Techstrong TV Wednesday, April 15, 2026

Hey everyone, welcome back here to techstrong TV. I'm very excited. This weekend I'll be getting on the plane and heading to beautiful Prague.

Mm. Czech Republic, for what promises to be, I think, maybe I'm wrong, probably the biggest SUSECON ever. It will be.

Yep. And, there's so much going on. We've been touching on it.

I did a webinar last week with Margaret Dawson, CMO of SUSECON, and of SUSE, excuse me. And we're going to be doing a lot more coverage there. We'll have a newsletter coming out for it, so stay tuned.

But I thought it would be good before the craziness, or maybe the craziness already has set in, but before the craziness- ... sets in, to grab Margaret for a couple of minutes here and give you all a little sneak peek into this year's conference and why it's so popular, why it's so important. Margaret, welcome to techstrong TV.

It's great to have you back on. Thank you. Always a pleasure.

Always a pleasure to be here. Absolutely. Well, it's my pleasure, actually, but for those who don't know, as I mentioned, Margaret is the CMO of SUSE.

She has a long history. Not too long. Not too long.

Pretty long. I realized when I said that. But Margaret has held a variety of very senior level positions that make her imminently qualified to be sitting in this chair and going over what we're going to talk about.

So Margaret, don't mean to embarrass you or say anything out of school there, but the theme for this year's CON is Shape Your Resilient Future. Yep. And I got to tell you, in a world where it's AI this and AI that- Mm-hmm ...

and what's AI going to do for you and me, it's refreshing to see a title that at least doesn't have AI in the title, though AI, I'm sure is going to have its place at the table. But when we say shape your resilient future, Margaret, what do you actually mean by that? What are we talking about?

Yeah, it's a great question. It was interesting when we were coming up with ideas for themes, of course, there's a million things that we could talk about, but whether customers were dealing with, "I need to reduce cost, I've got to modernize, I've got to get off VMware, I need to implement AI, I need to migrate more apps to the cloud or repatriate things from the cloud," whatever it is that is the priority, there was this theme that kept coming back, and it was around resiliency. " Right?

So for some, resiliency equals sovereignty. For some it equals just data protection. " Right?

We're seeing with everything going around, not only with AI, but cybersecurity, geopolitical pressures, you name it, people are just under so much pressure, and so what they need is that sense of security around resiliency. So it was very intentional. And the shaping your resilient future also is about doing this together.

So it goes back to our open source roots and community and the fact that anything that you do can be done better when you have your community around you, and that we can all see and participate in the open source way. Love it. Of course, when you came up with this and talked about it, I don't think you or the SUSE folks are prescient, but who would have thought that the week before the show, this whole mythos and Project Glasswing and everything that's blowing up.

You want to talk about resiliency. If we're ever going to need resiliency, it's going to be now, and if we're ever going to need community, because no one company, no one country is going to be big enough, I think, to really take this on, take the bull by the horns here and secure... I mean, everything's up for grabs.

No, 100%. And you're even seeing increased calls also for that open standard, right? Because we know that if we have transparency, it improves the ability for us to be secure.

It gives us hundreds and thousands of people working together in the community to improve the security. So I think, when AI and security are becoming so core, open standards, whether it's around MCP or around agentics or around anything, like how we provide those open standards so everyone is kind of working on the same page is so important. So there'll be a lot of discussions, I think, around that.

I agree with you. I have no fear. I think you ain't seen nothing yet when it comes to open standards, because truly the only way we're going to get through the gauntlet here of this vulnerability apocalypse is open, right?

Mm-hmm. Companies working together. That's this whole Project Glasswing.

There's 40 to start- Right ... but there'll be a lot more companies adding in. Working together as a community to harden and to be resilient.

I mean, resiliency is the name of the game. So kudos whoever on the team picked it there, your timing is impeccable. It was a group effort, I will tell you.

It was definitely a group effort. It kind of came together. But what was interesting is when we first came out with the theme, you weren't really seeing this term resilience.

And I swear, I don't know, like you said, I would love to say we were omniscient, but you see this word resilient, resiliency coming up more and more. So definitely the drumbeat was there. And the only thing I'll add when we talk about community is one thing I'm really excited about with SUSECON is we have moreKind of sponsors and partner ecosystem.

If I just look at the keynote stage, it's amazing. We've got AMD, AWS, Fujitsu, Dell, and I'm sure I'm forgetting somebody here that I'm going to get in trouble with. But there is amazing partners across, whether it's hardware, software, AI, you name it.

We're going to be talking to a broad ecosystem that is helping customers put these solutions together to become more resilient. I love it. Just kudos to you and the team, though.

You really nailed this one. As we get under resiliency- Mm-hmm ... and resilience, though, there are themes, kind of underneath that main current.

There are. Flexibility, control, choice. Yep.

And this goes to the heart of SUSE's history, right? Of their legacy, of their DNA. Open infrastructure.

We spoke a little bit about open, but SUSE was an open source company before open source was cool, right? Yeah. And, so that whole thing of giving customers choices.

Right. You don't have to use the whole SUSE stack. I remember when SUSE announced, you could mix in other packages and you...

This is going back a while. And then I think it was at last year's show, right? Didn't you put together your own secure packages of the most popular- That's right ...

Linux packages? Yeah. I think choice is absolutely the underlying, if I had a sub theme, right, it would still be the power of choice.

And open is core to that. But what you're talking about is we have a very composable architecture across our stack, so it's not opinionated, you could say, or it's not tied together so tightly that you can't do one piece without the other. So what that allows you is choice within our ecosystem.

But also, if you have a different operating system today and you want to run SUSE Rancher Prime on top of it, you can do that. That's very different than the competition. If you want to use all SUSE, obviously it works better than any other combination, but it's not required.

And I think this goes back to one of the core things that we provide that you and I have talked about before, is we are the only company that allows you to work with SUSE to manage not just our Linux, but any Linux as well as support. So we provide extended support for many flavors of Linux after the vendor itself has stopped providing that support, because a lot of companies need more transition time. The same is true for Kubernetes.

We obviously have our own Kubernetes, but we manage anything with our multi-cluster management capability. So the reality of most, if not all enterprises as well as governments, is they have a heterogeneous, complex environment that has a ton of existing infrastructure applications and the need to modernize and implement now AI and cloud native and all the latest next gen technologies, take it all the way to the edge and beyond. And so that ability to simplify management, simplify security across that heterogeneous stack is hugely valuable.

Absolutely. And here's the breath of fresh air, though. In an age where companies are trying to build walled gardens, trying to lock in, everybody's afraid of losing someone moving their cheese.

Everyone's afraid of losing- Right ... their edge with this AI stuff, right? And so they play the platform game.

It's an old game. You've been in IT, I've been in IT- Yeah ... and tech long enough.

Who has the platform wins- Right ... used to be what we say. Exactly.

Yeah. And they're still playing that game. Mm-hmm.

But you know the old saying, the harder you grab sand in your hand, the more leaks out between your fingers. Sometimes you got to set it free, and if it's yours, it comes back to you. The little Jonathan Livingston Seagull- Oh my gosh ...

for those who ever remember. That's so '70s. Well, yeah, that's me.

But anyway, but that's kind of the SUSE model here, which is, hey, take what you want, take what makes sense for you to use. Right. If you need the whole thing, the whole thing is there, and it works really well together.

Right. But the individual pieces play well with other pieces as well. Yeah.

And I think I'm just going to take it back to open standards a little bit. I just read this stat that said as we look forward to LLM models, it's expected that some 70, 80% of models in the future will be private models- Yeah ... not public models.

And they'll be customized as well, like the insurance platform will be based on its own private model. But how do you integrate across these different things? Or how do you talk to a private model and a public model?

And that's where open standards comes in, whether it's with MCP Server or we continue to look at open APIs, right? So there's always this place, even as you need to customize or create a private version of something, that we want to still have these open standards for that extensibility, for that interoperability, for the integration, because otherwise that walled garden becomes an inability then to innovate and scale. Absolutely.

And it's the balkanization of every... You lose the advantage of this whole great thing we're building in. However, the flip side is people want that flexibility.

They want that choice. One of the big drivers of this is digital sovereignty. And again- Yeah ...

this is something that SUSE has got out in front of and is really one of the leaders in digital sovereignty solutions. And not only solutions. Andreas is a friend.

True thought leadership. So not just trying to sell something. I'm talking about true thought leadership and what does it really mean?

AI sovereignty, digital sovereignty, cloud sovereignty, right? Software sovereignty. What is that?

All these different sovereignties, what does it really mean? And, again, SUSE, it's a topic that's so hot, and I think we mentioned on the webinar, it's not just a European thing, 31% or 32%- Right ... of American, of US-based companies indicated it was a big deal to them.

That's right. No, this is a global phenomenon, and I think, it goes back to all those things. So to be sovereign, which means I need control of where my data resides or where my capabilities reside for whatever reason, right?

We can say geopolitical is a pressure, we can say cybersecurity is the pressure. And as you mentioned, for some people, sovereign just literally means protection, security, and for others it has more geopolitical implications. But regardless, we still go back to, how do you stay true to that open standard mentality, right?

So you can be sovereign by choice, as we like to say, but open by design. So going back to that open architecture, going back to that modularity of composability, but with the end goal of sovereignty. And so I think what you'll see throughout SUSECON is that juxtaposition of AI innovation and open, digital sovereignty and open, right?

Heterogeneity and openness. So all of that leads you and allows you to be more resilient, and it all goes back to that choice of doing it your way. And not to borrow from the American Burger King commercials, but I really do think that is a good analogy.

Because if you're feeling out of control, how do you get back control? You have that choice to do it the way you need to do it for your organization in your specific situation, in whatever corner of the world you're in and whatever competitive pressures you're facing. Agreed.

So to me that's really, as counterintuitive as it may be- Right ... digital sovereignty is about choice. Right.

I need the choice to pick the right solution for me. Whether I'm talking about AI or cloud or platform or flavor of Linux even. I need the choice to pick what's right for me.

That's right. And that's why I think individual sovereignty is part of this digital sovereignty as well. It's interesting, I'm actually doing a session at SUSECON around this very issue of standardization versus risk management.

And it's all going back to, as you try to scale, there is benefit in trying to standardize on some of our architectural layers. Do I make some big bets around a certain flavor of Kubernetes, a certain operating system, a certain observability platform, et cetera. We could go on and on, automation, et cetera.

And sometimes you need to do that. You need to do that from a security standpoint, a policy standpoint, a cost standpoint. But then there's that, if I take too big of a bet or I over-standardize, is that just hurting my ability to do business continuity, to manage my risk, to not get so tied in with one vendor or one technology that I've lost that choice, I've lost that flexibility.

And the thing that I always talk about with customers is rather than starting with that layer, start with what you're trying to do. Is the goal of that workload or that dataset or that experience sovereignty? Is it more about a customer-facing app that's directly tied to revenue, and it needs to be really adaptable and always on?

Start with the criteria and the needs of that workload, of that application, of that experience, and then figure out what's right in terms of underneath the iceberg, so to speak, at the infrastructure layer or the data center layer or the cloud layer, right? Whereas sometimes we like to start with the answer instead of asking the questions. Agreed 100%.

I want to move to a fourth area that I think is going to be really deeply explored at SUSECON. And that's this, let's call it the new stuff, right? Yeah.

Well, some of it isn't that new, but cloud native, right? Yep. Look, if you're having a greenfield app, cloud native probably is your system of choice.

It's 70-plus percent of greenfield are cloud native. But it's also becoming the dominant stack for AI applications as well. That's right.

Right? They're running on Kube and so forth. AI workloads are containerized workloads most of the time.

Exactly. I'm sure there's exceptions, but the vast majority. A majority, like critical mass, 75%-plus.

The edge has become real, right? We've been talking about the edge for a couple of years. And again, SUSE positioned themselves well to be an edge player, right?

Well, we started that early, both with a couple things. One is a lot of people have followed K3s, which is a- Yes. Lightweight ...

Kubernetes flavor that is made for more resource-constrained environments, and the edge is a perfect example of that. We also have the ability with SLES, with our SUSE Linux, and that composability to just use the pieces that are needed in whether it's near, far, or tiny edge. And then, as you know, recently we acquired a company called Losant, and that has taken us all the way to the industrial IoT, so think sensors and manufacturing or the tiny edge.

Tiny. And so that architecture and how that all fits together from that furthest edge all the way to the data center, and how do you think about that in a consistent, resilient, secure, stable, and yet flexible way so you're literally using the hardware, the software, the chips, and the security that you need for that specific application or that specific environment? So there'll be a lot of talk about that, a lot of hybrid environments, this flexibility across all these different places.

That's the reality. And to innovate, you need to have that agility. So we've made it all this way.

