Techstrong TV November 19, 2025

Hey everyone. We're in Brooklyn. You're watching Techstar Bank.

Hi everyone. Welcome to this edition of Textron Gang. As I mentioned, Mike and I are in Brooklyn, New York today for a kinda unique, uh, events.

The first of this kind I've gone to, it's called AI Native Defcon, and it's in a place called Industrial City in Brooklyn. And I gotta tell you, I love the vibe already, though it's early in the morning. Um, I think, I think there's a future for this.

I think this thing's got less. We'll give you more of a report, probably not today, show, maybe tomorrow or on air. But in the meantime, Textron gang stops for no one.

And we'll keep going today. Uh, let me introduce you to our gang. We have the men up north.

Chris Blas, a new gang member, and we'll ask him to introduce himself here in just a second. Sid next Sidd, welcome to the Gang Sidd. If you wouldn't mind, take, take 15, 30 seconds, give people a sense of, of who you are.

Sure. Thank you. Uh, appreciate the invite and glad to be here.

Uh, so I'm currently the president and CEO of, uh, of Techon. Teon is a, is an advisory and analyst firm advising clients in the area of cloud and AI infrastructure and AI software and trends. Uh, prior to me starting off my own, on my own, I was a vice president of research at, at Gardner, where I tracked the same, uh, coverage space.

And, uh, prior to that, I've spent my career as a practitioner at an executive positions at Cisco Dell, EET, bell Labs, and did my own startup company for for six and a half years, which I took to an exit. So my, my experience spans sort of practitioner research as well as being an analyst in this industry in those companies. Thank you and welcome to the game.

And then last, Lisa, I, uh, and I always try to get her name right 'cause I keep trying Chaya Chaya. Yes, Andy, I've been on the show for five times now. I know.

And I messed up your name six times, but I keep char till I get it right. Anyway, thank you. Good to be.

So, Mike, we're gonna lead off today. You know, this is a big week. Nvidia has earnings on Wednesday.

So the market, and, you know, the market is in a bit of a, of a, a, of a share, not a shambles, but it's retracting. And people are saying, and didia might be a big reason why, but they're, they're keeping, they're trying to keep pushy envelopes. They're pushing the boundaries of visits.

Yeah. There's a super computing conference in, uh, St. Louis this week and NVIDIA's there talking about these new models that they're creating that are all wrapped around physics and letting people do some very, uh, intense research at the atomic level, right?

And they're talking about simulations or fusion reactors and helping people build new materials. And as I kind of look at it, I mean, and I got one other thing. They also are creating interconnects between supercomputers based on GPUs and what are gonna be quantum computers.

And they're saying that these supercomputers that they have will essentially be the control plane for the quantum computing. And we'll see how that plays out. But it feels like, you know, rather than just kind of focusing in on the GPUs, I can't help but wonder if I look at this and say, Chi, let's start with you.

Are, are we on the cusp of some sort of new golden age and science and research? 'cause it seems like all these projects that people are talking about are gonna lead to all kinds of innovations. I think I'm aligned in terms of their next step.

They do have the domain knowledge of the hardware. They do have the people who have worked on it. So it looks like they're taking the next step in the direction, coming up with their own model.

And I think one of the ideology that will help here is machine learning for machines. So think about it that the GPUs, that when built by them, if something goes wrong, the model understands where they can perform better and what are the bottlenecks and give more insight about it. So I think the data that they have collected over the years and building the infrastructure for it, they're going to use the same data set to train these models to come up with the right logistics, performance metrics and benchmark that they claim about it, which people have not even scaled yet because everybody's buying it, but nobody has scaled the GPUs to up to that extent where they say, yes, it actually meets this many number of tokens that I wanted it.

So yes, I am very optimistic about it, um, in terms of model, but I, I also feel there are too many cooks in the kitchen now. So that's kind of where I lead others to kind of share my feedback on, I haven't tried the model myself, but that's what going to be in the next thing. But if it's coming from Nvidia, it seems to be that they have the, I would've thought about it and trained on the, in initial, uh, kind of trains for it.

Yeah. Sy, do you want in here? What's your thoughts?

Yeah, so tectonics have been following, uh, in NVIDIA's progress over time, obviously. But, uh, uh, as far as Supercomputing is concerned, clearly, you know, the focus on quantum was something that, uh, was striking to me. Uh, but if I were to sort of summarize the takeaways, uh, you know, it's very clear that, you know, infrastructure is obviously advancing really fast, right?

The scale and ambition of systems being deployed with varied technologies, be it, you know, your traditional networking technologies with, with their spectrum announcement they made last at in at in their own Nvidia, uh, event in DC a few weeks ago. And now with, uh, with Quantum, you know, things are really coming together and integration of quantum is real, right? That's the other takeaway I would highlight where you think, like NVQ link shows quantum is entering infrastructure planning.

So it's no longer a sort of research project in the labs of IBM and other places, right? Um, so it's becoming more and more real. And then, uh, I heard one terminology that jumped at me that nvi, a talked Nvidia talked about, which is AI for science, right?

So things like life sciences, climate materials, manufacturing, uh, you know, focus on those kinds of things. So the high level narrative that jumped at me, I think we ought to track that as to what they're gonna be doing there. And then, you know, in, in terms of risks and governance, they talked about, you know, the whole quantum integration, quantum safe, the whole supply chain issues associated with quantum, the energy and thermal footprint, you know, the whole sustainability narrative is highly irrelevant as well.

So those things jumped out at me. So I think going forward, we wanna make sure you keep an eye on how NVQ link develop or deploys and develops over time, right? Tracks or the commercial aspects of these technologies, because oftentimes we hear companies like Nvidia and others talk about what's today on the truck, what they're gonna be doing in the future.

But it's important to understand, you know, in the, what the future's going to hold for them to be making revenue out their futures, right? And then evaluate the software stack maturity. They've already been in the market with Kuda, but with quantum SDKs, you know, what does it mean for the developer community and how do they build this thing through their whole ecosystem partner play?

So those are the things I would highlight. You know, I I, protein folding sticks with me as I look at this era of ai, and it was a couple years ago, right? You know, we basically solved the protein folding thing completely.

And if you're just a general science nerd like me, this is one of those things where the possibility space is so enormous that in the past we've forecast, you know, taking the computers we have now and forecasting 'em forward, it's still 10 trillion years until we could possibly do it that way. And we're done. You know, protein folding is done.

Amazing, right? And as I've learned in the last year, more about specifically how these systems work, you know, LLMs and the, and everything we're talking about right now, you would think that if you didn't know much about it, if you think about the old way, the digital way, we think that maybe it's vector math with GPUs or something is making it faster, and it's not, it's semantics, right? You know, because what those researchers basically did is they just asked the AI could do these things, right?

And what does that even mean? And we were stuck in this debate space around this, but it's not that complicated, right? You're, you're, uh, uh, you're reducing the possibility space, you know, like a human.

If you were talking to them and said, Hey, could you research this? You know, they would say from this point, the likely things are this direction. And not try to, you know, at, at every step do every digital, digital pothole and the savings in time and energy are hey, transformational.

That's why this is, you know, such a big deal. That's why, you know, to, you know, Helen and, and Sid, you know, uh, analysts like you, the business investments where people are putting the money right now, ah, I don't feel that comfortable about it, but the overall trend, yes. Because if you could speed up these things like protein folding, like physics research, not just by sheer CPU horsepower, but by semantically narrowing the space and sheer horsepower.

Holy cow. Exactly. I think, I think that's spot on.

You know, I read an article in the Wall Street Journal on Friday about this guy, Jan Lako, who's a, a chief scientist at Meta, and he was a contemp labs, and he's talking about how the new world models not large language models, because LLMs are not grounded in physics. So to your point, Chris, you know, pro about the protein folding analogy, right? Uh, world models are really going to be the next big thing because LLMs don't know basic these two sequence transaction, right?

If A, then B, because they have a pattern of text and they do NLP and, and come up with the logical answer to a prompt, but there are no physics, they don't know things that, things like balls roll downhill or liquids spill, you know, unless there's pattern actually appear in text. I think you're spot on in, in, in the Knowledge that that's very true. Chris, let me, let me get, so my, my take when I hear these things though is, you know, I, I'm gonna borrow a nursery right from the old lady who lives in the shoe.

There was a company called Nvidia who invented the GPU. They had so much money they didn't know what to do. Okay?

When you're a $5 trillion company, you can't, and you wanna keep growing that market cap, and in pleasing the street, you can't be doing incremental growth. You gotta make some holy, you know, uh, deep passes, right? Like Google did.

Remember when Google was untouchable, it, it controlled 99% of the, of the, of the search market. They were, they were printing money and they, they, they set up a bunch of Hail Marys, right? And some of them, like Google fiber, uh, you know, really civilization changing big things because you need that kind of stuff to get from 5 trillion to 10 trillion.

It's not gonna be about selling a couple more GPUs. You've gotta invent game changing new markets. And so kudos to them, not kuda, it's something else, but kudos to them for doing this.

But that's the game here. They need to find where's my next $5 trillion market gonna be? And, and so that's what this is about.

It might be protein fold in, it might be the, as Mike say, the control plane for quantum, right? And this way they ride that quantum because, you know, hey, Google's live, they have the willow as the quantum chip or any one of these players are making, you know, that are working on quantum chips and qubits and so forth. But Nvidia is not gonna abandon that market.

So they're, they're making a, a, you know, a bit of a Hail Mary there and a hail Mary here. They don't need all of these to hit. They need one or two of them.

And it's almost like the VC gig. Yeah. I think Nvidia jump in Nvidia is at an inflection point right now, because what you just said about their lineage, I mean, how do Nvidia get into the AI business?

It was an accidental discovery, right? GPUs are basically designed with the purpose of accelerating computer graphics and image process and render pixels on a computer screen. Now that, that function requires the ability to multiply very large matrices, right?

Turns out that Transformers, which is based on NLP and sequence transduction, also requires the ability to multiply large matrices. So somebody came up with that, Hey, why don't you use GPUs for processing AI workloads? And, and then, and then we know, we know what happened thereafter.

But I think as a company, Nvidia really ought to think about what is the, to your point, what is the next big thing, right? Is it protein folding? Is it something else?

You know, is it gonna be learning processing units? So lpu versus GPUs, where these things are built for inferencing in custom environments for small language models. I think that's the, that's the challenge they are currently faced with.

And it's almost like changing the engines of a 7 47 in flight, right? And many large companies go through this inflection point 'cause they're crossing the ca classic crossing chasm, right? So it remains to be seen how they sort of do both things at the same time and make money out of that, that, that transition, right?

But Sid, let me ask you this question. I do have one, like Nvidia is one of the biggest players in the chip, right? There's no competition around it.

Why? Why can't they continue to work what they're good at it and scale and reduce the cost of chips and GPUs instead of entering a market, which is already a multiplayer, Right? Correct.

You're right. So they're gonna milk that as they can Go ahead. No, you go, you go.

So they're gonna milk that as, as long as they can. Obviously I would do that because that's bringing me revenue, right? But, but they have to think about brand new architecture that's different from the GPU, right?

If they don't, then there are others who wanna come into this. There's already lot of developing going on in pockets within the hyperscalers that are building their own, you know, specialized ships that they're not even, that are, that they're not even, uh, selling to the, in the open market, right? I know that some of the hyperscalers already doing that.

I have information under NDI can talk about it here. But that's what's going to cause a problem for them if they don't evolve as a company. Go ahead, Mike.

Sorry. Yeah, yeah. No, if they, you know, they will be kings of the GPU and that might take 'em from 5 trillion to 6 trillion.

Jensen Wong didn't get here thinking small. No. So let's, let's play that out a little bit, right?

In my mind, there's no rule that says that Nvidia has to continue to only make GPUs in theory, they could go make another processor that is optimized for AI models as opposed to the one that they developed that was a happy accident. And we've already seen them starting to build CPUs and they have dpu, and it seems to me they're a lot more ambitious than just looking at GPUs and They want quantum, right? So, you know, I think that, you know, they're gonna be so far down the road on the model side that, you know, if they come out with some additional processors, 'cause they learned how to optimize those models, they might be in a better position than folks who are just pure play pro companies.

You might wanna look at Nvidia and think about it now as trying to own the entire stack. I mean, heck, they sell entire systems now, You know, they, there's gonna be bigger markets. I mean, a AI is huge and they, they've capitalized on it, but this is not the time to take your pedal off the, take your, you know, take your foot off the pet.

This is the time where you now have resources to double down and, and, and make some big passes. Some Hail Mary kind of attempts to, you know, who knows what, what can come of it, right? And they're already talking about the next two generation of GPUs beyond Blackwell.

