LIVE From CrowdStrike's Fal.Con 2026 | George Kurtz, Michael Sentonas, Daniel Bernard & Justin Boitano

**John Coogan** (0:00)
You're watching TBPN.

**Jordi Hays** (0:02)
We are live from Falcon here with George Kurtz from CrowdStrike. Welcome to the show.

**John Coogan** (0:06)
Thank you so much for being here.

**George Kurtz** (0:07)
Always great to be back here with you.

**Jordi Hays** (0:09)
Always great to have you. Congratulations on everything so far. I'd love for you to start by taking us through the big announcements today.

**George Kurtz** (0:15)
Well, big announcements just coming out of my keynote today. First, we started with our Falcon Guardian product, which is in the category of AIDR. So if we think about the category that CrowdStrike really helped create around endpoint detection response, now this is taking really what we do for a human and a computer and applying it to AI agents.
Obviously, AI agents are more sophisticated. They have access to data, they have access to compute, to networking resources, they do bad things because they're like a bunch of drunk interns that you put on your network.

**John Coogan** (0:45)
They can do a lot of damage.

**George Kurtz** (0:46)
They can do a lot of damage, right? So we built this technology, we talked to our customers, we worked with some of our largest customers to really figure out what they wanted like Amazon.
And we're super excited because the missing link to accelerating security, sorry, AI adoption is security. Customers for the first time want to go faster somewhere and they need security to go faster as opposed to a brake pedal, it's actually a gas pedal.

**Jordi Hays** (1:12)
Yeah, if you go back throughout your career, I mean, you've been working in security for decades and I've just been really struggling with the order of operations for the predictions that have come true. Like we got the hugging face attack and then like three weeks later, someone was able to use ChachiPT to book a haircut. And it's just weird that we're getting capabilities in this very spiky way. Does this match your expectations? How does what you're seeing today go back to your original thesis when you started the company?

**George Kurtz** (1:42)
Well, it's interesting. When I first started the company, it was really based upon what we called AI, but it was machine learning back then. Sure. Again, it was being more predictive in using the algorithms to figure out whether something was good or bad.
Now, if you fast forward to generative AI agents, it's important to leverage all of the data that we've accumulated over the last 15 years to get to a point where we're still doing that. One of the second announcements we made was really the super intelligence cyber lab. Yeah. This was very exciting and we actually partnered with Nvidia to create really the first, what I would call the agentic security platform that is focused on a red, a blue, and a harness that continually learns from each other. Yeah. So we based some of our models on Nemotron, right? We can probably get to that, but just overall announcements. So if you think about what we're doing, it's really creating a frontier type model and harness at frontier levels specifically built for just the defenders.

**Jordi Hays** (2:44)
Yes. So with that cyber super intelligence lab, you're going to have more tailored models, more specification, probably spikes that go beyond what's available with the stock frontier products, I imagine, over time, if not immediately. But I'm interested in the benefits of open source, the benefits of thinking economically, because I imagine that part of the battle between attackers and defenders is starting to become economic. How many megawatts can I put behind this attack? Is that what's happening?

**George Kurtz** (3:17)
Well, the limitation, you're exactly right. The limitation for these attacks are really going to come down to sort of compute and cost. Because the knowledge, and I talked about this in my keynote, has now been democratized, where, whether it's a hacktivist, an e-crime actor, a nation state, they're all now equivalent because of agentic technology. And we called it the rise of the agent state, right?
Meaning that now the...

**Jordi Hays** (3:41)
Post-nation state.

**George Kurtz** (3:42)
Post-nation state, right? So the apex predator is now the agent state. And I think what's really interesting is, and it kind of gets back to your spikes in these models and those sort of things, is that when you go back to Hugging Face, it's a fascinating read. You probably have read it and there's some great papers. We were actually called in to help OpenAI go through some of it. I'll leave it at that, but the papers are out there.
And when you look at what these agents were capable of doing and just how sophisticated they were with note taking and communicating and maybe working as part of the collective, it's incredible. But the thing that I really called out in my keynote was, that's all ground breaking, but really what was the aha moment? The aha moment was the same incredible frontier caliber AI was available for the adversary in this particular case, it was agents trying to pass a test, but it wasn't available for the defenders. And these spikes come with the model refusals and all the guard railing that was put in place. So again, our models are specifically trained on our data, which we think is a huge advantage. Harnesses that we built, and again we fine-tuned in the model creation and post-training in concert with Nvidia to come out with incredible efficacy at the lowest cost. And this is what you were just getting to, because customers want the best outcome at the lowest cost.