We haven't really talked a lot about AI. We've been hinting. But I'm sure there's going to be plenty- So there's going to be some really, really, really exciting announcements around AI I was going to say, I'm sure there's going to be something.

I so want to say it. I so want to say it. All right.

But I won't, I promise. Look, it's just you and I. Who's listening?

No. Oh, yeah. Next time.

Who's listening? It's just going to be on the worldwide web. But there is going to be...

Yes. There will be AI, right? " I know.

We don't even say that anymore. Yeah. No, we don't.

I know. No, there is going to be some big, big announcements around AI, major partners. I am super excited about this.

We are all in, and we'll be doing some things that SUSE's never done before with partners around AI, and it's all about helping our customers move to the future and do it in a way that works for them. So, you definitely want to stay tuned on... Tuesday the 21st is when all the big announcements will be going out, so I'm sure your newsletter will be full of that.

Shocked. And I think there's two things. I will say quickly that when we say AI at SUSE, we have two sides to that coin.

One is just the AI capabilities we are building into our infrastructure software. So MCP server, automation, agentic capabilities. So how are we making it easier to manage, integrate, automate, whether it's our container management platform, Rancher, or whether it's Linux or other capabilities.

So that's one piece, all the way, Edge and hybrid cloud, et cetera. The other piece is how are we building the best infrastructure, software, and solutions for your AI workloads, whether those be private LLM models that we just talked about. But AI capabilities or workloads, increasingly need to be able to scale in a way that we've never done before.

And how do you get Kubernetes to scale in that way? How do you have the security and the policy control that you need? So how do you manage across these different environments?

So there'll be a lot of discussion about that, and you'll hear announcements around both sides of that AI coin. I love it. You mentioned the webinar we did last week, and that was based on this fantastic survey SUSE did.

Yep. A lot of information. One of the things that stuck with me, asking people, where do you get your information?

Where do you trust? Where do you like to learn? That kind of thing.

Number one, I think, was still analysts and reports and stuff like that. Mm-hmm. But number two was industry conferences.

Great. Meeting with my peers, going to industry conferences. As people out here, if you haven't made up your mind, but you can get to Prague for SUSE CON.

Margaret, where do you think the big hallway conversat-- They could read the agenda. There's great stuff coming. But the hallway conversations, the water cooler stuff, the give and take that takes place in person, what do you think about that at SUSE CON?

What do you think those- Yeah ... are going to revolve around? I think the whole reason those conferences and why we still need that human engagement, especially in this AI era, is building trust.

I think a lot of those conversations are going to be, "What can you help me with? " And the great thing is we're going to have the end users will have partners across all the different, from channel to the ISVs to the SIs, the entire ecosystem. And I think a lot of it is going to be, how are you solving this problem?

What have you seen? Customers talking to customers and saying, "Oh, you did that with SUSE. That's interesting.

" So sharing experiences, sharing those stories and testimonies. And then I'll just tell you, in past years, SUSE CON is we're solving problems. We leave that event, and there's real work that comes out of that.

" But there's something about being face to face and having those meetings and going to sessions and hands-on labs and Demo Palooza, and it just, the energy, I think, is going to be amazing. You can feel it at SUSE right now. I know, I- Every conversation, there's such amazing energy.

But I think at the end of the day, the focus is going to be, how do we help each other get to that place that we need to go, whether it's resiliency or innovation or the combination of the two. And hearing real-world stories and sharing with your peers, that is the power. Absolutely.

You kind of jumped the shark on my last question, but let me ask it anyway. When people leave SUSE CON this year, what's the one idea or mindset that you hope they bring back to their teams, and it's contagious? SUSE's got you.

We're holding you in our hands. We can do this with you. We'll help you.

Whatever that journey is, we will do that. And like we say, it's shaping your resilient future together. And I think that is the theme that we want to take away.

Margaret, you're one of my favorite people to interview. I got to tell you the truth. It's a pleasure.

I'm really excited. We get there Sunday. We'll be there all week.

Awesome. My video team, our analystsMike Rizzardo will be there as well. And we're going to go share one bottle of really good wine because they have really good wine in Czech Republic.

Not only Czech wine, but you get Italian wine everywhere in the Czech Republic. I'm just saying, that's not part of the deal- Okay ... just to be clear.

But- Well, I- ... if someone sees me and you're at Susicon and you want to go have a good glass of wine, just look me up. I'm ready.

I'm going to hold you to it. Okay. I just got back from Napa.

I'm in a wine sort of mindset anyway, but we're ready. I think it's a Billy Joel song. " Sorry.

I'm confusing. Yeah. Well, but you could always...

Did I ever tell you he's my neighbor here? Billy Joel is your neighbor? He lives across the- Oh, I love this music ...

intracoastal right by me. Okay. Okay.

Me too. We're getting completely off track here. All right.

We're done. All right. But Margaret, hey, forget Billy Joel, forget the wine.

Yes. Come to Susicon. Don't miss it.

Thank you, Alan. It is next Tuesday, Wednesday, Thursday. We'll be there.

Margaret, thank you. Thank you always. We're going to take a break on Techstrong TV.

We'll be back in a minute. Hi, I'm John Swartz. I'm back at RSAC in San Francisco at Moscone South.

It's day one, and we hope you're off to a good start here. We're here with Matthew Andriani, who's the CEO of Maze... How do you pronounce that?

MazeBolt? MazeBolt. MazeBolt.

And Matthew, I'm going to ask you to take the floor and tell me a little bit about MazeBolt. I had a bunch of questions I want to ask you, but first let's lay a groundwork so our audience has a better understanding of what your company does. Thank you, John.

Good to be here. Thanks. We are in the DDoS space with Akamai, Imperva, Amazon, Cloudflare, all of these mitigation players.

We don't do what they do. We augment those systems. They've got good protection that's deployed at various enterprise organizations.

What we do is we find out how attackers are able to penetrate all of those layers of protection all the time. Mm. So that's what MazeBolt does.

So you enhance what those other companies do as an additive. Correct. Typically, what we see as we go in, there's around a 63% automated protection on average.

Using our data of attack simulations ongoing, we can get that to over 98% automated protection. Wow. So, just a sidelight, but it's important to know.

We're going to talk, I'm going to ask you a little bit about national cyber warfare and about geopolitical tensions. But you arrived in the US a few weeks ago- Yes ... traveling from Jordan.

Yes. How was that? It was interesting.

I took a taxi from where I live to the southern border in Israel, crossed the border, took another taxi to the hotel. The next morning, took a flight out to Athens, Frankfurt, and then to the US. How long did that journey take?

Left Thursday morning, got to the US where I wanted to be in Vegas Saturday night. Oh my God. Yeah.

Well, we're glad you're here and we're glad you're safe. Yeah. This is a terrifying era we live in right now.

And I'm imagining, given what's going on in the world and given the advances in AI, that we have this evolving landscape of DDoS attacks. There must be some sort of strategies that enterprises are using to stay resilient. Could you maybe explain what they're doing to keep themselves defensed?

First of all, you're right. The current landscape, even before the explosion of AI, was already a very high threat, where enterprises were deploying defenses with many layers of defense. What they are trying to do now is close those gaps before an attack comes and try and preempt.

I think this is a theme across not just DDoS. This is a theme across the industry. So before, just to be clear, it was a reactionary- Correct ...

approach. Now it's a preemptive defense approach. I think in general, across the cyber realm, right- Mm ...

people that are responsible, CISOs that are responsible for the organizations or government, they're trying to figure out, "Okay, we've got all these defenses in place. " But your existing defenses need to be working. Mm-hmm.

I think there's a huge focus in this area. We focus in this area in DDoS. It's interesting because I've worked with a number of folks who are security experts.

Right. They started companies, Alan and Mitchell, Still Secure, and they always talk about this concept of security where traditionally, maybe until now- Right ... it was more of an evolutionary industry or technology versus the revolutionary things that are happening around it.

" And that you're telling me in a sense that that attitude or that posture among CISOs and others is changing. I think you're right. The industry's evolving very quickly, and the technologies are evolving very quickly.

If you're not getting ahead of it and figuring out how to prevent damage, you're going to have the damage. And I think visibility is critical, and figuring out how you protect your particular organization is critical across the spectrum, whether it's from the external, internal, lateral movement, whatever you're trying to protect. So, that brings me in a sense, again, back to AI in thatWe get a lot of surveys.

We write about a lot of surveys, a lot of studies, and what we consistently see is that there is a pressure from the top down- Right ... to adopt AI as quickly as possible, maybe with not as much stringent governance or upskilling among employees, safeguards, guardrails, whatever you want to call them, and that has created a tension or created a very difficult situation for the CISOs because they're under pressure to put these systems in place, like agents, for instance, but they're also responsible for the consequences if something were to go awry. So I'm wondering how the CISOs are kind of reconciling the pressure from the top down to adopt AI, yet still maintain safe and secure operations.

So I think AI is a huge topic. CISOs are under pressure. Some CISOs tried to block AI at the beginning.

That lasted a few days or a couple of weeks at the maximum. What if they... I mean, were there CISOs who got forced out if they were too slow or resistant?

I don't know of any, but I think the internal pressure was very quick. I think what you've seen is the smart organizations are looking at what they've got in the whole AI space, providing a singular offering to the various departments, scaling down the amount of AI tools, but still letting people fluidly work. I think that any company that isn't using AI is going to just fall far behind.

They're not going to be around. They don't have a choice, right? Yeah.

They're not going to be around, and I think everyone recognizes that the speed is incredible. When you get to the attack side, you can see, if you just use ChatGPT, you can see the speed that you're getting answers now. If you just apply that in a very limited fashion to just orchestrating attacks against organizations, you can imagine the speed that that's moving at.

Any manual process that you rely on in an organization with an AI orchestrated attack, you don't stand a chance. Which brings us back to what we do in our company. We provide that data prior for those defensive systems to be immunized prior to that attack ever arriving, because any type of reaction with a human element in it is slowly going to become redundant.

And when I say slowly, I think over the next 18 months maximum. Maybe if you could go a little bit deeper into some of the products you have and what they do and how they work in concert with some of the companies you mentioned earlier. Are there a couple that you could just highlight just for those who are unfamiliar with the- Sure.

So at the core of what our technology does is we are a company that figured out how to simulate non-disruptive DDoS attacks against production systems. That's the core patented technology that we developed over many years. It was released in 2021.

So if you've got hundreds or thousands of services, we're launching hundreds of attack simulations validating how your defenses work through actual data. So you're kind of testing, but in a non-threatening way. " So we give exact telemetry on every single layer of defense you've got, and we operate on big data sets, so we're launching thousands of simulations over a month's period.

And with just a few fixes, you can de-risk many thousands of entry points for attackers in an ongoing way because of things like configuration drift in security policies. We, in 2022, started significant research in AI because we generate what's referred to as unique data in the AI industry. We are now able to find, with a limited amount of knowledge on the targets that we see in an environment, point our simulator there, knowing where those vulnerabilities are likely going to be, and get that data as quickly as possible to the vendor responsible for that particular layer of security, so that when the customer's attacked, you prevent this initial damage or extended damage at least.

Was your background always in cybersecurity or were you- Yes. So I'm always wondering what led you to... I'm assuming you co-founded this company.

Yes. What led you to co-found this? You saw immediate need, or you'd come across some examples of kind of like high profile incidents, or?

So I was very involved in forming the team in Radware, like in 2011. That was a research team that we scaled to an emergency response team that I was essentially dealing with real-time attacks against large organizations, like the New York Stock Exchange, Hong Kong Stock Exchange- Oh, got it. Yeah ...

Vatican, all the banks in the US doing large operations, coming up with solutions in real time to mitigate those threats. And I then started a services company, seeing that every one of those attacks that I saw that caused extensive damage sometimes, sometimes for months, could have been prevented relatively easily. Mm-hmm.

And when you look at these large organizations that had seemingly endless budgets, what they didn't have was the knowledge of how those systems are bypassed. So we started actually as a cyber services company, and through need, transitioned to a product company in 2021. So I'm assuming that business is probably booming for you.

Yes. Or you're getting more inquiries than ever because I'm thinking about this classic scenario of people employing AI agents. I mean, I even read that Mark Zuckerberg's going to have his own chief of staff AI agents.

Right. With access to his ideas and his information, and I'm just wondering, that must be setting off alarm bells in a lot of these sectors where the bad guys, I mean, they're making as much use of AI agents as the white hats are. Right.

But there must be a palpable sense ofanxiety, I think within enterprises, especially when as agents, of course, begin to be adopted at these companies. Yeah. First of all, yes.

And depending on what you're responsible for, if you're responsible for hosting the agent infrastructure, you've got an entirely new threat to deal with in terms of even how you inspect your traffic, right? Agents are- Yeah ... completely new traffic.

