Building Defense for the Agentic Era: Kevin Mandia

a16z General Partner David George sits down with Armadin founder and CEO Kevin Mandia to discuss what happens to cybersecurity when attackers can operate at machine speed. After 30 years in security and building Mandiant, Kevin says AI convinced him to get back on the field. He explains how AI changes the economics of cyberattacks, allowing attackers to probe thousands of paths simultaneously, and why that means defense will ultimately need to become autonomous too. They also unpack Armadin’s approach: continuously attacking customers’ systems with AI to find exploitable vulnerabilities before adversaries do, then building toward autonomous defenses that can respond in real time. Kevin shares what Armadin has learned from finding more than 90 zero-days in production environments this year, why humans can’t remain in the detect-and-respond loop, and how the entire security stack could change over the next few years.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  You don't have a defense on this. You have a great offense to go up against. You want to be the Baltimore Ravens defense in 2000. You kind of want to have your practice offense really push you. That's what Armadon is going to do. We're going to be the all-star team on offense coming at you. So you can train your defense with what we're doing.

• 0:17David George?

  But you built Mandiant, a great success. Why did you decide to get back on the field?

• 0:22Speaker 00

  I don't want to sit out the AI shift change. When I've done 30 years in security and the whole damn thing's about the change. What AI does in a microsecond would take 70 humans. They can't even do it. It's apples to oranges.

• 0:35David George?

  This is a tsunami like has never been seen before in security.

• 0:38Speaker 00

  The whole, let's slow down the models. We don't want cyber risk too late. The open models are already good enough. Armadon since January of this year. We have found over 90 zero days at customer sites, all in production.

• 0:51David George?

  This is not like rinky-dink companies like these are like Fortune 500 companies. The differences or similarities between nation state attacks compared to AI today? And then where you think AI can be in a couple of years?

• 1:04Speaker 00

  On the defensive side, we're going to say we're being attacked by these models. But we're not sure who's behind them. Is it a nation? Is it a human? Is it?

• 1:11Speaker 02

  Kevin Mandiant has spent 30 years in cybersecurity. His view of the AI transition is simple. Everything I did is dead and then everything else is new. In this episode, David George sits down with Kevin, founder and CEO of Armadon and the founder of Mandiant, to talk about what happens when cyber attacks move from human speed to machine speed. Kevin explains why AI gives attackers an immediate advantage. From probing thousands of paths simultaneously, to making less sophisticated attackers dramatically more capable. And he makes the case that there's only one viable response. Defense has to become autonomous too. We also get into how Armadon uses AI to continuously attack customer networks.

• 1:55Speaker 02

  What the team has learned from finding more than 90 zero days this year. And why Kevin believes the next two years could remake nearly every layer of the cybersecurity stack.

• 2:07David George?

  Kevin, thanks for being here.

• 2:08Speaker 00

  No, thank you.

• 2:09David George?

  Okay, so you built Mandiant?

• 2:10Speaker 00

  Yes.

• 2:12David George?

  Obviously a great success, many different chapters. You know, it ended up inside of Google ultimately. Why did you decide to get back on the field?

• 2:20Speaker 00

  It's a good question and I don't know if I decided it. And that'll sound weird, but I met with David Slater and with Travis Lanham, the other founders and Evan Peña I knew. I could say they started this company. They are the founders. I met them. They had the idea. They pitched me on what they wanted to do. And I saw the talent in them. Travis is a generational talent. David Slater's, and I mean it's in a positive way, freak of nature. Like these guys are really, really good. Evan Peña is exceptional at what he does. And when you meet that team and you talk to them, the whole time I was listening to what they were doing. I was thinking, I want to be a part of this. I don't want to sit out the AI shift change.

• 3:02Speaker 00

  When I've done 30 years in security and the whole damn thing's about the change. That's great. Everything I did is dead and then everything else is new. But meeting that team and they were starting the company and me realizing, I think I'm a real good fit with these guys to accelerate the need. What Armadon is building, every company needs now. And I was like, this team, I can build it. And I think I can answer the now. 30 years in security, you meet a few people. Let's go to those people and say, we've built what you need. So I almost felt compelled to do it. I know that sounds weird, but I would not have founded a company again. In mid 50s and I was doing venture. It wasn't like, oh, I'm an entrepreneur and I love starting companies. That's not it.

• 3:47Speaker 00

  And it wasn't, ah, I'm not a VC. I'm just an operational guy. That's not it. I met the team and went, we have to do this. I mean, that's really it.

• 3:56David George?

  Yeah. And this whole AIC change was happening, right? Like that's the catalyst, right?

• 4:01Speaker 00

  Yes.

• 4:02David George?

  So tell us about what Armadon does.

• 4:05Speaker 00

  So Armadon leverages frontier models and AI. On offense, the test, do you have exploitable risk? And that's what we do today. We call it Armadon Red. But when we started a company, Travis and David Slater and Evan all knew the future of cybersecurity is going to be, A, the good guys have to build the offensive cyber cannon and shoot it at networks to make sure those networks can withstand these attacks. Cause they're the ones that are coming. But we also knew it's going to be AI on offense built by the good guys, working and training with AI on defense built by the good guys. And you have to have both. So our act one was, we got to be the best in the world at finding exploitable risk. If we're five minutes ahead of the bad actor,

• 4:50Speaker 00

  whether it be a nation state, criminal nuisance. If we're five minutes ahead of them, we also recognized our act two, Armadon Blue. We got to stop it, compensating control, tourniquet. And so that's what Armadon does. We're building the force field you will need in the AI age to defend yourself from AI attacks.

• 5:10David George?

  Yeah. Tell us about the nature of the capabilities of AI attacks today and then where you think it goes.

• 5:17Speaker 00

  Wow, great. So the nature of them is first off, we're getting a weird window in time where we're seeing them. But not at the same level you'd expect. I've seen nothing like what Armadon's already built in the wild, which is there's 25,000 agents on concert, all working together, doing really, really smart things without going on bizarre fishing trips. Because when you respond to an AI attack, you can tell it's AI very quickly. At least I can, because I've thought about a lot of offense. I've responded to a lot of attacks in the past that were led by humans.

• 5:52David George?

  Right.

• 5:52Speaker 00

  And a human goes to point A, then to point B, then to point C through their intrusion. AI does little things like four or five differences. But one would be it'll break into point A, then laterally move to point B. Next you know, it's trying to break into point A again. You know what I mean? It's like, I get the drone swarm, but you could probably coordinate and think a little bit better. That's where it's at today. It'll get better and cleaner. But the differences are first and foremost, the scale of what AI can do dwarfs humans. Like in ways humans don't even get.