So, you know, and if they're on a cadence for delivering those, I think they said, uh, somewhere between a year and two years. I mean, the pace of this stuff is gonna just dramatically accelerate and maybe we'll all be living in a different world by the end of the decade because tales point some of this stuff, if it ever hits, we'll change the way we let. And I think also another thing we need to think about is what are they gonna be doing in the area of sort pervasive computing, right?

Because it's one thing, building a chip and putting all the intelligence in the chip footprint of real estate. But if I need one unit of compute to process, uh, an AI workload, do I need a pervasive computing environment? Which means I have GPU clusters or whatever, D-P-U-T-P-U cluster that are distributed in the distributed computing analogy.

So should they be focusing on, uh, connectivity of these cluster, of the compute clusters, which gives that one unit of compute from wherever is the most efficient resource for that, right? So now suddenly networking is becoming sexy all over again, right? In the world of ai.

So like, what did Nvidia do in the world of networking beyond just computing, right? It is gonna be an interesting challenge for them. I dunno what, I dunno how you guys feel about that.

That's a good topic to talk about. You know, they say Nvidia made hardware sexy again, so now they'll make networking sex sexy again. I hope so, because a lot of the systems they're currently selling look and smell like mainframes to me.

But wow, We're not outta time for this segment. Let's think quick, Frank, and we're going come back and talk about, uh, our next sec more AI probably. But you're watching text on game.

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Black clerk, digital executive protection, defending the new attack surface your personal life. Hey folks, we're back. And this is a little unusual.

It may be scary and something right outta 1984, but Albania has a minister for ai, and I guess there's gonna be more and more government decisions are gonna be fed through the AI first, and maybe somebody will check on this, or maybe they'll just say, Hey, that looks good to me, and away we go. But Chris, I know you've been kind of monitoring this kind of thing and, and have talked about this in the past, but it looks like it's here. Well, more countries essentially have ministers of AI and we'll just all, you know, wake up in the morning and be told what to do.

I I wouldn't, uh, end it that way at all. But, uh, yeah. So the last segment ended up being sort of a market, an, you know, business analytic and the architecture.

Lemme talk about narrative infrastructure, right? You know, so Albana is not the first, you know, here in Canada, just this year we have our first, uh, minister of ai, ev uh, minister of Solomon, uh, Evan Solomon. But last year, mark Sean, the was the first deputy minister.

And we know in cybersecurity, we've seen this happen before. Mark Weatherford, who's now at, uh, doing policy at Nvidia, was the first under secretary for cyber in the, in the beltway, in, in the US federal infrastructure. And Albania is an interesting case because, you know, they, they punch above their weight in EU and in, uh, a number of ways in this, in this case.

But we're going down this path, you know, these are important topics that need to be addressed at this level, at the policy level. Someone has to be responsible for it. You know, Mike, if it ends up being authoritarianism, I guess then, you know, democracy has failed, but I don't think we're going there, right?

And this, you know, Sid, you touched on something in the last segment that I really wanted to, to to pivot on because, uh, the Meta's AI chief, um, Yann, Luc, you know, leaving and his statements about needing to move AI into a, not a, not just a word prediction, but a world map, right. Models exactly what, but I, and we focus on in this attest civic AI world, and it's not that far reach. And it's interesting, uh, to see folks like, uh, like, uh, like, like Lako making those statements and those moves right now, right?

And just just to map this out for folks, LLMs are a language modeling thing that's modeled after what happens in our brains. But that's not the only thing that happens there. And mammals, 200 million years ago, started building a world map that's literally the term used in cognitive science.

So they could, it's like a, like an eight big video game, like a really, really simple one. You can navigate in 3D find the food and find the food you found yesterday, right? The world map that Launa is talking about, that that folks like myself and, and, and our allies are working on these days isn't about a whole new different ai.

It's about taking this capability we have and having it operate in a relational environment so it can basically have that world map. And in that it touches on the things that, like Mike and Alan and you guys, we've talked about week to week throughout this year, you can do so much more without so much energy, time costs, so on and so forth. So that's just, you know, that, that move, you know, out of, out of meta AI this week and this happening in Albania, you know, modeling what's happening here in Canada, that maps a narrative arc that's fairly straightforward, I think, I think we'll see the business and technology architectures follow from that.

Yeah, I think, I think the, and back to the world model conversation, I mean, the way I understand it is it's an AI system that essentially builds in, you know, an internal representation of an environment and then how it's used to simulate future states, right? So more of a outcome-based predictive model rather than LLM, which is a pattern recognition based technology, right? So, so I, I see that whole world model that Koon talks about is, you know, the predicting model, predictive modeling of physical systems like infer, object permanence, motion collisions, the physics thing I talked about, you know, gravity, things of that nature.

Uh, it also has a relevance to autonomous planning. So you can run thousands of simulated rollouts, right? Uh, it has, it's more grounded in decision making rather than sort of like, you know, in the case of sequential transaction, you know, it's very, very one way, right?

So, I mean, I can say I, I know based on text collecting the LLM database, if you wanna call it that, that Tom Cruise with mothers Holly Cruise, but it can't tell me sun is done, right? Because it goes only in one direction, sequential, right? So, so world models will kind of overcome those kinds of things.

And you know, it's also gonna have things like embodied intelligence, so robotics, autonomous driving, manufacturing, drones, gen software, all sort of require this, right? So I, I look at sort of LLM use for reasoning word models used for simulation and a chance and agent for action, right? That's of the triad of future of AI architecture, in my opinion.

Well, and, and the, the, the, the value of the world map for now, m is i, is is is it self transformative? And that's why I think this era is, you know, historically we may back, look back at this, the hype cycle wasn't big enough, but it was the wrong hype cycle up to this point. But I think we're starting to get it and, and we build LLMs modeling ourselves.

Like that's literally what we're trying to do, extrapolate a little bit farther back, why are mammals, how do they do it? And we're talking little mousey creatures who got it, uh, evolutionary advantage by having that really simple world model. I think that's what we can do today, right?

It, uh, and, you know, attestation channels and the systems we build and demonstrate all this all the time and can, it's just happening this year. So it's not like we need to create another LLM industry, another multi-trillion dollar thing. We need to take these tools and work them in a relational environment that allows, you know, the result to act as if there is a world map.

Like mammals do it, you know, nothing like we do at this point ourselves, but that's the path we're on. Well, looks like, uh, not the Albania, like what, just one point on the Albania thing, looks like they came up with something called dla. Are you guys familiar with that?

It's sort of a special, I don't know if it's LLM that's developed by the National Agency of Albania in cooperation with open AI at, uh, just I aspect, sorry, go ahead. Chai. You a point.

Uh, no, I was just saying that going back to the original point of we are having a minister, which is a ai, um, power, I've been a citizen of that country, I'll be excited, I'll be excited to see the politicians are getting a revamp or a new perspective to make the decision, and it might take the country the direction they want it to. So I think as I, I'm not talking about the technical aspect of it, but I'm just saying as, as the humans who are taking this decision into consideration, is a good move, um, politically, I think it'll, uh, give the governments the insight in terms of the directions where they should invest in take, take the insight, take the inputs, but can they rely on it completely? I think it's too soon to do that.

Yeah. I think, I think also, you know, just because we have an AI that spits something out, well, when we determine that whatever that truth is, that it's inconvenient, we're still gonna ignore it. Yeah, I, yeah, I, I think a lot of these countries have essentially, like Albania have long faced systemic issues with corruption, you know, nepotism, weak public procurement practices.

So, so the more they do in, in, in, in terms of openness and creating these AI initiatives that span obviously within their, their own country, but overall across integration with the eu, let's say, or the European Commission, right? Uh, I think those things kind of give, give an optics that they're more open to sort of collaboration and interoperability the rest of the world and creating these AI initiatives is probably one way to address that. Uh, so I look at, I don't know, maybe, well, I'm a huge fan of the, of, of capitalism and democracy and freedom of speech and so forth for the reasons of evolutionary pressure, right?

Because I honestly believe that the better systems are better people and ethical and, and so forth. And again, if I'm wrong, let's find out, we'll play it out in the markets. But, you know, to Mike, to your, you know, and I, and to be clear, you know, we, we, we, uh, uh, uh, spar on this one, but that's good.

You know, I need a razor to go against 'cause I'm an optimist, but it's just, if I, I, right now I'm looking around the world, I'm seeing countries like Albania, like Canada, where I have good faith there to be reasonable effort to have an AI minister and do it properly. I expect a number of countries will do it wrong. I think it will cost them, it'll cost 'em economically, it'll cost 'em in global power.

It'll cost 'em in trade and relationships. And while I could be wrong, I think this is the kind of role like cybersecurity. I was glad to see that get into the public sector because it's a technically intrinsically kind of more honest than just I said so kind of thing.

Those of us in this, in cybersecurity know that that's not entirely true all the time. But I think this topic does drive it down further and further if your actual, here, let me try to end on this, right? We talk a lot about canon, right?

Canon in our, in our terminology means what you actually do, what you say you do, right? And AI tools are actually really, really good at this right now, right? And lots of use cases and, and we're seeing in real world.

But I think the countries, governments, as they semantically analyze their actual canon, they'll find out whether or not they're doing what they said they do and opportunities to be more or less corrupt. Pick your, pick your choice. I think you're looking at it wrong in all honesty here.

Here's the deal. I, I've said it before, I'll say it again. We're at the beginning of the beginning of the AI story.

We're still at the beginning of the beginning. We don't know where this is gonna go. Will it turned out as, as that chief scientist in the Wall Street Journal article said that LLMs are sort of a dead end and we need to go to these world models to really make this work better or to recognize our dreams.

I don't know, but it's gonna be big enough where we need a government element. You probably need a world government element to it as any one country alone. But it's not just to regulate ai, right?

North Korea will regulate ai. The old Albania will regulate ai. You know, the people who sit clutching their pearls saying, oh my, what could AI do bad?

They're dinosaurs. They're already road guilt. Forget about it.

AI is going to go as fast as people can make it go. No one's gonna stop it. No government, no nothing.

It's gonna go, what needs to happen here is governments are gonna recognize, how can we use ai? How can we harness ai? Not how we can control it, right?

So it's not just a regulatory function. And, and quite frankly, and I am no fan of Donald Trump, anyone who knows me or has heard this show knows I'm not. But what he did early on in that administration is he appointed a so-called czar for ai.

I haven't heard much from him since, but I assume he is working behind the scenes on all these deals that they work. We need a government policy that probably says, Hey, AI is gonna be world changing, civilization changing, perhaps we need to be in on the action. We need to understand what's going on.

We need to try to influence it the best we can, given our resources. The resources of the US are very different than the resources of Albania. And they're very different than the resources of Canada.

But government resources will be brought to back here. And, and rightfully so. It has to, if it, if it's as big as we think it's going to be, it naive to think the government's not gonna be involved with.

I think it's not that somebody gonna try to control it 'cause they will, because for humans, Well, it will it be the government or some strong man or who that, you know, who knows? I mean, I like to, I, I like to see the government. I like to see the government, uh, Be providing some guidance on responsible ai, right?

I think that's key, right? Because we can't have all these private companies go burst. So again, I'm, I'm a, I'm a capitalist, don't get me wrong.

We, but we can't have chaos, right? And there's too many competing positions, ones being taken by Elon Musk and Xai and Grok and that stuff. The ones being taken to open ai.

And you've got a whole host of other positions, right? Meta and so on and so forth. Like, so we have to be somewhat cognizant of how that is managed, for lack of a better term, uh, from a responsible at respective.

But I don't wanna see government interfering in ai, right? So I don't want government come stepping in and say, if you sell this chip to China, gimme 15%. I mean, to me, that's socialism, right?

Like, how is it a different Ab right? Either you're formula, you don't want China to have it, or you do, but you don't. It's not, You criticize socialism.

On the other hand, you participate into socialism. Agree. That's a problem.

And we, we all, and then what the other thing is, I like to see government actually deploy AI with their own agencies. I mean, if I have a government minister, that person should be responsible making sure government is using ai, right? I'm not seeing any of that happening, right?

Well, Elon must supposedly, but guys, we gotta take a break here. We're overtime. We've gotta come back for our third segment today.

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But we have talked about one of the biggest issues with AI is energy. We don't have enough of it. The grids kind of, well, shall we say, shoddy.

And so now a lot of folks are saying, well, we're gonna have these massive batteries that are gonna enable us to store energy so that we can mitigate some of the impacts these data centers are having on our grids. And it's an interesting theory. I just don't know if the science behind the batteries is up to the task or not.

