Transcript
Today, my guest is Nikesh Arora. Nikesh, welcome to Threat Vector. Thank you, David. Nice to see you. It's nice to see you, too. We're gonna start out with a little bit of a rapid fire today. All right. Something that's a little bit different. So, I wanted to ask you, what's the coolest thing about working at Palo Alto Networks? Well, it's different today than it was seven and a half years ago when I started. Today, I think it's cool that we are the largest cybersecurity company in the world, which is kind of cool. You lead your sector. I think it's also cool that every day, we're making thousands of customers safe from bad actors, so they can go ahead and do what they need to do. So, we're kind of mission-driven. We're not selling social media. We're not selling advertising like I did when I was at Google. We're actually solving real problems for our customers and our companies, which is kind of great. And it's also great that we all get to work with cool people at Palo Alto. How about your favorite memory of working here at Palo Alto Networks? That's a good question. There are so many to pick from. I think in no particular order. We have these employee events. People bring their kids. You get to talk to them. They talk to their families. You get to see what actually makes them wake up every morning and try and come to their best, because you'd be surprised how many children want to see their parents succeed, how motivated parents are for the children to put their best foot forward. So, it's kind of inspiring in a way. It brings it back to humans. As we talk, you'll see a lot of this will come down to people on a constant basis. I think it's interesting. I remember what we did in the first year I was here, we did it in a quarter, two years ago. So, that's kind of an interesting milestone, saying, well, what we did for 12 months now happens in three months. So, it's just things like that, or the germinating an idea like XIM, and we sat here and said, oh my God, our median time to detect and remediate cyber security is four days. And I'm like, oh my God, I fell from my chair when I heard that the first day somebody told me. And now that we're able to bring it down to one minute, it's kind of like, stuff is, oh my God, you set a North Star, you go grind towards it, you go achieve it, and you go turn that into a product in the market, and it becomes hugely successful. So, all these things just are amazing things that have happened in the last seven, seven and a half years that I've been here. If you're not here, where's your favorite place to be when you're not working? Home, with my kids, my family. Clearly, because we all work, and this is kind of like where we spend 60, 70 hours a week. You actually get less time, waking time, with your family. So, if I wasn't here, I'd spend more time with them, maybe for a bit, and maybe I'd want to go to something else, because spending too much time at home is also not that exciting. But, no, I'd probably be home, spending more time with my kids. My kids are young, I watch them grow up, cool. Favorite sports team? This is a tough one, right? Because I have this theory that I grew up playing cricket. So, for me, that's what I did when I was a kid. You wake up, my son's 10 years old, he's obsessed with basketball. He wakes up, he watches the Warriors, he plays his NBA games, which have basketball players. He's trading them, he's doing all kinds of stuff. So, this is what he grew up with. Imagine that same thing happening when you're living in India and growing up with cricket. So, that still gets me excited. I can still literally feel the passion when I watch a cricket game. So, towards that end, today, the Indian cricket team would be my favorite sports team. Now, in the context of where we are, it'd be the Warriors. What's your New Year's resolution? You know, the good news is it's pretty consistent. Every year, I want to be healthy. So, I start off the year really well. In fact, actually, I started off the end of the year really well. I went into, like, literally after I went to Israel as part of meeting the people at CyberArk and Pilot Networks, which I hadn't done for a few years. It was amazing. I spent four amazing days there. And then, I took a week off quietly. I went off to a health detox. So, my resolution continues to be lead a healthier life. What do you wish for leaders of tomorrow? What do you wish for leaders who are willing to say out loud? Like, we have a philosophy at Palo Alto, which is you call a spade a spade. You actually look at everything and see if it's achievable. You're going to get it done or not. I think the best way to get stuff done is to confront the issue, figure out what the resolution is, and solve the issue. I think a lot more stuff will get solved much faster if leaders just spend the time understanding that not everything is perfect. Yeah. Because it never is. In our personal lives, our professional lives, there's always something that needs to be done better or fixed. I think part of our job as leaders is to fix that or at least create the culture where we can fix that so we run into less issues. I think part of our job is also is look around corners to see where the next big thing's coming towards