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

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We are live from Falcon here with George Kurtz from CrowdStrike. Welcome to the show. Thank you.

Straight into it.

Always great to be back here with you.

Always great to have you. Uh, congratulations on everything so far. I'd love for you to start by taking us through the big announcements today.

Well, big announcements, uh, 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 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.

They can do a lot of damage.

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.

Yeah.

And we're super excited because the missing link to accelerating security— sorry, AI adoption is security. Yep. 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.

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 3 weeks later, someone was able to use ChatGPT 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?

Well, it's interesting. When I first started the company, it was really based upon— we called it AI, but it machine learning back then. But again, it was being more predictive and using the algorithms to figure out whether something was good or bad.

Yeah.

And now, if you fast forward to generative AI and agents, you know, 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. And one of the second announcements we made was really the Super Intelligent 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 Nimotron.

Nimotron.

Yeah.

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.

Yes. So with that Cyber Superintelligence 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 much, how many megawatts can I put behind this attack? Is that what's happening?

Well, the compute, the limitation, you're exactly right. The limitation for these attacks are really going to come down to sort of compute and cost. Yeah. 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, state, they're all now equivalent because of agentic technology. And we called it the rise of the agent state.

Yes.

Right?

Yes.

Meaning that now those—

Post-nation state.

Post-nation state.

Yes.

Right. So the apex predator is now the agent state.

Yes.

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 it'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.

Yeah.

But the thing that I really called out in my keynote was that's all groundbreaking, 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—

The drunk interns.

For the defenders. And these spikes come with the model refusals and all the guardrailing 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 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.

And I want probably AI review, AI/DR at every endpoint, every transaction, every API call, every single possible moment. And that could be very expensive if it's running on a really expensive model, right?

Right. Yeah, so our AI/DR is going to— again, there are 2 separate announcements, but you're going to be able to run that from the platform. announced it today, but the red Tempest, which is the name of that model, and the blue Solano, which is the defensive model, are part of the SafeMind system.

Sure.

Okay, so SafeMind, you think about as the harness, right? But those models and harness will be available in the platform to make everything smarter and better and faster. And then we have a trusted access program for customers in our Quiltworks program that they would be able to use the models directly.

Okay, so when you read the agent traces from the Hugging Face attack, do you see anything in there that feels difficult to detect? Because when I look at those, I'm like, okay, they're crossing a line. This is odd. This flags something in me. But we've seen examples like the how many Rs are in the word strawberry where AI just kind of falls flat on its face when you're trying to analyze a particular shape of problem. Yeah.

Do you—

how tractable is this problem? How optimistic are you about solving it?

Well, it's tractable because when we built our system, it was designed to look at sort of these, we call them indicators of attack. So if you look at the whole attack chain, and if you saw the keynote this morning, you know, it's just linking all these together. So irrespective of like what happened, these are kind of known attack chains. Part of the issue was it was sort of flooded with so much information That I think it was just sort of buried, you know, what's going on, is it real, is it not real? And what is going to really take place is the defenders have to use AI to be able to connect the dots on those, which we do, but you also then have to strip out all the noise. So you have to separate the signal from the noise, and that's where these sort of models perform well.

I mean, obviously there's an incredible amount of attention on AI. What is the role of deterministic threat detection these days? Is there still, is that a useful tool in the tool chest? Are there still advances being made there? Because I imagine that for certain problems, throwing a more deterministic, you know, security structure around something could actually be beneficial.

Well, you have to. And if you look in the Hugging Face incident, this was more of a forensics what happened.

Sure.

Right? If you think about deterministic, Security, it has to be in line and you have to make a decision. You know, you have to be right the first time, right? First time final, as we call it. So I haven't seen any sort of models, if you will, actually stop a breach in its tracks because it's, you know, as it's happening, you're kind of looking at data and those sort of things. It's not in line.

Sure.

So a lot of what the models are good at is sort of sorting out what happened, you know, sifting through lots of data and those sort of things, finding vulnerabilities. But you have to have a deterministic system, which is what we built.

Yeah.

And I think what people maybe get confused on or maybe aren't quite sure is when they hear things like Mythos, it's like, wow, you know, this super powerful model is going to hack the world. It really hasn't come up with a new invention of hacking.

Sure.

Okay, this is very important. It's come up with— it can find more vulnerabilities, so more of and faster, right? And when you combine those, you have And you combine and link these things together, you have greater success. But they haven't invented a new way to hack. This is very important because I think the public may look at this and say, well, Jesus, a super weapon that can hack anything. And it really is the same techniques. There's just more of it. And it can keep track of more things.

The concern is like you're taking a 10x hacker and making them a 1,000x hacker.

Correct. Yeah. It's almost like Iron Man. You put the suit on somebody who's smart. Is a heck of a lot smarter.

Yeah.

So how are the threats evolving? I imagine you've been talking about agent states, which makes sense as a new concept, but I imagine that you still have nation states that are deploying their own agent states.

Correct.

On their behalf. I'm sure the same thing is happening with various, you know, loosely tied hacker groups, but how is the threat evolving? What are you talking with customers about these sort of new threats?

Well, it's interesting and it is the agent state is going to help the nation state, the e-crime, and the hacktivists, right? Everybody in between. So obviously that's just an umbrella. But I think if you look across those different groups, they all have capabilities. They're all leveraging things like these open weight models, right? We talked about obliteration, really taking the guardrails off an open weight model.

For sure.

And you go to Hugging Face now and you can download these obliterated models and you can run them basically on a beefy Yeah. System, right? It's incredible. And you put a question in and you're like, there's no way it can answer this. And it builds like you want a full malware ransomware kit. Boom, it's done. Crazy.

Great.

So this is part of the issue. This isn't theoretical. It's here. And what customers are asking for is we want to give visibility into these agents. Got it. We want to stop these sort of threats, but we also want to know if it's an AI attack. It's actually very important question that they need answered. Is it an AI attack or is it sort of an adversary with maybe AI assistance? That's been one of the number one questions because it informs them on what they need to defend against, but it also informs them on how they express this to the rest of the company, the CEO, and the board.

Yeah. What's been the biggest, or what do you see as the, the biggest bottleneck for you in terms of actually deploying solutions to customers? They're asking you, do you need more Sales reps? Do you need more, just more customers to come to you? Just scale up what you already have? What's the shape of the next 12 months for you?

The great part of what we built at CrowdStrike is it's a very scalable model. It's a single agent, single platform with a single control plane. So you know what people need to do to roll out AI/DR?

Turn it on.