They're not traditional web traffic or API traffic that you were used to in the past, this is different traffic. And I think that protecting these agents is going to become very complex because they're very dynamic. They're expanding and contracting.

Can I ask you really quickly, so conceivably, we're going to have security AI agents- Yes ... that defend against AI agents that are malicious. So could we conceivably have AI agent versus AI agent duels between good and nefarious purposes and good purposes, or?

I think in the enterprise space, you're going to see definitely orchestration agents operating. We already got it in companies. We're actually going to release later this quarter a very significant AI capability, which I can't get into too much yet.

But it's going to be something that is going to validate a lot of these types of protections because we understand that very, very quickly, and we're already getting some information from vendors and customers we're working with, that AI is going to be orchestrating a significant amount of attacks. And- In that vein, do you expect a fair number of announcements at RSAC along those lines, like AI agent defense systems of sorts that are brought out by companies. They're going to have- Yeah ...

some sort of platform or architecture to address this special problem you're talking about, or? I think there's going to be companies dealing with many areas of it. You say AI agents, but obviously AI is a large area.

Or autonomous. LLM poisoning, finding out, for instance, all of the models that you use in AI, how contaminated are these models? Where do they come from?

Yeah. It might be open source. What's in those models?

Who made those models? How are they leaning? There's models made in China, models made in America.

What's inside those models? How do you isolate those models in an environment to make sure that you're not going to damage your environment, and have unnecessary leakage? For instance, what we're doing in our company, we've got a significant project ongoing now for a couple of years, where we have a significant infrastructure being built, which is actually completed now, that we kind of anonymize all of our PII data before even starting to utilize it in that area, what we deem the non-PII area of our environment.

Because we don't know what these LLMs are going to do. Even if they're privately hosted, you don't really know, so you need to assume. Kind of like in the cloud.

You send data in the cloud, if that data's not encrypted, you don't know where that data's going. It's very similar with an LLM model, whether you're forming it locally or using a local database to maybe query external LLM models like ChatGPT or Claude or whatever it might be. To me, what's stunning or what's kind of troubling is the speed with which these new models are being pumped out.

Right. Conceivably, it seems like every other month, there's a new model from Claude. There's a new Claude model or GPT or what have you, and there's a lot more use of open source.

So the speed with which things are moving and advancing- Right ... makes this a particularly difficult time to defend your operations. I think it also opens up a lot of opportunity because, for instance, companies like us, again, we generate a lot of proprietary data, vulnerability data on environments across the spectrum.

We've got millions of data points, which allows us to leverage this to better protect our customers. And the AI allows us to get big data sets much quicker, to be able to deliver to the vendor in a more organized fashion to eliminate the most amount of vulnerability in the attack surface as possible. So it does bring a lot of opportunity, but you have to have, at least as a vendor, you have to take into account what you're doing with the AI, what the threats are, make sure that everything is QA'd between results automatically.

AI kind of checking AI, QA'ing the AI, so that it's reliable for your customers, that there won't be an accident. I'm not sure if you share the names of some of your customers. But if you don't, I'm wondering what sectors are they primarily come from, and what, if any, are their particular concerns?

We're in the 87th percentile plus in the BFSI industry, so banks, insurance companies- Mm ... trading platforms, payment processors- Got it ... credit card.

Government also, large e-commerce, but we primarily focus on the BFSI industry. Okay. And they're concerned about infrastructure uptime, service uptime, banking continuing, no disruption to banking services, transactions.

There's a high volume of transactions happening in these environments. You can't have downtime. So I was thinking about the landscape, in terms of the infrastructure, there's this big movement in the infrastructure towards faster, more use of data, AI, and I'm thinking about the landscape.

We have these geopolitical tensions that you've experienced firsthand. We've got open Claude phenomenon, whichI mean, it's hitting executives within companies like Meta. There was an incident recently there.

These increasingly sophisticated AI attacks, there's a lot to digest, and I'm wondering, do you foresee more geopolitically motivated attacks or even national cyber warfare? We talked a little bit about this before we started filming, but I'm wondering, you mentioned DDoS involving drones and others. I mean, can you maybe go over that a little bit again?

Sure. So DDoS is used extensively in cyber warfare. We saw it in Georgia, we saw it in Ukraine, Iran.

You see it all over the place. When you want to cripple infrastructure, cut communications, DDoS is a great attack tool to cause chaos. You also see DoS attacks more accurately, not DDoS attacks, for jamming drones.

If you look technically speaking, this is an actual DoS attack against the receptor on a drone, and this is what stops communication and drops the drone. So this is utilized in- Have you seen instances of that in the conflict in the Middle East now? Or it's probably existed, but are we starting to see an escalation of that or maybe even infrastructure?

I'm not an expert in drone warfare, but you can see that there's a lot of activity in the area. You can see recently that the Americans even asked Ukraine for assistance in this area. Yeah.

Definitely. I was recently in Texas in a very prestigious research institute that does a lot of research for the DoD, and they shared some very interesting findings on what's going on with drone warfare. And what was very interesting is how much DoS attack is being used in that warfare.

So definitely it's being used. Wow. That's a little something to ponder.

I mean, can I just ask you, how do organizations anticipate sudden surges in disruptions in their infrastructure? I mean, you're helping them, but are there other means that they use to kind of anticipate things before they happen? I mean, I don't know much about your field or is this something that is especially used, I would assume, in banking, in governments, finance?

Of course, the main thing any organization will do is try and have a solid architecture in their deployment and make sure that it's redundant and all these traditional concepts. I think what they're also trying to do is secure the application layer very heavily, too. Right.

So we're very focused on the application layer. Services are all over the place. They're in the cloud, they're in DC, they're in multiple clouds.

So I think organizations are trying to first get a grip on the attack surface, figure out how to protect that attack surface as best they can, and have the redundancy to scale. But without the protection, no matter how much scalability you've got, you'll- This is like a high wire act. I mean, in a sense, there's so much going on there.

The upside is incredible. Right. And we should probably point out that the upside, for the most part, is what these companies are looking at in terms of efficiency, profitability, et cetera.

But there's always that kind of a threat lingering in the background that they have to be aware of. You can see organizations that get hit with a cyber attack that makes headlines. You can see the immediate market cap effect, which can take- And we're seeing more of those ...

12 plus 24 months- Yeah ... and sometimes never get back to the position that they were at. So there is that imminent threat.

I mean, it's not a threat for everyone. It's not going to happen to every company. But for each company that this does happen to, it sets an entire industry kind of on alarm, so.

Right. And I think this is going to be a story we're going to see repeatedly over and over again. You always just wonder when it's going to reach a point where there is the defining events, and I'm not sure if we've reached that event yet.

I agree. I don't think we've reached an event that says there has to be some fundamental policy change or something like that. And bit of good luck of that happening.

Maybe, by the way, in cyber warfare, that has happened because there's a lot of very quick targeting of targets on the ground utilizing AI and stuff like that. But that's, of course, not in the headlines. Yeah, exactly.

So I think AI has had a tremendous impact on warfare in general. Just the speed at which everything is moving. It's in warfare.

And it's only going to get quicker. Yeah. And of course, that translates into the enterprise space.

We see it already that there are AI attacks being identified, and the EU Council is doing testing on AI attacks, and other governments are checking how they're going to respond to this. So this is clear that this is happening now. Right.

It's not the future. It's happening now. It's interesting.

Well, Matthew, this was a fascinating discussion. I'm glad you shared your expertise with us and let us know what's going on because things are changing faster than we could ever imagine, and it's going to make for very interesting times. I mean, I've never seen anything in the tech industry like what's happening with AI and especially on this side of things.

Right. So thanks again for your time and- Thank you, John ... it's nice meeting you.

You too. And we'll be back with more interviews later today, day one of RSAC. Hello, everybody.

We're here in Amsterdam at the KubeCon + CloudNativeCon Europe Conference, and we're having a little chat with my friend, Himanshu Singh from Broadcom, about, well, what's going on with VMware and Kubernetes. Welcome to the show. Thank you for having me.

This is fantastic. I mean, we're super excited about being at KubeCon. It's the preeminent conference in the Kubernetes space and for the platform engineering community, so we're glad to be part of it.

As I understand it, there's been some new extensions made to VKS, and maybe you could walk us through what those are a little bit. But as it looks to me, I think you've added support for the container networking interface, and you are kind of now building out an ecosystem. So what does that look like?

Yeah. And I want to kind of maybe even take a step back to bring people through kind of what are we really delivering overall, right? So of course, the primary offering we have is VMware Cloud Foundation, which is the private cloud platform, and VKS, or vSphere Kubernetes Service, is an inherent integral part of that.

And VKS delivers a CNCF-certified, fully conformant Kubernetes runtime, right? So for the platform teams to be able to use and build all applications. Now, along with VKS, we also include a variety of other building block services, VM service, volume service, network service, private AI services as well, because AI is a topic that you can't have a conversation without, right?

And so the idea is you've got all the building blocks in VCF overall to kind of build whatever modern application you are building, your AI application that you might be building. And it's fully extensible to any third-party service that is CNCF conformant as well, right? So what we're trying to do now is in addition to, for example, you talk about CNI with VKS, we ship in a built-in CNI with Antrea.

We include Calico in there as well, open source Calico. 6 release that recently came out, we're introducing the idea of bring your own CNI. So, you want to do any third-party CNI.

In this particular case, you want to do Calico Enterprise maybe. You want to do Cilium, for example. Absolutely available.

This actually takes the point of view we've had with our Kubernetes platform and kind of extends it. The point of view being that we're not trying to create a highly opinionated ecosystem of our own. We want to be part of the existing community ecosystem.

So the way we have built VKS, it is very, very close to the community of Kubernetes, which means that, one, it's easy to adopt, right? There's no customizations and all that that you got to do or jump through hoops and everything. Also, it helps us release newer versions of our Kubernetes distro very, very quickly right after the community release comes out, typically within 60 days, right?

So that helps. In addition to that, we're also being able to provide support for multiple releases, like N minus two or more than that. We're including 24 months of support for all our Kubernetes releases as well.

So what that does is it simplifies things from the platform team for the infrastructure teams, so that, one, you don't have to worry about, hey, all these different applications need to be upgraded to the newer version at the same time. Every different team can be on their own timeline when they want to. And also by having that kind of long-term support included, it just reduces or eliminates any kind of, "Hey, we only get 12 months of support.

We need to buy extra support and all that," and those kind of things. In terms of Kubernetes, like the community comes out with a new release three to four months. So it's just for us to be able to do that with 24 months of support, you're going to be able to upgrade within that timeframe no problem.

So it just simplifies things a lot overall. So from a Kubernetes perspective, that's one area we're really happy about. The other thing I wanted to also call out is with the new release as well, of course, and folks might not know this, as part of the VCF platform, we are providing or entitling you to Ubuntu OS for free as included.

However, if you'd rather have RHEL, for example, and you want to use that, you can bring your own RHEL license. We support that completely as well. So it again furthers the idea of having a very open platform for you to be able to use the tools and the technologies that you really like, build it on the VCF platform, build it using VKS, whether you're modernizing an existing application, you're building new AI applications, for example.

So I think that has been something that's been very core to VMware over time, and we're really excited to be able to continue to focus on that kind of mindset as we go forward. It seems like we're starting to see more convergence. And early on I might have seen like a DevOps team or a platform engineering team managing Kubernetes in isolation on a handful of workloads.

Now it looks like Kubernetes is becoming more mainstream, but it still runs on a VM most of the time. Yeah. So it seems like we're moving to some point now where those teams can work a little more easily together because there's administrators that know all about VMware, but there's not many of them that know about Kubernetes.

Yeah. So how do you kind of make this team work a little more hand in glove? Yeah.

And this is a topic that's very, very common across organizations. One is about, hey, we've got people who know the platform. Can we help them uplevel and upskill them to be able to expand their scope of influence, grow in their careers, for example?

Then also looking at, can I do things in a more consistent way, no matter whether I'm using virtual machines or containers, or I'm trying to build a new application? Can I avoid creating these silos, right? And so with VCF, that's been very fundamental to our cause.

So one, as an admin, you can deploy VMs or containers, containers running in virtual machines, so they're getting all the security and isolation benefits that VMs get. But you can do all that with the same set of consistent operations. So you don't have to kind of completely learn a whole new skill.

You extend and build on what you already know, and you grow yourself from being an IT admin, a VI admin, to a cloud admin, to a Kubernetes admin, for example. And so that's a key benefit of that. You get all the governance policies, all the control that you need, but you're able to then provision your infrastructure for the person wearing the platform...

hat at that point in time. I don't want to say a platform team because you made the exact point of this is converging, and then we are seeing the same thing. People are wearing multiple hats.