us so that we can prepare the business in that direction. Nikesh, you've had this front row seat to technology shifts. As you look forward to 2026 and beyond, do you think that people still misunderstand cybersecurity and where it's actually heading? I think part of what is important to understand is that most technologists think about technology, not about cybersecurity. Cybersecurity is kind of like insurance. Let's go make great things happen. Let's make sure on the way we purchase insurance or we make sure that we're not gonna do it the wrong way. So cybersecurity usually ends up being an afterthought as opposed to the primary thought. I mean, I just talked to a CIO this morning. He's busy trying to figure out how to deploy AI. As part of the AI deployment, he's more concerned about how is that gonna impact customers? Can they actually build a viable product? Can they actually train their AI to be able to solve real problems? He didn't mention even once that I'm worried that this thing's not gonna be secure. See, security is when you think something's gonna work amazingly well and then you're worried that people are gonna break into it. If you're still going through the motions trying to understand, can I actually make this thing work? You don't worry about security. So what if it doesn't work? Does that hurt? Worry about security. As much as we like to say secure by design, which is what we should do, is like design in such a way that can't be breached, very often when new technologies arrive, people spend a lot of time trying to just deploy and make it work. So I think we're in that phase as it relates to AI. And AI has become the biggest inflection point, as you know, in current technology. So I think we're gonna see behaviors where people are too busy deploying and then security will become an afterthought. It's our job, it's Palo Alto and our industry, to make sure as they go, build these experimental ideas into real production capability that we're staying in lockstep with them and say, oh, by the way, here's something that can secure what you just built in a way that is not gonna get into trouble. It's funny enough, the CIO said, oh, we worked on some stuff ourselves and we're just jerry-rigging some things to make sure this happens securely. I'm like, jerry-rig production and security don't work together in three terms. I started my career in design and used to build a lot of things and then got into security and realized I really made people's lives hard. I wanted to build delight. And I think you're right about this idea of I wanna figure out if I can build a thing and we'll deal with the security later. What about that gap that seems to persist worries you the most? Look, worry is a big word. I don't think it worries me as much because I understand the psychology behind it. Like, think in our normal lives, right? When you go to the airport, what do you have to do? You have to go through a scanner. You have to take your belt off. You gotta take your liquids out. You gotta take your laptop out. All that is overhead, right? You wish your experience was more seamless but you wouldn't have to do all of those things. If there was time, then you could do that. So, by definition, security causes some degree of latency or overhead. There's no way to avoid it. It's very hard to do security in a seamless, frictionless manner. So, I understand why the gap is. People don't wanna create friction when they're trying to create delight and look for acceptance. They believe in the goodness of mankind. So, oh my God, I'm gonna design this. People are gonna use it the right way. But then you figure out, as it starts to scale, it starts to become more omnipresent that there are bad actors who can get access to it and do bad things with it. So, at some point in time, it's the right time to think about security. Now, if you're really good, you've designed security right off the bat in the beginning so that when it comes time, you can go put it together and it works beautifully at scale. But I think that's the aspiration, not quite the reality. As you said, when you do design, you actually don't think about, you think about functionality. You think about usability. You think about value. You don't think about security. So, I understand the gap exists. I know that the app needs to be bridged before things get out of hand. But I think there is a right time, right place for people to start evaluating whether they've done it in a secure fashion or not. You've talked about inflection points when things quietly change before anyone notices. What signals are you paying attention to right now that you think the next shift is already underway? It's funny, I was on the phone, I was a few minutes late and I was talking to somebody because, look, there's stuff going on out there. But it hasn't impacted our lives in a more aggressive fashion. It hasn't impacted our customer's life that much more aggressively. I read somewhere a few months ago where people talked about in the context of technology, you start seeing signs early and then you look around and you don't see enough impact. You say, okay, maybe this is going to be just a passing shower. But you don't realize that over time this thing's getting