five years out. I think that the base at which we are, things will happen much faster than we used to. So you just have to believe that what will happen, what you thought was going to take five is going to take two. What you thought was going to take 10 is going to take five. So you just have to change your horizon in terms of what you want to think. I think if you go back and think about when we went through a technological sea change last like this was in the late nineties with the internet. There was crazy valuations on certain companies because people thought that these things were going to Grow infinitely, and we're seeing sort of a bit of a phenomenon at this point in time, similarly, where the market's perhaps getting ahead of itself or not, where it believes there's infinite capacity, infinite demand for AI, which I think there is. I think it'll be interesting to watch. Some players will move around because the market moves so fast in terms of capability. At the present, the market is pricing in perfect execution for every company. Every idea that you see, the market wants to reward it because it thinks that Their returns are outsized, and the gains are going to be so huge that it doesn't matter. Even if you fumble your way to some amount of success, it's going to be a lot better than where you are today. I think two years from now, that wil…

AI assessment note: “what you thought was going to take five is going to take two”

Q Why is M&A so kind of consequential for cybersecurity companies? Because this is a common theme, they're very acquisitive.

A It is the most innovative industry in the world because the bad guys are trying to figure out how to attack you in a different way every time. The moment we suss out how they did it, they moved on to find you the next time. So we're constantly trying to chase them saying, holy shit, they figured out another way to attack us. Let's go figure that out. By the time we get to there, they move on. So you're constantly chasing and anticipating the bad guys who are constantly looking for a new way into your infrastructure, which makes them extremely innovative. And they're all over the world, nation states, people in their basements, People with, you know, Nintendo in front of their hand or laptop, they're all trying to figure out, either for trophy reasons or for economic reasons, how do I break into something? So it requires us all to be very innovative. Every new technology that comes in the market requires a different kind of sort of harnesses, different kind of tools, different kind of capabilities in our products. And if you don't pay attention to every new technology, the customers start buying something else. It's almost like we have to stay on our toes on a constant basis to anticipate technologies and to anticipate bad actors Makes us the most innovative companies, the most innovative sector. In that environment, it's impossible that all the innovations are going to come fro…

AI assessment note: “impossible that all the innovations are going to come from us... Make them part of your team”

Q The main topic was really on cybersecurity. You were part of that. You signed it as well. So why did you make that decision?

A Look, at the end of the day, if you want the diffusion of technology in a way that everybody can use it in every shape, way, shape, or form, you want to make sure that there's no constraint to innovation. And having open source, open weight, having close weight, all these things are important parts of the puzzle to make sure that people can deploy them different circumstances. I don't think it's necessarily bad. To hold back the development in open source or open weight for that matter. Open source will allow people to make these things available globally at the right price point for various people to be able to use. Open weight will allow a significant amount of fine tuning to make sure that can you adapt a model to your specific use case in a way that is more effective and efficient for the task at hand. So all these are important parts of the puzzle to make sure we get innovation right. So that's the reason we signed it. I think the There's an over-indexing on the model part of it. I think to make AI useful, the models are important, but I think it's also important to get all the context collected and all the training data right. I think billions of dollars were spent to train my favorite example of Waymo. I think billions of dollars will be spent over the next few years training a whole bunch of use cases in enterprise or consumer to get that part right.

AI assessment note: “to make sure that there's no constraint to innovation... that's the reason we signed it.”

Q What does a typical day look like for you?

A Like, podcast in the afternoon, breakfast in the morning, golf in the evening, just kidding, no. Enterprise jobs are, are interesting. They're, they're, let's say, one percent inspiration, 99% perspiration, so in some way, shape or form, either you're fixing a product, you're adapting strategy, you're trying to hire people in places, or you're trying to meet customers, but look, I joke that every job in the company Which requires some accountability is already taken. Like, I have a CFO. He's responsible finance. I have a marketing person. So I kind of don't have a job, right? My job is to orchestrate these people in the strategy. So my job is to set the North Star, define the strategy. My job is to make sure I resource the North Star. If I want to go win in this, I just need to understand how many people it takes, how many hours does it take, what other things do I need? And then Give it to the right people. Then my job is to remove obstacles from their way and course correct them if they're falling short. That's the job, right? It's course correcting, getting people lined up behind you, making sure that you have the right people in the right place. You know, when I came to Palo Alto, for the first few months they all sat and looked at me, who is this guy? He's strange. He has different ideas. What, what's he about? Then I realized we didn't speak the same language. Didn't unde…

AI assessment note: “either you're fixing a product, you're adapting strategy, you're trying to hire people”

Q So how are you keeping track of everything that's going on?

A Really hard. Watching your podcasts, listening to, look, it was fascinating in the last two years you've seen, we've been through so many iterations of AI. I started with ChatGPT, OpenAI is going to go run away with it. Anthropic came from nowhere. People had written Google off, and they were not going to be able to compete. And like two years hence, we're sitting here watching all the announcements from all the cloud companies, which are sort of going gangbusters because people want to use more compute, want to use more AI. And now we've gone from LLMs to agents. Agents are going to help us do a whole bunch of stuff. You've gone agents to open weighted models, open source, closed source, So there's so many variables because the market continues to evolve on a daily basis. In cybersecurity, you gotta go make sense of these trends and see which ones of these trends is likely to catch upon, catch on, so we gotta go build the security infrastructure and harnesses around it. So it's kind of a bit of a dancing on your toes and constantly being nimble, trying to figure out where this thing is gonna land. Uh, it's interesting. I think some things are beginning to emerge. I think a lot still needs to be figured out, but I think one thing is clear, the appetite for AI is huge, and I don't think that trend is going to reverse itself. So if you believe the demand is infinite, then a lot o…

AI assessment note: “Watching your podcasts, listening to, look, it was fascinating in the last two years”