But Alan, what do you make of it? Can batteries kind of solve this issue for us? It, it, it could help if you believe we can get there, you know, on yesterday's gang, we spoke about JP Morgan Chase put out a report that now they expect 5 trillion, 5 trillion.

I'm back to that 5 trillion number. I love that number $5 trillion of data center build out over the next couple years, right? What's the biggest bottleneck to bringing these data centers online and operating them energy?

We don't have the energy to operate those data centers. We can't build nuclear and get it approved fast enough. We, what?

Are we gonna burn coal for this? Uh, the government is not a big fan of solar and wind, and that's probably our best bet. So much.

And this is again, the beauty of AI and, and the, and the first segment and video making some hail Mary bets. The beauty of AI is much like the NASA space program to the moon in the sixties, right? They knew to get to the moon, they had to invent some things that didn't exist right now, right?

They had to do better computations, they had to make materials better. They, they needed mathematics. And, you know, they, a lot of technologies got invented and commercialized as a result of the mood program.

We are in the same boat here. We know the key to making our, you know, to solving the energy issue for data centers and, and for beyond data centers is to have that a battery storage, right? We could then really store all that solar and wind that gets generated and, and stored for a rainy day, so to speak.

So I think this is gonna spark better battery technology. And I think we've already starting to see these kinds of announcements, right? And that's what this is about.

We need better batteries to make our data centers and our world better. You got trillions of dollars at stake here. Let's go build better batteries.

I just wonder if these batteries are gonna be kinda, you know, a substantial impact, or is it gonna be like, you know, when I get that electric vehicle and if I pump the brakes, the battery will recharge. But it never really does. I don't think that's, I don't think that's what we're talking about.

I, I think we're talking about, I think we are not talking about the recycle waste this battery is going to generate over time, right? Because if you see Tesla is the one who entered this space years ago, and now this is the time where they're changing the batteries because their battery's supposed to last seven years. So where is this battery waste going to we get disposed of?

So it's not just about data centers getting electricity. I mean, you just said Alan few minutes ago that we are still at the beginning of the beginning. So when, when we are not sure with AI where we are heading to, and we are building data centers and we don't, we do not have a clear concrete plan in terms of what are we going to do with this batteries when they're run out of life.

We are still in that circle where we are building things. We don't know what use case they are in. And we are probably producing more environmental hazards, which will be more dangerous than the benefits of ai.

The last I check this, government wasn't very concerned about environmental hazards. Wait, wait, you now have some, all those rockets that Elon Musk and Jar Bizos are building, Right? Send them up in space.

I I, I think it's important to recognize what is the role of the battery. The battery's not gonna be the primary supplier of electricity gives data centers, right? It is gonna be that power buffer, right?

And in the grid and the racks. And the reality is that GPUs have very high peak average power issue. So, uh, the, it, it's a very spiky and sort of a denser, less predictable power profile, right?

So AI dense racks, I think the last time I read was like, consume 40 to 60 kilowatts today and then going up to 120 kilowatts, right? So the question then becomes like, what is that? What is the role of the battery that's going to be, uh, going to be relevant for this buffer power buffer, as they call it, right?

And already the hyperscaler, like Amazon, Google and Microsoft are deploying what they call battery energy storage systems, or best they call it, which not only generate the power, but also self capacity back to the grid during peak demand. So I think all of that is an interesting topic, but equally important that someone touched upon is the environmental aspect of these batteries. Like, what are we going to do with all this battery waste, right?

That gets, uh, generated over time by powering creating those power puffers for these AI AI data centers, right? So I think those are some of the interesting things to, well, I I I, I've really enjoyed the, the, the power, you know, when I look at these shows over the last year, right? We keep coming back to this issue.

And I, and this is one of these issues that comes up where we're mostly talking about ai. We talk about power, but I've been involved with the grid for decades and the last 15 years particularly has seen a lot of work in this direction. And this use case is just for these sort of, you know, from a power engineering perspective, you know, one of these CEOs slap your forehead.

Of course they, you know, of course we're gonna throw this in so into the specifics, kinda like the last segment. You know, I am on an international level. I am looking for countries to disprove things that seem popular, you know, draconian, authoritarian, whatnot.

This particular, uh, legal move in this particular jurisdiction, I think is a good idea. Cattle just this week, you know, the largest battery produced on Earth is coming out, has announced that the production level of their next generation of the lithium iron batteries. And that should be a, a big quantum step here in Canada.

Volkswagen is building a giga plant, uh, shovels in the ground, uh, battery plant, uh, that'll be producing, uh, platforms in 27. And, and, and, you know, take everything else we're talking about here over those timeframes, if you know, hyperscale or consuming energy data, uh, in bigger data centers with more Nvidia GPUs was gonna follow exactly the curve that it's on right now. That's physically impossible.

What are we going to do instead? Right? And, and whether it's these individual things with, with best, with battery storage systems, I, I saw a neat little thing that again, I don't think is the answer, but I love these sort of things in the uk they have a programmed now where you can run a micro data center in your shed, literally in your backyard, and it'll provide the heat for your house and lower your costs, You know, which, well, that Finland, Finland is building underground data centers and using the heat to, to heat how homes, old towns.

So Yeah, this winter, I have enough GP news running at home right now this winter. I'm, I I will in fact, you know, lower my heat bills. So anyways, you know, this is a complex issue, but there's pragmatic realities in, in power terms.

We talk about, you know, rotating mass, right? You don't, you don't think about this. If you plug something in, there's some spinning tons of steel that feels that momentum.

So we have battery systems now that can mimic that, which is bloody amazing. But we're still so early in this that again, grids and jurisdictions will make bad choices. I have a lot of popcorn.

I think we'll all learn from mistakes, but yes, this is where we're going. So maybe, maybe, maybe the future is where all these big corporations that are building these AI data centers will work with consumers and install GPU clusters in every home power with batteries, which can also power their refrigerator, generate enough heat and save money. So maybe that's new Steady kind of thing.

So, So Sid, are you saying that the Energizer bunny is gonna save ai? Yeah, exactly. Mike, you summarized it very well.

That's why I love 'em so much, right? I mean, I don't wanna raise my kids under the house where GPUs are running. I don't know, what are the ultimate race gonna do to this American life?

Well, You put it in, you put in a shed in the, in the, in the yard, you know something. I mean, still, still around. Yeah.

Yeah. I think on that note, we we're gonna end today's text drug gag gag. Thanks for joining us.

This was a great, great discussion on some great topics. Thank you for watching Micah. And I'll be reporting here from, uh, AI native Deron in Brooklyn today, tomorrow.

So stay tuned for that. Stay tuned for the rest of the text on TV coming out you right after this. But for now, half of the gang live in Brooklyn.

We're out. Let introduce you to my friend Homan Singh. Haman is with Broadcom Homan.

You welcome. Thank you. Thank you for having, Enjoying, enjoying Q con so far.

Absolutely. Very exciting day one today. Yes.

It's been a, an energy, always a lot of energy. Oh yeah. At CubeCon.

Yeah. Haman, you, before we get into, we, we've got a couple things we want to talk about. I want to spend a little time just letting our audience know a little bit about who you are and Yeah.

You know, so give them, if you don't mind, a little bit of your background. Absolutely. So yeah, I am director of product marketing, um, at, uh, VMware by Broadcom.

Right? So my focus areas right now are around Kubernetes on VCF, which are, which is our VMware cloud Foundation offering, uh, everything AI as well. And then also looking at our kind of cloud operations, cloud consumption, uh, capabilities used to be part of the old Aria portfolio.

Sure. Uh, essentially, right. So a few of those things kind are, you know, very related areas to each other in terms of how consumption works in a private cloud.

So happy to be, you know, working on that visa, but not VMware coming to 12 and a half, 13 years now. So, wow. Lots of changes.

But also, So you were v VMware before broadcast. Oh, yeah. You've seen a lot of changes.

I have seen a lot, and I have the scars to prove it. Yes, I bet you do. I bet you do.

You know, a lot of people look in the software world, I think everyone knew VMware, and I think everyone knows that vm. Not everyone I guess, but most people know VMware is now part of Broadcom and Broadcom's a name I, again, I think a lot of people know Broadcom by name, but they don't realize all of the things that Broadcom is part of. Without asking you to be the Broadcom spokesman, what you're going to be, give us an idea of the different tentacles, if you will.

The Broadcom Yeah. Tentacles. That's interesting.

Uh, it's, it's less, Well, an octopus is a very intelligent network, Very intelligent. Then let's just go with that, right? Yeah.

So, um, Broadcom actually right now consists of, I think 26 different divisions. Oh, I didn't realize it was that many. They operate as almost as independent businesses.

So you have a lot of flexibility. Each kind of GM has a lot of flexibility in terms of just going to market as, as they were. So it's Broadcom's known in terms of what, of a hardware company for a very long time.

Yes. Massive hardware, innovations, et cetera. I mean, you know, um, but at the same time, in past, I wanna say close to a decade, they've went into software, you know, very strongly to kind of really think in terms of, if you look at a hardware business, which is very kind of seasonal, uh, you know, there's this like press and troughs versus software.

It brings kind of more stability. And I think that's what Tan was thinking about in terms of, you know, growing Broadcom beyond the hardware pieces. So you got, you know, a few different pieces.

The, the Broadcom software group now has, and then of course VMware by Broadcom probably the biggest acquisition in the industry when it happened in 2023. Timeframes 65. Yeah.

I would say Broadcom, VMware, or ca was a big buy too. Yeah, CA was big as well. C was like 16 Something, but it was older.

So you got go by, you know, if you put inflation on those nuts. Oh, that's true. Yeah.

It Probably is closed. Yeah. Ca was a long time ago.

And then of course, I think that was the first big software. Yes, absolutely. And so they started with that, and then they kind of got the flavor of it, and so then they went Symantec, they went VMware, uh, et cetera.

And VMware is a whole kind of different story, right? Because Oh, yeah. 'cause I think, you know, the, the kind of ecosystem VMware brought with it for Broadcom, uh, there was a huge amount of, I think learning in terms of the Broadcom culture as well.

And we are very fortunate to get like, the support that Hokan has provided to VMware. Um, there's been a lot of focus for sure. Yeah.

Um, VMware behaved very differently before, um, kind of an amalgamation of a bunch of different groups versus now it's extremely focused. We got 1 1, 1 key offering, which is VMware Cloud Foundation. Um, and then really making sure that we are going after the private cloud, the value we're delivering and building capabilities around it into VCF.

Um, and that's been doing like very well for, for VMware overall. Uh, in terms of, you know, how, you know, Look, you've been in VMware, what'd you say? 13 years?

Most. 13 years now. Yeah.

I've been following VMware longer than that even. Right. And if you look at the history of VMware, very interesting.

Right. For those of you out there, I'll give you a little history as I know it. Right, of course.

It was kind of, it was kind of spun out of, actually it was started and then brought into EMC, wasn't it? Yes. Right.

The original founding team, kind of, there were a lot of hypervisors vying for the market space back then that Time. Yes. Um, the Red Hat one, there was some open source swans, but VMware, it, it was very, at the time, everyone thought it was very lucky to get hitched into the EMC uh, orbit.

Yeah. You know, and similar to Broadcom, it was basically kind of a hardware company. EMC was a hardware storage company.

Storage. Yeah. And now all of a sudden they've got this hypervisor company, and I think it was a bit of a redheaded stepchild, if you will, because it wasn't core to what EMC did, saying then now EMC goes and gets acquired by Dell, another hard hardware company.

That's Right. Although Dell would argue, like by the time they came to Quest, right. That, that They was software company.

Well, again, much like Broadcom, they were transitioning to software Yes. To even out the cyclical, the cyclical hardware cycles. Yeah.

Then Dell goes private. Yeah. Spins out.

I think they spun VMware out and was the first time that VMware was truly, truly independent. That is true. Since it was first.

That's true. Yeah. Formed, that's probably around when you joined Or it's, no, so I joined back in, uh, 2013.

So That was still Dell or EMC? Yeah, that was EMC. Okay.

So it was EMC, then Dell came in 2016, I, I believe. Right. Um, and, you know, a whole bunch of things through that.

And then of course, VMware became a spun out independent company. Uh, I think we might have been technically independent for like six months. Right.

And then Broadcom kind of made the announcement of the acquisition. It's so an amazing thing. Yes.

No one's ever let VMware just be VMware. It is Extremely valuable in terms of, I think that VMware has and the call Based, well, it's also the market share, right? Oh, yeah.

VMware though, as we said, there are a lot of open source hypervisors and public cloud hypervisors and so forth. VMware is the hypervisor. Right.