So when you're wearing that platform engineer hat, hey, because the VKS as a Kubernetes platform, it's CNCF certified, is extensible, it runs all your applications, right? So that worry is completely out of the question. You get that support, et cetera, that we talked about that simplifies things, and it just comes with integrations with all these kind of common PE tools that you'd use, whether it is Argo CD, whether it is Helm charts, for example.

So just to your point about, hey, how do we simplify things? That's the idea with built-in integrations. On top of that, in fact, the other thing, what we're doing is, we're not trying to create an ecosystem of our own, right?

We're trying to integrate into the existing ecosystem when the way we're doing it, we're making sure that there are validations available on VKS with a variety of other cloud native leaders in the community, in the industry. In fact, at the conference, we announced new partnerships, or new collaborations that we've had with folks like F5, folks like Kong, Tigera, et cetera. And so that it just, when customers are looking to build on VKS, it's easy for them.

You've got reference architecture, technical guidance, et cetera, that's available to them. And this adds to all these similar kind of guidance that we have with others, like Run:ai, for example, or MuleSoft or Cosmonic for WASM. And so I think just bringing it all together, the key idea is we want to make things simpler and easier and more consistent when it comes to the cloud admin persona or a platform engineer persona.

And if you look at it from an organizational perspective overall for the decision-maker or somebody with a P&L kind of responsibility, one, hey, all of this contributes to you being able to modernize your applications at a significantly lower TCO, while you're getting all the benefits that VMware has built into the platform over multiple decades, right? The enterprise-grade security, compliance, all the reliability that comes with fundamental VCF platform, no matter what kind of workload you're trying to build on it, right? Whether you're deploying on virtual machines, you're deploying on containers, you're trying to do an AI application.

And to your point about skill sets earlier, right? That this is extremely critical because it helps to, again, not create the silos, but also be able to make sure that your organization and the resource of the people you have are able to grow in their roles and be more productive, and not have to worry about certain things that the platform and the consistency of the platform can take care of for them as well. So I think across those different types of roles that people play, we're super excited about how VCF and VKS are playing that role to make things easier for our customers.

Now, we're also seeing a new type of workload in the proverbial IT zoo, and it's these AI inference models that are coming through. Is that going to force this convergence conversation? Because I can't really have a third set of teams to go support that either.

So is that kind of the thing that's really going to break the proverbial camel's back and get everybody to reorganize? No, I hope not. And fundamentally, while I think there's the data scientist kind of team that typically is generally a team as well, and they're really focused on getting the best out of the model, the LLM that they're trying to do.

And as I mentioned earlier, those private AI services that VCF comes with, we've got a set of capabilities really for that persona. But the idea is, hey, you can extend the same platform built in the same consistent way, and you're going to build it on Kubernetes, right? If you're building an AI application today, you're building it on a Kubernetes platform.

So VKS becomes that substrate that you can build your AI applications. When it comes to the infrastructure side of things, we're giving you that set of capabilities, whether it is things like being able to monitor your GPU utilization and all sorts of different metrics, having consistent dashboards in your existing VCF console to be able to get all those details in there. But also, for the data scientist, you have services, for example, if you need to build an agent, there's an agent builder service.

There's things like data indexing, retrieval services. There's a full model runtime that comes in. There is something called a model gallery, which helps to make sure that one, you have a role-based access, for example, so the right people are able to access the right set of models.

But also that you have the governance to make sure that you're not just downloading a model from somewhere and starting to use in your enterprise. Because fundamentally, and unfortunately, we've seen this in the industry already, where people don't realize that they're using models that might be public, and they are using internal IP or data to query and do those kind of things, and the model ends up kind of absorbing that internal IP, which is never good for an organization. " You can be deploying your private cloud environment on a hyperscaler, at an edge environment, at a CSP, for example, or in-house, kind of on-prem data centers.

But the same benefit setup that the VCF platform is able to provide to any workload is applicable for AI as well. So that's kind of the way we're looking at not creating this separate silo, separate team, but bring it all together. People can specialize in the areas that they're trying to do, as a data scientist, for example, or as a platform engineer, for example, but you're building on that same consistent platform that is able to meet everybody's needs as well.

You guys have been making a case forThe convergence of compute storage and networking for a while now. As we look at this convergence and all these things coming together, will we reach a point where maybe we need to fundamentally rethink how the IT team itself is organized and as another way of thinking about this? Yeah, that's a very interesting point of view, right?

There is always going to be, as we talk to customers, there's more and more expansion of that IT team's role and bringing those capabilities together. " And we completely agree. There's going to be things that an IT admin can do on the network side to get things started, and we've introduced some of that into the platform as well.

But at the same time, you will have that kind of extra specialized needs for that next level. So you can get started easily, get started faster, so that we're not creating delays in the system while you're still able to bring in that special expertise to really optimize the network, for example, or optimize your storage, or optimize your compute, for example. And so the platform is built that way.

So to enable collaboration across these different teams and help them see the value that they provide into the overall system, versus be part of that system overall, versus be separate as a silo on their own. Mm-hmm. It also seems, sometimes, we'll talk about things in senses of extremes, but the reality is a little more nuanced.

So we have a lot of cloud-native applications being deployed, and we have a lot of legacy monolithic applications. And those are still being updated as well. They're not just being put on the side per se.

And then we're going to have integrations between them. So as we put all that together, does that also require the IT team to get in tune with the development team that's building more complex applications than ever, and they're all connected? Yeah.

If you look at IT teams, at the end of the day, you need to be able to manage that infrastructure, provide the right SLAs to your customer team, right? Whether the customer is the platform team that's managing certain things, or if the IT team is more extended, where you're serving the needs of developers, right? You need to be able to have the governance and the control and all that stuff that you need while being able to provide self-service access to the dev teams, et cetera.

Provide that sandbox environment where they have all the access and the flexibility that they need so they can be productive, they can be creative, be innovative, and have faster time to value as they build these newer applications or modernize some of those applications. But extending a monolithic application to be able to meet certain needs or being able to consume services from a third-party provider, for example. So from a platform perspective, that's a very key piece that we see VCF to be able to do.

And so the idea of the IT teams being able to serve the needs of all those different personas or the internal customers is critical. So being able to manage the platform in a very consistent way, so you get the governance that you need while providing the flexibility for the other personas is something that's built into VCF as a very fundamental aspect. "?

Well- ... I think different teams are at different stages and different environments, so it's going to vary a lot. " We do see, to your point earlier, that convergence happening more and more.

There's a lot more, I would say, collaboration across those. And then there's organizations where they are trying to basically bring those roles a lot closer together. I think as we are seeing the evolution of this DevOps and SRE and platform teams happening.

IT admins that used to be, for example, having a very specific role are starting to wear multiple hats, to my point earlier. And I think as that changes, as that happens, there's going to be some growing pains. There's going to be some of that learning that different teams will have to do.

But I think that's very specific to individual environments. And the customer, the user teams, are going to be the ones who have the best understanding of what works for them, right? Based on how they're organized and where they want to get to.

I think the critical piece for vendors like ourselves is to be able to provide the platform capabilities that meet all their different needs, and that flexibility needs to be in the solutions that vendors offer. And, so by having the point of view that I was talking about earlier, we're not trying to create a platform and an ecosystem of our own. We're trying to make sure that we are part of the ecosystem that exists so that all the different personas are able to do what they like, do what they prefer.

And so we're meeting them where they are, versus other teams trying to come to them. " Mm-hmm. I think it's the art of all teams, right?

There's only one team, but we need to figure out how to let everybody do what they need to do without getting in each other's way. Yeah. Hey, Himanshu, thanks for being on the show.

Thank you for having me. All right. And we'll be back in a minute.

Hey, everyone. Welcome back to our day two coverage of RSA C. RSAC Conference here in San Francisco at Moscone.

I couldn't think of a better person to end our day two coverage than with my friend here. If you're in security, you may know her. Her name is Chenxi Wang.

Chenxi has held about every title you could think of within the security food chain, from analyst to CSO to chief strategy officer to VC, founder. Founder. She's done it all.

Chenxi, welcome. How are you? Thank you for having me.

All right. It's great to be back. Thank you for coming here.

You don't have to thank me. Chenxi, I didn't want to embarrass you, but all of those roles that I mentioned, and did I mention she's Dr. Chenxi Wang as well, technically, with a PhD.

You know, I did all these things because I didn't know what I want to do when I grow up. Grow up. And I hope you stay that way- I still don't know ...

for the rest of your life. Yes, thank you. Because that keeps you young.

Thank you. Well, let's jump into it. You just came off the stage.

You were on a panel that you put together. Yeah. NVIDIA, Cerebras, and I'm missing one.

And Glean. And Glean. Mm-hmm.

Tell us about that. So NVIDIA, as you know, is the fastest maker of billionaires. Yes, it is.

Right? Glean is now a very fast maker of millionaires, and Cerebras is getting there. Yes.

They are already billion, like double-digit billion. We're seeing them broken. And super interesting companies, obviously, Cerebras and NVIDIA are both chip makers.

NVIDIA has more software stacked today, but Cerebras is getting there, and Glean is purely software layer. Mm-hmm. An enterprise AI layer for search, for building agents.

So they're all in the ecosystem, tightly integrated together, and I had three of them on stage today just to talk about, from their respective points of view, where this agentic enterprise trend is going. So it's a super interesting discussion. We had a room full of people and questions, and love to talk about that.

So what was the consensus? Well, there wasn't any consensus per se, but we talked about how this is a security conference, right? Mm-hmm.

So security people like to put controls in place and feel comfortable before things move. The panel talked about why we need to move with imperfect controls, imperfect infrastructure, imperfect data. Move fast, refine controls, iterate, and then potentially achieve perfection.

So some people call that DevOps, you know? You're right. DevOps.

Yes. That's exactly what they're describing. Yes.

Right? MVP. Yeah.

Get your MVP out, iterate, feedback loops, reiterate. Yep. Yeah.

Some people have tried that before. Look, I have to admit- Mm-hmm ... we have been on our own agentic adventure at Techstrong.

I wouldn't call it enterprise per se, but we have been not even playing. We've been really digging in- Mm-hmm ... on agentic.

And we're not a software development shop, right? We don't write a lot of software. Right.

But we produce an awful lot of content. Mm-hmm. And everything that's involved in distributing and getting that content out to market and all of the pieces of it.

Yep. Everything from shooting this video, editing the videos, writing the articles, publishing the articles, distributing, amplifying, everything that goes into the business. I made a deal with my people.

Okay. It's very similar to Jensen. I'm no Jensen Huang.

Oh. Very similar to Jensen. I'll give them- Jensen shimout.

Yeah, Jensen. No leather coat, nothing. But I'll give them money to run agents.

Token money, whatever you want to call it. Yeah. I just ask that every week, give me a progress report on how your agent work is doing, and at the end of the month, let's talk about what did you do this month.

How did this month go? Mm-hmm. And should we continue with this?

Yeah. And I got to tell you, it is like a Cambrian explosion of ideas and life and looking at things we haven't looked at. Ah.

Yeah. And so there's not a doubt in my mind. Isn't that exciting?

Super exciting. It's beyond exciting. It's almost drugs.

It's intoxicating. It's intoxicating. Beyond even intoxicating.

It's drugs. I'm telling you, I've got people coming in the office on weekends, staying late at night, coming in the next day like they've been up all night with their agents doing things. That is drugs.

That's drugs. That's drugs. Yeah.

It's not just liquor. But it's better drugs than the actual drugs. Yes.

So I'm all for it. It's healthier for you, I think. I'm not sure how healthy it is.

Well, you're right. Staying up late and not getting sleep. No, you're right.

But it's fine. It's funny, we turned Mitchell onto it. Mitchell Ashley, who used to work with me for Future.

Oh, yeah. He still works with me. I hooked him up on Perplexity Computer last night.

Oh. At dinner. He was on his phone.

He didn't even eat dinner. " I said, "Whip out your credit card. " But it's true.

So-I do believe that what they're saying is-- And I'm a security person, it hurts me to say this, but they're right. Yeah. We are in the middle of an evolution, right?

A revolution. A revolution, not evolution. Revolution.

And everybody wants to be on the cutting edge. If you're not, you're not only left behind, but you kind of feel like it's a societal tide that- Yes ... you want to be part of that.

We all want to be cool, right? Yeah. The cool kids.

Exactly. Especially in tech, a lot of us weren't cool kids growing up. Yes, but for businesses, it's almost existential.

Yes, it is. Right? And so if you don't tell your employees to experiment, to really understand the full power of AI and agentic AI as an extension, then you're not doing yourself- No ...

the right service. Right? And also, it's like-- What's the analogy people are saying?