You know, sign the PO.

They need to turn it on.

That's it, right? It's the same agent that's there. That's great. And we spent a lot of time Making sure that we can instrument, we can find shadow AI. Is it Claude? Is it Codex?

Whatever it is.

Sure. We can instrument every action that agent has taken, every action with a specific identity, every tool call, every spawn of an agent, every network connection, every prompt. We have that visibility. It's incredible. So it's sort of like the EDR moment when we developed EDR. When we first showed people, they were like, I've never seen this before. And when you do this to an agent, they're like, we've never seen this, we've been dying to see this. So I think when you look at our model, we're combining a very scalable platform, turn it on, same agent. That's a huge win for us and a huge barrier to entry for other competitors. We have the most security agents deployed of any pure-play security company. So that's one. And 2, we combine that with a very flexible licensing model, which is Falcon Flex.

Yep.

So you'll be able to use It's a token-based system. So the more AI you use, the more you pay because there's more cost to this. But at the end of the day, you'll be able to use those credits and burn down from your Falcon Flex licensing model.

Yeah. And I imagine with Nimotron and just the advances in models, like, there's a world where token prices come down over time if you're scaling up and stuff. So there's a lot of flexibility there.

Well, and we have different models which make it a lot more cost efficient.

Yeah.

So the goal for us is to really— yeah. is actually to really, it is, it's not just one model. Yeah, of course. So we're really driving down the cost, and I think that's a huge advantage for our customers, and then providing that sort of trusted access. We've been doing this a long time, and customers want to retain their data and the provenance of that data, the sovereignty of that data with us.

Yeah, take me a couple quarters forward, a couple years forward, as far as you can, because it feels like there were sci-fi stories about cybersecurity incidents, related to AI. Then we got the Mythos moment, the Hugging Face moment. Now we have a really solid response, and it feels like there's, you know, the, the never-ending Cold War continues. But are we, are we in a stable equilibrium here? Are you expecting some big change one way or another in the posture between the 2 warring groups here, the red team, the blue team?

I think it goes back to the story as old as time. Yeah, it's good versus It really is. It just plays out now in the modern day with agents at a speed that we could never really contemplate.

But we can fight.

But we can fight, and we will. They'll get better, we get better. And part of what we delivered today with the lab is the red-blue training loop. Very important is that the blue learns from the red, right? So the defensive model continually learns from the offensive model, and you have a very fast cycle. It's very important. You know, there's going to be all kinds of new technologies, new agents, new systems, things that we haven't even heard of today. And we have to be able to defend against that. And I think what remains, while there will be a lot of change, what remains constant is security parallels the slope of the technology curve.

Yeah.

So the technology curve, I mean, you know, I started in the early '90s doing this, right? It was like this and then it's like that. So you have to have security that actually parallels that. We don't do everything. You know, what we do, we do really well. We're a big platform company. There's only a few of us. I think that's going to win in this market, but it's a big market. You can see by all the companies around here.

This is like a— for those of you that are tuning in, this is a— it feels like you set up a town here, like 10,000 people. It's massive.

It's unbelievable. Yeah, I mean, you know, maybe you'll see some of this in B-roll or whatever, but this is a massive security conference. We have Companies coming to this going, we're not going to any other conference. And it was just an offshoot because we've got the best customers. It's a big audience. But I think what's important to realize is we understand and value the ecosystem. We can't do everything. Like, what we do, we do really well, but it's part of the whole ecosystem and network, which is why NVIDIA was here. Obviously, Jensen Huang this morning, Libutan from Intel, Greg Brockman from OpenAI, all partners, plus all the many that you see here.

Yeah. Sorry, Jordi, please.

What groups or institutions are not paying enough attention to this new technology cycle that everyone here is like paying attention to this, obviously the AI boom, new threats, things like that, but is there a set of groups globally that need to be paying more attention to the new set of threats that aren't today?

Well, it's a good question, and I think the Mythos moment has really provided much more visibility from the board all the way down to the CEO level. I mean, my phone was ringing off the hook from Fortune 10 CEOs going, hey, what does this mean? How can you help us? Etc., right?

Yeah.

So, you know, from a visibility standpoint, that's good. And then you look at a Fortune— we'll call it a Fortune 500 company. For the most part, they have or will find the money to deal with some of this, and depends on the industry how much they spend, but generally they have a view and it's regulated, etc. The have-nots, those are the have. The have-nots are—

I mean, I'm thinking like local utilities.

Local utilities.

Hospital systems.

Hospitals, NGOs. Yeah, like utilities, forget it. I mean, they're running such old software. So it's the have and the have-nots. And I think part of what we want to do, and even working with OpenAI, is how do we help, you know, give a hand up to people who, you know, need it because they don't have all of the security people they need. They don't have the money for all of these sort of advanced software and technologies. But we got to— it's a collective community effort, and that's part of what we're helping to drive in partnership with many others.

What does it take to make it at CrowdStrike these days? You're hiring AI researchers now for your new intelligence lab. You have a lab.

With 270 PhDs. Wow.

Significant. So what is the shape of the new all-star up-and-comer at CrowdStrike look like?

The up-and-comer, I mean, it depends on the—

I guess the question is just like, how much AI are they using? How much are the human skills still hyper-relevant? What is the balance? How familiar do you have to be with these tools? What are the pitfalls? Because I think everyone's sort of realizing as they run large companies that people can get lost in the sauce if they're using— too reliant on it. How do you think about this in terms of like your own management style?

Yeah, I think that's important because I mean, we try to be very deliberate about it. Security is very important to us. So where we use it, how we use it, what groups we use it in, you know, we've expanded out obviously. But obviously a big part is going to be around coding.

Sure.

And you have to make sure that you get the right secure code out of it.

Yeah.

You know, it used to be in the early models, I would say a little less so now, but in the early models, it was like the early days when coding, when someone would go out to the internet and they would just copy and paste snippet of code, you would take that vulnerability and would propagate for everybody that needed, you know, that snippet of code, right? So, AI was originally generating some code, and you're, you know, I have my own models I've built. I, you know, have my own security agents that I built just to play around. And it's like, well, the same model that just built my code, then I built an agent to figure out whether it was secure. It was the same model that goes, it's not secure. Like, okay, why don't you build it, you know, in the first place. So you have to be aware of that. But what I think is important, getting back to your question, is if you don't buy into AI as an enabling technology and you're sort of scared for your job, you're not going to be successful at CrowdStrike. If you want to use AI in the right places at the right time with the right cost, we have all the room in the world for you here.

I love it.