Has been absolutely. Continues to be. Now Broadcom board it and you know, there was, there was all kinds of rumors and feelings about what that meant for VMware, but as you said, I think htan surprised a lot of people in that he didn't treat it like ca Yes.

He didn't treat it like some of the other software acquisitions, I think, because for the same reason Dell and EMC, they recognize that you got a diamond here. Right. You, you can't, you gotta shine it up.

You can't try to break, you don't want to. You're not a diamond cutter. Absolutely.

And, um, and so it, it's, it's had, its a reflowing, if you will Yeah. With that's good word. Yeah.

Yep. Yeah. And that is, look, we all talk about license changes and all of these things, but when you look at people who are either staying on VMware or leaving VMware, they don't cite cost as the issue.

The issue is freedom. Do I wanna have a multi-cloud a a, uh, hybrid cloud? Do I wanna just stay in my private data center?

Do I want to be locked into anyone's walled garden? These are the things people care about. Yeah.

Yeah. But, And, and I think, um, this is the thing with, again, any kind of like platforms that we have, you know, no matter which vendor you're talking about, uh, you know, at the end of the day it becomes a platform play. You know, where do you wanna standardize on?

Um, there's always gonna be, you know, some silos that you might have. Hey, companies acquired this and that, uh, and or they grow certain things organically. But by and large, you know, when you look at large enterprises, they want to look at overall cost, overall sanitization, um, that helps with cost, but also from an over, you know, just ongoing operations perspective, skillset perspective.

How do you make sure that what you have can be leveraged and, and then basically expanded more and more. And this is the kind of story that works for, I mean, it doesn't matter if it's, you know, Broadcom or VMware or some of the other vendors. You know, you wanna make sure that you are able to provide the benefits of standardization.

While, uh, and I was just having this conversation with, with a colleague earlier, while giving the folks who are doing the innovation, the flexibility of being able to do that without feeling locked in. Right. And that's exactly what we're striving to do when it comes to kind of VCF and, uh, yes.

This, we went through a whole bunch of changes, uh, in terms of bringing things together, uh, which also for the first time, interesting. Big, big, big focus. I mean, VMware fantastic culture, but the thing that we lacked before was the focus on making, making sure it all works well Together.

Discipline, right? Yeah. There was a little a DD, if you will, entrepreneurial a DD.

Yes. Um, and you know, that's not a bad thing, but focus is a good thing. Now we're here at Cube Con, though, and people say, okay, hypervisor cool, Kubernetes, how's the, what's the connection?

And if you're asking that, then you really don't understand. Right. Uh, containers, orchestration of containers has run on, have predominantly run on hypervisors.

That's right. From day one. That's Right.

Uh, VMware pre Broadcom was a huge supporter Yes. Of Coup. Absolutely.

Of, of CNCF. They continue to be under Broadcom as well. Yes.

Uh, talk to us a little about that. Yeah. So VMware has been involved with CNCF for the longest time, and you know, basically Right, right from since inception, pretty much Yep.

Got involved with Kubernetes right up front. Uh, and, uh, we've been, Ian, this is something that folks are actually surprised to hear that we've been, if you look at long term Kubernetes projects, uh, you know, contributions by companies, we are the number three. People are very surprised to think, oh, VMware, you, you guys have been that active.

Yes, absolutely. And it's just that we never kind of talked about it. No.

Right. But then we've right there, people Put together since, Since the beginning, you know, if you, this is again, coding c nnc, f sta statistics, um, it's been a top, top, uh, contributor. We've got a lot of people who are maintaining a lots of kind of, uh, CNCF projects, Kubernetes.

So the idea has been that we've not been like just the users of Kubernetes and incorporating it and making sure it works on a platform. We've been right there with the community building it help, helping to build it all this while. And, uh, and we wanna continue to do that in an even stronger way as we go forward, because, um, as you think about core infrastructure, it doesn't matter.

You wanna run applications on virtual machines or on containers, which predominantly, as you said, pretty much, uh, you know, uh, everyone, including all the hypervisors, run the containers on Kubernetes on a virtualized environment. Everybody has their own kind of flavor. And because it brings a certain amount of, you know, benefits to be able to do that, all the isolation, benefits, security, and all that kind of good stuff as well.

Um, and making sure that we provide this experience of running containers and Kubernetes as good as folks have enjoyed running virtual machines on a VMware environment, right? We have been always known for, for VMs, of course, you know, we, we are the market leader, uh, no matter what metric you choose, and we are doing the same when it comes to containers and Kubernetes, um, to make, to provide that experience. And this is exactly where, as part of this VCF platform I was talking about, the vSphere Kubernetes service, or VKS kind of comes in.

We used to talk about this as, uh, a tan, zu, uh, service Yes. Back in the day. And, uh, as we came into Broadcom, we moved all the Kubernetes and infrastructure pieces as part of VCF.

Again, to that point of focusing, focus, simplifying, providing a better experience to customers. At the end of the day, that's what it's all about. And so our Tan Zu team is focusing very much on a PAs environment, uh, uh, going directly to developers while the VCF piece is working with platform engineers predominantly, and of course, our core kind of audience, the IT admins, the IT team that have been running infrastructure.

So that's kind of how the overall evolution has been. And there's just, there's so much more that we are now looking forward to do, because when you focus, you can do so many more things better versus just doing a whole bunch of things in average way. So we're very excited about that.

I, I, I, I don't, I could see why. Right. I, I could see that happening.

So here's one thing we haven't mentioned, though. That's been a big thing, and that's ai. Yes.

How is AI changing, influencing, showing itself in this, in this ongoing evolution? So we, um, been involved when it comes to the AI space and providing the infrastructure for AI workloads for quite a long time. And we've been working with NVIDIA for more than a decade at this point in time, to make sure that all the innovations from nvidia, therefore the gpu, vgpu, et cetera, are available as part of the, as part of vSphere before.

And then now VCF, of course, the other thing is, um, I forget when it was, but I think might have been 2023. We kind of put our foot down and, and talked about private AI as a key piece. We basically said, Hey, uh, private AI is, again, not about like the location, but the concept of privacy of your data.

AI in itself is all about massive, massive amounts of data Yes. And where it resides. So we wanna make sure that customers are able to get the insights from all that data without having to move the data around, keeping it within their boundaries, keeping it safe and secure.

And again, if you folks have used vSphere or VCF, they understand the level of, you know, enterprise grade security that comes with the platform. And so we are bringing the exact same thing to all AI workloads. And the, of course, when it comes to ai, you're deploying it using Kubernetes, you're deploying it on containerized, the applications are typically containerized.

And so making sure that the experience we get for all our private AI services and capabilities that are all included in VCF with V Kubernetes service as well. In fact, um, today at the CubeCon, they talked since CFC announced the new, uh, Kubernetes AI conformance program. And we are one of the first, one of the few really, uh, starting kind of conformant and certified platforms.

Um, you know, VKS is as part of that. So we kind of underlines the importance of AI in general and how we see at the end of the day, it's just another workload. And we wanna make sure customers have all the tools available on the VCF platform to be able to use VKS, use our private AI services to build those, uh, those, uh, you know, applications that they do.

I, I, I think, I'm not sure we're running low on time, but one of the things I wanna close with, and, you know, I'm directing it right to our audience, and you look in that one when you respond, which is, look, VMware's always been a supporter of the Cloud Native Computing foundation of Kubernetes, of containerized, of cloud native computing in general under Broadcom. That commitment is of anything stronger than ever and remains so today and tomorrow. And, uh, you know, anyone who says different is, doesn't know the truth.

Yeah. Just need to get educated. That's all they need to, like, it's an education.

Learn more figure, figure it out, and, and they'll see the value. Yeah, Absolutely. Hey, thank you for all you do.

Thank you. It's a pleasure as always having you on. Um, I hope we won't wait till the next cube con.

I would love to, you know, get in touch earlier and Well, we shed this conversation. We do these every day outta the studio. All you gotta do is write me.

Absolutely. So it's on you. Absolutely.

It's on me. All right. How you sing?

Sing, uh, Broadcom, VMware, Broadcom, VMware, Broadcom the right term here on Techstrong. We're gonna be back in just a minute. Hey, if you've watched Techstrong TV over the last few years, you may may have seen this gentleman on his name is Colton Andrews.

Andrews Andrus. A-N-D-R-U-S. That's correct.

Not Andrews my funny French accent. You gotta be careful with Tech Colton. But Colton is the former once and present and future CEO of Gremlin.

That's right. Right. And, um, if you don't know who Gremlin is, stay tuned, we'll tell you.

But Colton, it's great to have you in person. You usually do this, you know, remotely over text, drunk tv, but here you are in the flesh, man, good to See you. Remote's fun, but different energy when you're live So much.

Enjoy. You know what I, um, I gotta echo that, right? I, I just had this at a, we were at a dinner last night and I was talking to some people, whether it's a, a sales environment where you're there talking on a potential customer or a partner, or even a friend.

Nothing, nothing takes the place of person to person. And, and that's not, and that's something AI's never gonna be able to do. Yeah.

Right. Such a timely comment. Yeah, exactly.

No, but humans are social animals. And though, like, when we were locked in our houses for COVID and everything else, zoom was the next best thing we had. It pales in comparison Yeah.

Of, of this kind of communication. So, hey man, it's great to have you here. Yeah, Yeah.

Thanks for having me. So, Colton, I made a little reference to once present and future CEO, but there's been some gaps there. Talk, tell, give people a little bit of your history.

Yeah. Well, uh, for those who don't know me, I'm Colton Andres, engineer by trade. Uh, grew up working for a bunch of tech companies, had an opportunity to work at Amazon for a few years, focused on their reliability program, got to join Netflix, got to continue my good work there.

And that really led to going out and founding Gremlin. Uh, first few years I was CEO, uh, for six years, you know, out building the product, learning the market, really advocating champion for the idea. Uh, brought in another CEO to run the go to market side so I could go focus on product and engineering.

And that was really a go into the lab, you know, understand the problems well, and go fix 'em. And, uh, I got that done. Engineering's running great product's in a good spot.

So I took back over as CEO and excited to be, you know, running the whole ship again. You know, look, I know a lot of guys who were, you know, founded companies, became CEOs and then moved into product role, CTO role, chief evangelist or strategy. But I, I'll be, I'll be honest with you, I haven't seen many come back to be the CEO.

Yeah. Um, so kudos to you on that. You know, if you wouldn't mind, you know, I don't want to go Barbara Walters on you showing my age even saying that, but what, what kind of, what was, what was like, what was the light that went off and said, okay, it's time for me to come back as CEO?

Yeah. Well, I think it was twofold. I mean, just to be, just to be completely honest, you know, if it's your first time being CEO, you have some doubts.

You wonder if you're doing things right. If you could have done things better, Joe. Right.

And so, you know, you bring in another CEO, it's an opportunity to learn, listen, observe. Uh, and I'd love to say, you know, that the person I brought in taught me a bunch of things I didn't know, but a lot of it was actually, you know, kind of par from the course. You, you know, I was doing it.

Okay. And You needed that reinforcement. Yeah.

And so that was part of it. Uh, and then the, the product and engineering side, I'm an engineer, I'm a product guy, I'm a builder. And one of the mistakes I made was stepping too far away from the engineering side and really delegating it.

I see what you mean as CEO. And so, yeah, my, my three years as CTO was getting back in and make sure we were building product correctly, we were understanding it. Well, part of it was getting our engineering team just humming, you know, making sure they were shipping.

It's the lifeblood of a tech company. And if you've got issues that are preventing, you know, consistent quality delivery, those have to be fixed. So once I had those fixed, that left me in a position where I felt like I could come back and take back over the reins as CEO.

And I think one of the, one of the big things for me is, one of my roles has always been an evangelist role. And it's actually a bit easier in the CEO position to be that evangelist. Sure.

To be in front of customers, to be in front of prospects, to be at events, to be doing interviews with great guys like you, to allow you to get out and spread the message. And so that was, that was a big impetus. Flat, flat flattery will get you everywhere, my friend.

Thank you. But, you know, I, I had a little bit of the opposite from you where, and, and this is another sort of, uh, persona that I, I've seen in startups where CEO founder is the chief sales guy. He's the guy who closes deals.

He's the guy who has the network, or she, in some cases, right, they're the ones who are primarily responsible for making it rain. And sometimes, you know, revenue is key, revenue is king. And you're so focused on trying to go out there and make it rain, bring in the revenue that you, you, you lose touch or you lose focus on is is product running, right?

Is engineering is operation our case, it's operations, it's, it's, you know, all the little things that beyond doing these, 'cause I'm the face of it, beyond, you know, making it rain. And, and that's a, it's a tight, you, so you live this too. You're just living it from the engineering side.

