No Priors: Artificial Intelligence | Technology | Startups
00:37:01 · Sarah Guo
[00:37:01] S1: The only tactical thing I I think is an interesting idea is the idea that you could, over time, if if it is going to be mostly agent written code, you could enforce better security architecture. And, you know, perhaps fear vulnerabilities or a lot of people where, you know, formal verification has always been enormously niche. Right? But even even short of that, like, okay, why is all the software insecure? Because, you know, one one big reason is that engineers are, you know, there's a limited number of them with limited capacity, and we're all trying to move very quickly. But if you can scale at the speed of compute or your willingness to spend and agents have infinite patience, like maybe we could actually end up with more secure software over time. It's an interesting... I
00:37:47 · George Kurtz
[00:37:47] S0: think there is like the industry's at a point now where the code is probably good enough where you're going to get definitely some benefits. But again, the code was was also trained in other areas like it was trained on stuff that you know may have had issues, so you know I have my own developer license. I build my own sort of apps and things like Claude and and you know I have my own security agent that reviews the code and it's like well Claude just created the code but then Claude is now with its security app going well that code is insecure. Well you just created it like why don't you just do that in the first part? You know, maybe there's some optimization, but I think what people don't necessarily realize is that even with with zero vulnerabilities, which I hope the industry can get there, you're still going to have breaches because a lot of what we see people today doing is they're not necessarily breaking in the logging in. There's such an issue around identity, but at the end of the day, we can get better code and we can have less vulnerabilities and we can ripple that through, that'll be great. The challenge is it's such a long tail. You take Microsoft as an example. Just because of all of the the. You know, compatibility that they want to maintain going backwards, backward compatibility. You know, there's things that never kind of get fixed or modernized. And you know, that's just one important element in our ecosystem. But think about all the other software that's out there. You're not going to just fix it all overnight, so it's going be a really long tail.
00:39:15 · Sarah Guo
[00:39:15] S1: You've been running CrowdStrike for fifteen years, and before that, you were an entrepreneur. Security... I've always loved security because, like, we're never... As a business person, it's both an interesting and important mission. As a business person, like, this problem is not going away. Right? But I I feel many many CEOs of large established public companies are feeling a little bit unmoored in this period of time because so much of the value that they have built in their incumbency is is being challenged. Like Mhmm. How do you how do you, you know, think about keeping yourself up to date, keeping the organization agile, continuing to win? General advice on that?
00:39:59 · George Kurtz
[00:39:59] S0: Yeah, happy to jump into that. So first, I think you have to recognize it's a different operating model and cadence. You know, we've got thousands and thousands of people, right? And when you think about some of the AI native companies that just started, they have a handful of people. Know, Claude is running all day. They've got agents doing all kinds of stuff like that's the that's the new world, which is great, but you can't be in a not that we are, but you can't be in like the waterfall mentality of development, like things pop out a year later, you're going be out of business. So I think you first have to realize that having these massive teams and these long schedules, like that is not going to cut it. So having smaller teams that are, you know, squads or you know smaller groups that are focused on a problem, they can leverage AI, but you can't have like thousands of people show up to solve a problem. You got to have a smaller team to be able to do that, and we've done that. We've done that with like our Falcon Guardian product, and to your point, like I was personally involved, you know, at three day a week meetings. I was involved in the design of it. It's like here's what we're doing. Like change this, change that, and you got to get back to your like startup roots because it takes that level of change. Know in a bigger company and there are many companies that are much bigger than we are, and you know you just can't be slow and plotting. So that's number one is to realize that the operating model and cadence is changing and you got to change what you got to disrupt yourself internally. And then you just have to look at like, well, what are your moats? If you're a system of record, it's a pretty big moat. We're a security system of record, right? And we have everyone's data for many years. And by the way, we're net data creators. Our sensors, we call them security agents, right? But I mean, like not to be confused with AI agents, the software that endpoint agents, right? That is a net data creator. So we're creating 7,000,000,000,000 or so events like a day. And if you're constantly creating this new data stream, that is going give you an advantage because what's the lifeblood of any AI system is the data that you feed into it. I think, you know, for us, it's always like, well, what are our motes? How do we look at it?
00:42:05 · George Kurtz
How do we make sure that, you know we disrupted the incumbents? We disrupted the semantics, the McAfee's, you know, all those other players are like all gone for the most part or changed or bought or whatever, and you never want to be in a position where somebody you know disrupts you. So we're always like, how do we disrupt ourselves? How do we do things differently? How do we think differently? But the end of the day, know, my main focus and I tell this to our team all the time. If we take care of the customer, the rest takes care of itself. What the customer wants is they want to be protected. They want to have trust in their in their vendor and their partner, and at the end of the day, want to make it super economical like no one wants to spend unnecessary money, so give them the best outcome at the best cost and an experience that doesn't take, you know, seven consoles and six chairs to run around in and just make it easy. That's the number one thing you know that our customers always tell me is like it is so easy to deploy your stuff. Just we're at a meeting this morning. It was like you know what we're There's two companies merging together. They're going to go with us. The other company didn't have us, and it was like, Your stuff just is so easy to deploy, and I think that's a big one is time to value.
00:43:16 · Elad Gil
[00:43:16] S2: So a lot of people right now are talking about job losses due to AI, although that really hasn't happened. I think the opposite has happened in terms of net job creation so far, And similarly, there's a lot of questions, What should my kids study? And What will happen in the future for jobs? The like. What is your view on that, or where would you recommend people go going forward? You know, is this even a long term issue?