more and more momentum. It's getting bigger and bigger. It's going to be more impactful. I feel the same way about AI. Like, there's a $4 trillion company called Nvidia. They're selling chips. They're running out of fashion. They're not running out of fashion. People are just buying more and more chips. And there's like hundreds of billions of dollars of infrastructure that seems to have to be built in the next few years. Or there are people looking at nuclear energy or fixing the electricity grid or looking for alternate sources of power. I was with a guy, big Thanksgiving, he's got a methane gas company. All his capacity was bought out by one of the cloud providers. I'm like, oh my God, these guys are really going out there. So there's a big spend happening on building AI compute. I noticed individual behavior. I used to never talk to chat GPT or Gemini. Now I'm doing 10 or 15 conversations a day with these AI chatbots about anything and everything. How does this thing work? How do I do this? What should I do this? So I was in Tokyo. Literally, Gemini was my best friend because I don't speak Japanese. I can't go scour Japanese websites to find things. And boom, I was asking, I want to take my kids to a sumo wrestling show. Where should I go? I ranked them all, great. That's better than me trying to go read 14 websites to figure out what makes sense. So you can see that there's a rising consumer trend. You can see there's a rising trend in enterprise from coding, et cetera. You can see there's a large spend coming. So this thing is going to change our lives fundamentally. But we're not seeing it at scale in our customers just yet. That doesn't mean we can sit back and wait. It means we have to get ready for this future. How do we do that? Which means a lot of uncertainties. And well, if you don't see scale, how do you create scale and security? So you got to figure out, you got to make a bet. This is where do we think this is going to go? This is where we're going to lay our bet. This is going to go prepare so that when our customers get to a point where they actually see the need, where there is a solution. Mikesh, you've seen industry evolve through multiple cycles. Where do you think we are right now in the hype between AI automation and geopolitics versus the reality of AI automation and geopolitics? Well, we talked about AI, right? I think what you're seeing is a rapid adoption of the consumer use case, right? I think in the next 12 to 24 months, it'll become impossible. People will be talking to their chatbots about everything, whether it's how to deal with personal things or how to deal with whatever the topic. You pick your topic and I think things will get more and more specialized over time. Or you have your favorite, kind of happened in search. I used to work at Google. There's a time, there's one big search box and then Maps became a thing and then Google Local became a thing. So you start seeing more and more training is going to happen in very specific categories for things you're going to get good at. For example, today, there's a different model that creates videos for you and there's a whole automation around how to create videos. There's a different model that has a textual conversation with you. So I think you'll see some degree of specialization and these models are going to get more and more powerful. That's going to happen. I think as it relates to automation, automation has always been around. We used to do process automation, workflow automation, robotic process automation. Process automation has already been around. I think on AI first, you're going to see we're going to get more and more hungry for more data. Because the more data you have, the more you can train AI to solve harder problems. We'll discover that in the enterprise context. Today, any enterprise probably collects 20% of the data they need to run it more efficiently. So we're going to actually have to three to five times our consumption of data in every enterprise to get our outcome. You know, why should 3,000 sales people have to go discover the problem every time and try and solve it themselves? Why, if we had collected all the data, how this guy solved it two years ago, we should have a beautiful chatbot when you go to the next customer, it says, boom. Here's all the learning I have from the 300 interactions I've been tracking. Add your interaction and here's the best strategy I can give you to execute the problem. So we're going to become very hungry on data consumption, which is why they're spending so much money in creating all these large infrastructure that is needed to be able to train these models, train the use cases, train the applications. I think on the automation front, eventually people will want AI to execute on their behalf, which is like an instead of, if you're so smart AI, you can tell me, why can't you do it? To do it requires automation and connection to control systems. I mean, think about, you know, Waymo. There's no human being in the car. Somehow the model's figured out from more machine learning than generative AI. Machine learning's figured out what the right solution, what the right response to that scenario is, and actually it's connected to your brake, your