I'm living it from the revenue side. Right. You, it's tight rope between how much focus do I internally give to the, the guts of the company versus my external focus on making it right.

Yeah. Yeah. And that's, that's one of the parts.

Yeah. I think one of the unique positions I'm in is being an engineer that has done it and lived it. I have a credibility, I have a, a wealth of experience I can speak to, and that's relevant, whether I'm talking to engineers or I'm talking to executives.

Yeah. And so, but yeah, if you get, you know, gotta gotta have revenue, gotta build a healthy company, gotta make sure the company's moving forward, and that, that focus can steal from kind of the pure engineering. Are we solving the problem well?

And are we really making the progress we need to Absolutely. Tight balance. Absolutely.

It is, it, it is a tight balance. And, and the other thing, and, and, and I would say this is probably another mistake that CEOs make, especially first time CEOs or more inexperienced CEOs, is you hold on to things so tight, right? I, I can't let go of engineering.

I'm, I'm an engineer. I, I know I have the vision. I God will see that through, I'm the best advocate evangelists we have.

I I'm the one who could close these deals. I'm this, I'm that I, I, I, I, you can't be all eyes. There's gotta be some we in there.

And so learning to delegate, first of all, it's what's, It's Having a team, you could trust It. It's interesting you say that because I actually think one of the traps I fell into was the too much good advice trap. Oh, you delegated Too.

And I delegated too much. I tried to find the perfect executives that Could. So that's the anti tattered.

And a lot of what I've been learning and doing the past year is just falling back to what I find. You know, there's a balance. And so, yes, I think what you're saying is totally valid.

You gotta build the team, you gotta build the expertise. But sometimes if you over delegate or you do too much, then the company goes astray. It's, it's, it's wandering too much.

There's too many away From you Options to go. Right? And so I think that's the beauty of being in both roles and being in both positions is I arrived at this happy medium, which is, I have the confidence that I know the direction we need to go.

I have the confidence in the pieces I can do to it, but I have a team I can trust, that I can delegate to, to ensure that I don't have to be the one who does everything. Love it. It's, you know, it's an interesting thing.

We're here to talk about Q Con though, but this is great. Look. Sure.

com. They'll be happy to answer 'em for You a hundred percent. Um, But Colton, let, let's talk a little bit about Gremlin.

You guys kind of, I mean, for in, in many ways you invented, well, Netflix did, but you invented chaos engineering, and of course you were there at Netflix. Mm-hmm. When chaos engineering kind of took root and gremlin, I at least for my money, was the Chaos engineering company then.

Yeah. Right. Now the world changes, things change, technology changes.

But talk about today's gremlin. Yeah. So I think the Chaos engineering Gremlin was a cool idea and a cool project, but really needed to grow up a little bit to be effective in today's enterprises.

I think a lot of what was great about the early product is it lets you go out and experiment and test and understand. And it was a bit how an engineer would build a freeform, figure it out. If you need help, come ask us.

Well, most enterprises don't have time to go out and figure it out, and they're busy. And so what they need is a bit more guidance, a little bit more prescriptive approach. So a lot of what happened over the last few years is let's take what we know the best practices are and just build them into the tool.

So people are starting out with the right patterns. And some of that is, uh, you know, the engineers aren't sure what to do. Let's tell 'em what to do.

Let's tell 'em what tests to run. Let's integrate with their monitoring. Let's tell 'em if they passed.

Let's, let's take the homework away so they can get the work done and get to the answers they need. The other thing that Chaos Engineering struggled with is how does the company view it? And is the company view it as important as security?

Is it something the company says, yes, this is something everyone should do? Or is it an unproven idea? That sounds cool.

And I think we saw a lot of sounds cool, but we've seen over the last few years and the way we've taken the product, a lot more companies buy into the, this is how it should be done for our company. And one of the biggest parts of that, one of the things I love to ask, uh, my customers, I've asked it three times today, is if you prevent a large outage, can you get promoted for it? 'cause we know you can get fired if you cause a big enough one.

And the answer is, if you don't have some way to measure it, some way to track it, some way to prove it, then the business isn't gonna believe you. And that's really a lot of what we've filled the gaps in. Do you, Do you think it's a question of the business doesn't believe you, or the business doesn't value it?

Kind of the same thing in the way I'm talking about it, which is, you know, if it's, if it's a clear value to the business, saves engineering time, it prevents customer pain. It prevents us from losing revenue. If they have confidence that our solution gets them, that we are, we're aligned, we're off to the races, we can get a lot done.

It's when people aren't sure. And we really have to go out and prove it that, you know, we got work to do. I agree.

I agree with you, man. Um, interesting stuff. io?

com. com If you want. Nice and easy more Information on probably, well, everybody tastes got io, ai tv.

That's my series A money went to our domain. I I It's a good, I Got it. And more, more first time CEO advice here from Colton.

Um, let's talk CubeCon. Yeah. You guys, you guys made a big announcement.

Yeah. Talk to Us. Yeah.

Excited to announce our Dynatrace partnership and integration. We got a lot of great monitoring tools, but Dynatrace is one that really gave us what we needed to make it easy to do the right thing. This is something you'll hear me say a lot, make it easy to do the right thing.

And when it comes to this kind of testing, you really have to know how's the system behave? Did it work well? Or else you're flying by blind, right?

You know? And so Dynatrace makes it really easy for us to find the code, the code that we're testing, we can go find the monitors, automatically pull 'em in and associate 'em without the engineer having to go do a bunch of legwork. Uh, and so it allows us to, uh, one, create these services within Gremlin based on what's already created in Dynatrace.

So we can just pull it into Gremlin, set up your services, set up the monitors, and now day one, you're ready to just click run and go get answers instead of doing this homework you have to do in advance. Absolutely. You know, we, we work a lot with Dynatrace.

I've had Dynatrace on here a number of times. They really got their act together in this observability in space and everything. They, you know, Dynatrace is an interesting company as well, right?

They, they're not new. They've been around, they were originally a European company. They bought a big American company.

They then merged. And there was a little, I think for a couple of years back then, a little struggle over what culture and what vision they were following. You know, we didn't have something called observability then.

Right. It was a, a, uh, A-P-M-A-P-M. And, um, but now they've emerged over these last couple years with their act together, certainly.

And they're killing it. I've seen a lot of great product innovation. Yeah.

And there's things that, you know, beyond just alerts and monitors, you know, when it comes to reliability, you need very fine grain data. This is something where we need to know what's happening every second, not every five minutes. Right.

And we found that granularity. We found the nice places we could integrate to get that visibility. Yeah.

No, I've, I've been impressed with the product innovation and, and the partnership. Absolutely. Let me, let me put on my CEO Rainmaker had again here.

All Right. I love it. How, how is this translating in the market for you?

Or how do you expect it to translate? 'cause it's new? How do you expect it to translate in the market?

Well, I think we see a lot of, uh, shift in the observability market, uh, from our position. A lot of companies are reevaluating their vendor of choice. Uh, cost is a big issue.

Sure. And so people are trying to right size and find that value. And the truth is, we are, we're pretty tied to that observability.

If you can't see what's happening, you really can't do intelligent testing. Agreed. Uh, and so this ability to really understand what's going on, integrate in and get that helps us to be able to just move so much faster, be able to get that value so much quicker.

Agreed. Agreed. So, yeah.

Is there, is there plans of how you go into market here though? Is it, are they gonna sell this solution or offer it or talk about it, or, I mean, right now it's an, it's an integration and it's something that shows up in our product. We've got some things that we push into their product as well, so people can know what tests are happening and when they're occurring, they can correlate 'em with events.

Um, but for us, we just, we have a lot of important Dynatrace customers. We wanna see them be as successful as possible. And so leaning in with Dynatrace lets us go build a better product for our customers, which leads to our customers getting better adoption, better reliability results, customers.

That's the flywheel we want to get going. Love it. Other observations around coup con, I realize it's only day one.

Well, if you were here yesterday, right? There was a lot going on, but what, what, you know, what do you think? It's been interesting.

I've, I have only been able to walk the floor a little bit. Um, you know, I think the last conference or two, you were kind of getting beat over the head with ai. Yeah.

I feel like it's balanced out just a little bit. Not every single person's talking about it. Uh, you know, I thought it was a, a compliment.

I got, uh, a customer came by the booth, uh, or a company, a customer company, not somebody I'd worked with directly. And they asked for the details. We told 'em all about.

They're like, great, we want this. And then he is like, you win because you didn't swear you didn't say the, the curse word at me. And I said, what?

Ai, what curse word? He said, ai. And I said, well, you know, there's, we've got some intelligence stuff.

We think it's important, but that's not, we're not, we're not here to just jump on AI targeting band answer for Everything. It not, not to say that it's not real, it's not disruptive, it's not all of those things, but it's, it, frankly, it's not the answer for everything. Yeah.

I think there's great uses and places for it. I'm an engineer, so I'm a little cautiously optimistic. I want to see the value be pr It's the same as chaos engineering.

I wanna see the value be proven. Yep. Before I go all in.

And look, we're, we're building intelligent capabilities that make it easy to do the right thing. Well, it's, you run the test, you know how your system responded. Well, the last step is you gotta go fix it.

So we built a great product this year that tells people how to fix the things they find. And to us, the key is it's credible. It's, it's accurate, you know, and it provides good advice.

And, you know, we're not, we didn't just slap it on everywhere. We put it in a very specific spot, we tuned it well, and we feel really good about those results. But, you know, the dirty secret is we're not just shelling it out to an LLM, you know, we're, we're doing some machine learning and modeling in the background, and you're treating it a bit more like a, a classic data science AI problem than just a, Hey, could the LLM solve this problem for me?

I love it. Hey Colton, we're about outta time. com.

That's the important thing to remember. Good luck for the rest of CubeCon this week. Um, I guess we'll see you on Text Trunk TV next.

Yeah. Yeah. I'm looking forward to it.

Thank you very much. Al Colton Andrews, CEO of Gremlin here on Text Drunk tv. We're gonna take a really short break 'cause I got my next victim sitting in the barber chair.

Ready to go. You're watching Text Drunk tv. We're live at Cube Con.

Hey everybody. We're at Ingram Micro one. We're talking innovation with my good friend Bill here.

How you doing Bill? Going On, Mike. Good to see you.

Good To see you. One of the things that's come up at the show is that we're talking to the partners about becoming more of business advisors rather than just technology advisors. And for years we told everybody that they were gonna be a trusted technology advisor.

What does it mean to be a business advisor? When and how does that transition them, the way partners engage with their customers? Absolutely.

You know, that's a great question, Mike. And, and you know, this, this industry, if it's one thing, it's always evolving. And, you know, when you think about technical advisor versus business advisor, right?

I think today it's more around business outcomes. Companies are looking for business outcomes. They're looking for ways to differentiate themselves in market.

They're looking for ways to be ahead of the competition. And so it's no longer just about the technology, it's about the overall desire of the organization and where they see themselves going and how they see themselves showing up differentiated from the rest of the field. And so I think being able to have that business conversation around where a company is looking to go, where they see themselves in three to five years, and how they wanna show up to their partners.

It's more critical today than ever before. The technology is great and it's required, but it's more than technology. It's people, it's process, it's how we show up.

And I think that's what, what's changed. Does that change any of the business models of the partners? Am I gonna tie my, uh, revenue to an outcome versus maybe traditional time in labor or some sort of annual per proceed fees?

Is that gonna change? You know, I think as this industry evolves, everything changes, right? And I, and, and I know we're at this, uh, really exciting time in our industry with, you know, AI that we talk about all the time.

But that's forcing all of us to rethink how we do things. How do we compensate, how do we look for value and where we can capture value and how we can monetize value. So I do believe it's going to change how companies look at rewards and recognition, how they look at compensation models and how they look to drive value in the interactions they're having with their partners.

Do the partners need to go deeper in the business? And I'm asking this because, yeah, it's one thing to provide, I don't know, an email security service, but it's another thing to go in and understand a workflow that drives revenue and how to optimize it to, you know, create a better bottom line for the customer. So does the partner have to get in there and kinda understand a little bit more about each vertical industry and what those people are doing to apply the tech to that process?

So when you think about, I, I always look at now, the deeper you can get into the process, the more you can understand where can you automate, where can you find efficiencies so that you can free up the rest of the time for your individuals to be doing far more proactive consultative or a more valuable, um, work for the, for the organization versus that transactional. And that sometime cumbersome, you know, operational stuff. Mm-hmm.

So the deeper you get in the business, the more information you will have. Of course, you can't walk down the street these days without somebody leaping out to tell you about their great new AI thing, and this show is no different. Um, but to that point, uh, how do you have that conversation with people?