And we have these sort of AI builders And we're deploying them into all the different functions. So those are the folks that you go, hey, it'd be great if we can do this. And you turn around and get some coffee and they go, here, it's done. Yeah, that's what we like.

No, I love that too. I love that too. Even in our small organization, we would love for you to sign this helmet. We have a Sharpie here. Would you mind signing right here? We want to get an autograph from you to commemorate the occasion. And we also have a gong with a mallet we'd love to get you to smash. Smash this for the occasion. Here you go. Give us a gong hit. We'll let you know how it goes.

I got to get a backhand on this, right?

Yeah, you can do a backhand.

Where's the sweet spot?

I think the sweet spot's right here.

It's right there?

Just give it enough force. You'll be good.

Oh.

All right.

With authority.

There we go. With authority.

Well, thank you for the gong.

And I just want to say, I love the aesthetics of everything here. You got Agents of Chaos back here. It's incredible.

It's incredible. Well, congratulations to you. How are you? Because I know you had a new baby.

I did.

OK.

That's breaking news. OK.

I had a new baby.

Sorry.

No, no, it's great. It's not a secret.

Did I scoop you?

You scooped me.

OK.

Sorry about that.

No, no, no. It's great.

All right.

Great to see you, George. Great to see you guys.

I hope to see you on the track, hopefully.

I'm going to leave it.

I'm going to leave it.

There we go.

But yeah, I won't walk away like I normally do. We'll see you at the track.

Yeah.

Stay tuned for the race this weekend.

We're excited.

Hopefully our men do well, and we'll go from there.

Okay, thanks so much.

All right, yeah, bye.

See you soon.

We'll talk to you soon. Cheers. Uh, that was fantastic. Of course, the show is breaking news, sponsored by Ramp. Time is money. Save both. Easy-use corporate cards, bill pay, accounting, and a whole lot more all in one place. Thank you to Ramp for making TBPN possible. We have a bunch more guests coming on from Falcon here in Las Vegas, and I believe we have our next guest ready to rock. We have Michael Sentonas, the president of CrowdStrike, here to take us deeper on everything CrowdStrike is doing in cybersecurity in the age of AI. The AI revolution is here.

Are you ready?

That's what it says outside. A little ominous, but probably accurate.

Accurate.

Good question to be asking. How you doing, John? Pleasure. Nice to meet you.

Welcome.

Welcome to the show. We're going to have you throw this headset on. We'll get this out of the way. Get comfortable. And we will ask that the microphone just go a little bit close to your mouth. 'Cause it's noisy in here. You've got a lot of partners here. It's a huge company, huge conference. Did you have anything to do with that? Are you the reason why everybody's here?

You know, a little bit of a reason.

A little bit of a reason, okay. Yeah, yeah. Well, yeah, let's start with your role. What do you do at CrowdStrike? Little bit of your history, and then there's a whole bunch of hot topics I'd love to go into.

Happy to go wherever you want.

Let's start with your role, your day-to-day.

President of CrowdStrike. So go-to-market reports into me, our product and engineering teams, researchers, our threat hunters.

Researchers too?

Researchers too.

Researchers and go-to-market, how are those— feel like different groups? How does that work? Is that operational? Are you spending more time with one or the other? How does that blend?

Look, I think my background, I started through the product side of the organization. I was the CTO of the company for quite a while. One of the things that I talk a lot about is you can build the best technology in the industry. If you can't sell it, if you can't talk about the value, if people can't deploy it and they can't ultimately keep themselves safe, it's kind of irrelevant. So it's trying to bring together the smartest people. Obviously you had George on before. We worked really closely. He's got a bunch of people that report into him as well on the engineering and research side. Yeah, it's bringing it all together and then making sure that we keep people safe and secure.

Yeah. What are, what are customers in the go-to-market side actually concerned about? Because there's an immense amount of attention on cybersecurity right now. I imagine that makes sales easier, but at the same time, we've all seen token maxing and AI budgets and people, you know, they have to find the money somewhere. So what is the tension that you deal with? How are you thinking about positioning that for customers?

Yeah, look, every organization has, huge requirements, but they've also got a budget. They've got a business to run. The business is not there unless you're a service provider and your business is cyber. You're building cars, you're building houses, you're in medicine, and you need to keep yourself safe and secure. So every CISO, every CIO is trying to basically do the best at what they can. They came into 2026, suddenly everyone's trying to work out how do I find tokens to pay for all of the things that the business is doing. Every second organization has token shock. So at the end of every month, they just realize that they spent $20,000 more than they should have per employee. And we got to work with everybody to show them there's a better way. There's a more efficient way. We give them a vehicle that they can procure and get CrowdStrike Flex that I think you guys have talked about with George in the past.

Yeah.

And we show them that they get a much better solution. It's just easier to live with day to day. It's not only showing them the cost of buying it, but how do they deploy it and then operationalize it? Yeah, because cyber, you got to live with it. You got to use it every day.

Yeah. Okay. So in deployment, let's talk about the balance between attackers and defenders in terms of AI capabilities. I'm pretty confident that you, OpenAI, Anthropic, the big labs have the advantage on raw power, intelligence capabilities in terms of defense and probably offense too, but you don't use it for that, you know. But does that map to your reality that the open source frontier is small?

The only difference is like you guys need to be successful every single time and an attacker only needs to be successful one out of 100,000 times, right?

Yeah.

I mean, that's the way it works. Okay. Every organization can't get it wrong. And equally, they've got additional pressure.

Yeah.

They've got to get it right 100% of the time, but they also have to not stop business.

Yeah.

It's easy to get it right 100% of the time.

Turn off everything.

If you turn off everything. So, you know, it's not gonna fly with the CEO of the company if every day, you know, the security technology is slowing people from browsing. You can't use the AI that you want. So there's an added level of complexity. The defender has things like change control. The defender has things like, you know, regulatory guidelines and process that they need to follow. attacker doesn't care about any of that. You know, you go to Europe where everyone in Europe is talking about like AI laws and privacy and regulation. I said at a conference, this is fantastic, you guys are leading the world in all of this regulation, and everyone was proud. The adversary does not care.

Yeah, the adversary, yeah, they're already breaking the law, so why would they not do—

why would they follow other regulations? They love it, they're in there, and that's kind of some of the challenges that people face with. And then you have the cost pressures. Yeah, you can't just pour everything into tokens. Yeah, you can't just pour everything into, you know, IT budgets. Yeah, so that's why we spend a lot of time making sure that you get the best that you can. And a lot of the time we come in and say, okay, here's a product, we're going to try to take 2 out. Yeah, it's not 1 in, 1 out, it's 1 in, 2 out, 3 out.

