Large companies need startup-speed teams and clear moats

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 38:37

   you know think about keeping yourself up to date keeping the organization agile continuing to win any any general advice on that 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, you know, Claude is running all day. They've got agents doing all kinds of stuff. Like 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, like you're going to 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,

2. 39:26

   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, you 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 in 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

3. 40:07

   disrupt yourself internally. And then you just have to look at like, well, what are your moats? Like, 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, but the software that endpoint agents, right? That is a net data creator. So we're creating seven trillion or so events like a day. And if you're constantly creating this new data stream, that is going to give you an advantage because what's the lifeblood of any AI system is the data that you feed into it. So I think, you know, for us, it's always like, well, what are our modes? How do we look at it? How do we make sure that, you know, we disrupted the incumbents,

4. 40:57

   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 at the end of the day you know if 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 vendor and their partner. And at the end of the day, they 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

5. 41:40

   run around and just make it easy. And that's the number one thing, you know, that our customers