'cause I think on the one hand, you've got business executives who think some magical thing is gonna instantly happen and transform the world. And then you've got, uh, some employees maybe who are like, well, this is interesting, but it only, you know, helps me write a better email. But that doesn't really change my world.

Right? How do I kind of navigate that spectrum as a partner and engage those different constituents? That's a great point, Mike.

And, and the thing is, is everybody's gonna be coming at it from a different perspective, right? You have business owners who are trying to understand, what does this mean for me? How do I capture the value that this is supposed to provide?

Okay? You have line line workers, folks who are driving different business units within a company who are trying to figure out how can they take advantage to help automate drive efficiency and streamline their go to market strategy. And then you have, in some cases, associates who are saying, Hey, what does this mean to my job?

And so I think it's really being clear what the message around what you're trying to accomplish, right? I think the focus is automation. And I think if that does free up part of someone's day, you're able to repurpose that individual on a more strategic focus for the business.

I think it's a win-win for everybody. The work that we used to think was valuable because it was very time intensive and it was very transactional, is not necessarily the kind of value we want to create as companies. When we do business together, the value we want to create is a true partnership where we're looking for growth, we're understanding where opportunities lie around the corner, and we're building a strategy to go capture those opportunities.

I think sometimes we get ahead of ourselves a little bit when it comes to emerging technologies like ai. Not a shocker. But, um, are we entering like a new phase here?

'cause we're talking now about agentic ai and it might actually deliver more of the promise that we initially made on the first round of AI with copilots, which, you know, are kind of assistance to people. But agentic ai, it feels more like an autonomous process that I'm letting something get automated through. And that's a different mindset and a different way of thinking about a business process.

But is that, like, are we on some sort of arc of a journey here? I mean, agent AI is truly transforming the way everyone thinks about what they do. And to be able to build an agent that can, that can focus on a specific task or project and actually learn how to make it better and grow in efficiency as it continues to learn and evolve, is truly kind of mind boggling when you think about it.

And it's exciting because it opens a door to a ton of possibility. And I really think it's, it, it's only limited to people's imagination right now, really thinking about how they can leverage this technology to get into a business process at every step of the journey and find ways to streamline, automate, and drive efficiency and make a better experience at the end of the day. Mm-hmm.

I sometimes feel like the partners wind up being diplomats within the customers that they service, right? There's a lot of constituencies. There's sometimes they have competing agendas.

And so do the partners, if they're gonna be business advisors, have to kind of get in there and start understanding the dynamics and the relationships between the IT people, the marketing people, and the salespeople, which may not always be, you know, in agreement with each other. In fact, I'd be hard pressed to find an example where everything works, you know, all happy and everybody's working together, uh, in symphony. I think, uh, you're, you're 100% correct in the assumption that companies are going to have different priorities.

Different business departments are gonna have different priorities. And it is critical for business partners to understand every aspect of that, of that organization. How they operate.

Where is the influence, you know, where is the sphere of influence? How are they able to build trust amongst each one of the constituents? Because that's the key piece, right?

If the, if the organization believes, oh, this guy has always been working with it, they're, they're on the side of it, they're not really thinking about a business outcome, they're not really thinking about how they're driving, uh, efficiency and, and, and cost to serve. You have to be able to show the company that you have an interest in each one of the pillars for their success and how much they play a role in what each other do. See companies get siloed and they get very defensive over their areas of business.

I think we have to all rethink that. And we have to think we're all here for one reason. We're here to drive one objective, which is the success of an organization.

And it takes each of those functional areas to get it done. Each one plays a critical role. So how do we work closer together?

So the business partner has a great opportunity to bridge that gap, help them understand how the work they're doing is going to help everyone in the organization be better and have the company succeed at a higher level than ever before. So they sit in a very unique spot today, more so than ever before. How should their partners think about their own talent pool to accomplish that goal?

And I asked the question because I love the partners, but a lot of them are what I call accidental entrepreneurs that came outta the IT world. And they don't necessarily understand the business side all that well. Should they go out and recruit people who have business expertise in the vertical, whether it's manufacturing, retail, or whatever it might be?

I do believe that would be a great step. Because if you think about it, if you are, if, if it's not an area where you came from, where you're familiar with all the nuances and, and you want to go, you know, what's the first thing that you do personally in your personal life, right? You go do research and you go figure out what do I need to know before I go make a purchase or go make a decision in my life?

I'm gonna go get information. So I think it's really important for partners to figure out what do they want to do? Where do they want to go?

Who do they want to be? And then once they understand their strategy and their plan, then go find the resources required to be able to drive success into that, into that strategy, into that focus. And I think getting people who are experts in the field that you wanna play in is a great step to be able to help you build and shape an organization to support and grow that piece of the business.

So what's your best advice to the leaders of these organizations? How do I have that conversation with my teams in a way that it resonates? 'cause I think a lot of them are also, well, frankly, most of them are so busy putting out fires that they don't have a minute to think about fire prevention.

But how do I create that space? You've gotta set the north star. You've got, as a leader, you've gotta set the direction and you've gotta let people know where you're going and then you have to give them the why.

It's one thing to tell people what you're doing, but if you don't tell 'em the why, I think you're gonna lose a lot of the people along the way. Or you might not get the kind of buy-in that you're looking for. So you have to be able to explain why you're taking the steps, you're, you're taking, why you're making the changes you're doing, the, the changes that you're making, and how are you positioning your organization for success, their success so that collectively everybody sees the big picture and they understand what their role is in driving that.

I think one of the other bigger challenges here, and it's right here on the show floor, there's so many vendors, so many technologies, so many piece parts that have to go into something to create something that feels like a solution. How do partners navigate all that? Because it's a little overwhelming, let's be honest.

And I'm intact for 30 years and I find it overwhelming, right? I think I'd like to think that's where Ingram comes to play. I really think that that's where we can play a bigger role.

And I think it's a role we've played for many, many years. It just continues to get more sophisticated as we go, as technology continues to get more sophisticated. But, you know, our job is always to go find the best and the brightest technologies that are entering into our marketplace.

We're there to vet those companies out and make sure they're ready for primetime, they're ready to get in the game and help our partners grow their businesses. And so our job is to help navigate and help our partners navigate that vendor ecosystem to understand how to put together the best case scenario for the customer's exact needs. And I think now we can be very prescriptive and we can get very focused and, and do a great job with a lot of the different players that are in the space.

This is a huge market. It's trillions of dollars of tam. There is a lot to go around.

And all of the vendors here know that. They just wanna know where they can be focused, where they can have the most success and drive value into the equation so that it's a sticky relationship that lasts a test of time. And how does that change their relationship with a distributor?

Like you guys, or, I'm not even sure you are in a distributor anymore, 'cause you're so much more than that, but it seems like to me, I look at the portfolio and there's all these professional services now that I can lean on as a partner and I'm kind of just, I don't need to invest in hiring all those people. I need some, but right. It feels like I can lean pretty heavily on you guys.

And has that changed the relationship? It has. It absolutely has.

And it's something that you're gonna see us really double down on in years to come. So Tim Aman, uh, who recently, uh, rejoined the US business, came over from leading our Australia business, is running our services practice. And I think what he's bringing to the table is a really a, a a, a great tenured approach in this industry.

He's got a lot of, uh, learnings from working around the world, and I think what he's able to do now is understand what are the solutions and the services that partners are really looking for so that we can make that invest investment proactively. And partners don't need to do that right outta the gate. They can find opportunities, lean on or micro get scale, and then add competencies and capabilities as they choose so they can leverage our experience and expertise as an extension of their business.

But then they can grow and add on whenever they're ready. And our job is to make sure we help them understand that roadmap and we help them understand where the opportunities exist and let 'em capitalize on those opportunities at a very low cost of entry and then continue to grow for profitably. So let me ask you this, what's top of mind for you?

And then when you pull into the parking lot in the morning and you're about to go in the office and before everybody disrupts whatever it is you're thinking about, like what are the top two or three things that you're looking at to accomplish and kind of, you know, if you looked at the next year, if they happen, what would be the definition of success? I will tell you what keeps, what keeps me very, very laser focused right now are the people. Our processes and our system, our platform, those three things, people, process and platform is what I think about every single day.

How, how do I leverage the platform, the power of our platform, drive a differentiated experience? How do I elevate the people in the organization to be that true trusted advisor alongside our partners to help them find growth and scale? And then how do I fix the processes that exist around the ecosystem to make it easier to do business with Ingram and make it more efficient for our partners to serve their customers?

If I can do those three things, I think I, I think that's success. Alright. Hey folks, you heard it here.

People process and platform. The funny thing about that is the more things change, the more they stay the same. Hey buddy, thanks for coming by.

Thanks Michael. And we'll be back in a minute. Hey everybody, welcome back to day two of Ingram Micro one, and we're having a little chat about what's going on in Latin America with my new friend Luis here.

How you doing Buddy? Hi, Mike. Nice meeting you.

Nice to meet You. What is the state of the market in Latin America? I think a lot of our folks who are watching this may not know, but I know it's highly competitive and I know it's highly fragmented, so, you know, what are you seeing out there and what's going on?

Yeah, we're seeing, um, you know, the dynamism in the market today. I think it's one of the best times for that. So the market, it's, it's growing.

The future is bright for the technology market because of all these changes that are happening, right? All this evolution on technology, AI adoption, and, you know, the cloud business, which is exploding in some, in some countries drive that, uh, the, the optimism is across the board, right? You know, that in Latin America we have a lot of countries that are catching up on technology.

So that open also the door for, you know, big opportunities. A lot of those countries are also maybe skipping generations of technology because they're going to the latest and greatest. They're not just going through the last thing, right?

Absolutely. Absolutely right. They are catching up on the new trends that are seeing and, uh, you know, the new, the new necessity also of all the businesses to become much more productive.

So the technology is helping and, and enabling those, those companies also to become much more effective. Are there partners in this various countries getting better at differentiating themselves? And do they have some ability to say, I do something that the other one doesn't?

Yeah, I, I think it has been a journey, right? It has been a journey. Obviously we have huge partners that have big different differentiators in the, in the markets, right?

Another ones that start like their journey of transformation, right? From being legacy partners or partners that we're focused on transacting now to, to become, uh, solution providers, right? So it has been a, a huge evolution from the, from the channel I would say we had very, very good partners that provide solutions or have that have been very innovative on, on developing solutions that today are sent across the world.

One of the themes of the conference has been this notion of becoming more of a business process consultant, a little more focused on the business outcome and less on the enabling tech per se. I think a lot of partners focused on being the trusted technology advisor for years, which is good. Yeah.

But it feels like there's a ship going on where the end customers saying, I need you to be more involved in the business process. Are you seeing that in Latin America? Absolutely.

Absolutely. Right. The, the, the businesses are requiring that the it guys become much more consultants and become part of the, the solution of the company, of what the company is requiring.

And we have several of our, of our partners that have gone through that transformation already, right? They, they have become like the trust advisor for our end users where they rely on, on, on their, their advisors, on their, on their, uh, partners, you know, to come up and build solutions that help the company become much more effective, right? To really drive, uh, their, their results that they are expecting, right?

The companies today, they don't have, I would say all the vision on what they could get out of the technology, but when they got a good, a good advisor, that changes, right? The advisor helps them, or, and our channel helps them to understand what are all those opportunities that could be, that could be fulfilled with technology, you know, and we are seeing that, we're seeing a, a lot of, uh, adoption in cloud, for example, right? The adoption in cloud that we're seeing in several countries is huge, and it's because the demand has increased at the end user level, right?

They want to be much more secure, they want to have their information available at any time. So we, we've seen that level every time going up and up and up. The requirements have been, you know, raised in the, the bar.

I think every channel partner around the world wrestles with this following issue skills, getting the right skills, making sure their teams are up to date on skills. Now we're asking them to kind of become more business experts. Where do they get that expertise to kind of converge the business acumen with the technology skills?

Right. Well, first, first Of all, I would say start with a willingness right of them to change on moving from selling hardware now to sell solutions or, or be together with a, with end user. Uh, and we work together with them.

We have several programs through the region where we start with an assessment on where are they today and what do they need to do in order to become much more a solution seller, a real integrator that will help the, the end user. So we have seen great changes in some partners that went from selling hardware that today they're, they are very good service providers, right? That went through the whole process with us from understanding where they, where they were and where, where those, uh, what were those requirements that they need to start professional analyzing their sales force and also their skills, right?

To become much more integrated with their end users. So it has been a fantastic, a fantastic journey in, in several channels and in several countries. I think there's also a fine line between the skills that I go higher versus maybe relying more on you and Ingram for professional services as far as I can tell.