Sure, sure, sure. But so, talk about the pace of AI diffusion, AI adoption in in cyber? Because it feels like even though there's immense go-to-market operations, AI adoption among the bad guys has to be incredibly quick because it's often free. It's, you know, highly motivated.

Download Hugging Face.

Just download the thing. And so I feel like that's maybe more of the challenge than like raw intelligence. Is that a reasonable frame of mind to think about? The real scope of the problem is like the slope of adoption, like the good guys need to adopt more security AI faster than the attackers.

Look, we've talked about this for 20+ years. If you went to a security conference 20 years ago, everybody talked about this time in the future is going to come where attackers are finding vulnerabilities and they're weaponizing them at a speed that you're just not going to be able to deal with.

Sure, sure.

We're here now.

Yeah.

And if you think about the technology, I mean, the adversaries get access to everything. The best thing that's happened to them is the advancement in the open weight models. They can go and get a Chinese model, they can go and get a model effectively from anywhere that they run inside their sort of framework. They can build it, they can train it, they can tune it, and because they're running it in their environment, they can customise it in a way that you don't know what they're doing.

Yeah.

And then the first time they use it is the first time you have to deal with it. And it's becoming cheap When they run it internally, they don't have the costs of sending the tokens and everything else. They need the hardware, they need everything out there.

Yeah, do you feel like their adversaries are compute constrained right now, or are they just able to do a lot with a little?

It depends on the adversary. You know, the kid at home is going to be compute constrained. If you're dealing with a nation state, if you're dealing with some of the most well-funded, well-structured, well-trained adversaries that now have this capability as well. This is the challenge. That's why there was a packed arena this morning. That's why Jensen came out to talk about what they can do. Because if we don't do something and if it's not a community, it's going to be really hard to compete with this technology. It's so good.

Yeah.

Yeah. What kind of conversation are you having with governments these days? We were just talking about, you know, it's not just enough to secure the Fortune 10. the Fortune 500. You need to secure the local hospital, the local utilities operation. And it feels like the government, various governments might try and incentivize different rollouts and speed things up there. What are you hearing from talking to people in government generally?

I think you've nailed the point because the world's business runs a small business.

The world's economy, I should say, runs a small business.

They don't have the resource They don't have dedicated people, they don't have the dollars, and most often when they have a problem, it's also very hard. Where do they go?

Yeah.

And they think, you know, I'm not going to be able to get the resource of the largest banks, etc. We want to spend a lot of time with them, and that's super important. But importantly, governments around the world that are also starting to say, hey, we need to make sure that our economy keeps working, we need to make sure that critical infrastructure, you know, the power is on, water is flowing, flowing, you know, rubbish trucks arrive. Otherwise we're going to have chaos. And, you know, we've seen examples of critical infrastructure taken out. We can't have banks get compromised with ransomware. We can't have, you know, just pure chaos out there. And I think there's an opportunity now to work more collaboratively. And every— coming back to your question, every government wants to talk about AI. You know, what do we have to worry about? How do we use it? How do we embrace it? But what do we have to be worried about when other people that have malicious intent, what could they do to us if they start using all of these open weight models? What do we need to know about them? So a lot of partnership, a lot of collaboration. And I think that concept of community that we're talking a lot about this week is super important because if we don't do that, we're just not going to be on top of it.

Tons of attention on AI for very good reasons. Is quantum getting underdiscussed? And I say that because I've heard that there are adversaries who are hoovering up encrypted data with the hope that quantum computers in the future will be able to decrypt that data. They're stealing it now. They can't do anything with it. And so maybe even though AI is super important, we should be talking about it 99% of the time. Should we be talking about quantum 1% of the time?

We are. And it's— look, it's a big topic. Not a day goes by where a customer, a partner, an analyst, someone asks a question about quantum and what that means. Yeah, I love the point just to kind of dive in where people are taking data.

Yeah.

A lot of the time you see examples where attackers will basically exfiltrate all your data.

Yeah.

And then you don't see it again.

And you get the email saying, yes, your name was in clear text, but everything else was encrypted and Now you have to think in 5 years that might be decrypted.

Sure. But sometimes when those attacks happen, you understand when you see your name in the list, you understand what they were doing. Yeah. You understand that you are the person that they're monetizing.

Sure, sure, sure.

But what happens when they take terabytes of data?

Yeah.

They're not selling it. They're not acting on it. They're doing something.

They don't even know what it is, maybe.

Well, they didn't do it just because they wanted to have fun. So there's intent. Now, whether it's decrypting it down the road, whether it's training models.

Yeah.

You know, you need to think every attacker, there's a motivation for it.

Yeah.

Yeah. And, and it's fascinating when you actually start to get behind what's, what's driving them.

Yeah. Yeah.

You got to imagine there's at least a few people out there that just love the game.

Well, that's how, that's how it used to be back in the day. You wrote malware because you wanted a company like CrowdStrike to say, hey man, that Jordi guy, he nailed it. Like, this is an attack. This is really innovative. We talked about it with graffiti. Yeah, you felt good about it.

You got in a hard place.

Doesn't work that way anymore.

Okay. Yeah.

How, uh, how is AI impacting various social engineering schemes?

Well, it's funny because, you know, a few years ago it was really easy to tell people about social engineering and said, you know, if you read something and it read, you know, reads like, you know, a 10-year-old wrote it or someone with bad English, you know, it's probably not The bank that you have all your money in. Yeah, it was an easy telltale sign.

Yeah.

Uh, now they, they learn how to use, uh, you know, ChatGPT. They learn how to use Gemini. The, the emails that they write are phenomenal. We used to see about a year ago the click-through rate in phishing was about 11 to 12%. Today with AI, that still feels incredibly high. It's over 60 now.

Wow. Because yeah, it's so real.

Written perfect. Grammatically, they probably write better than us now.

Yeah.

And you kind of look at what comes out. It's really hard to work out what's real, what's not. So they're getting a lot of opportunity. The thing is, you grab an OpenWaite model and you basically say, how would I carry out this attack? It's going to give you the playbook. I've done cyber since university. You don't need any of that anymore. I kind of feel like wasted youth now because you just need a model. You ask the question and it tells you what to do.

Yeah. The company is on Okay, we got to move to the next— we got one more question. We got time for one more question. I mean, the company's on an absolute tear. I'm interested in how, you know, you oversee all these groups. What were you telling people during the SaaSpocalypse in earlier moments? Even go back further, just, just throughout the company's history, you've had a very clear vision of where things are going, the value that you're creating long term, but there's gyrations. What is it like actually managing all of these different teams?