• 6:21David George?

  Right.

• 6:22Speaker 00

  So you have a scaling problem in that humans could always find only one path into a network.

• 6:26David George?

  Yeah, they had to be selective because they had to devote their limited resources to one direct path, right?

• 6:31Speaker 00

  Yes. And then so scale is a challenge. Speed ridiculous. What AI does in a microsecond would take 70 humans. They can't even do it. It's apples to oranges. And then, so what was always lacking is AI creative or effective. But when it comes to what we do, we don't need the fanciest model. We're not trying to speak 400 languages with our models and all that kind of thing. What Armadon is doing on offense is we're finding vulnerabilities, exploitable risk. That is code. That's a structured language, a structured process. Because it's structured, AI is going to be great at it.

• 7:08David George?

  Right.

• 7:08Speaker 00

  Right? So I really think it's already here today. Like the whole, let's slow down the models. We don't want cyber risk too late. The open models are already good enough and these things are coming now. It's just a matter of the minute you have anonymous availability of GPUs, you'll see far more criminal attacks.

• 7:26David George?

  Oh, interesting.

• 7:27Speaker 00

  Yeah. You know what I mean? But until you can attack anonymously, and it's hard to do crime when people know your name. It's better if you can, if you can commit a crime anonymously. Here's my tip for criminals. If you can commit a crime anonymously, that's a lot smarter than doing it with your jersey on with your name on it. And so anyway, the difference in attacks and what we're seeing now, we are at the precipice, first inning still of AI-led attacks coming. And I think that's just because of the cost and availability of the models is not as readily available to criminal element as it will be in the future.

• 7:58David George?

  Yeah, exactly. Okay, so you, your experience in working in the security industry for 30 years. You probably saw a fair amount of nation state attacks, right?

• 8:10Speaker 00

  Every day.

• 8:11David George?

  Every day. So talk about the differences or similarities between nation state attacks. And I use that just to say the most sophisticated, most, most successful, if you will, types of attacks compared to AI today? And then where you think AI can be in a couple of years?

• 8:28Speaker 00

  So everything's going to change rapidly, right? But I can tell you, nations on offense have never, in my opinion, they've never really been, when you're hacking for espionage and for security reasons, you hack with what I would call kind of a sniper round. You're not spraying and praying. For the most part, modern nations on offense restrict their targeting and they go deep at very specific things like 30 defense contractors or .mil. And they go hard at that. Kind of think of it as that sniper round. With AI, I think it becomes more like a drone swarm. It becomes a little bit different in the cyber domain. And I think even modern nations are thinking, what will our protocol be?

• 9:12Speaker 00

  If we want to attack this company, do we swarm it and just burn tokens on it? Because AI is going to do a lot of things humans just wouldn't.

• 9:21David George?

  Right.

• 9:22Speaker 00

  So it's a little sloppier, a little louder, but it's more effective.

• 9:26David George?

  But it's more comprehensive, right?

• 9:27Speaker 00

  You got it. It's more effective probably. And so there's going to be so many things a nation's got to think through right now. And their whole doctrine will shift as the AI shift change comes. Like how does AI change what our mission is? Do we maybe use the cyber domain differently? Do we drone swarm sometimes, sniper round other times? How do we balance the two? Does it depend on risk, target, how surreptitious we want to be? Cause right now AI is not a surreptitious action on offense. Unless you've done a ton of post-training, you got to maybe a human in the loop, really looking at, are we doing smart things? Because if you just go, hey, here's a prompt, hack abc.com.

• 10:07Speaker 00

  AI is not going to do it in a surreptitious, smart way. And I think even if you ask it to, it's still not going to. Till it's been really trained and really had some human influence on it. So, but more generally, what you're going to see is less capable attackers, less technical, less successful, are going to appear way more successful. It's the equalizer, right?

• 10:29David George?

  Yeah, because of the volume.

• 10:29Speaker 00

  Yeah. Every, when you start using models, over time, what it's going to be is, on the defensive side, we're going to say, we're being attacked by these models, but we're not sure who's behind them, those attacks. Is it a nation? Is it a human? Is it, and we'll have some clue, but attribution will get a little difficult. So that's a long-winded answer of saying in the AI age, it does democratize far greater expertise for attacking victim networks.

• 10:55David George?

  Yeah. So then that is a good segue back to Armadon. So you have talked about the defense needs to be a great offense, right?

• 11:05Speaker 00

  Yes.

• 11:05David George?

  Like, like best.

• 11:06Speaker 00

  Got to train your defense with something.

• 11:07David George?

  Yeah, of course. You got to train your defense with something. And then it needs to be continuous.

• 11:11Speaker 00

  Right.

• 11:11David George?

  Right? So, so how does the product work? And then how do you get a level of sophistication such that you can identify and remediate these vulnerabilities, like what you're describing? They're more sophisticated than a basic prompt.

• 11:25Speaker 00

  Okay, lot there. I could talk for 45 minutes on it. But first, I can tell you this, you don't have a defense unless you have a great offense to go up against. You know what I mean? Like, so even think in sports terms, if you want to be the Baltimore Ravens defense in 2000, you kind of want to have your practice offense really push you. You know what I mean? So that you know how good you are. And that's what Armadon is going to do. We're going to be, you know, the all-star team on offense coming at you. So you can train your defense with, with what we're doing. And that's, that's going to be important. And you can't really have a human in the loop in the AI age for tactical autonomous defense. Like, you got to do something fast. You know, you got to tourniquet the wounds as fast as you can. So thinking back to our, like, you want to be able to do it continuously. And that's the complexity.

• 12:10Speaker 00

  So we do a thing called a hyper attack.

• 12:12David George?

  Yep.

• 12:13Speaker 00

  And David, that's just a fancy word for we throw a drone swarm of agents at you and we map your network, every service, every route, every system, all assets. We may end up with terabytes of metadata on your network from this hyper attack, done super fast, just it lights you up. So that, that way, we can now, it's almost like a metadata twin of what we can see. If we're on the inside, do the same thing. Let's just map everything. This is the attackers view of your network. But with that metadata, we now just poll you almost like a heartbeat. What's changed? What's changed? That's continually looking for, did an app change? Did a route change? Did a service get updated? Did a new machine get presented onto the, you know, into the target area?

• 12:55Speaker 00

  So that we can poll cheaply for change and then attack the change.

• 12:59David George?

  Yep.

• 13:00Speaker 00

  What you really want in the future, in the AI age, is that you want the constant pressure of models attacking you, but you can't do it all the time. Because A, it's not, it's cost prohibitive, but B, it's unnecessary.