Walking around, you guys have built a fairly deep bench, so are the partners starting to tap into that to kind of achieve that goal? Absolutely. Absolutely.

I would say today, one of the most difficult things today is to get a customer, but once you get a customer and you are partnering with us, we can basically complete your value offering without having you, or without the, without the channel having to build the full infrastructure because we are behind. So we can support a channel with our infrastructure, with our expertise, with all our technical resources to really support their value proposition so they can go out and sell anything without necessarily having a full infrastructure to support the requirements of the customer. So we have a, a full stack of professional services, a full stack of technical resources that could support the end user requirements together with a, with a, with a partner.

So it has been a, a very good, uh, a very good journey and alignment with our, with our partners, supporting them with our professional services offering. This is my assumption, but I think if you're selling more of a consulting engagement and a, and helping with a business outcome, there's less conversation about, um, you know, how to compare the price of one server versus another, and we don't wind up in this kinda, you know, race to the bottom kind of feeling. Absolutely.

Absolutely. I would say the price is not the most important piece anymore, right? Obviously it's a, it's a, a big piece because they want, everybody wants to maximize their, their margins and, and their profitability, right?

But at the end, when you build up a solution, it's not necessarily easy to compare on the price, right? When you build up a solution that comes together with, uh, uh, with services, but also because also what we are looking with the services, it's like to create the thickness to the customer, right? So the customer, once they start seeing the benefit of the services, they start asking for more and more and more and more because they see the benefit in their, in their, uh, in their company results.

So that, that's, that's what really the vision that we want to accomplish, right? We want to create a huge thickness to the customers so they won't have to look for another, for another partner, right. We're here at the show, and I don't think you can walk maybe 20 yards without running into somebody talking about ai.

Um, what are the partners telling you about the opportunities there? What are they looking for? What do they need?

You know, I, I would say it's, it's in two levels. There's a, a big piece of our channel that today is trying to understand what, how to sell ai, how to use it first, and then how to sell it, right? Those are the ones that we are still working, you know, that we have an AI enable enablement program with them where we, where we took them again, with an assessment on where they are all the way until they, they become really experts on selling ai and the other one, it's a channel that, that I would say was born more on the, on the solutions space that quickly adopted the ai, uh, the AI trend, right?

Those guys, we have set, we have seen, uh, you know, huge, uh, use cases in retail, in manufacturing, uh, in, in, uh, in health that are helping also the, the communities and the end users, you know, to become much more, uh, I would say u the, the use of the, of the technology. It's helping them to become much more productive and more effective. And so, so we have clear examples in several countries.

Ingram, of course, has invested heavily in AI to take a lot of the friction out of the, the process of transactions and all of the things that's involved with that. Um, is that gonna play out with the partners and the partners also investing in AI on their side and the two together might, you know, create a, a channel that is friction free maybe, or something? Yeah, yeah, yeah.

No, absolutely, absolutely. You know, that we have been developing our platform, right? X vantage.

We have been already for over three years developing the, the platform, and every day we see more traction. We, right, we see the, the partners using it much more frequently, taking the advantage of all the data and all the insights that they could get out of the, out of the, out of the platform. Now, the platform is also helping us to become, to become much more proactive on bringing opportunities to the channel, right?

That we saw through the data, through all the analytics that the platform is giving us through all, all of these, uh, AI models that, uh, that the platform works with. Uh, it's creating, you know, a lot of, uh, opportunities that today, or that the customer that, that our partners weren't seeing, no, now they're seeing it because we are putting them on the table. We're telling them, okay, you, if you're selling this, a lot of customers that they sell this also sell this, so you should also explore, right?

Complimenting your offer with all these products or with all these solutions, or with all these services, right? So I think it's, it's getting traction. And on the other side, the customers are also seeing the benefit, the operational benefit of being, working with the platform today, right?

It's much more effective for them to devote time, you know, to the, to their relations and to the, you know, to the, uh, strategy development with us while the platform takes care of all the transactional piece, you know, so it's, it's, we are gaining traction every time. Mm-hmm. Historically, the best partners, I think, have built some sort of solution or something that differentiates with them, and a lot of times they work with you guys to kind of craft that.

I think AI is gonna drive that further and deeper, because I need something that is tailored specifically to a business process. So are you hearing more from the partners about collaborating with you guys to build some unique solutions? Absolutely.

Absolutely. You know, that we, we have basically all the, all our vendors solutions. So we promote all our vendors, ai, AI solutions, right?

So there's a stack of already I would say use cases, opportunities already there. Uh, but what we do with the customers is that we work together on the specific requirements of their customer, of the end users or, or the users, right? So collectively, we build solutions that are much more effective according to what the end user is requesting today.

So we have all these, uh, I would say processes and communication. We are all the time with, uh, trainings, we're working with trainings, we're working with seminars, right? In order to, to work with them.

And we also go with them to create demand, right? To generate demand without the end users. Like talking about all the opportunities that AI could bring to those companies.

So we are, it's, this is a, I would say an ongoing, an ongoing process. And obviously we start with those guys that we're already selling solutions, right? Because that's, I would say that those, those are the most feasible to, to start, like accomplishing or building that business model that could support the end users.

We of course, live in a global economy, and of course, times are interesting, but still we see more international cooperation, especially around IT solutions. How is that impacting the partners down in Latin America? Are they working more closely with vendors and partners around the world?

Absolutely. I mean, uh, we have examples in Latin America of countries that are really, are well advanced in the adoption of the technologies. One, a clear example is Brazil, right?

Brazil is one of our, I would say worldwide, one of our top subsidiaries on the adoption or selling on cloud and solutions. So we have huge partners in Brazil that deliver great solutions. So we took advantage of that also, to go and train and share best practices and also share those solutions to other countries.

So we're trying all, all the time to learn and to try to, you know, to export from those countries that have really good practices to export them to the rest of the, of the LATAM countries, and in some cases, to the world, because we have really good, um, and develop partners in, in, in our countries also. Are there partners in these various countries working with each other across borders to build solutions themselves? Ye yes.

And we are starting now to build our trust tax alliance community for Latin America, right? Where we want the customers or our partners to start in, uh, you know, uh, interacting between them through the region so they can, they can expand to other latitudes with their, with their solutions, but don't having to have, or having to have the full infrastructure based in those other countries, so they can go much more quickly or much more rapidly expanding their solutions to other countries. All right.

So we're coming up to the end of the year. You get your little crystal ball out. What's 2026 look like to you?

It's, I, I think 2026 is gonna be a bright year, right? The adoption continues, uh, the adoption and the necessity of te of technology continue, continue growing rapidly, right? We just saw all the trends and what I disease predict, predicting for, uh, for next year.

And we saw a huge growth, double digit growth, basically in everything, even in devices. The growth is not gonna be that high, but will start, will continue growing because the devices will be the base for the usage of the technology, right? At any, at any level.

So we, we still see, uh, all our, our technology and products with good trends of growth for the, for the following years. So that is exciting for us, right? So we just need to continue building and complementing all, all these solutions that could help us, you know, build a huge value proposition for the end users, right?

So that's, that's, I, I think that's what we're gonna be continue working on, right? All right. Hey, folks, like the man said, things are happening in Latin America, and I can't wait to see what you guys are doing this time next year.

Thank you, Mike. Thank you. Thank you.

And we'll be back in a minute. Hey guys, thanks for the throw. We're here with Todd Cassidy, who is managing vice president and divisional CIO for associate experience at Capital One, and we're talking about what it takes to build and foster a tech culture.

Todd, welcome to the show. Hi, Mike. It's great to be here with you.

You know, everybody in his brother who's in the tech sector, who's always trying to, uh, get the latest and greatest kind of thing and play with various toys. And, and so the attitude is, right, but how do you harness that in a way that's productive for the company? Because, well, there has to be something that gets generated at the end of the day, right?

Absolutely. Um, you know, I think it, our, our engineers crave the latest tools in the marketplace, and, and we really want to encourage them to take advantage of the evolving, you know, marketplace of tools that are out there. And, um, you know, I, I think a couple things really set this up for us.

Uh, capital One's investment, um, in our modern tech stack, I think really gives a, a nice, um, opportunity for our developers to use the latest technologies. We also work hard to maintain a open culture that fosters collaboration and encourages innovative ideas to solving problems. We think innovation really thrives when associates feel supported and have room to explore ideas.

And that's really where we, we emphasize collaboration. Knowledge sharing is celebrating experimentation. Um, our developer first culture, um, ensures that our team has the best tools and infrastructure to innovate at scale.

And there's really three programs I would, I would call out that we leverage to inspire innovation inside the company. Um, the first is we've had a lot of focus on patent innovations and, um, in recent years we've, we've been at the leaderboard for the number of patents granted each year and have over 6,000 US patents to date. Um, we also have a recognition program internally, uh, that we call Tech Excellence, uh, which is designed to recognize and reward contributions of our technology teams.

Um, w we publicly share the winners across the company quarterly, and then those quarterly winners compete for our annual CIO Elite Award. Um, and the recognition that comes along with this is also showcases what accomplishments the team has and, and shares that broadly. Um, lastly, uh, the one thing I would call out here is we also have an internal conference, um, that allows our teams to demo innovations that they have with the rest of the company.

Um, this in, uh, this is an annual conference that we do internally with keynote speakers and curated demos from teams, um, across the company that allow us, uh, allows us to share that innovation broadly and, and, you know, create reuse and, and celebrate those accomplishments. When the developer first culture, how do you strike a balance between, I guess, what we'll call operational excellence and standardization, and the fact that the developers want to be able to play with whatever tool they find and do something? That's a great question.

Um, certainly we have a big focus on being well managed and resiliency of our infrastructure. Um, but we also recognize that technology advances quickly and our, you know, developers want to work on the latest technologies and apply that to the business problems they have. And I think there's a number of factors that, that we have in place that support this.

First is, uh, we, we have a continuous learning culture, and, um, I think that just encourages our associates to continue to evolve their skills, um, to support that. We have an, what we call tech college. It's an internal learning platform that allows, um, both self-paced as well as instructor led training that our associates are encouraged to leverage for upskilling.

Um, uh, we also provide our associates with leading industry tools, um, particularly coding assistant tools is, is a hot theme, uh, right now. And we really want to, you know, create time for our developers to experiment and learn these tools and then apply them to, as I mentioned, our modern tech stack. And we have really challenging business problems to apply these new skills towards and take advantage, advantage of the new tools.

Um, you know, as an example of this, when we were an early adopter of, uh, Amazon workspaces, um, I'm sorry, AWS um, sorry, I had my other hat on for, for other aspects of my, of my role. But as we proceeded that migration to the public cloud with AWS, we had a big focus on, uh, training our associates about AWS. And so we had AWS certification initiatives really to help raise the water level, because public cloud was not something that we were in before that.

And so we wanted all of our associates to learn that. Um, what I would say is, in my experience, when you, when you provide developers with a continuous learning environment or in culture, um, industry leading tools, time to experiment with them and learn them a modern tech stack to apply them to, and then creative business challenges to, uh, solve using those tools, I just think amazing things happen when those things come together. You hear the phrase platform engineering a lot these days, and it's all about kind of work making or providing at least a better developer experience.

But I can't help but wonder, were you guys kind of doing that all along and you kind of woke up one morning and said, well, it's nice that somebody put a name to it, but that's kind of the way we operate. Yes. I, I do, I do think, I would say we, we've always had a focus on this.

I think, uh, you know, one morning that we've had is we've moved from data centers to being in the public cloud, is our developers had to take on the role of full stack engineering, including, you know, the, the infrastructure parts with the public cloud, that includes vulnerability management, some run the engine went up. And so as we reflect on that, we're really focused on automating as much of that as possible so that our developers can spend their time on the most important aspects of creative problem solving and innovating, um, on top of that versus the kind of rote tasks that kind of, kind of come along with managing, um, that. And so the, the more that we can kind of peel away at tasks that are not really necessary for our developers to focus on, um, is a big area of, of, um, of focus for us right now.

Mm-hmm. Do you think maybe, you know, early on with Full Stack, we were all talking about shift left, and I wonder maybe if we shifted too much left and the developers got too much cognitive load and now we're trying to swing the pendulum back to something in the middle. I, well, I guess my perspective was, or is that I do think we shifted left and probably shifted left before we had some of the tooling in place that takes some of the burden off of the developers at as we shifted.

Um, I personally still really like the full stack, um, um, accountability that comes along with that, and the capability that comes along with that. You know, if I went back to, um, you know, our data center days, our developers were frustrated that they often had to wait for infrastructure to be ready for them in order to, um, you know, begin their project. If they needed a server and, and we didn't have that capacity, then that might need to be ordered and then be racked and stacked before they could even begin their project today.