It's got to be funny that, like, the height of the SaaS-pocalypse, you probably had the phone ringing off the hook more than any other point in history because at the same time people were realizing like, whoa, models are now at the point where—

Yeah, yeah, yeah, yeah.

Look, I've known George, who you had on just before, for over 20 years. And I remember one of the first things he ever said to me, look after the customer, everything else takes care of itself. And that mantra goes throughout CrowdStrike. So all of this noise, you know, we just basically say keep looking after the customer, keep innovating, keeping them safe and secure, things will take care of themselves.

Yeah.

We know the way the technology works. You know, for me, the SaaS apocalypse thing, there was no merit to it. It didn't make any sense at all. Even today when people say, hey, all the models are going to find all the vulnerabilities and then we're going to get this state of normality. No, we're not. We're going to get more vulnerabilities. We're going to get more attacks. It's only going to get harder. And that comes from just having So many years of experience. It's having an engineering team that is at the cutting edge, at the forefront, but it's putting the customer first. And, you know, it's a, it's a good formula and it always works.

I love it. Well, thank you so much for coming on the show. Have a great day. Congratulations on fantastic Falcon. Up next, we have Daniel Bernard, the Chief Business Officer of CrowdStrike. You got 5 minutes though. You got 5 minutes to hang out.

60% click-through rate on phishing emails. What are you guys— what are you guys doing out there?

What are you guys doing? Uh, speaking of phishing emails, there have been a raft of, uh, of, uh, password reset attempts on X.

Uh, I wanted to ask him about—

oh yeah, yeah, well, we can, we can go into that with the next guest. Uh, Nick Carter posted on X, a lot of people getting unsolicited X password reset attempts in their email inbox. Do the following: go to X settings, security and account access, security check password reset protection. Don't let people hack into your X account. It's too— simply too valuable. You can't let—

And this is because, uh, X Money's rolled out to a lot more people.

Oh, I saw that notification. Financial incentive now because you could potentially steal someone's money if you got in, as opposed to just post a meme coin link or something like that. Uh, anyway, the other story we got to talk about is, uh, uh, YouTube creator-director Markiplier has acquired an 8.5% stake in GoPro. Did you see this? The action camera maker. They've been sort of, uh, in the doldrums, a lot of competition from China. But, uh—

And then immediate questions because GoPro just got acquired today.

Oh wait, it was a full acquisition?

Yeah.

Oh, I didn't know that.

Wow.

Uh, yeah, so this news comes out yesterday, and, uh, just today GoPro has entered into a definitive agreement to merge with privately held Starman Optical in a deal valued at $285 million. So it seems like Markiplier is up, uh, massively, which is gonna immediately—

Or he was like part of the deal.

Yeah.

Well, it's gonna immediately draw a lot of attention.

Uh, yeah, but a lot of times these things happen as like one piece of a larger deal and the stake gets disclosed at a certain time because it's part of this remaking of the business. Uh, do you think GoPro can come back?

That's a good question. I, I owned a GoPro back in the day. I never— I never— GoPro was one of those things where for the average person, you're capturing footage that is only entertaining to you.

Yeah.

No one else is going to care.

Yeah.

Um, you know, I'm a pretty good snowboarder, pretty good surfer.

Just pretty good.

Um, Sean Maguire was like, Throwing shots, but we'll set up a heat, Sean. But anyways, I always felt like I would film something with my GoPro and then it would be mildly entertaining for me and not that entertaining for someone else.

So you don't watch game footage? You don't get out there on the waves and rewatch what happened?

If you're watching game footage, it's better to watch yourself from the third person.

You don't want to watch the first person. Interesting. Interesting.

Yeah.

I've owned a GoPro at various points in time, but again, like, never really found a good use for it.

Yeah.

And it felt like the GoPro budget for consumers shifted to drones. Yeah, they didn't get there.

They tried.

Again, that's a third-person view that is like, I think, a lot more interesting.

And there's even some drones that will follow you out while you're surfing and track you well and stuff. Yeah. And then, yeah, just the innovation.

I would like— I still have very positive feelings towards GoPro. Great brand. They work with so many amazing athletes over the years. They were a pioneer. The bigger challenge was just the iPhone. The iPhone got very durable and the quality got amazing. So why would I— I can take— you can take your phone out on a ski run, whatever, and you'll be fine. The other thing, like Meta glasses too. Meta, the Oakley Meta glasses.

I think Best Buy reported earnings and said that smart glasses are driving significant in-store sales for them. Like they're, they're actually moving, they're selling well. Uh, we haven't really seen that yet.

Yeah, so anyways, I don't like to see Insta360—

Yeah, and DJI take over.

Take over. So I hope they can—

But if you watch the independent product reviewers, like those products have innovated in many, in many, many ways that, uh, that GoPro has not been able to keep up with, mostly because of the manufacturing, uh, side of the business. But, uh, interesting to see, you know, is this Markiplier's way of like buying a new merch line. Like, that's one potential view on this, is like, okay, uh, you buy a stake in this and then you run— you basically run ads on your platforms to promote the new products. Uh, maybe he has a vision. I mean, he did make a whole movie, uh, with a lot of VFX. Maybe he wants to, uh, grow GoPro into something that's more for filmmakers and, uh, and cinematic— cinematic creating.

The, uh, Starman Optical, the Markiplier is an American company that describes itself as a privately held US optical photonics company focused on developing and domestically manufacturing optical transceivers. So when I first saw the news, I assumed it was a Chinese company buying it up, but we'll see. Hopefully they can make and sell a lot of GoPros here in America.

I'm rooting for Markiplier. I love his journey, and I think, you know, this feels like an outside-of-the-box move. It's not just another Uh, you know, sparkling water brand or hard seltzer brand from a, from an influencer. It's him thinking about business in a very different way. So it's exciting.

Uh, more news.

Uh, first let me tell you about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agent to deploy web apps, servers, databases, and more while Railway automatically takes care of scaling, monitoring, and security.

More news. MrBeast has launched a book, a book for his audience of voracious readers. Uh, people are clamoring. Uh, people in his audience have been asking for a book. Yeah, he delivered.

Yep.

Um, no, he's turned the book into effectively a lottery. Okay, away a million dollars to somebody that buys the book.