• 13:11David George?

  Right.

• 13:12Speaker 00

  You do it when either the threat changes, hey, new models come out, new intelligence is available, or B, your network changes. So you want to test whether that happens.

• 13:22David George?

  Yep.

• 13:22Speaker 00

  And then C, you probably just want to test, we have a board meeting tomorrow. Let's see how we do.

• 13:26David George?

  Yeah, exactly, yeah.

• 13:27Speaker 00

  Let's audit ourselves to see where we're at. And that's what we had over the weekend. There was a zero day in a popular product. And Amelia, we've already got the heartbeat. We just polled who's got the problem.

• 13:37David George?

  Yeah.

• 13:38Speaker 00

  And our goal at Armadon is to go from, you know, common vulnerability or CVE to, or a, we can find if it's exploitable or not before bad guys can.

• 13:49David George?

  Right.

• 13:50Speaker 00

  You know, and not all bugs allow for human access to your system in a stable way. So not all bugs are created equal, right? And so we want to make sure, hey, this one's one you really need to worry about, or which ones don't give remote command execution. So long story made short, that hyper attack, that metadata that we get, allows us to kind of poll for change and attack you when your network changes. And that's the best you can do for continual. And, and we'll get better and better at it. And the cost for the polling will go down. You know, it's on small networks, doesn't cost much. But on a network that changes all the time and is very large, you'd be polling it quite a bit to make sure you don't have an exposure window.

• 14:30David George?

  Yeah, of course.

• 14:30Speaker 00

  Yeah.

• 14:31David George?

  So that is actually a very good explanation for why this continuous approach matters.

• 14:35Speaker 00

  Right.

• 14:36David George?

  It's so fun, like, you know, you and I share.

• 14:38Speaker 00

  Well, you're already up against it. Somewhere out there, the criminal element will always have that random scanning. And they probably aren't even using AI for it. They've got one exploit that they think works and they're just kind of scanning the world for it and then coming at the exploitable risk, you know? And so you're already getting some pressure on your network from an unseen force that's not well-intentioned, you know what I mean? So you might as well have a better force built by the good guys, constantly putting pressure on you.

• 15:04David George?

  Yeah. It's interesting. So you would kind of, Armadon, I don't know, a year ago, would probably be placed in the category of pen testing. And you and I share history and relationship with George at CrowdStrike.

• 15:17Speaker 00

  Right.

• 15:17David George?

  And so they famously redefined the category from AV to EDR. And of course, they did incremental things.

• 15:23Speaker 00

  Sure.

• 15:23David George?

  But the category redefinition was on the back of major infrastructure changes and product changes, you know, and allowed them to create a product category that was far greater and bigger than AV. Talk about pen testing. What is the historical view of pen testing and why that's not what the future is?

• 15:41Speaker 00

  Yeah, a couple of things. I mean, you had to do it, right? It was kind of like first gen AV, you have to buy AV. And I think when you look at Armadon, we will be as ubiquitous as AV because you have to have that AI force field of AI on offense, training AI on defense. You have to do it and you can do it. So why wouldn't you? And so you look at that and

• 16:03Speaker 00

  it's, pen testing to me is always just scanning for what's already known. And it doesn't prove whether you're really exploitable or not.

• 16:11David George?

  Right.

• 16:11Speaker 00

  So it's always created a larger list of volumes that don't matter.

• 16:16David George?

  Right.

• 16:16Speaker 00

  And so the way we wanted to do it at Armadon was, we actually can carry the exploit out. We verify, so there's no false positives. We can get remote code execution or get data off of that machine. And a lot of pen tests are nothing but hit your infrastructure, not with a thinking, learning technology that memorizes and knows your infrastructure like an AI agent can. So it's not going to do custom apps. It's going to, at least the old versions of pen testing, you know, the Tenable, the Rapid7, the Qualus was more a hygiene sort of thing.

• 16:49David George?

  Right.

• 16:49Speaker 00

  What do I have out there and what services are exposed? And are there CVEs available against those services or known exploitable volumes against them? When you have an AI-based attack, it'll find logic flaws rather than code flaws in custom applications. It'll exhaust all routes all the time. And it's like, all I can tell you is Armadon since January of this year, in 2026, we have found over 90 zero days at customer sites, all in production. And.

• 17:20David George?

  And by the way, your customer base is like.

• 17:22Speaker 00

  They're happy we found them.

• 17:24David George?

  And they're like, fortune, this is not like, you know, rinky-dink companies. Like, these are like Fortune 500 companies.

• 17:29Speaker 00

  Yeah. And I don't mean that as fear, uncertainty and doubt. But the difference is that we've trained our models, we've post-trained all our models with real red teamers, real folks that actually can develop exploits. And that's important. And so when we're scanning networks, we don't have source code to review. We're not finding these zero days with source code. We're not finding these zero days because we can log into an app and now we have access and we can get to other things. We are black box coming from the internet over 90 zero days in major software companies. And they're thankful. And so you, everybody's like, wow, Mythos came out and you can scan source code and find vulnerabilities and you find thousands of them. That's noise.

• 18:08David George?

  Yes.

• 18:08Speaker 00

  We're coming from the outside and then we're calling a CISO, you know, usually within 48 hours, hey, we've got remote code execution in your DMZ. And usually from there, we're getting in. And they agree with us. And they, and the nice thing is we're going through, you know, the fix side's a little bit harder, takes a little bit longer. But those companies go right into incident mode. They respond as if it's an incident. And that's not a pen test. That is like a real adversary coming at you. And the difference between red teaming and pen testing is pen test to me is a hygiene step. And I think over time, everybody would have red teamed everything all the time if they could.

• 18:46David George?

  Right.

• 18:47Speaker 00

  It was cost prohibitive and people prohibitive. With AI and an agent doing it, or in our case, we have lots of different types of agents doing different things, you can now do that. So I think it'll replace pen testing over time.

• 19:01David George?

  Yeah.

• 19:01Speaker 00

  That's just, that's like a small portion of what a red team coming at you would do.

• 19:07David George?

  Yeah. So you talked, you, you mentioned earlier, you know, obviously that's Armadon red.

• 19:12Speaker 00

  Yeah.

• 19:13David George?

  You mentioned Armadon blue. Talk about Armadon blue.

• 19:16Speaker 00

  The Armadon blue is like, we can't, David, just show up and say, hey, you know, you're vulnerable, see you later.

• 19:21David George?

  Right.