That all the kids are running and you're staying here, and the world is running, too. And what are you staying here for? Right.

Right. Well, is it worth staying there for? There may not be anything to stay at if the world moves.

Exactly. Yeah. So now let me turn this around.

Put on your VC hat for me. What does this mean? It's hard.

For a VC, it's really hard because things are changing so fast. What's hot or what's interesting this month, next month, the month after may be completely obsolete because it could be built into the AI platform. I know we saw with Anthropic's announcement of their- Scanning ...

product security capability. Right? " Is AppSec done?

Is AppSec done? I don't think it's done, per se. No.

But if you're an AppSec founder, you'd be like- So I've written about this. Look. Yeah.

AppSec, for the most part, was founded on finding bugs. We scanned. We fuzzed.

Mm-hmm. We found bugs, and then someone has to fix them. But someone moved the cheese in a week.

We could find as many bugs as- Yeah ... more bugs than you could handle. Yeah.

People are shutting down their bug bounty programs. Mm-hmm. The focus in AppSec now has to be governance.

It's possible because the way I think about it is we move from assembly code to high-level language code. Mm-hmm. And now the high-level language code is written by AI, so what are we moving to as a human?

We're moving to a higher level abstraction, and that is probably requirements and governance controls, and at the end, testing controls, right? Yes. So human-- Today I saw a term says we're not doing human-in-the-loop anymore because that's just too expensive, not scalable.

We're doing human at the helm. Yes. Right?

I've seen this, too. Right. So human at the helm, meaning that we are higher level abstraction thinkers, so we have to test things and look for bugs at that level, right?

Because if we're still looking for bugs at the language level, we're obsolete. You're done. You'll never...

Exactly. Yeah. So AppSec has to move to that level.

And then if you think about that level, looking for bugs and fixes, the current technologies may not be relevant. I got a really personal, hard question for you. So I wrote another article earlier this month.

I was going to call you to get your opinion, but then I just published it. I was reading an article, I don't know if it was in "The Times" or "The Wall Street Journal"- Mm-hmm ... about VCs- Okay ...

and AI making some VC functions- Mm-hmm. Yeah ... obsolete.

Yeah. Right? " You may not.

Yeah. But you know "Moneyball"- This is the Brad Pitt movie. Yes.

Yeah. Well, you think of it as a Brad-- My wife does, too. To me, it's a baseball movie.

But anyway, the- We know what we're focusing on here. Yeah, exactly. Okay.

But the thing about it is there's two schools here. One is let's look at the analytics of baseball and make decisions based on- Mm-hmm ... pure analytics.

The other school of thought is baseball lives in the gut. Mm. Your knowledge of baseball.

You make a gut decision. This guy could really pitch. This guy could really hit.

He's a player. He's not, et cetera. And there was this big fight.

And eventually "Moneyball," the analytics won, right? The analytics don't lie. It's the same thing I see happening with VCs now.

Some VCs say- Mm-hmm ... you could run spreadsheets till the cows come home. It's a gut feeling.

It's an art, not a science to pick a winner- Mm ... as a VC. How do you feel?

I agree, meaning that you can probably use AI agents to make decisions maybe even better than we can make decisions. But I can tell you as a VC, making decisions, picking the company is only part of the job. Another part of the job, let's say it's a very hot company.

It only has room for four VCs, and you have 10 VCs who want to go in. Who wins? Who wins?

Everybody's got agents. Who wins? Who wins?

It's the personal relationship. And it's- It is, and still today is, right? Because the founders looking at the different firms, they'll say, when timeBecomes hard.

Who do I trust? To work with. To work with.

Who's going to have my backs? And if everyone has agents, how do you make that decision, right? So still, you have to have the personal trust, and that is a thing that I think a level of relationship that agents do not replace today.

Right. You know what? " Right?

If I send my agent, you- Keep walking. I keep walking. Keep walking.

Right? Right. So.

You know what? I think that's very analogous also to the whole IT analyst industry. Mm.

Right? You look at the Gartners, the Forresters, the four or five ones, and you were an analyst. Mm-hmm.

You know this. Mm-hmm. If the AI could do the analysis as good or better- Mm-hmm ...

than the human can, well, what value does the analyst bring to me? Well, it's the personality. It's that human-to-human relationship.

It's trustworthiness. It's the gravitas- Yeah ... of the person- Mm-hmm ...

not just of the numbers- Yeah ... and number crunching or analysis like that. And I think it's still a very easy thing to think about is on LinkedIn now, everybody's writing their LinkedIn post with- AI.

Yeah. Right. So all the posts are similar.

But still, some people get more likes than others. Why? Because they have personalities.

Personalities. Right? And here's the thing I learned.

I strive really hard to put my personality- Mm-hmm ... into my AI stuff- Mm-hmm ... because I want it to be me.

Yeah. I despise the AI tells, as I call it, and all of that. I'll talk to you offline about it, but I've got a whole toolkit to talk right for the AI to talk in Shimmy voice.

Yes. Yes. You know?

And then I have two, actually. I have classic Shimmy and Brooklyn Shimmy. Because when I really want to go off, I tell it right in Brooklyn Shimmy.

But, it's a personal thing for me, but I think that's the world we're headed towards, where people are going to count, personality's going to count- Mm-hmm ... reputation is going to count. Very count, yeah.

And look, that's going to be good for some people. But then, and I'm not knocking Gartner. I'm not knocking Gartner.

But Gartner, for the last 10 or more, maybe 20 years, 15 years, has tried to sort of anonymize their agents or their analysts, right? Because their analysts, I grew up in John Pescatore being at Gartner. Oh, John Pescatore.

Right. I remember him. Yeah.

Yeah. They were giant. They were personalities.

Personalities, yeah. You think today, who are the personalities at some of these large analyst firms? So- They're almost interchangeable.

Yeah. Analyst is one industry that it's hard to pinpoint, but the other industries have the analogy of, a lot of things are done by agents. Yeah.

And what distinguish you is your personality, your emotional sharpness, and whatnot, right? And I think that continue will be- Yeah ... an interesting point because I subscribe to, like, 30-some YouTube channels.

Right? Too many. Me too.

So in the beginning of the year, I'm like, "Oh, too many. " Right? So I noticed in the past six month, a lot of them started having AI-generated content, right?

The channels I visit more are the- Are human ... human channels. The channels that have more and more AI-generated content, I visit them less and less.

Not because I consciously think about it- No ... just because I'm just not interested in them anymore because they all look the same. I've heard some people say there's no soul.

There's no soul to it. Right. So, you want that.

When all the cities look like Dubai, you're going to want something else. Right. Right.

Someone used to say that because growing up in New York and then moving to Florida- Mm-hmm ... right, I always, whoa, the weather's beautiful here. Yeah, the weather's beautiful.

But you can only appreciate Florida if you understand what the weather is in New York. Yeah. Mm-hmm.

Otherwise, it's just all the same. But I love New York, so. Me too.

Yeah. But my wife won't move back there, so I'm stuck in Florida. But, we go to New York once a quarter at least, and my oldest son's up in Boston now, so we go there pretty often, so I get my share of that- Yeah ...

I'm home. Yeah. But Hawaii's like that, too.

Well, now they just had terrible flooding, and I'm sorry, but generally, it's 82 degrees every day, all year round. And it's paradise, but- That gets boring, right? It does.

When everything's manufactured, then you crave for organic things. It's like that movie. What was the movie?

The guy lived in... It was all just, like, a big movie set. Jim Carrey was in it.

Oh, The Truman Show. The Truman Show. Mm-hmm.

That's kind of- Yeah ... boring. Yeah.

It's boring. Yeah. Anyway, Chenxi, it's so great catching up with you.

You are always a pleasure to talk with. Enjoy the rest of our essay. I will.

Good luck. Where can people follow you and find out more about what you're doing? Yeah.

Find me on LinkedIn, Chenxi Wang, Rain Capital. I publish a lot of content- Yes, you do ... on LinkedIn, and I'm on X too, although LinkedIn is my primary- Me too ...

vc Absolutely. Chenxi, thank you. Thank you.

All right, we're going to wrap up day two. Yeah, I guess it's day two. Yesterday...

We'll be here tomorrow, we'll be here Thursday, but for now, this is Alan Schimmel. Enjoy. Take care.

It's Jensen Schimmel. Jensen. Yeah, I'm getting a leather coat.

Hey everyone. This is Alan Schimmel, CEO of Techstrong. Welcome.

Welcome to this very special virtual event that we are producing in partnership with our friends at Microsoft. The event is titled "Unlocking the Future of Agentic Experiences," and it's going to be a series of videos in this virtual event that you're going to be able to take a look at and interact maybe with some of the analysts and speakers here. I really think you're going to enjoy and get a lot out of these videos and this event, and look forward to hearing your feedback.

I'd like to kick things off with our keynote, and it's our keynote because I think we've got two terrific speakers in this one, and it's around the future of apps, right? And it features Futurum CEO and principal analyst Daniel Newman. If you've ever seen Daniel on any of the many TV shows or conferences that he keynotes, you know what a dynamic thought leader he is.

I think you'll enjoy it. And Daniel is going to be speaking with none other than Ryan Cunningham. Ryan, of course, is corporate VP for the Power Platform at Microsoft.

And Ryan is going to share with Daniel and with you the all-up vision, the all-around vision for Power Platform. We're going to connect the dots between apps, agents, and interfaces. Right?

Ryan and with Daniel are going to illustrate how Microsoft is leading automation in this AI era. He's going to articulate how Microsoft is enabling every organization to build, govern, and scale intelligent solutions with unmatched speed and trust, driving the future of agentic apps. It's a great discussion, and I think it's a great learning experience.

So here's Daniel Newman and Ryan Cunningham. Alan, thanks so much for that introduction. And to introduce myself, I'm Daniel Newman, CEO of Futurum.

Very excited to be here today with all of you, and even more excited to introduce my guest for this conversation, Ryan Cunningham from Microsoft. Ryan, why don't you say hello to everybody and give a little bit of background on the work you do at Microsoft? Thank you, Daniel.

It's awesome to be here with everybody today. So I'm Ryan. I'm the corporate vice president for Power Platform here at Microsoft.

So look after all the teams of product people and engineers and designers that are building really our low-code application platform and the future of where that is going. Really excited to talk to you about that today. Ryan, I've been working with and around your team for many years as an analyst.

It's been great to follow. Mm-hmm. Of course, the change that's been going on in this market is extraordinary, and I think that everyone out there is going to leave this conversation knowing a little bit more.

And hopefully, maybe you'll give us a little bit of that secret sauce about all the stuff Microsoft's doing. Nothing too secret, though. You know how that goes.

Oh, I know. So let's start big. When we talk about the future of apps, connecting agents, interfaces, applications, what is the North Star for Microsoft?

What are you guys heading towards here? Yeah. Look, it's a crazy time to be alive in a business application platform environment, right?

Because this whole world is being turned upside down in actually two dimensions at the same time. One is how we build software, radically changing in a world of agents and vibe coding and everything that is filling up our LinkedIn feeds as technology professionals. What's really interesting right now is the dramatic expansion in efficacy of what I can build, and the dramatic expansion of who can participate at the same time.

You have to be evolving the platform even more and even more quickly- Right ... to get them what they need and what they're trying to do to accomplish the future that they're trying to build. Yeah, 100%.

And I would say to even build on your last comment, because it's relevant here, it's not just an opportunity for more people to tinker and build things. It's actually really an imperative. If we're really going to accept the premise that every company that wasn't born yesterday is operating inefficiently and needs to rapidly advance in a world of agents, then the expertise you need is not just the AI technology expertise.

You actually need to go get all of the process expertise. All the humans who know what it really means to run a more efficient HR department or finance department or whatever it is, they're sitting with a real job in that department today. You've got to go figure out, how do I harness that expertise and bring those tools right to the point where the process is actually happening today?

And that's where you need a higher abstraction platform that has agents built into it that help do the coding, that help do the work. Where we're really focused right now, particularly in the space of business applications and productivity, is really make that relevant to the way companies run and operate. We're not out there to serve any possible whim of any possible developer on the planet.

There's lots of great tools for that. Microsoft makes some of them in other places. But here we're really focused on the core operating system of a company.

And by that, I don't mean Windows, I mean sort of all the business applications, business processes, specialist teams of people that today make a company tick. We're seeing consolidation in this era. Customers have a ton of choice.

Yeah. " Right. What we're going to want to see is the orchestration is going to be super important, and then, of course, the speed, flexibility, access to all the tools, data, cloud, and of course, Microsoft's in a very small group- Right ...

of companies that has pretty much all of those things. Right. Not the only, but one of a very small number.

Yeah. And I think that makes you competitive. I want to go to the pragmatic side, because a lot of the viewers here are probably thinking about how do I do this?