Was that on day one or is that downstream? I don't know. I guess that's day one. That's the, that's the promotion. So, uh, anyway, he partnered with James Patterson, who is a huge author. Uh, good news for the subset of MrBeast Beast fans who'd love to read mystery novels. The YouTube giant's collaboration with James Patterson is out Tuesday, uh, that's today, accompanied by a flurry of marketing on MrBeast channels. Read my book and you could win $1 million. Uh, bad news for HarperCollins: the book-buying subset of MrBeast fans appears to be vanishingly small. 2 people close to the project say The Most Dangerous Games is on track to be a historic bomb, with pre-orders numbering in the 4 digits as of last week. But why would there be preorders if it hasn't launched the marketing yet? This— I'm sort of skeptical about this.

Yeah, this is the first time I'm hearing about it.

This is the first time I'm hearing about it. And it seems like MrBeast just uploaded the actual contest. And like, you could say he shouldn't be running a lottery, or I don't like this type of book promotion. But like, that's—

And I will say, if the preorders or the orders still stay in that 4 digits, there's some hedge funds getting involved. Hedge funds buying up, buying up more of them.

Oh, go to win the million dollars.

Yeah, yeah, you could win hedge funds.

Well, typically with it, with a raffle like this, you don't have to actually buy the book. You usually can just sign in and, and send it over. But, uh, will you be reading it?

I think one of us has to read it, or at least Tyler.

Tyler, where are you? We can get Tyler to read it anyway. Uh, we'll have more fun with that in just a minute. Let me tell you about public.com, investing for those that take it seriously. They got stocks, options, bonds, Crypto treasuries, and more with great customer service. And our next guests are here. Welcome to the stage at Falcon with TVPN. Great to see you. How are you doing? Great to see you.

What's happening?

How you doing? Well, yes, John, Jordi, uh, we're gonna have you throw on these headsets, and it's a little bit loud in here. There's a lot of CrowdStrike fans. The CrowdStrike fan zone's going insane right now. And so, uh, Just get the microphone sort of as close as you can. Let's move this around, flip this up. Yeah, there you go. Is it? Oh, I think you put it on backwards. There we go. Anyway, let's start with introductions. Introduce yourself. Tell us who you are, what you do.

Hey guys, Daniel Bernard. You can call me DB.

DB.

Chief Business Officer at CrowdStrike.

How many— how popular are internal nicknames at CrowdStrike?

They're super popular, but there's only one DB.

Okay, let's hear it.

Justin Boitano. I lead the enterprise business at NVIDIA. So good to see you guys.

Yes, good to see you again. And tell us about the partnership. Tell us about the news today.

Well, big news today. We launched SafeMind, cybersecurity's first frontier models and harnesses custom for cyber, made by cyber for cyber. We built this on Nimotron and it's bending the curve of frontier AI and the advantage of defenders. Better protection.

Harnesses, plural?

There's multiple harnesses.

Why would you pick one? What's involved in selection? What are the differences? Are we talking about pure economics, tokenomics, or are there more like, you know, the right tool for the job?

Right. Go ahead.

Yeah, let me give a little bit of color. I think the big news too is that the frontier is in the harness.

Okay.

It's not really about just the model. It's about the entire system. And so what the CrowdStrike team have done a phenomenal job doing is tuning the harness for attack, tuning the harness for defense. And, you know, the harness is the thing that's going to sit there and reason and call tools and, you know, work through solving the problem, whether it's finding vulnerabilities or finding and writing detections.

Yeah.

And so I think the work that we've done both through the harness and through the open model creates this like super capable agentic system that is going to always be on, And be able to, I'd say, learn from enterprise environments. Jensen talked a lot about how we're deploying it internally. We're building the digital twin of our environment. We can basically go through these attack defense simulations to build the best defenses for our organization.

That's great. As you went about building this, how important were benchmarks to you? Public benchmarks, private benchmarks? How do you see that fitting into the tool chest of building a great product?

Super important. We need it to be more performant than what's out there today.

Yeah.

Like the goal here that we both set out to achieve is this thing needs to be better, faster, and more cost-effective than the other open source and frontier models of the day for cybersecurity use cases.

Yeah.

You know, that's the big thing. Like we're not here to change the world of science, math, manufacturing. We're here to stop breaches. We're here to make cybersecurity better. That's offense, that's defense, and that's continuous learning.

Yep.

Better performance at each step of the way. And that's what the data we have that we're able to— that we shared with the market today.

Talk about the decision to go with Nimetron. There's a lot of open-source models. I can imagine why you didn't pick some of them, but break down the decision.

Look, there's a really, really close relationship between CrowdStrike and NVIDIA, so that we didn't even look at anybody else because, you know, when it comes to like the foundational layer of AI that we've built, business on, you know, that's GPUs. And who do we get our GPUs from? The creators of them.

It's NVIDIA.

And so when it comes to open source, and you can look at NVIDIA and Jensen, such a strong perspective, and really across everything you're doing too, Justin, like the world needs open source, the world needs choice. That just aligns with us very culturally as well. So there was nowhere else, like why would we go anywhere else?

And for us, the feeling was mutual. I think Jensen said on stage, CrowdStrike is our number one partner in cybersecurity. They have the perception system that really understands what's going on in customer environments.

Yeah.

So if you pair that perception system with, we'll say, an open model that we built, it's built as general knowledge, but we put out there the datasets, the open techniques, and the weights so they can be customized by CrowdStrike so they can build their own specific cyber domain intelligence. and be able to build a new business model where they're like selling tokens, right, to secure enterprises. And they're doing it in the most cost-effective way by building on that open foundation.

What else is NVIDIA bringing to the table around a project like this? Because Nimetron is obviously the model layer, but also the GPUs. But yesterday I saw a fantastic deal with our buddy at Lambda for, you know, a big—

Because they're busy.

Yeah, you're busy. Uh, a big GPU cluster. Is there advisory that you can provide even if CrowdStrike is going to be racking NVIDIA GPUs? Like, how deep does that partnership go beyond just like, cool, here are the weights, we signed on the line, you can use them? Okay. Yeah, yeah.

I think, uh, most— I mean, as I mentioned, most of the advancements at this point is research in the harness. Sure. So we're, we're, uh, our research teams, um, you know, George announced this, uh, what it's Cyber and Superintelligence Lab. Cyber and Superintelligence Lab. We have a bunch of cyber researchers. And basically what we're doing is we're constantly publishing where advancements are coming in the ecosystem or in these environments. Like we put out there a few weeks ago some new harness research that we called AVO that showed in Arc AGI-3, we could take a frontier model from 30% accuracy to 100% accuracy.

Wait, on Arc AGI V3?