• 19:22Speaker 00

  And hey, the true north for every CISO should be effective autonomous response. We got to build that. And, and we knew all along, you can't just say, hey, we, we want to be the best in order of finding exploitable risk. That's goal number one. But then goal number two, and be the best in order of doing something about it. And that means Armadon blue. And Armadon blue will be, take the information about exploitable risk and work with the defense plane, you know, whether it be endpoint EDR or firewalls, and create compensating controls at speed.

• 19:55David George?

  Yes.

• 19:55Speaker 00

  So that if we find an attack, five minutes before someone else using a model finds an attack, you're already safeguarded. And these safeguards are going to be rudimentary, potentially out of the gates, right? Over the next few months, a year from now, they're just going to be there.

• 20:08David George?

  Yep.

• 20:09Speaker 00

  Because the whole cyber domain is progressing at a speed where you're going to have to defend autonomously, for better or for worse.

• 20:16David George?

  Yep.

• 20:17Speaker 00

  You know, I, I'd rather have a bad patch stopping a bad guy from getting in. Then have an intrusion.

• 20:25David George?

  Right.

• 20:25Speaker 00

  You know what I mean? So you gotta take your lesser of two things. And one's much more manageable. You never want an unknown person with arbitrary access on your network.

• 20:36David George?

  Yeah.

• 20:36Speaker 00

  You know?

• 20:36David George?

  Yes, yeah.

• 20:37Speaker 00

  And so you want to prevent that any way you can. And I would say the first generation is we're working with CrowdStrike on it and they know it has to exist. We're working with PAN on it. They know that it has to exist. They want to all, you know, shift into the AI age with autonomous defense as well. And so we need to inform those defense platforms, you know, the Fortinet's and everybody else. Here's what you can do about it. And I likened it to, you know, kind of field dressing in war. Someone gets shot, you patch it up, but that's not the hospital. You know?

• 21:06David George?

  Yeah.

• 21:06Speaker 00

  That's a, hey, we kind of stop the bleeding. And, um, but then you gotta maybe do something else with more time in humans potentially, or even, you know, agentic approach to it down the road. So you're going to see it happen even in, if you're a CISO, you're going to see autonomous defense happen even if you don't ask for it.

• 21:24David George?

  Right.

• 21:25Speaker 00

  Because of the defensive platforms you've already invested in.

• 21:27David George?

  Yeah. You mentioned earlier, um, you know, some of the blurring of the lines of different categories within cyber. And I think you joked that your, your old days, your 30, you know, your 30 years of experience is, uh, is out the window or relevant or something like that.

• 21:45David George?

  What is the future of the SOC? And then what do, how do the categories, how do the categories within cyber blend together or change?

• 21:52Speaker 00

  You know, if I'm a CISO, I do believe my true north is effective autonomous security. You want to keep your best people engaged. You want to automate the processes that work for your organization. But you are absolutely saying what survives in the AI age and what doesn't.

• 22:08David George?

  Right.

• 22:09Speaker 00

  And I think we're still working through that process. I think there's whole processes in the SOC that'll just go away. And for whatever reason, we're automating right now.

• 22:17David George?

  Yeah.

• 22:18Speaker 00

  You know, it, over time, I can tell you this. If you have humans in the detect and respond loop, you're going to be too slow.

• 22:26David George?

  Yes.

• 22:27Speaker 00

  You know what I mean? It's just not going to work well.

• 22:28David George?

  Mm-hmm.

• 22:29Speaker 00

  So you have prevent, detect, respond. Prevent's going to be governed by AI and detect and respond is going to be done by AI. And the goal in cybersecurity has always been if you have, you know, you want to prevent.

• 22:40David George?

  Yeah.

• 22:40Speaker 00

  You know what I mean?

• 22:41David George?

  Yeah.

• 22:41Speaker 00

  You don't want to detect and respond. So I just see the constant narrowing of the window of every phase to the point where, you know, we're really not doing a lot of detection and response. Cause the window to do it.

• 22:53David George?

  It all happens too fast.

• 22:54Speaker 00

  Yeah. You got it. It's a little bit too fast. So, but you still gotta have that onion peel to some extent of systems backing up systems and assuming failure somewhere.

• 23:02David George?

  Right.

• 23:03Speaker 00

  You know, like even Armadine creating in the force field, sooner or later, somebody's going to get around it. Someone's going to create an exploit before we find it somehow, some way on a platform or, or a, um, or an app that we just haven't assessed yet. It hasn't been in production at a customer site. And so we haven't looked at it and someone else finds it. And when they do that, you will want to have a trap behind saying, we've got unauthorized access or unlawful access to a system. Those traps are, that you just can't have a human there.

• 23:34David George?

  Yeah.

• 23:34Speaker 00

  I mean, it's just gonna, because we've already done it at Armadine. When we break in and have agentic aware internal command and control, it proliferates at a speed that is shocking. You know, like I remember as a human, you're like typing on your keyboard. I want to go laterally move with this passphrase from here to here. And you're so slow and you're doing one thing at a time. This thing just does a thousand things at once. It's just a everywhere and you're like, whoa, okay, done.

• 24:00David George?

  Yeah. So the, so the, each one of those steps of the process has to be automated. Can't be a human loop.

• 24:06Speaker 00

  Yeah, it's as bad as this. I mean, I don't have great analogies. It's like the balloon popped, you know?

• 24:10David George?

  Yeah.

• 24:11Speaker 00

  Someone gets in, it's just like, they're gone. Your whole defense apparatus just popped. So you gotta get prevention right. And then an immediate lockdown on detect and respond, however you want. And there's always gray areas between those phases. Cause people say if you detect and respond automatically and fast, that is prevention.

• 24:27David George?

  Yep.

• 24:28Speaker 00

  So all of it's going to change. Every system's examining it. Every vendor's examining their role in changing into the AI shift. And, uh, so it's going to all change now, but I can't tell you if anyone's positive on how it changes. They're examining their workforce. They're examining their headcount. They're examining their processes, meaning the CISOs are. And they're saying, what do I need to look like in the modern era? But it's too soon to tell where it lands.

• 24:54David George?

  Yep. Um, so too soon to tell what they look like, what their defense apparatus looks like.

• 25:00Speaker 00

  Yes.

• 25:01David George?

  Maybe, so you have a bunch of Fortune 500 customers. You're close with a bunch of others that are not customers. Like what is the state of their vulnerability today?

• 25:12Speaker 00

  Rapidly shrinking. You know, everybody's worried. There's a desperation in the moment in both directions, by the way. If you're on offense in Iran or Russia, you have a desperation in a moment of getting now.

• 25:23David George?

  Yeah, could get it, get it before the security is in place.