accelerator, your turning signals. Everything's connected to this effective brain in your car, where you're given the autonomy to that brain to execute. Imagine that having to be applied to everything in life, right, your, you know, digger if you're in construction or something that, you know, pavers your, stuff that you use in agriculture. All these things could, over time, be trained to execute on their own behalf, but it still needs a lot more training to get there. So I think that's what's gonna happen in automation and AI. I think geopolitics is a different one. I think because of the humongous amounts of data involved, a lot of countries will get very nervous about their data leaving their country. We've seen that in the internet scenario. I think you're just gonna see this at scale where people say, wait a minute, that's too much information about my employees or my citizens, and I don't want this data to leave the country. You're gonna see a lot more rigor around data sovereignty, people wanting their data in their own countries, wanting models to be built in their own countries, which I think is kind of a false argument because, you know, this happened again 15, 20 years ago when search came around to Google and people in every country wanted their own search engine, but you don't realize that you have the scale and the capability and the competence to go build this 150 times across the world. So we'll still see large global companies solving these problems, but we'll have to figure out ways that these become acceptable to nation states, and I think there's gonna be a whole set of social challenges in if AI gets too good too soon. What happens to those who, you know, succeed and those who fall behind? Well, look, any time there's an inflection point, there's tremendous amounts of uncertainty, right? You know what is gonna become obsolete, but you don't quite know what is going to become trendy. Now you can sit there and say, well, I'm just gonna wait till I figure out what becomes cool and I'm just gonna move from where I am to there. The problem is it's not that easy, right? You have to not just anticipate where the trend is going, you have to prepare your organization and the resources to get there. Otherwise, the risk is that Silicon Valley will go fund those people who are thinking all purely about the new world, and there are 10 different people who are trying 10 different ideas in your space, and one of them's gonna hit, and then you'll be two years behind with no organization, no resources deployed against it, and you'll be behind the eight ball. So part of our job is to sit there, especially in times of inflection, and look around corners and say, hey, where do you think this could be going? Where should we take our bets? But maintain the agility and flexibility of turning on a dime if things don't go in the right direction. So some mistakes will be made. Hopefully you can make less mistakes and get more things right. And, you know, our brains move faster than reality sometimes, so you usually have some window, but you have to be ready. I think part of what you're doing at Palo Alto, what leaders have to do around the world, is get their organization to be ready. Start embracing new technology, understanding people who are getting good at it, people who need to be trained, or people who need to go out and learn again, and get good at it, because I think this has the property of fundamentally transforming almost everything we do. You've talked about building with intention rather than reacting to the noise, and I think that you're talking about that a little bit when you're saying, you know, you don't want to wait, you don't want to overreact and go for the wrong things, sort of find that balance. How does that psychology and that philosophy show up here at Palo Alto Networks when you're thinking about the future of security and where to drive this company? Well, look, if you go back, and it's easier to go back in hindsight and show you what happened, like when I came here, we were a firewall company. At that point in time, I kind of like, in my plastics moment, I wrote cloud and AI on a piece of paper, and I talked to Nir and Lee, founder of Nir, and Lee who's our chief product officer and our board member now. I said, look, I don't know how you guys did security, but I will tell you the two biggest technological changes in our life are going to be cloud and AI, at least in our lifetimes. At that point, cloud was just sort of taking off. It wasn't fully developed, people were still experimenting or just doing early deployments. It's obviously done phenomenally well in the last seven years but what it did was it fundamentally changed everything. It changed the network architecture, it changed how services were delivered, and just that insight allowed us to move and transform all of our on-prem services to the cloud, it allowed us to build firewalls for the cloud, allowed us to build a SASE business for our network infrastructure. So I think you have to have the right insight. And then we, at that point in time, just like I said, there was a thousand flowers bloom, there were so many people trying to invest in so many different businesses, and we just looked at it and