Yeah.

That's insane.

And that's all open research that we're sharing with us.

Big surprise in the last month is people harnesses showing what's possible with a different harness versus Arc's standard harness, right?

Yeah.

Yeah. So we share all of that open research together to advance the industry. And ultimately, we're not a cyber company. They're the cyber company. They have the domain intelligence, the perception into customer environments to understand real attack paths that people are trying to exploit. You add to that these new agentic attack paths that people are trying to understand in their environment. And ultimately, we want to help power defenders and give them this differential advantage that Jensen and George talked about.

Look, I'll add on to that. I think every meeting that I have and that everyone at CrowdStrike has with NVIDIA, they all start the same and they end the same. How can we help you grow? It's the first question. It's the last question. It's from Jensen all the way to the person at the front desk.

I love it.

And so Your answer to your question of where, like, what's on the table, everything's on the table.

Everything.

Yeah.

The whole shop's on the table. It's like, what do you need from us?

That's great.

We're here. So like, when we, who's the best AI partner that we have? It's NVIDIA because they're helping us take cybersecurity to a whole new space and we're bringing them to over 100,000 customers and everybody that's on the show floor here today.

Yeah, that's great. How important is human design of RL environments for this harness development? You obviously have the most insane data collection, correct? Decades of experience across the entire organization. There's a lot of value and ways that I could see if you're— there's a huge jump. I'm not surprised. I'm sure, you know, congratulations. But, um, but, but how much, how much is it about actually designing new environments and then go training?

Intelligence, I believe, is really becoming somewhat commoditized. I think what's really real in this next chapter of AI is how you contextualize based off of specific situations. So the fact that we have Falcon Complete data, that's managed detection and response data from human analysts that took actions over the last number of years across, you know, all these different environments, the fact that we have frontline incident responders that stop the breaches, all that, that data set lets us curate something that's super relevant and super focused. And then we take that and we operationalize it with the harness so that we can bring a better model that's built on Nimotron and have an appropriate harness for solving different problems and have an iterative learning loop. Like, where this all goes, in my opinion, is you'll see more models and more harnesses from us in the SafeMind family that solve different security use case problems. And that's all based off of the experience of our practitioners. You know, CrowdStrike is cybersecurity built by and for cybersecurity practitioners. I think that's really different in the market for us versus a lot of the other random companies that you find that say that they're here to work in cybersecurity. Like, everything is based in solving a real problem. Yeah.

How are you thinking about educating the customer, the buyer, on cost and how to think about the shape of cost in this token maxing? I mean, a breach can be It's so devastating, throw all the dollars at it, but at the same time, there's amazing trade-offs that you can do with smaller models, different infrastructure, and different pieces of the puzzle.

Let's start with Justin because I think you've been evangelizing open source and trying to find—

Well, in our environment, so you got to remember, so one, we are also a big enterprise. We have to look at the same threats as everybody else, right? Of course. So, and I think a lot of the conversation has been steered around code vulnerabilities, but in a production environment, it's really about also the configurations in your running environment.

Sure.

And so, you know, for us, I mean, to your point, the harness should be able to use the best of frontier and the best of open to reason through and figure out which problems you need to use which models for. And ultimately, we assume it's going to be always on. We want to start by trying to make it as low cost as possible by providing open intelligence that they can domain adapt. So the SafeMind models are probably the default, with the exception being the Frontier if you want to look for very novel new things. And that kind of gives you the best cost benefits when you run this all the time across code, binaries, and configurations in your environment.

Yeah, we've heard it loud and clear from customers that just going one direction with Frontier Labs is just too cost prohibitive. But open source at this point point, like generic open source is sort of like you don't have the— it's a compass that's spinning in a circle. So what we need to do is have the best use cases, the best results, the best outcomes, and also deliver it at the best cost. And that sort of is the aperture that we need to play in with this thing. And so I think every enterprise is grappling with— we have this new line item in COGS that's called tokens.

Yeah.

You know, 5 years ago it didn't exist. And it's not like you necessarily And that doesn't necessarily say goodbye to anything else, by the way. Yeah, you're doing more with your cloud providers. You're using a lot of software. You need to secure all of it with CrowdStrike, of course. So, you know, I think everybody's in this redistribution or rethink of how you do budgeting in this, in this new AI-first world.

Yeah.

And I think every enterprise is planning to spend more on AI next year, but at the same time trying to be a lot more efficient. Right. And so that's why these two, these closed models, open models can coexist. And actually the industry can continue to thrive.

Yeah. How do you think about the— we were talking about this earlier, but the economic warfare between attackers and defenders? Because the benchmark performance, all the stats that you mentioned, those are great, but I'm almost more excited about the cost savings because this is a technology that needs to be always on, running all over the place. It needs to be, you know, Too cheap to meter, essentially, as fast as possible, so it can be everywhere, because if an attacker's only trying to come through one door, you gotta make sure every door's secure. So how are you thinking about the economic balance between attackers and defenders?

Well, the way I think about it is prices, I mean, value creation is always measured economically in a P and a Q. What's happening right now is the Q is going out of control. So, like, that's the big picture. There's more attack surface than ever before. And that means there's more opportunity to come back to your question. There's more opportunity for adversaries to play around.

Yeah.

And they don't have to be right every time. They just need to be right once and go get something off the shelf somewhere and use the weapon. And if the weapon works, that's a good day for them.

So do you think 2026, if we look back in a decade, do you think the attackers are going to be like, that was the best year we ever had? Or do you think it's going to be the moment when the defenders are saying that was the moment we figured things out.

I'm going on a limb here. Justin can back me up or you can have your own opinion, but like, SafeMind changes the curve. Like, I think Frontier AI has disproportionately, uh, advantaged— well, one, everyone sees advantage. Yeah, but I think sort of until, until like this time, it's sort of disproportionately advantaged adversaries.

Okay.

And I think it's time to change the Sure. And that's why we're working together and we want to see that change happen and make that a reality. There's a lot of great technologies on the floor here. There's a lot of great cybersecurity companies and there's a lot of companies that we're keeping safe all the time, but it's too easy and it's too dangerous for these adversaries to get their hands on things that are way too powerful.

Yeah. And I think it's another example of a domain where general intelligence can come and do attack, but it's going to be pretty expensive to run these attack paths. through these frontier large models. Think of it like a battleship, right?

Of course.