• 25:25Speaker 00

  Got it. And then if you're on defense, you're of a desperate, uh, you're desperate to patch every window.

• 25:32David George?

  Yeah.

• 25:32Speaker 00

  You know? And in fairness, both sides are accurate in their desperation. I mean, because we have near-term pain in the AI age that it advantages offense.

• 25:42David George?

  Yes.

• 25:42Speaker 00

  Right? So that's fine. That's, that's just the nature of it. But both sides recognize it's for long-term gain.

• 25:49David George?

  Yep.

• 25:49Speaker 00

  Meaning AI on defense, being trained by AI on offense and being autonomous, is going to do a far better, more diligent job than humans peering at packets, you know? And so we're just going through the window of exposure, let's call it, where everyone's at risk on defense and they're all hustling. I've seen incredibly powerful efforts at every company right now. And I'm not aware of any large one A enterprise not actively scanning for exposure and doing something about it in real time. And what's interesting, David, is it's like, and it's team ball everywhere. Like the CIO, the CISO, the product teams, the business lines are all like, okay, we found something. And it's almost like war roomed.

• 26:30David George?

  Yeah.

• 26:31Speaker 00

  Like, we gotta go fix this.

• 26:32David George?

  Yeah.

• 26:32Speaker 00

  You know, and the composite of those teams are pretty broad. So there's no way to make the next year pretty. That's the best way to say it.

• 26:38David George?

  Exactly.

• 26:39Speaker 00

  You know what I mean? It's, it's a cocktail party out there right now, a digital cocktail party. And, um, everybody's in a race.

• 26:45David George?

  Yep. Yeah, it's, one of our most sophisticated companies told us they took a large percentage of their engineers and research organizations and just devoted it toward fortifying their own walls.

• 26:56Speaker 00

  Yeah.

• 26:57David George?

  Which was like an all hands on deck.

• 26:58Speaker 00

  Yep.

• 26:58David George?

  Um, and, you know, the alarm bells started ringing very recently. Like this is within the last few months, right?

• 27:04Speaker 00

  I think Mythos was the biggest. I mean, we saw it coming long before Mythos, but the Mythos moment from a marketing standpoint, got everybody to go, okay, threats changed.

• 27:12David George?

  Yep.

• 27:12Speaker 00

  And a lot of people said Mythos came out, find vulnerabilities in our own software. And you have to do that if you're doing software security out of station. So all the vendors ran out and did that. But the way I responded to Mythos is that just made it very well-known about AI on offense coming at you. And, uh, I think that's what accelerated it. You know, that was pretty much a firm stamp. It's coming.

• 27:34David George?

  Yep. What about the hugging face incident? I'd love for you to talk about the learnings from that.

• 27:39Speaker 00

  I've given that a lot of thought. I mean, I'm certain at OpenAI, like, oh, or at a regular, they were like, ah, we could have done this and this, and it wouldn't have happened. You know what I mean? So they've already figured it out. It's been my experience in every technical modality shift, we underestimate the adversary's capability. And in this case, we underestimated the model's capability. Because, you know, when you really read it post facto, ah, they could have stopped that, you know?

• 28:03David George?

  Yeah.

• 28:04Speaker 00

  And, um, they could have put guardrails on it, some deterministic things. And, uh, and I think they realize that now. But I think when you're in a race, it's almost like a lunar landing race, right? The AI race. And you have R and D people and they're doing the work to create models in a way where even those CEOs are like, we can't slow it. Let's get the government to help us slow it. You know? That means you can't even control your own innovation, right?

• 28:26David George?

  I have views on that, but we could take it another time.

• 28:28Speaker 00

  And so when you have, and I get that, R and D people are like chasing that innovation. And it's really hard to package them with then like security, experienced security people that have the skillsets to cage that thing.

• 28:42David George?

  Yeah.

• 28:42Speaker 00

  You know? And it's hard to marry those two up because the security people don't understand the AI as well. And the AI people don't realize, one of the things that we did in our model, I mean, make no mistake, Armadine has made the beast that we're all worried about. We've made a model that attacks. We made many of them. We have a system that attacks production networks and is highly successful breaking in. Well, is it safe? Well, our guys instinctively knew, we gotta have obviously a secure, you know, we gotta have a hypervisor, we gotta secure this thing, we gotta lock it down, host base. We have to have a proxy. It knows the proxy, it's proxy aware, that's fine. But then our guys did something and even I was like, nice job.

• 29:22Speaker 00

  They passively, surreptitiously look at every single prompt done. Do we like it? Do we not like it? And the majority of the time, if we kill an agent, it's probably nothing to do with safety. It's that the agent's wasting money.

• 29:36David George?

  Yeah.

• 29:36Speaker 00

  You know what I mean? So kill it. It's off on a goose chase we've already done or don't want to do. But there were so many layers of validation that the agent was doing the right thing. And the other thing was assume every layer of your security will fail. And you have to have deterministic rules that eliminate certain activities. But what I did learn, reading those incidents, it does take domain expertise to secure agents behaving in certain domains.

• 30:04David George?

  Yeah.

• 30:04Speaker 00

  You know what I mean?

• 30:05David George?

  Yeah, it's a great.

• 30:05Speaker 00

  So I get that. So like, like without a cyber background, I get how you're going to make, you're going to test something, go, ah, didn't think of that.

• 30:13David George?

  Yes.

• 30:14Speaker 00

  And you would have had to have an experienced team look at what the, the evals look like to say, you know what, it's going to do this and it's going to do that. So you got, that's why Armadine, we combined the exploit developer types and red teamers with the AI folks. Cause our evals most of the time are made by the red teamers.

• 30:32David George?

  Right.

• 30:32Speaker 00

  You know what I mean? They're the ones that understand this stuff. And we created 24 kill chains at Armadine that humans have done in the real world, period, at different victim sites and, and our experienced operators have done when testing networks. And we had no model go through the entire kill chains of more than eight. So that's where it was eight out of 20.

• 30:53David George?

  Yeah.

• 30:54Speaker 00

  And here is what's weird, by the way. We tested the open weight ones and the most advanced closed models, they all found eight.

• 31:00David George?

  Yeah, really?

• 31:01Speaker 00

  So if you're, yeah, so it was all about just speed and cost, you know?

• 31:04David George?

  Yeah.

• 31:04Speaker 00

  And, you know, the closed models were faster to finding exploitable risk, but that's coming down. But we kind of let the open models run longer and they got to the same place.

• 31:14David George?

  That's it.

• 31:14Speaker 00

  So in the cyber world, the differentiation between closed and open is not as great as in other domains probably.

• 31:21David George?

  And it's compressed. Yeah.