said, eh, eh, eh, I don't think those are going to work. And we've seen that. You see like, you know, you see the debris of startups in the cloud security space, you see the debris of startups which try to go out to SASE. So I think it becomes, you can get caught up in the noise. Oh my God, look at all these 10 different companies that are doing this, we should do the same thing. Well, the same thing happened, for example, in our SIM example. We sat down and said, hey, it takes us four days to solve problems in our SOC. I said, we need to get to it in real time. And literally, everybody around me was like, what are you talking about? What do you mean real time? It's like, you got to be able to analyze it, be able to do it in real time. But to the credit of our team in Israel, they said they got the idea and said, we understand, which means we have to start analyzing data as we get it, not wait when the problem happens. So traditionally, SOCs would analyze the problem when the problem appeared. They're like, forget it, we're going to analyze everything to see if there's a problem. That architecture fundamentally transformed what we do in the SIM compared to everybody else in the market. So today, we have the most radically different architecture which allows us to aspire towards getting our customers to one minute. Most existing SOC solutions can't get there because they don't do that part of analyzing data upfront. They still wait to do some of the risk correlation, UEBA at the back, which gets you closer, gets you faster, but doesn't get you real time. Exactly, no, I look at the whole thing and it's like, no bank would allow for four days after they've been robbed to go, I think we've been robbed, we should probably call for some help. Yeah, nobody would accept that. But we accepted that as a norm as we've grown into this tremendous problem. Okay, how do you decide where to lead and where to follow when you've got a thousand blooms in front of you and you could chase or you could hold? Look, in the end, it boils down to impact and prioritization and a little bit of survival. What I mean by that is, we look at the landscape and say, where can I have the biggest impact? And what do we need to get this right? Right, if you don't get the network transformation right, 80% of our business will falter. You got to get that right. If you don't get two features in cloud security right, it has less impact. So the question is, you got to sit down and prioritize and where is the maximum impact today, tomorrow and three years from now? If you can identify those and say, those are the nuts I'm going to chase or those are the things I'm going to go pay attention to or focus on, that becomes sort of a self-driven prioritization mechanism. At the same time, you look at the other end and say, where do I get in trouble if something breaks? Right, because your risk is not just that you didn't capture the upside, your risk is also that the risk of downside. So you can say, if our customer support system crashed, then we'd never be able to support our customers, that'd be a bad thing. Or if somebody got breached, that'd be a problem because that would destroy reputation for us if we wouldn't be able to achieve our targets. You actually look at both ends of this from Marble and say, where's my biggest opportunities from capture more market share or more business? And then, where's my biggest risks of where if these things don't work, we'd be in a fundamentally bad place? And then there's a third piece to say, what am I doing different? Where is my bet? If I'm doing everything everybody else, the same thing that everybody else is doing, then I'm just going to be better executed. Where's my radical bet? Like XIM, where's my radical bet? Like buying 30 companies and trying to integrate them to Palo Alto, where's my radical bet? Which if we get right, it's going to fundamentally transform who we are. Now, we've done it once, we're going to do it again, right? We did it seven years ago saying, how do we become the largest cybersecurity company for $18 billion? Now we're with CyberArk, we're 150 plus. The question is, how do we take it from 150 to 500? And that requires a whole different thinking in terms of what do we prioritize and where are the big nuts that we got to chase and where are the things we got risks, et cetera. Do you have a set of principles that you use to guide those decisions? Yeah, yeah, there are. Part of it is situation dependent, but when I came to Palo Alto, the first few weeks, I would say things and people would look at me strange, like, what's he talking about? Why do they think about this stuff this way? I realized, oh my God, I don't work at Google anymore, I work at a different company. These guys and me don't speak the same language. So I actually wrote down my business principles over a weekend and brought them into my staff meetings. I debate this, this is why I do things the way I do it. Over the last seven years, it's become an 11-page document and pretty much most senior people who come to Palo Alto it's required reading. You got to understand how we think about things. So it kind of creates the same language. Yeah, I feel like that's chapter in the memoir someday. I don't