And then what you want to do is you want to help defenders have the equivalent of drones, like super low-cost models that they can run everywhere so they can run across their entire estate. And to DB's point, the goal is, I think, to help specialized cybersecurity defenders have the tools. And their advantage is also they know the code, they know the configs that they run. The people coming in from the outside don't. So on the inside, you can do all that recon, you can map your environment, you can use these lower-cost models to find potential new attack paths, and then continue to close them down and do it at a lower cost if you use these new platforms like SafeMind.

Yeah.

So you guys are in the position where you can be at the frontier with these capabilities, but there's not this insane pressure from billions of users out there, hey, you have to release these cyber capabilities to everyone, right? Whereas the Frontier Labs are in a different position where you have hundreds of millions or billions of users that want the best capabilities for things like coding, right? And these other capabilities.

So, well, we have the pressure of lots and lots of big numbers of attack surfaces. Those are endpoints, identities, cloud workloads, and they're putting a lot of pressure on us because they all need protection.

Yeah.

You know, we can't let any of those things get compromised. So like the threat's real, the need is there. The budget's there, but the market's asking for something better and something different. You don't treat a specialized illness with a generic pill. You need to have the right dose, the right therapy. I think that that's really what we've done here.

And I think with every platform company, we're a platform company, we know what we are and what we're not. We're an accelerated computing company. We're not a cybersecurity company. And so these natural partnerships sort of emerge to allow us to go in a specialized way, solve the problem in a very focused way. I think, you know, even the frontier labs are probably thinking to themselves, like, where do they really want to own, call it alpha, and go try and compete? Where do they want to partner? And I think in these areas of, like, specialized intelligence for cybersecurity, you know, we generally think the best approach is help, you know, protect critical infrastructure, help make the world a safer place, and we'll all be in a better place.

Yeah. What As a platform company, what is the advantage that you see occurring over time around having diversification in the actual chip fleet? I mean, there's this Groq deal coming online. There's already a number of different configurations of rack-scale servers and all sorts of different— back to the gaming chips. I mean, I see people running AI loads on those too. What is the advantage and the shape of that over time?

Well, we're an accelerated computing company, right? So we have to accelerate everything. And the reality is, you know, different models need different capabilities. And so ultimately, we want to be able to provide the capabilities, whether you're doing prefill and inference or decode, have the most performant, capable architectures. And then ultimately, you know, as Jensen always talks about, we're building rack-scale infrastructure with 7 processors.

Yeah.

We're trying to be best of breed across all of those so that we can build these large AI factories and drive the best token efficiency per watt, and then ultimately have a great partner ecosystem that can extend that efficiency into these new domains and use cases.

That's fantastic. Well, congratulations on the deal. Thank you so much for coming on the show.

Pleasure to be here. Thanks, guys.

Have a good one.

Thanks for having me.

Thanks for hopping on.

Thanks.

This was fantastic. Thank you to everyone who's tuned in live from Falcon.

Great to see you.

Cheers. Okay. There are a few more stories that we should get through. Let me tell you about Shopify. Shopify is the commerce platform that grows with your business, lets you sell in seconds online, in-store, on mobile, on social, on marketplaces, and now with AI agents. Jordi, was there anything else that you wanted to get to?

Give John Ternus a quick follow over on X.

Yes, John Ternus has hit the timeline.

What a, what a, what a moment for X.

Yes.

In some ways.

Yes.

Right. You know, we're how many years into the platform?

Yeah. But I mean, when you're on a platform, it's going to die.

If you assume an important position in the world of business, you simply can't afford not to be on X. Yeah.

No.

The fact that, I mean, it's not like he's like, you know, tweeting random stuff or actually like breaking news there yet.

Since we started the show, he started shitposting.

No, I'm kidding. No, he tweeted hello lowercase, very online, very like native. But the fact that Jensen's on there, Mark Zuckerberg's on there, like the AI conversation is truly happening on X and it's exciting to be a part of it. Apple investors want the new CEO to be an innovator. This is in The Wall Street Journal. Ralph Winkler writes, talking about there is one way, there is, there is one way which company observers have said has been lacking since the Steve Jobs era, revving up Apple's innovation engine, especially in artificial intelligence. Tim Cook's brilliance was to take the company Jobs built and scale it massively. The year Cook took over, Apple sold 72 million iPhones. This year it will be 255 million, tripling volumes, hitting annual release dates like clockwork, minimizing risky capital investments, and returning more than $1 trillion to shareholders. That is a size-gone moment. Helped Cook multiply Apple's valuation by 13 times. But, uh, Ralph Winkler in the Wall Street Journal says that Apple's investors now want Ternus to change things up. It's not enough to rest on your laurels, just focus on operational efficiency. He's got to innovate, according to the Wall Street Journal, they say. Uh, but in Wall Street parlance, the positives look priced in. Apple's trade— Apple stock trades at 33 times next year's earnings compared with the S&P 500's collective multiple of 20 times. Apple gets that premium even though its earnings are growing half as fast as the market. Investors are paying up for Apple because it looks safe at a time of broad anxiety over returns to be had on massive investments in AI. But when the valuation gets stretched, safety isn't safe anymore. And there are negatives that investors may be overlooking in the age of AI. Apple has lost its status as the consumer— as the company that defines how consumers interact with devices, a title it held for 40 years from Apple II to the iPhone. So, uh, The Wall Street Journal wants Ternus to take risks, launch new products, uh, you know, go, go aggressively. He certainly, uh, seems like he's stepping back from the Apple Vision Pro, sadly, but, uh, we'll see, we'll see what he does. It'll be an exciting time.

And last but not least, Dyson just released a new AI-powered toothbrush with integrated 4,000-pixel macro lens camera. for $499. I know a lot of you people have been asking for AI in your toothbrush. I certainly know I have. And I'm glad that—

This can't possibly be the first AI toothbrush. There have to be other ones.

Somebody's got to get this and try it out. I certainly have never wanted AI—

Wait, what are we doing with this 100,000 pixels?

—in my toothbrush, or really a camera in my toothbrush. But—

That's not how people measure camera lenses. They say megapixels, which I think is a million pixels. So it's actually a 0.1 megapixel lens camera.

But I think we've got to give it a shot.

OK. We've got to give it a shot.

I don't want to judge it too much. I do like a good wooden toothbrush.

Wooden toothbrush?

I like a wooden toothbrush personally. I think they get the job done. But oh well. We've got to try it out. We'll be back in the UltraDome tomorrow.

Yeah, back in the UltraDome tomorrow.

Cannot wait.

We're heading back to Hollywood. Thank you for tuning in, folks.

It's been an honor.

A pleasure.

A privilege.

We'll see you tomorrow. Goodbye.