• 31:22Speaker 00

  Yeah.

• 31:23David George?

  I would say that's somewhat consistent.

• 31:24Speaker 00

  Yeah.

• 31:25David George?

  In terms of like the capability gap, at least closing a little bit. But that's interesting that their performance is basically the same.

• 31:33Speaker 00

  From my perspective, seeing the charts from the team, all the lines ended up in the same place. You know, and when you're looking at, it was immediately time. Uh, cost and then call it effectiveness or creativity. They all ended up at the end of all their operations where they hit diminishing returns. They ended up in the same place, not on cost, though.

• 31:54David George?

  Yeah, not on cost. Yeah, that makes sense. Yeah, that makes sense. So it's a, it's a decent segue maybe to talk about what kind of models you guys are using. And then what role do you think the lab companies play in the future?

• 32:05Speaker 00

  Well, and I don't even know if I finished answering your last question, other than domain expertise on security is going to have to work with the AI folks. Cause I did read the, you know, the, the meter publication and I was like, well, these guys are AI people, but I'm not sure they've done a lot of investigations.

• 32:20David George?

  Yeah.

• 32:21Speaker 00

  And that's going to happen again, the modality shift, because here's one. It's when cloud started emerging, you know, I was running a bunch of incidents. We were responding to breaches for a living at Mandiant and we had to learn what's a cloud breach look like.

• 32:34David George?

  Right.

• 32:34Speaker 00

  We now have to learn what's an AI breach look like, how much data is at Anthropic or the model companies that are being leveraged to do the attacks? What do you wish they logged and how they will change behavior as well to have better audit trails, better forensic capability. So it's early onset to the technology and we all clearly have to mature into it in a way where we have the accountability. When these things go rogue, you can say, here's what happened and when, and it shouldn't be like two weeks of forensics to figure it out. I hate to say it, like we log every single thing our agent does, source IP address, time and date and what it did. You know, so you gotta go backwards and replay these things. And I think they've learned lessons the hard way and they're probably way better today than they were even three months ago.

• 33:18Speaker 00

  I'd open AI and Anthropic and testing these things. And whoever had a regular labs, they're looking at this going, okay, we gotta tighten up a little bit here. And, and I get, they were surprised because they underestimated it. And we've, and we've done the same with human adversaries. It is the weirdest thing. My whole career, everybody underestimates the top tier of what you're up against.

• 33:38David George?

  Right.

• 33:38Speaker 00

  Cause you don't have to see it every day.

• 33:39David George?

  Yeah.

• 33:40Speaker 00

  You know, and, and you don't want to fear the, the bogeyman, as they say under the bed. So you don't want to have FUD, but you still want to respect the technologies that you're creating and test them in a way that is meaningfully guarded. Got to cage the beast, David. Do you know what I mean?

• 33:55David George?

  You do. Love it.

• 33:56Speaker 00

  And I would argue cage it too much, release a little bit, find the line. Because if you do overly deterministic, here's the, the art form to safety, running AI, at least in cyber on offense. Is you want to leverage the intelligence of the frontier labs to do stuff, but not do the wrong stuff.

• 34:16David George?

  Right.

• 34:16Speaker 00

  So you need classifiers, you need a model that looks at everything going outbound, everything coming inbound. We've created that with people and humans going thumbs up, thumbs down. That's good, that's bad. You gotta train it, classify and look at it. But if you get too deterministic and disallow too much, you're probably not leveraging the creativity of it. You let it out, some, so it is a gray area. And that's the problem with that gray area is that's why no one would ever say, we're a hundred percent certain we're going to get what we expect.

• 34:43David George?

  Yep.

• 34:43Speaker 00

  You know, period. It's, it's, it's a battle we even have, but we have yet to have an issue because we can put a human in the loop. Or we have classifiers to say, human needs to decide this. We don't know what the hell just happened. You know what I mean?

• 34:56David George?

  Yeah, yeah.

• 34:57Speaker 00

  So if you're inspecting everything that's come, you know, either prompt to the, to labs, everything coming back and something comes back. And we don't know what the hell it is, pause, escalate, judge.

• 35:08David George?

  Yeah. What do those great security operators look like inside Armin?

• 35:14Speaker 00

  A lot of experience, 15 years on offense, 15 years of red teaming. I think we've red teamed literally 99 out of the Fortune 100 throughout our careers.

• 35:22David George?

  Wow.

• 35:22Speaker 00

  We didn't get one and I know who it is and they've never hired me and I love their products. So one day maybe I'll get.

• 35:28David George?

  How do we get, let's go get those guys?

• 35:30Speaker 00

  Talk to them all the time, never landed them. That's all right. They might be good. But, uh, you know, they are very experienced and, uh, and they all, you know, when I look at our 90 plus zero days, the majority have been found by human.

• 35:43David George?

  Right.

• 35:43Speaker 00

  But they're found by humans because we're leveraging AI to do 90 plus percent of the tedious work, which is pen testing done automated. Web app pen testing in creative, articulate way done automated for the 98th, 99th percentile. But we're still putting humans on it. But here's where it gets interesting, David, the last few zero days, tech found it.

• 36:04David George?

  Really?

• 36:04Speaker 00

  Yeah.

• 36:05David George?

  Oh, wow.

• 36:05Speaker 00

  So we've made the turn.

• 36:06David George?

  Yeah.

• 36:06Speaker 00

  You know, and, and most people already have made the turn. Their tech, if you're on offense leveraging AI, your AI agents are finding zero days.

• 36:15David George?

  Yeah. I want to shift gears now to, uh, your philosophies and mindset in building a company.

• 36:22Speaker 00

  You know, they're different. Yeah. So a couple of things there, like the first time I built a company was 2004. And I wouldn't have said I was an entrepreneur. I started Mandiant in 04, February, and it was self-funded and profitable. And we were successful because in hindsight, it's like you almost learned nothing at the time. And I look back and go, oh, I did learn right then and there because of the pain usually. But, uh, I, I remember, you know, I look back on Mandiant now, we had a premise, nobody actually believed in 04. Because our first website said, security breaches are inevitable and nobody believed it. And I don't even know how much I believed it and.

• 36:58David George?

  It's a pretty good tagline.

• 36:59Speaker 00

  By the way, I'm slightly off. Our first headline was, you cannot solely rely on preventive measures. And that was so boring. But that's same as security breaches are inevitable.

• 37:09David George?

  Yeah.

• 37:10Speaker 00

  Can't rely on.

• 37:10David George?

  Better, better ring on this.