How do we do this in our firm? We hear some of those stats about AI ROI in the enterprise, and then let's just say that I'm an absolute believer, but I do think there's some hurdles. What are those key enablers you're seeing, fundamental enablers that enterprises need to get right now- Right ...

to make sure that those POCs and those production AI projects start to work and really show value? Yeah. We're seeing customers adopt exactly the mentality you're talking about.

Not just how do I run the current process faster, but what if I fundamentally changed the process itself to really great effect? We've shared some stories of retailers that are starting to use agents and apps and automation together to totally change how they do things like fraud detection and even refunds and returns management. If I go contact an online retailer and say I want a refund, traditionally that's a human going and vetting, is that a real customer?

Did they buy something or is this fraud? Does it meet our return policy? Which is, by the way, usually a 50-page PDF that changes once a quarter.

And then do I want to issue the refund or can I save them as a customer? And that's super slow, and it's super inefficient, and it's really expensive, and often it's outsourced to vendors. Can I go implement an agent that does that instantaneously or at least does major parts of it instantaneously?

It really starts to change my operating and my risk profile and my customer relationships. And so even in use cases like that, starting to see millions of dollars of value unlocked really quickly and just better customer satisfaction. Actually, the balance of value is really shifting towards that process expertise.

" That's just not a thing that happens to most regular people. But a whole lot of people woke up this morning and said, "Man, this part of my job sucks. That could be better.

" And really harnessing that energy, that value, those skills and those people, and bringing great tools to them, that's part of the whole thesis behind why a platform is critical right now. What does it mean to totally change that interface into a human and agent collaboration space? What does it mean to go see the activity of what agents are doing on your behalf when they need your input?

Let's talk a little bit about Plan Designer. Yeah. We're seeing we go from manual to automated to agentic level orchestration, which is great.

One of the key things, too, is going to be trust. We got to trust our systems. We got to be sure that the agent workflows we're building, that they're inspected- Yeah ...

that they're constantly modified to be sure that they're right, that they're traceable. Talk a little bit about how Plan Designer can help companies, because that's a lot of work, by the way. Yeah.

That's a lot of work- Yeah ... you can automate or- Yeah ... streamline some of that out of the process.

Yeah. Well, look, for folks out there listening that haven't experienced Plans in Power Apps, it's worth trying out. com.

You can try it today. But what it really is, is a different kind of AI-centric development experience. You go type into that box a business problem.

We do not assume that you just want us to spit out a thousand lines of JavaScript that you need an app, like a lot of vibe coding platforms today. We actually do what a real software team would do. In fact, we've built in a digital software team.

We've trained a requirements agent, a process agent, a data agent, a solution architect agent. It's a highly collaborative environment. This is not a sort of throw a paragraph over the fence and watch magic happen.

It's really sort of training and teaching people with process expertise how to think like software architects and solution architects so that they can know up ahead of time, why do I want AI to do certain things? Where do I want it to work? How do I want it to interface with humans?

And that's really the foundation of that trust in a system. Have you seen some examples out there of Plan Designer being sort of delivering promise? Because it sounds- Yeah ...

super optimistic. Are people using this? Oh, 100%.

We have started to see really interesting sort of challenges thrown at it. We have customers in highly regulated financial services contexts that are taking decades of old, homegrown, non-compliant software that was built over, whether it's hacked in Excel or built one-off, and sort of saying, "Can I use this to rapidly modernize what I had before in a way where traditionally going and-Turning all that old stuff into full stack software was just incredibly costly and cost prohibitive. Starting to bring those things into plans and generate a more robust plan for modern software, moving much faster.

We've even seen huge extremes of that. " And actually, the results were pretty promising. So, people are getting really creative with bring the problem, bring the challenge, bring the business area that you want to improve, and then start working with these agents and on this digital software team to design a solution.

So, we're doing all this work. We are trying to train people to think differently, remove constraints, whatever's possible. But the UI is it that seems to be the next frontier.

Like the old enterprise software, it's like these are the things you can move, and these are the things you can't, and here's what you can customize, and here's what you can't, and here's your dashboard, and it's like, great. But in the future, like- Right ... I might just want to say, "Hey, Microsoft," whatever.

Yeah. " Right. And then I want it to obviously learn based on my behavior over time, what I want to know.

Right. Then I want it to continuously, things like that. Right.

How do you see, being in this space so much, the UI evolving? Yeah. I think, specifically chat as a UI is super compelling and natural for a lot of things.

I do not believe that we're going to go regress 40 years of UI innovation and go all back to chat in the command line, though. There's a lot of things for which text is actually a terrible modality, in which just paragraphs are not great. And I think there's a more underlying thing here that you're touching on, which is a lot of traditional experiences, whether it's text-based or visual, assume a human shows up knowing an intent, right?

As opposed to an agent being really proactive and taking care of something for me, or pushing me an update or a notification when I need to know it. And so I think those experiences start to evolve a lot. What gets really interesting is where they meet.

And we really see a lot of this task-based data entry, repetitive stuff, increasingly getting delegated to agents on your team. But that means you'll need to work with that team in a totally different way, right? And where a traditional CRM system or HR system, or whatever, pick your business application, was previously, like we talked about, people typing into boxes and then other people viewing reports.

What does it mean to totally change that interface into a human and agent collaboration space? What does it mean to go see the activity of what agents are doing on your behalf when they need your input, when they're blocked on something, or they've noticed a trend or there's a form they tried to fill out but didn't complete? Then that's an important meeting space to go have experiences and user experiences.

And a lot of times, those do need to be structured in a visual way. A lot of times they could happen ephemerally or with a chat message. But how do you route people to the right place at the right time?

We're working across all of those fronts. That's why we have a robust set of tools in Copilot Studio for building the agent part of all of those things. It's why we have a ton of evolution in Power Apps, sort of becoming this new agent-centric experience where I can see a feed of that activity, I can have agents help me do the work in the applications.

And those two worlds will just continue to evolve together as we start to bring things into the future. So you heard me talk a little bit earlier, Ryan, about governance. Governance is part of the critical constraint and one of the things that differentiates software, right?

The reason we can't just use OpenAI for everything would be because it doesn't know how to handle the data. It would be like, oh, let me talk, help me do a job offer, or help me do a- Yeah ... compliant healthcare notice- Right ...

to somebody. It doesn't know how to do that. Right.

So building applications that do know how to do that is the key. You got to build it with-- And of course, we want to go fast. Right.

So fast is the new rule. Right. But the trust and scale are the other words.

I know you often use- Yeah ... these words, but like- Yeah ... what do you think, and we're a company sort of struggling with governance and scale here with automation, and how do you think what you're building in Agent Oversight can help them?

Yeah. So I'd say there's a couple dimensions to governance and scale. There's the breadth dimension.

We have a whole lot more people who now can build a whole lot more things. How do I make sure that all that stays on the straight and narrow when I can't centrally top-down code review every single thing that every single person and agent is doing? And then there's sort of depth scale.

When I do want to roll out a mission-critical solution to 100,000 employees that has AI in it, how do I make sure that that AI is not just functioning, but actually continuing to get better every single day? And the good news is, we're not inventing any of that from scratch. Breadth scale and depth scale were a challenge in the first generation of Power Platform.

And something that we've built a ton of capability into the platform over the last couple of years to really tackle at huge scale, and we call that the managed platform set of capabilities. And within it, there is managed governance, managed security, managed operations for life cycle, ALM management, stuff like that. And managed availability, even.

How do I go ensure high availability, run disaster recovery drills for critical workloads? All of that is built into solutions baked on the Power Platform. And all of that value accrues to this next generation of components being built as well.

An agent built in Copilot Studio benefits from all of those managed capabilities. A new app built in Power Apps with intelligent capabilities in it... benefits from that entire stack.

And so that's why you start to see even highly regulated financial services firms, government agencies, et cetera, really trusting Microsoft here as opposed to a 20-person startup that was founded yesterday to really take the bet on standardizing for this segment of software. Then you get into the operational oversight. Okay, I have agents doing work.

How do I have humans managing the work of those agents? That's not a developer role anymore. That's really an operational role.

What does it mean to be an agent manager or an agent boss in a claims department at an insurance company or in a supply chain operation? That's where we need these new interfaces, and that's what Power Apps is building in with concepts like the agent feed. How do I build a purpose-built oversight experience for really high volume activity of agents?

This is one of those things that there's so much doubt across the industry about being able to do this in a sort of when you give up the human in the loop or even just have one maybe guiding, but you're moving so fast. It's like, are they safe? Are they auditable?

Because when you're in a business, everything needs- A hundred percent ... to be traceable and trackable. Yep.

Is it predictable, the outcome? Right. Like, hey, you're going to have an agent interfacing with your customers, or you're going to have an agent- Right ...

doing a bunch of accounting work, which, by the way, it's like a spiral. One mistake- Sure ... and then it's just, you know how that goes.

Yep. How are you guys overcoming that doubt, through the guardrails you're putting up, through the oversight, the accountability that you're kind of baking into your platform? Because I think if you get over that hurdle, Ryan, we move a lot faster.

I think what's interesting here is actually a lot of our customers have had to build these systems already. A lot of our customers already operate critical processes across massive employee bases and even larger vendor teams that operate at arm's length already today, right? And we've already had to go build in a world of a whole lot of variability of who's doing a task, how do you create an audit trail?

How do you create rules? How do you create data policies? How do you create oversight?

A lot of those concepts exist today because there is variability in the human system, right? And so a lot of the way we approach this, okay, how do you adapt those existing concepts, policies, features, capabilities? How do you adapt that to a world where it's humans and agents doing the work?

And what are the sort of incremental 10% shifts that you need to make in those systems to accommodate agents, but not completely pave them and rebuild them from scratch, right? Because a lot of these sort of trust concepts, or zero trust concepts in a security concept, are already built into the system. And so there's a ton of work we're doing there in the managed platform, in a lot of the ways that a lot of the Microsoft security governance and oversight concepts apply to agents.

And that's, again, one of the benefits of building on a mature platform and a mature system in Microsoft is we're not having to recreate all that stuff from scratch like a point solution startup would have to do. Yeah. So the last thing just specifically on security.

Yeah. Security is a super hot topic. Yep.

What do the customers, how do you want them to think about the approach? Because in the end, you can get it all governed and right, but you have to keep your doors closed, locked, and- Right ... that's an increasingly large problem.

AI is as much- Yeah ... enabling it- Yeah ... as it is fixing it.

Right. Well, look, we could probably spend an entire hour on security and threat model approaches in the AI era. It is absolutely critical.

And like any security challenge, there is no silver bullet. Every customer needs to have a defense in depth strategy and needs to think about: What am I doing from a data security perspective? What am I doing from an exfiltration perspective?

What am I doing from an access perspective? The good news is we have a lot of that built into the platform today. Even a customer building their first Copilot Studio agent and using the managed Power Platform to roll it out will see a security score in the Power Platform admin center, will see AI-driven recommendations about what to do to improve that security score.

It has a whole bunch of capabilities in there that go all the way to operate this in the cloud, but with a private VNet, with your own managed encryption keys. Again, we have a lot of highly regulated, very security-conscious customers that are working with the platform today. I would say, though, to zoom way out and look at that, and maybe connect it to some of the rest of the conversation we've had, it is absolutely risky to go too fast.

It is also very risky to go too slow. And the rest of the world is evolving, including threat actors and competitors, right? And so the cost of standing still is probably the most costly position to be in.

So let me, as an analyst- Yeah ... I have to ask you, because I've got a few things. But what kind of in this whole evolution, this exciting moment for the future of apps and automation, and agents, what's keeping you up at night?

The biggest concerns that you see out there, and then what are the upsides for you? Yeah. What do you most think could be the biggest surprise into the future?

Give us that big- Yeah ... visionary moment here, Ryan, to take us home. Look, I think I'll do that in reverse order.

I think there is a ton to be excited about right now. NET code in their life. What unites that community is this sense of we can make something better.

This can be better. Let's do it better. And I feel like we're at the precipice of just blowing a huge lid off of the ceiling of what you can do there.

And there's a whole lot to be excited about. You joke about a night job. I stayed up last night vibing a Power App that's just a Tetris game because it was awesome and fun and so much faster to create it than it would have been in the last generation of the technology.

And I think that's a tiny microcosm of go take that creative energy and apply it to everything that's inefficient about every aspect of every customer organization today. We're really standing on the precipice of completely rewiring how companies work, and doing it with people who have deep expertise in that process and a deep desire to make it better. And that's just incredibly exciting to me in this moment.

And then to flip it around, okay, so what stands in the way of that? It really is all about speed and pace of iteration. And really it's about time to wrong.