know. Yeah, yeah. ChatGPD probably is a better set of recommendations. Oh no. All right, so the threat landscape has evolved. How do you think about balancing innovation with responsibility, especially when the stakes from a security standpoint are so high? Look, the threat landscape by its definition has to evolve, right? Because if we plug the holes, the bad guys got to look for different ways to come by this. It would be a seriously boring industry to be in. Exactly, well, it wouldn't be an industry, right? If the bad guys, oh, thank you, you've stopped everything, I'll go off and do something else. So by definition, the threat landscape constantly evolves. How secure you are depends on how big a hammer they come with. So you got to get your hygiene right. You got to make sure that stuff that everybody gets right should be done. We talked about it, yeah, they're constantly trying to figure out how to deploy this so cool that they can look good for their customers, et cetera. So they don't spend much time thinking about security. So we have to make sure we think on their behalf on how to innovate, how to make sure they stay secure as they try and get the benefits of the D.U. inflection point technology. Similarly, we are also a company. Our job is also to do the same to ourselves, right? You have to eat your own dog food, so you got to make sure that we are innovating as well without getting bogged down by a lot of requirements. At the same time, we have to be doubly sure because if we get breached or we're in trouble, we risk the reputation risk of our customers wondering what are we doing with this stuff? So I think the standard for us is slightly higher when we do these things versus our customers. And Nikesh, you've talked about judgment and leadership and earlier you talked about seeing around corners, but there's always a human, you know, no matter how bulletproof your decisions look like when we go in hindsight. And I want to spend a moment there and talk to you a little bit about you. Oh, okay. How has your relationship with pressure changed over the course of your career? It's gotten better because if you think about it, my job is to sit down and cogitate over the strategy of the company, where we should be going in consultation with the leadership team and other smart people in the company, which we do a lot, a lot, a lot, a lot. Once we do that, then the next question is an assessment of, well, we've got these plans or how do we execute them? Do you have the right resources? Do you have the right people? Can we afford it? So it's kind of like funding the plan. And then the third thing is I'm sort of troubleshooting, saying, oh, let's make sure we tweak this a bit and sort of keeping track of it. That's kind of the three jobs that a leader has. Define the strategy, resources right, as in manage people, put the people in place, capital, whatever you need. Third is to make sure you monitor the progress. That's what every leader should do, pretty much, because the rest of the work is done by people. Now, in that context, I always joke, you know, we have 16,000 people at CyberArchive or there's 20,000 people. I think all the easy problems get solved before they come to me, right? But it's an obvious answer, people go execute. So only hard problems keep getting escalated. The hardest problems come to me. So my definition, I don't get a call from somebody saying, hey, Nick, I just want to let you know, we had a great meeting with a customer. They're buying everything, everything's working great. And the customer says, your team was great, thank you for your business, and thank you for letting me do business with you. That'd be the best phone call in the world, right? I don't get those as many times. I do get them sometimes, very nice of people. But very often, it's somebody who's got a problem that needs resolution. And it's clearly a complex problem because people in the rest of the organization have not been able to solve it, keeps getting escalated. So I joke, like, my job, if I took pressure, every time, everything is pressure. It's kind of like working in the ER. If everything is sort of a life or death, matter of life and death, then it becomes normalized. So over time, I think the pressure is normalized. I get into fixed mode as opposed to stress mode. So you have three logical ways to solve the problem. There's none of these ways that makes everyone happy. So we're going to make choices. Well, what choices do we have to make that stick to make sure that we don't impact our long-term aspirations and it doesn't change our principles? Makes it a lot easier. When things do get heavy, do you have something that you go to to reset? Well, first and foremost, when things get heavy, there are some trusted people who want to bring us a conversation, share the burden. The only reason that, yes, sure, I'm the CEO, doesn't mean I can't talk to people and ask their opinion. So I'll call our lead director, I'll call some of my people on my team, we'll chat about it, we'll cogitate what the best options are. So it allows me to at least run things by people over time and get them involved. And then make a decision. And if that requires you to go for a long walk by yourself or around the