• 37:12Speaker 00

  Yeah, I got it wrong because I'm not a marketing guy. But anyway, so security breaches are inevitable. And the premise was that let's respond to every breach that matters. So we have first mover intelligence on how to prevent it happening again.

• 37:24David George?

  Yeah.

• 37:25Speaker 00

  And so the first model of intel and all cybersecurity was antivirus. You know, it was like, we look for malware.

• 37:30David George?

  Yeah.

• 37:31Speaker 00

  We have signatures for it. And if we miss, David George has to find the malware and submit it to us so we get better. And that's a bad model. My mother's not finding malware on her laptop.

• 37:40David George?

  Right.

• 37:40Speaker 00

  I mean, it's just going to eat her laptop a lot. So that model was bad. So we decided a better model because I had responded to breaches. And the reason I was responding to them is AV was easily evaded. And so we were like, well, let's learn all the, you know, let's second layer AV because it stinks. And that's what George now owns, you know?

• 37:59David George?

  Yep.

• 38:00Speaker 00

  So that's second layer AV. You still have to have AV though. I beat it up, but the reality is, is you still need it. Um, or something that replaces it. So the second layer of defense was required. So AV was a maginal line to here, then you extend the maginal line with something that can learn and think. And, uh, so we wanted to do that. And I actually look at Armin, it's just the third wave of intel. Like, why are we waiting for a victim and learn from that? That's ridiculous. You've got to find your own problems first. Don't wait for, you know, defense contractor A to be compromised. And then quickly share the information to make sure it never happens again. And that model still needs to exist for the things that are somehow get there, they beat you. But, um, we got that model now and it's just not good enough.

• 38:43Speaker 00

  So back to your question, uh, you know, Mandiant was self-funded. There's not a, I don't know of self-funded companies these days, David.

• 38:51David George?

  Well, the speed, the speed requires that you gotta be fast. That's the difference.

• 38:56Speaker 00

  Yeah. You, you look at, we started Armin and the philosophies were different. When I started Mandiant, it was, hey, this is what we do for a living. Let's make enough money to do it for a living. That's it. I mean, so we hired the best people and we had a philosophy of, we're going to pay you more than our competition, but you're going to work harder.

• 39:13David George?

  Yeah.

• 39:13Speaker 00

  So we always felt like we had less people working harder.

• 39:16David George?

  But better people.

• 39:17Speaker 00

  Yeah. I think we had a, we were known for having great talent and that talent has prevailed. There was a time about a year ago, somebody sent me a text and they said, congratulations. 43% of the RSA main stage keynotes are Mandiant alumni.

• 39:30David George?

  Come on.

• 39:30Speaker 00

  And that's the text I got. I never verified it, but the guy's pretty accurate. Um, I'll take that stat if that's true, you know, and I think it probably was. You know, we, we've got a lot of reach over time, uh, with a lot of talent. And, uh, I mean, look at Founstone, look at George Kurtz. We, he and I worked together at Founstone in 2000. You know, he, he has spawned a lot of, uh, from Founstone, you've spawned a lot of successful companies and, and people. So same thing with Mandiant, but the differences are this, A, gotta be funded.

• 40:01David George?

  Yep.

• 40:01Speaker 00

  B, oh, your growth rate, get the market now. Like I look at Armin's opportunity, I feel like we have an 80 mile an hour tailwind, but we don't have a sales force. We don't have a go to market. We're not international. All that just has to happen. And the only way to thread the needle in today's economy to beat the bigs is get this go to market in place with exactly the right tech at the right time. And you better already have your act two ready.

• 40:26Speaker 02

  Ready.

• 40:26Speaker 00

  And your act three behind that ready because you don't want to get boxed into a corner. So Armadon's got an act two, we have our act three planned, but we're in the process of building go to market, which requires the funding and you have to build it ahead of time. The consumer AI companies created such meteoric rises in revenue. I don't think they can be replicated in enterprise security sales.

• 40:47Speaker 02

  Right.

• 40:48Speaker 00

  But you just saw the compression. Wiz got to over a hundred million in AR in 18 months from their first release, right? We're going to try to beat that. And that's what you have to do, especially when you're needed, necessary, and you have to exist. And that's not easy to do. So you've got to get the funding. You've got to constantly think, how do you rapidly grow? You can't let the wheels on the bus get wobbly, meaning how do you go that fast and maintain process?

• 41:12Speaker 02

  Yeah.

• 41:12Speaker 00

  At Mandiant's pace of we were self-funded and profitable with no competition because nobody believed the premise, we didn't get that wobbly, you know?

• 41:21Speaker 02

  Yeah.

• 41:21Speaker 00

  We just had great leadership and discipline and we could do it. Growing this fast, you have to hire scalable leaders right away than understand institutionalized process. You can't win with grit, gut and moxie, you know? You actually have to proceduralize, almost industrialize the Armadon way.

• 41:42Speaker 02

  Yes.

• 41:43Speaker 00

  That, you know what I mean? And that's what I'm trying to figure out. It's a, how do we do that and feel comfortable doing it? And here's complications. So let's do it. A, you gotta grow fast. B, in the AI age, it used to be development was at a speed where you trained sales at sales kickoff in January and you're good.

• 42:02Speaker 02

  Yeah, exactly.

• 42:02Speaker 00

  So I'm trying to figure out, wait a minute, we're different every two weeks. What is the modality now of having a sales corps that is right up to date? And here's the challenge that I thought every, every CEO I've talked to is like, how does AI change our business? And we all sort that out, but how does it change our manpower? When I look at AI's influence on sales, the reality in enterprise security sales is people still buy from people.

• 42:28Speaker 02

  Yes.

• 42:29Speaker 00

  You still need the same damn go to market structure for now. And in fact, it's even more emboldened because the tech's changing so fast, you can't put that onus on the customer to figure out, how did you change? Where is it at? So we have got to create a process institutionalized where sales is trained every week. Where are we at? How are we doing? And these are processes that will get you to win, you know?

• 42:50Speaker 02

  Yeah, paired with the credibility on the security side, right?

• 42:53Speaker 00

  Yeah, exactly. Yeah, you gotta be great. Yeah. And by the way, there is no replacement for any company I'm involved in. We are not ever aiming to be, let's be number two in our space. That sounds fun. It is be the best in what you do. And when we hire people, I remember getting a question once, somebody asked, well, how do you know when you're the best? And I'm like, when you are the best, you know it. You know, you have to be the best in what you do.

• 43:14Speaker 02

  If you have to ask the question, you probably not.

• 43:16Speaker 00

  Like, I'm pretty sure, you know, there was a time in, you know, LeBron James's career where he knew, I'm going to have to work harder to stay the best.