There's so much that we need to go invent and co-invent with customers and experiment with and try, and nobody out there is perfect right now. What will define winners and losers for technology companies, for customers, for operations is how fast can you be wrong, and then how fast can you get less wrong and more right? So that's the journey we're on.

That's the hill we're climbing. But it's just a super exciting time to go think about what the top of the mountain can be. Ryan, this was a lot of fun.

It was a great conversation. Appreciate you sharing a little bit about where all of this is heading. There's so much potential for companies to really start reimagining and- Yeah ...

realize just how big of a leap forward we are having right now with AI, with agentic, and the work that you're doing in Power Platform. So Ryan, thank you so much. Hundred percent.

Really, really enjoyed the conversation, Daniel. Thank you for the time. Everything about the way we work is changing very quickly, thanks to the advancements in applications and, of course, agents, automation, and what interfaces may look like in the future are all going to continue to change.

And they're going to enable, and they're going to power businesses to be more efficient and, of course, to be more productive. It was a great conversation over the last hour. We really did reflect across not just Power Platform and how they are thinking, how Microsoft is thinking about building its future, but really about how businesses should be thinking about developing their future, removing constraints, being able to look at problems in new ways, and then being able to apply software, and then being able to utilize resources in new ways that can deliver more value to your business and, of course, to the customers that you serve.

And this is not going to be easy. It's going to take some time. There's going to be some effort, but it is something that can be done today, and companies can start to extract value right now.

And moving quickly is going to be more and more important. That's something I'm seeing as an analyst, and that was clearly something that Ryan had seen as well. We talk a lot about that is the customers that are moving fast are going to be the customers that get the biggest results and, of course, are able to benefit the most from those efforts.

And lastly, we still have to keep all of those considerations that have existed with enterprise applications, with software that runs our businesses, and that's going to be the governance, that's going to be the controls, that's going to be security. And that, of course, is going to be putting people in the right roles and enabling them to do the work. All those things remain similar but, of course, with a new bend.

We're going to upskill the talent. We're going to think about problems in new ways. We're going to move more efficiently, and together, we're going to drive the future.

Great conversation. Appreciate everybody spending the hour with me. See you all soon.

Awareness of agentic AI has reached the general public, with millions of people, even outside the technology industry, deploying OpenClaw and other agentic systems. This episode of 'Utilizing AI' features Dave Graham and Frederick Van Haren discussing the real status of agentic AI. Welcome to 'Utilizing AI,' the podcast focused on practical applications of artificial intelligence from the Futurum Group.

Every Wednesday, we explore news and use cases of the ways in which AI is transforming enterprise IT and the industries it serves. I'm your host, Stephen Foskett, President of the Tech Field Day business unit here at the Futurum Group. Before we dive into the conversation today, let's meet who's on the panel.

My name is Dave Graham. I'm the Director of Marketing at ML Commons Association. So we're a member-led industry technology standards organization that's designed around benchmarking and characterization, both in the AI risk and reliability space, as well as the infrastructure, AI infrastructure space.

Yeah. Thanks for having me. I'm Frederick Van Haren.

I'm the founder and CTO of Highfence, and we provide HPC and AI consulting and services. And of course, I am Stephen Foskett, your regular host and a good friend of good old Frederick and Dave here. We've known each other for many years.

We've been talking about this stuff for many years. As I said in the opening, today we're going to talk a little bit more about sort of where the industry is at, where people are at with rolling your own agents. And I want to kick this off, well...

with an anecdote. So I'm driving home last night or the other day, and listening to NPR's "Marketplace," and there's a guy on there, the guest on there is talking about agentic AI. And his pitch was essentially, this isn't quite ready for prime time.

We don't know exactly where it's going to go. But you, dear listener, not techie, just NPR listener, should be deploying agentic AI now, so you don't get left behind. And he gave a metaphor for that about how basically if you're not experimenting with AI agents in your life and in your business, then you're going to be basically behind on the football field.

And it got me thinking because people like us are actively experimenting with this stuff. We also have a lot of technical skills, a lot of deep knowledge. " And frankly, OpenClaw has reached, especially in China, but increasingly here in the US as well, has reached public consciousness to an extent that people are out there, like regular people, normal people, are out there deploying agentic AI for themselves.

And this is an interesting situation that we find ourselves in because, frankly, I have been aggressively experimenting with this stuff as well, and I'm not all that satisfied with the performance and the user experience of it. Let me throw this to you first, Frederick. What's your reaction to somebody telling normal NPR listeners on their drive home that they should deploy OpenClaw?

Well, I think the first problem is people don't necessarily have an understanding of an AI, but let that alone for a little bit. People want personal assistance, right? You have thousands of emails.

You want to go through your email and figure out what did you miss in the last week. Do you need to go through all these emails? So people are looking for personal assistance and an entry to an easy AI solution.

And I think today what we're seeing with OpenClaw and others, it's really the beginning. It's really easy to install it. They promote no code.

The no code also comes with no understanding of what it's actually doing under the covers, which a whole different conversation. But I think what people are trying to do is to get a taste of AI, and they're trying to do that with some kind of an assistant that looks at their own data. To me, it's the beginning.

Should we tell people to try it? I would say let's try to understand it first, what it can do for you, and also what it shouldn't be doing for you. If you give OpenClaw too much information, it actually will use that information, not necessarily for you, but in some cases against you.

So it's the beginning. Should people experiment? I guess so, to better understand what it is.

But should they bet the farm on it? I don't know. Yeah.

I teeter on the edge of Luddism when it comes to some of this stuff. Which is ironic, isn't it? Because, here we are.

But I feel the same way, Dave. Yeah. So, it's a principle thing.

Did I go out and buy a Mac Mini? Yes, I absolutely have a Mac Mini. It's sitting there right behind my head running, I think I'm running some auto research benchmarks right now.

Because it's the fascination that Frederick and I, and yourself have, Steven, in these things is what keeps us going. But we're like, I wouldn't say we're the 1%, but we're the 1%, right? Well, the techie 1%.

We're the techie 1%, right? It's a running joke that you go on Reddit, and you see everybody complaining about X and Y silicon vendor not doing overclocking chips the right way. Well, dude, you're a rounding error in the relative environment of everybody else, right?

But they're the ones that tend to yell the loudest, if you will. So I think we're in that type of situation at this point, right, where the pantomimes at conferences about OpenClaw, or NemoClaw, or whatever claw, and IronClaw. I mean, everything, it's going to be an evolution.

You're right, Frederick, I acknowledge that everybody wants this concept of a virtual agent or a helper or assistant. I think this is-- I use one, Little Bird is mine. I'm on a Mac, and Little Bird's my go-to agent.

It rolls me up a journal every day of the activities that I've done and watches what I do and kind of interacts, and it's great because it keeps a level of logic into my day. It just starts to look at patterns. But again, this is a patterning engine underneath it all anyway.

It's looking for patterns. This is something that's been designed to do statistically and kind of algorithmically. The next step beyond that is this, Steven, to your thing about NPR.

Should everybody experiment? Yes, sort of. You're always going to run into it.

I can use Claude on Chipotle's chatbot, on their website. If I really want to do this. We're interacting with agents that we don't actually understand what we're doing every day.

So I think there is this, again, that razor's edge of should everybody experience it? Maybe. Are we experiencing it whether we know it or not?

Yeah, absolutely. And we need to kind of figure outWhat that looks like. There needs to be an education cycle around it, all that to be said.

Yeah, and that's an interesting point. So first, a couple things to unpack there. First off, I had another interesting conversation this week about AI tools, and somebody asked me how we're using AI tools internally at The Futurum Group, and I said: "It's funny because, on the one hand, I think if I ask most people, they would say they're not really using AI as much as they would like to.

" And so it's like, but they're not thinking of them as AI tools. They're thinking of them as tools. "Oh, I need a transcript of this video.

" "Oh, I need a summary. I need some keywords. " Boom, throw this to ChatGPT.

Use Apple's built-in summary tool. Use Parakeet to trans... And suddenly you realize that these tools are really pervasive in our daily lives.

And so from that perspective, I think the use of AI tools really is already everywhere. But there's a different thing when we talk about using an assistant. Now, I will say, too, Dave, I also have been experimenting with Little Bird, because a friend of mine suggested that it was a really helpful advanced platform.

I've not gotten to the point yet where I can render judgment on it, but I'm excited by the idea that we will have professional, usable tools out there, because I will tell you, I didn't buy a Mac Mini because you don't have to buy a Mac Mini because it'll run on fricking anything. I'm using, actually, a stack of old MacBook Pro as my lab for OpenClaw, and I have a half a dozen of them running various incantations and incarnations of this thing because I wanted to see what it's like. I wanted to see what the default is like.

I wanted to see a better way to deploy it. I actually, over this weekend, deployed it in Docker Compose in a very locked-down situation. Previously, I had just deployed it with a bunch of junk data and a fake account because I am terrified of what it can do in your name if you deploy it.

And frankly, I've been very disappointed with the default suggestions because, on the one hand, everybody says, "This thing is dangerous. " But yet the default, normal, whatever internet, go ahead and try this thing out instructions, give it access to everything in the world. It's the generic install is exactly the wrong way.

" It's going to give you, I'm sorry to say, it's going to give you a terrible, insecure recommendation, and people are doing that. Yeah. So, have you all tried it in various configurations?

What are you doing? So, I'll go, Frederik. Yeah.

Yeah. I'll bounce it over to you in just a second. So my initial, I was early in the OpenClaw.

" And I think this was before OpenClaw, so whatever it was the nomenclature and the repository before that. Before they put the pretty ribbon- Yeah ... on it to try to make it useful, quote unquote.

It struck me that a lot of what it was trying to do were things that were low effort human things. Right? It's go out there and do X, Y, and Z, right?

Just real basic kind of principles. env file when you upload and things like that. JSON has all- Yeah ...

your tokens and keys in it, and people upload that all the time. Well, and I've kind of come to this realization that OpenClaw is the next evolution of the Amazon billing problem that Corey used to talk about, where you all of a sudden wake up one day, and everything, your bill is insurmountable. " So I approach it with a certain amount of caution, just simply because listen, my life is pretty well boxed in, and I want to keep it that way along the line.

So my initial input was, yeah, this is good. It's a science experiment. It probably has some really reasonable outputs and pretty useful for some things.

But those are things that right now I want to do. I want to continue to engage in these type of things, and I'm really looking for offloading. Again, the concept of take meeting notes for me.

I don't need OpenClaw in order to do that, and Gemini does it. No, all you need to do is be on any meeting in the world now, and you're going to get 12 different meeting notes. My CRM has a marketing bot.

Little Bird, I can record it. I can record it. Whatever.

So, that was my inception. Frederik, what about yourself? Yeah.

I think when we look at AI being a tool, the interesting piece about AI-driven tools compared to, let's say, traditional toolsIs that the AI tools typically that are being promoted or pushed for are not really ready for prime time. It all started way back with the large language models. It's almost like it escaped out of a lab, and then the drive for large language models was really from a competitive perspective.

It's the other large language model vendors that started pushing for it. And I feel like that's what's happening today, too, is that a lot of these AI tools are experiments, and we're kind of the guinea pigs to see what works and what doesn't work. And so that's the consumer side.

And then when you look at the vendor side, the large language vendors, I'm trying to remember what Jensen, the CEO of NVIDIA, said on stage at GTC a few weeks ago. Didn't he say something like, if the engineer is not spending 200K on tokens, then he's not doing it right? Yeah.

And so it's almost like the push for let's do it and generate as much or as many tokens as possible. The reality is that us, the guinea pigs using all those tools, it gives a lot of data to the vendors to work on the next level of AI tools. And so I don't think it's wrong for us to try these tools, but we have to- Yeah ...

realize that when OpenClaw came out, it was leaking data left and right. And it was not considered a concern. It was considered as, well, it's an experiment, it's an AI tool, use it at your own risk.

But they make it so easy to use today that I don't think people understand what those tools potentially could do. Yeah. And I think that's kind of the risk.

So if we really look at AI tools, and we transparently want to use them, we need a better way to make those tools ready for prime time without having to suffer the consequences afterwards. Yeah, 100% agree. And that's actually my feeling.

Again, I have now installed and configured and played with versions of OpenClaw for a few months. I have done half a dozen different start from scratch implementations with different scenarios in different ways, and my verdict on it, at least as far as it stands today, is this is in no way ready for prime time, and people shouldn't be using this. But the amazing thing that it does, and this is the wow factor of OpenClaw, is that by allowing it to have persistent memory and a schedule and iterating over itself, it is as transformative as the sort of introspective GPT models were that came out at the end of last year, in that it takes things to an entirely new level simply because it's able to autonomously act and do things.