neighborhood and come back and say, guess what I'm going to do? That's what you do. And look, part of what you need to do as leaders is to eliminate uncertainty and create clarity. Now, that's why those hard problems come to you because your job is to sift through them, find the solutions so people can go on and get shit done. So that's gone as far as the course. It sounds a lot like parenting at times. Oh, that's harder. Shifting through it. Remember, parenting has another human being on the other side. So it doesn't matter what you think, it matters how they interpret what you think. That's a whole different problem. That's a whole different episode of your podcast. What's something about you that doesn't show up on your resume, but shapes how you lead? It shows up, I think it may not show up in a resume, but if somebody is a keen observer, they will observe that from having worked with me or having seen how we work at Palo Alto. I find solace in first principle thinking. Otherwise, you can get caught up in how things are done. I think that my pet peeve is when somebody says, well, this is how we've traditionally done it. Well, you use the word traditional and use the historical context saying, yeah, sure. They used to go dig fields with picks and shovels and use tractors. So that doesn't mean that the fact it is one way applies in the future. Part of it is you have to go back and rethink the problem under the current circumstance to see, could this problem be solved differently? And if it was solved differently, would it create a great outcome? I think that's the job of every leader. Every leader should be looking at things to see, how could we do this differently? How would this be better differently? How would we add value more if we did it fundamentally in a different way? Is that something that you grew up with, your parents and your family taught you, or that you picked up when you started your career? I guess subliminality is always there. I think it comes from a deep laziness. A deep laziness? Yes. When you're lazy, you're always trying to find a better, faster way to do it, right? How do I get this done better, faster, without putting in as much effort as everybody else is putting in? Okay. It's kind of a counter take at laziness. So you strip away the titles and the expectations and the noise of this moment, and you look back on it. What do you want people to remember about your leadership and our place in cybersecurity here at Palo Alto Networks? Look, I think there are a lot of facets to that, right? As I said at the beginning, we want to do the right thing for our customers. We want to be the mission-driven company that's always looking to solve the problem in cybersecurity wherever it exists. Now, seven and a half years, we operate in a certain sliver of the industry. Today, I'd say we have coverage for 80-plus percent of the industry, which is great, which means our customers can come talk to us about a myriad of problems, and we can actually cross-correlate across all the different things we do to see how well we can solve the problem. So I think from that perspective, the fact that we are trying to simplify cybersecurity and solve the problem should be something that people hopefully remember. Palo Alto was the first company to go from industry tracks towards a platform approach that was delivered to the customer. I think outside of that, I think personally, going back to what I said, I think people need to understand we're looking for constant, continuous improvement, right? We're always trying to do better. It's impossible to be perfect in a professional context. Everybody has things. We have 16,000 people, soon 20,000 people. Somebody is going to slip up somewhere. Our job is to make sure that customers understand our intent. As long as they believe our intent is right, that we're going to do the right thing, they will excuse anything that didn't work out the way it needed to work out, as long as we show up the next day and say, I'm here, I'm going to fix it, I'm going to keep at it until I solve the problem. So I think intent becomes important. Intent is a cultural thing, not just me, it's the whole company. We all have to have the intent that our intent is to make sure we solve your problem with you, stand by you all the time. That's why we say the words cybersecurity partner of choice for that reason, right? And lastly, personally, I'd like to be seen as somebody who tried to do the right thing and was fair, and that's about it. Nikesh, thanks for coming on 100th episode of Threat Vector. I really appreciate you giving us a bit of your time today, sharing your thoughts, your philosophy, and your insights. Well, thank you. Congratulations on your 100th episode. Well, thanks. That's it for today. If you like what you heard, please subscribe wherever you listen and leave us a review on Apple Podcast or Spotify. Your reviews and feedback really do help me understand what you want to hear about. I want to thank our executive producer, Michael Heller, our content and production teams, which include Kenny Miller, Joe Ben-I-Kort, and Virginia Tran. Mix and original music by Elliot Peltzman. We'll be back next week. Until then, stay secure, stay vigilant. Goodbye for now.