• 43:23Speaker 02

  Yes.

• 43:23Speaker 00

  Right? And that's how I want us to feel at Armadon. The sports analogies all work. Tom Brady never walked on the field going, well, I'm the second best quarterback out here.

• 43:30Speaker 02

  No, always.

• 43:31Speaker 00

  But it requires harder work, better people, and you have to constantly test, are we the best? Are we the best? And you learn very quickly from your customers if you got to do better.

• 43:41Speaker 02

  Right.

• 43:41Speaker 00

  So that feedback loop, customer straight in to the engineers is critical as well. So long-term, mid-short, speed has changed, got to do a capital raise, got to scale processes and test those processes all the time.

• 43:56Speaker 02

  Yeah.

• 43:56Speaker 00

  What I can't stand is chaos. A CEO's job is to absolutely like hide chaos at a company from the employees.

• 44:05Speaker 02

  Right.

• 44:06Speaker 00

  Period. You've got to make sure they're not like, we're like so loose, we have no idea. Wrong. You have to just say, here's the process. If process is too much for you to study, that's the person you go to. All you need to know is a guy or a person's name. And that's how I look at it. How do we grow rapidly without feeling chaotic? How do we grow rapidly earning it with better product? And how do we change fast? I don't know how long IP lasts. So it's like, you've got to build a Ferrari engine and say, you know what? Whatever we're doing today, someone else is doing in six months.

• 44:36Speaker 02

  Yeah, yeah, yeah.

• 44:37Speaker 00

  So how do you differentiate over the next six months is go to market.

• 44:40Speaker 02

  Go to market.

• 44:41Speaker 00

  Get customers and make them happy. You got it. The brand itself has to be built too. You have to become a brand that is the seal of approval.

• 44:47Speaker 02

  Yep.

• 44:48Speaker 00

  So I just gave you a jumbled answer. I wish AI could summarize really quick to here's the four differences. The funding, the speed, the branding matters, the go to market buildup. You have to build it way faster today than you had two years ago.

• 45:01Speaker 02

  Well, and the big reason why that's the case is because this is a tsunami like has never been seen before in security, in the security market, right? CrowdStrike, you know, and then the other players that were around it, they redefined the category, but they had to create the category.

• 45:17Speaker 00

  Yes.

• 45:17Speaker 02

  In the case of Wiz, part of the reason that it was able to grow so fast is because it was a bam, hit you like a ton of bricks pressing need.

• 45:23Speaker 00

  Yep.

• 45:23Speaker 02

  And so everyone felt like they needed to buy this or something.

• 45:26Speaker 00

  I think they innovated really fast too, though. You get a halo early, like, you know, you got to get the halo. And I personally think you get the halo, trade secrets. You get the halo by getting the right customers and making them ecstatic.

• 45:39Speaker 02

  Yes.

• 45:39Speaker 00

  You know, you like, no offense if there's a place called, I don't know, Suzy's Cupcakes, they don't get you the halo if you make them happy in cybersecurity.

• 45:47Speaker 02

  Right.

• 45:48Speaker 00

  But the money center banks do, the best retail does, the airlines do, you can get it.

• 45:52Speaker 02

  Yeah, of course.

• 45:53Speaker 00

  And so that's why Armadon's making one enterprise focus number one. Solve the hardest problems.

• 45:58Speaker 02

  Yep.

• 45:58Speaker 00

  And I think Wiz did that, so.

• 46:00Speaker 02

  Yeah, they did a great job of it in one of our companies too. We love those guys. All right. What else do you want to talk about, anything?

• 46:05Speaker 00

  Well, I'd never answer your question on the differences too. It's a, there's more founders today than ever before.

• 46:11Speaker 02

  Yes.

• 46:11Speaker 00

  There's more startups than ever before and they're all able to capitalize now. So you will have competition in anything you choose to do right now. There's no good, there's not going to be a Mandiant. Security breaches are inevitable and it's right and there's nobody else there.

• 46:25Speaker 02

  Yep.

• 46:25Speaker 00

  That's not going to happen right now. So everyone's in a crowded market. So I think every founder has to recognize you have to differentiate and probably right now because of the noise in marketing more than ever before, the only way to differentiate is get customer, make customer happy and repeat.

• 46:41Speaker 02

  Yep.

• 46:42Speaker 00

  There is nothing else that will differentiate you other than your customer base raving about you.

• 46:46Speaker 02

  Yep.

• 46:46Speaker 00

  So you better go do that. That's it. So I just gave away every trade secret I've got, but none of it's rocket science. It's like literally, honestly, it's the same thing that's always been in business.

• 46:54Speaker 02

  Yeah, but it's just at hyperspeed now.

• 46:57Speaker 00

  Just got to do it faster and that speed requires, never forget what you should focus on. Get customer, make customer happy, repeat.

• 47:04Speaker 02

  Yep.

• 47:05Speaker 00

  That's it. And you got to do that. And then everything else is like around that is to make sure you do that really well. The training, the sales enablement, the marketing, the people you're hiring, your hiring process, the teamwork, you know? So in some of the ways we differentiate as well, well, you know, we have all our engineers in one room.

• 47:23Speaker 02

  Yeah.

• 47:23Speaker 00

  We're a big believer in that, you know? I think managing distributed teams is more complex than standing up and asking questions and 20 people are in the room to answer.

• 47:32Speaker 02

  Slow speed, if nothing else.

• 47:34Speaker 00

  Yeah. So it's a great time to start a company though, because almost every, well, every industry is going to change.

• 47:43Speaker 02

  Yes.

• 47:43Speaker 00

  And in cybersecurity, every single tech stack is going to be different over the next two years.

• 47:49Speaker 02

  Yes.

• 47:49Speaker 00

  Yeah, the people are going to get ripped out, put in new tech. It's all got to be revamped and so it's fun and exciting to be part of that.

• 47:56Speaker 02

  It's the tailwind of a lifetime in cyber.

• 47:58Speaker 00

  Yep.

• 47:58Speaker 02

  Well, look, we're so excited about what you're building and through your partners. So thanks for being here.

• 48:04Speaker 00

  That was fun.

• 48:07Speaker 02

  Thanks for listening to this episode of the A16Z Podcast. If you liked this episode, be sure to like, comment, subscribe, leave us a rating or review and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts and Spotify. Follow us on X at A16Z and subscribe to our Substack at A16Z.substack.com. Thanks again for listening and I'll see you in the next episode. As a reminder, the content here is for informational purposes only, should not be taken as legal, business, tax or investment advice, or be used to evaluate any investment or security and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast.

• 48:51Speaker 02

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