Essentially, what it's doing is it's showing us where this technology is going to go next. And that to me is the exciting thing. So when we see NVIDIA on stage saying that they're going to create their own Claw-like agentic, and we see OpenAI acquiring the OpenClaw team, we see Apple and Google and everybody else saying, you know what?

Everybody is looking at that and saying, "That's the guidepost. That's where we want to go. " And I think that's healthy.

I think that's where the industry should be. It should be looking at ways of building systems that deliver that wow, like OpenClaw, but aren't just incredibly bizarre, hacky science projects that barely work. And Dave, I know that you guys are working with a lot of these companies.

There's a lot of this stuff coming, right? Yeah. To even backtrack a little bit to what you just said, we look at the iPhone, for example, as the inception point for basically this turn of the wheel, this digitalization, this an actual social phenomena that turned into a technical revolution, right?

Yeah. It was the first time that you had really had the ability to capture the world around you in more realistic ways. Embedded camera.

You're interacting with a human interface to a machine. And so actually in academia, we look at 2007 in the introduction, 2005, I forget, 2007, in the introduction of the iPhone as one of that, a social revolution. When I view OpenClaw and tools like it as that kind of second step on that revolution.

Because it's starting to embed into our social fabric the idea of agents or non-human digital actors that have or don't have, and not to make this into an entirely academic conversation, agency or the ability to go out there and fulfill a role of its own devising or fulfill a role that another or deus ex machina, to a certain extent, that somebody else is projecting upon it in order to go and do. So a lot of that's kind of a prelude to why MLCommons and reason why we're interested in characterization and kind of the embeddedness that we look at here is that we're interested in the entire groundswell, what you build from the foundation on up, as well as top-down. So infrastructure and silicon and all the technological marvels that make yes make it work, that you run on top of is one part of it.

But the other part of it is that stickiness at the top. So Frederick, you talked about it, and Steven, you talked about it as well. These devices and the influence that those digital personas or those agents have on the world outside of them, right?

There's a risk involved, right? You give it the wrong... env file, right?

env, it's right there in the JSON. Yeah. So, I don't know how you run your thing, but this is something I had to learn as well, right?

When you go back and do a CodeRabbit audit of a GitHub repository. Anyway. So, put all these things out in the open, right, there's a certain risk and reliability aspect of it.

You can call it safety if you want to, but risk and reliability kind of focuses in on this, where you start to see where this shapes markets, it shapes cultures, it shapes society, and that comes with its implicit dangers. We look at the mental health crisis that we already had. That's in our teen, in the pre-formative brains of our youth, worldwide, right?

And you now exacerbate that by access to tools that build digital cliques and build these digital communities that are highly focused in on presentation, what you look like, and all these kind of invariable, immutable attributes of yourself and all this stuff. Anyway. All of this stuff kind of starts to become this really crazy foment of everything.

So, again, it's delving into sociological and anthropological phenomena here a little bit, but that's the reason why MLCommons becomes so interested in these things. We're working on both ends of the stack to try to understand. It's a characterization.

It's a benchmarking as well. But it's all a means to an end to understand better, ultimately, how these tools will impact both infrastructure, the ecology, the power, the fundamentals of things from the silicon side, as well as the social side and cultural side from the risk and reliability perspectives. Yeah, and I think it's important to kind of realize where the focus is nowadays.

It's at some point almost like all of the focus was on training. How do we get the greatest and the best large language model? So everybody expected the large language model to do all of the heavy lifting.

Today, the shift is completely different. Certainly, there's a bunch of vendors generating large language models, but they're roughly good enough in order to get going. And so I feel, certainly from our perspective and certainly MLCommons too, where originally there was only a focus on training, now it's all on the inference and more consumer, let's call them tools if you wish.

But that's where the focus is, is to make it a lot better and improve and innovate. And I think that's what we should expect moving forward. Me, personally, I still think that large language models would benefit from more specific markets, more market-driven as opposed to being generalist.

But in the end, for now, it's not bad to focus on tools that can deal with those large language models and continue to innovate. Yeah. That's a real good point, Frederic, and that's been my experience as well.

I'll just say that I have been actively hopping back and forth between OpenAI, Anthropic, Gemini, as well as the open weight models, Qwen and Kimi. And what I've found is that frankly, these models are really good. They've gotten very, very good today.

Yes, some of them are better than others, but at least as far as agentic applications go, at least as far as my experiments have gone, the defining factor, honestly, is the cost per token, not like this model is far and away better. I agree with you, Frederic, though. I think that there's probably headroom for somebody to develop better tool calling models, lighter tool calling models, especially as we deploy more and more systems that have agents and sub-agents and so on.

I'm using, for example, I've got a Gemini Flash instance and a sub-agent that's basically only doing security scans and tool calling, and so that I can use a very lightweight, quick little model for that little guy, whereas you might want to use a heavy duty GPT for your real agent, that kind of thing. But a lot of that stuff is still fiddly dial turning, and that's why I'm more excited and more interested in where this goes. There are companies that are going to be developing these things and rolling them out.

And people are going to be experiencing these things increasingly. I don't think that that's going to be a situation where people are deciding, oh, do I want to use Anthropic or OpenAI? I think it's going to be a situation of, I signed up for such and such application, and it just freaking works, and it just does the thing.

And then it's more of a question for that service provider to decide how and when and which models to develop and so on. And then that kind of leads us to the next point, and I want to jump into where Dave was going here with what does that do to us? What does that do to society if we've got sort of a silicon persona that exists in our lives that is assisting us?

I love the idea, especially if it works. What does that do to everything? And Dave, I know you've got some thoughts here.

I have lots of thoughts. As I expect, you have lots of thoughts about things. Well, I always like to joke, or actually, even to my executive director, we both come from the humanities side, not the computer science side, right?

And I have two degrees in psychology and counseling, and worked as a time as a social worker here in the state of Massachusetts, right? So very human-based, right? So the impact oftool of things on bureaucracy, even on society.

And a lot of these things was part and parcel of what kind of I grew up in terms of my knowledge with. So I'm very, I think probably pragmatically more interested in looking at the effects of these tools on society, right? How does this increase a person's agency, their ability to function in a society, right?

So if we look at, I have huge issues with the way this was expressed, but if we look at this concept of universal basic compute, which a certain individual from a company that I will not name talked about, versus a universal basic income, right? I live off money. Universal basic income is a good thing.

It provides a common platform. If I look at universal basic compute, and we look at kind of the analogous relationship between those two, if I'm providing this level of computational credits or tokens or whatever you want to call it these days, I feel like I'm going to Chuck E. Cheese.

" Like, "Throw it in the ball pit and see what happens," right? Is there a positive benefit that comes out of this for somebody that doesn't know how to use these systems? Going back to the original thesis of NPR, talking about how everybody should experience it.

If I look at my mother, who, congratulations, has made 80 years old this month, right? This is a huge milestone. But she's not interested in an agent telling her what to do.

She's interested in being able to function and engage with her doctors and the services that are required of the elderly mindset. So a lot of these things, and as I get older, I care less and less about the fancy stuff and more about just being able to live life, right? So I think this is where there's a possibility here where some of those offsets become taken over by digital actors.

I think there is, let's solve the bureaucracy problem. How do I get to my benefits if I'm on Medicare or some sort of social benefit? How do I solve going to the DMV or the RMV problem, which everybody universally hates, right?

So a lot of these things. How do I understand bills? And having these type of things become a positive, I believe, net benefit to society over time, and this is where that capability of models that are increasingly trained on public data sets that start to understand common systems and processes and problems that we all encounter in our daily lives, whether we want to believe it or not.

Solving a tax problem or interacting with these things. I think this is where there's a lot of net positive effects. There's always going to be room for the 1% or 20% or however you want to call it, in the digital space where we can kind of push the envelope and figure out, hey, now you can do stock trading with your OpenClaw instance, and you can give it your portfolio and let it run wild.

That's an exception to the general rule, and I think this is where we're seeing these kind of step functions go into place, right, where it becomes useful. That's the part I'm excited about. I'm less excited about a compression from the top down where you must use in order to function.

I think that's the wrong way that this thing, it should be a socially augmentative type approach versus a compressive or oppressive approach of you have to use, you must use in order to participate in society. So... Yeah, I think it's interesting.

I think those tools can help us do some tasks. There is a risk, is that you built a digital twin that pretty much takes over, right? There's a lot of services today that are relying on interaction with assistants, and so the last thing I want is to have a large language model that makes decisions for me because it believes it has all the data for me.

So I still want to consider AI as a tool. I still want to be in control. I want it to improve my life, but I'm not a fan of creating a digital twin that can speak for me, so to speak, right?

So I think in general, it's an exciting time to live. I had another conversation with a colleague this morning. The market is growing so fast that it's very difficult to try it all out.

There's a clear shift from training to consumer/inference. It also means that the audience got a lot wider. It's not difficult to install these tools.

But I still feel like we're experimenting, and to consider those tools as ready for prime time, I think we're not there yet. But that doesn't mean that people shouldn't try it out, experiment, learn from it, and also understand that AI is just more than buying a Copilot license. Yeah.

And for that matter, I will echo my friend from NPR and say anyone listening to this show really should be trying this stuff out. You know what I mean? I would say that anyone who is motivated to listen to an enterprise AI show, like "Utilizing AI," if you haven't gone out and tried installing OpenClaw, you should.

I will say that you shouldn't do it on your primary Mac with all of your data and applications on it. I strongly recommend doing it in a sandbox and doing it slowly. The installation will ask you to connect to everything.

Don't. In fact, start by connecting to nothing, and then add connections later as you feel more comfortable. Worry about security.

Make it read-only. That's a very good idea. Don't let it send emails or post social media or do stock trades on your behalf.

That's just a terrible idea. But basically, it's gotten to the point where you need to try it. That being said, I don't think that this is going to be the end-all, be-all.

I think that, again, OpenClaw is really a surprising transformative use of this technology, and I think that what we're going to find is that there are going to be companies, and I'm going to just say right now, I look forward to what Google does. I look forward to what some of these companies that have a lot of experience building these things do in order to build agentic experiences and agentic companions for people that actually deliver the goods. Like Frederick said too, I'm going to throw this one out there too, I think that there's a looming conflict and question about whether we will have a digital twin that acts as us or a fake person that supports us and interacts with the public, or an invisible agent that gives us superpowers.

And we'll see where we go with that. I've actually been experimenting with all three scenarios to see what would happen. The first one, obviously in read-only mode, because I don't want to go out there and share some crazy stuff.

But it's been interesting to see sort of to what extent it's able to duplicate me or duplicate a person or just assist me. So we'll see where that goes. We do have to wrap.

We're getting toward the end here. One thing I'm going to do is I'm going to give you each a chance to tell us a little bit about how we can continue this conversation, because as you can tell, I think that we all have a lot to say. We are all going to be at AI Field Day coming up next month.

I can't wait to see you in person and have these conversations in person. And those of you listening, of course, we would love for you to join us for those videos. Check out Tech Field Day website for more information on that.

You can watch them on YouTube and LinkedIn and Techstrong. But of course, if you're listening as well and you're saying, "I'm just as good as Dave and Frederick. I should be part of this thing," we can also have you join us.

So reach out. I'd love to have you join us in the future. So before we go, Dave, where can people continue this conversation?

" I think number eight? Yeah, eight, next month in- That's right ... Santa Clara.

Otherwise, I am on LinkedIn like a gnat, mostly because I'm doing a whole bunch of benchmarking characterization. You can find me on GitHub, Elemental Collision. I have an auto research repository that I'm working through right now with a good acquaintance that I've made through this benchmarking and characterization process.

And I have a little sneak peek of a project coming up that I'm hinting at on LinkedIn as well that kind of talks to a lot of what we've talked about today. What happens when you let an agent just become. And so that's out there too, and more revealed in time.

Not quite ready yet, but yeah. Frederick? Yeah.

So I will also be at Tech Field Day AI. I don't think I missed one, so I think I went to all of them. So hopefully I didn't jinx it.

But I'm looking forward to see everybody face-to-face, no AI assistance interfering. And you can find me on LinkedIn as Frederic V. com.

And as for me, of course, I will also be at AI Field Day 8, which again, is May 13th through 14th and 15th. And Frederick, I believe that you have been to all of them. Also this week, as you listen to this, I am at Qlik Connect in Orlando.

Qlik is a great data company, and we're going to be talking a lot about the relationship between data and AI and how that all works out. And so I look forward to the experiences there. Of course, it's going to be at a great event.

Frederick, you're at Qlik Connect as well, so folks can learn more there. " It seems like that's my experience every week. " So thank you all for listening, especially Dave, Frederick, thank you so much for joining us.

It's been great to have this conversation. I do look forward to having more of these conversations in the future. If you're listening to this and you enjoyed this, please do subscribe.

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