Within minutes, they can spin up new environments and, and really take control. And just our speed to market has, um, advanced dramatically. I would also say our re the resiliency of the solutions we put in place has, uh, also dramatically increased.

Um, with that said, though, I, I think the, the focus we have around the automation around some of those aspects and just taking some of that burden off of their workload is, is, uh, key to where we're headed. Of course, you can't walk down the street these days without somebody leaping out to tell you about their great new AI thing. But what are you guys doing with AI as it relates to software engineering?

So we, we have, um, a number of, you know, large initiatives across the company on ai. And I think Capital One's investment in our modern tech stack and our data ecosystem, along with the strength of our AI specific talent, I think really dispositions us to be at the forefront of leveraging ai. We have a number of initiatives internally, um, where we are building our own LLMs and, and applying that in different ways across the company.

Um, I, I think, you know, all, all, you know, we're also providing a lot of, uh, you know, commercially available products for our associates, particularly coding assistance as well as Gemini, um, Google Gemini, which we rolled out across the enterprise this year, not just for our technology organization, but for the entire organization. And we intend to have that in the hands of all associates by year end. Um, I think, you know, there's a common theme here across these, these tools.

We're gonna be building things internally ourselves. We're also gonna use commercial products and, and roll those out to our associates. But I think empowering them to learn and get the most value out of those tools is gonna be a bit of a journey.

Um, so far we, we've, uh, you know, we're allowing a lot of experimentation, um, but I think that there's more we can be doing in, in, in are tending to do, to really help our, as associates take the, take the most and get them, you know, get the most value out of these tools. As we look ahead. I think one of the issues that people are wrestling with is, we're clearly generating more code, but more code doesn't necessarily translate directly into more applications being deployed, because a lot of that code needs to be reviewed, and there's a lot of other processes.

So how do you kind of go in and start looking at some of the bottlenecks in the process, and how do you think about eliminating those? I think it all comes down to automation. Um, you know, we, we have objectives to automate testing, um, to where we don't do any manual testing before deployment to where we can get to a place to where we're doing, uh, continuous deployment, um, across the environment.

And I, I think that will be a big unlock for us now, clearly, um, the, the resiliency of our solutions and, and making sure that we don't have disruption as we have change is gonna be important. I would say that we, we've been on a really incredible journey of, of just the resiliency of our solutions, I'll say cloud-based, you know, advantages, uh, play out pretty big here in what we've seen from a resiliency perspective in recent years. And we we're really proceed, we're performing right now at all time lows as a company in terms of, you know, you know, technology outages and disruption.

Um, and what's pretty amazing about that is we've had a pretty robust, um, you know, technology agenda as we've been transforming our tech stack, moving to the public cloud, and a number of other things that we've been doing as we've made that shift. And our number of releases has continued to rise dramatically. Um, our number of incidents has decreased dramatically along that same time period, which I think just shows our balanced per, you know, a balanced approach from wanting to be more productive, but also doing that in a well-managed way.

Mm-hmm. I don't think it's much of a secret that occasionally developers and the centralized IT team don't always get along. So how did you, you know, bring together these two disparate cultures in a way that kind of gets them to work together cohesively short of, uh, maybe locking everybody in a room till they see since?

Yeah. Um, you know, I have, uh, I've been with Capital One for a long time, and I've worked in all different areas of the company from our, our card business to some of our enterprise technology functions. And, um, I just think our collaborative culture and, um, having shared goals across teams, I don't see major issues.

Um, with this. Now, I will say it was a bit more challenging when we had a separate infrastructure team that was managing data centers from, you know, the ability of what comes with public cloud. It just allows a lot less dependencies across teams as the, you know, the full stack developers have control of their infrastructure through the public cloud.

And, and it minimizes some of that, but, but your question's a good one. I think, you know, clearly there's still gonna be dependencies, um, across many of our horizontal functions, whether it's with cyber or network. Um, you know, the team that I, I lead our associate experience team and others that partner closely, um, with those, with, um, you know, our, our customer focused, uh, teams across the, the company.

So ultimately, what's your best advice for your fellow CIOs when it comes to dealing with developers? Well, you know, we, we believe that attracting and growing talent is the most important role, um, that our technology leaders have. And I think from a, uh, attraction perspective, you know, or sorry, from attracting developers to our, to our environment, we look for builders, people that are naturally curious and, and passionate about solving problems with technology.

Um, and, you know, technical skills matter, but we also look for creative problem solvers and adaptability and a learning mindset. And once those engineers join, we invest heavily in their growth, um, through a bunch of different things from structured learning programs, mentorships, internal events, great assignments, um, and rotational experiences, which are really intended to expand impact and growth. Um, you know, from a, um, how we continue to grow our associates, I think there's also a bunch of factors that come together from, um, creating a, a, a learning, uh, a continuous learning environment, I think is critical.

Um, I think setting an example of that and encouraging that, whether it's through, you know, an internal tech college like we have or other mechanisms, um, we also provide our associates with, as I mentioned, industry leading tools and time to learn and experiment. Um, which I think is, is, is really important I think in my experience. When you provide developers with a culture that's, you know, pivots around continuous learning, industry, leading tools, time to experiment and learn a modern tech stack and challenging business problems, just amazing things happen when those things come together.

Um, folks, you're hearing it here when it comes to software development and developers in any age, there's no substitute for a good culture. Hey, Todd, thanks for being on the show. Thanks, Mike.

It was great to be with you. All Right, and back to you guys in the studio. Everybody's trying to figure out how AI fits into the political, social, uh, individual.

And of course, it landscape, people are trying to get out ahead of it. Uh, people are, some people are trying to step out of the way and, and see what develops. That's what we're talking about on this episode of utilizing ai.

Welcome to utilizing ai, the podcast focused on practical applications of artificial intelligence from the Futurum group. Each episode brings together a diverse perspectives to explore news and use cases in the way in which AI is transforming enterprise IT and the industries it serves. I'm your host, Stephen Foskett, president of the Tech Field, a business unit here at the RUM Group.

Before we dive into the discussion, let's meet who's on the panel today. Hi, I'm Nick Patience on the AI Practice lead, um, at Futurum Research. Hey everybody.

I'm Mike Baard, chief Content Officer for the Textron Group when we publish Textron AI among other things. Absolutely. And, um, you know, Mike, uh, you and I are on the Textron Gang quite often talking about, uh, news and what's going on in the industry.

Um, and of course, AI is just everywhere. It's become, uh, front page news for basically everything that's happening in the world today. Uh, Nick, uh, let's kick things off by talking a little bit about the ways in which governments are trying to get involved in ai.

Sure, yeah. I think it's been apparent, um, for a long time that AI will be a regulated industry of some, uh, uh, to some extent, to a large extent or another. It already is in, in, obviously in in China, uh, to a much greater extent.

But one thing that kind of caught my eye, um, was, uh, sort of talk here in, in Europe, uh, I'm in London, but you know, we still consider ourselves part of Europe, um, that the, um, European Commission is thinking of watering down somewhat. The EU AI Act, which has already passed, hasn't been fully implemented in every, every, uh, every country yet, or all the 27 countries. But they're talking about that.

And it, you know, there was a story, I think it was in the FT originally, and there were, there was saying about, you know, the commissions come under a bit of pressure from big tech companies, um, not surprisingly. Um, and they're talking about having grace year long grace periods before certain aspects have to be, uh, implemented. Those you, you may remember, it has a kind of, um, a risk hierarchy of like, you know, unacceptable risk, high risk, medium risk, low risk types of, uh, applications, and low risk would be spam filters.

So everybody uses it, no problem at all. High risk and things like that would be, um, you know, facial recognition and unacceptable risk things, facial recognition. So it's, it's an interesting if that's, if that's gonna happen.

I mean, there's been a lot of talk over the years when the EU was trying to figure this out, that they were trying to, um, put the cart before the horse somewhat and regulate something that hadn't come out yet. In fact, just before they, they passed it, um, you know, or they were, they were negotiating chat, GPT came out, and that caused 'em then to rewrite drafts. Um, you know, we've better to get this, this generative AI stuff in there.

Um, and so they were trying to react to that. And now of course, you know, we've got agentic coming up, uh, and, and those kind of things. But if for enterprises, for those that, you know, this is utilizing ai, so it's, you know, it, it could be relatively good news.

Uh, and obviously this is not just EU headquartered companies. This is companies doing business within the eu. Um, so it could help them, it could, you know, could help enterprises, you know, reduce their, uh, immediate term compliance needs and compliance costs, uh, and things like that.

So it's a, it's something we'll, uh, I'll certainly, uh, be keeping my eye on because, you know, compliance and sovereignty and, and all these kind of things are, are really, really key issues in ai. You know, I'm having a hard time wrapping my head around this whole thing, and I'm hoping you can gimme some insights here, because on this side of the pond, it kind of looks like, well, you know, the EU for some folks was gonna save us from ourselves and institute all these rules, but there's also people who say maybe there is a legitimate case being made here for not having so many prescriptive rules so early. And other folks, of course would say, you know, those folks in Brussels will just overregulate everything, and they're basically gonna be like, you know, just standing in the way.

So what is the mood over there? I think the, you know, especially in, you know, I may be in London, but especially in continental Europe, it is quite a fundamentally different way of looking at things, um, and certainly on the data privacy issues. So that's why obviously GDPR, which came into a, that came into, um, effect in 2018, um, yeah, those kind of data privacy issues, privacy, privacy, call it what you will, um, is extremely embedded in the culture.

And so it, it does seem a little bit, um, weird, I think to, to, to, to folks in North America that, that kind of obsession. But, you know, these things go back with a, a long and a somewhat troubled history. But, uh, I think it's, you know, I think there is a, certainly a case to be saying they were trying to, they were, you know, as I said, what the cart before the horse, the flip side of saying that is, I think there was a 75 year gap between the Model T Ford, um, the first model T Fords being shipped and seat belts being mandatory in the us, you know, and obviously hundreds of thousands of people died in car accidents between, you know, the, the first and the second thing.

This is not the same thing. You know, I'm definitely not on the kind of, um, munging, um, AI is gonna kill us all, um, side of the argument. I think there is certainly though, um, you know, data privacy issues that are look completely legitimate about, um, about, you know what, it's not so much what companies collect because I think people that kind of cats out the bag.

It's, it's whether the government can have access through back doors, um, you know, to your, to, to your data. And I think that we're seeing, we're seeing a lot of, uh, issues with that, you know, in here in the UK with Apple, um, you know, and, and the government, you know, haven't negotiating with them on that. Um, but the, but the, uh, the EU act is, is pretty, is pretty broad, and to say it's very sort of risk focused.

Well, the, on the GDPR front, that's a really interesting point that Mike makes though. Um, how do they square that on that side of the pond, uh, with all of the intense data collection that's gone into the building of these AI models and the kind of data collection that's gonna be feeding these AI applications in the future. Um, are they expected to, uh, abide by GDPR rules?

Or is it sort of like a, eh, well accept ai, I think accept? Yeah, I mean, LLMs and, and how they vacuum up stuff on the web. I, I guess a lot of that doesn't really count as, um, data that's private.

So, you know, vacuuming up publicly available data is, is, uh, is not really covered by it. Um, and so I think it's from that point of view, while some people worry about it, um, it's also quite difficult to figure out obviously, what the training sets were or are because, um, yeah, the companies are not exactly particularly transparent in, in, in what they're doing. Um, so I think it's, I think that doesn't, the LLM kind of aspect how LLMs were built originally, um, isn't so much of a, of a, of A-G-D-P-R issue.

Um, but, but yeah, it's certainly, and there hasn't been, let's face it, a huge amount of massive, um, cases. Yeah, it hasn't been all these kind of, because obviously there's, there's, uh, revenue, there's, you, you can be fined up to a certain percentage of revenue, and there hasn't been these kind of, you know, 300, 400 billion Euro fines, um, um, administered. So you could argue that, um, you could argue that it's doing its job because it has now, or you could argue that it wasn't quite as needed as, um, as some in, uh, Europe thought it might be.

Yeah, it's pretty surprising really that there hasn't been more cases, because of course, people have, um, legitimate concerns about the kind of data that, uh, AI is, is vacuuming up. But I guess, uh, that kind of leads to this whole question. Is AI a different animal from all other IT applications, or is this just a wild west still that hasn't been regulated?

Um, do, do you think that AI is, um, fundamentally a different animal and needs different types of supervision? I think the, if you kind of contrast to something like, you know, just a relational database, um, that's obviously, you know, where a lot of this data is stored. We don't have, um, relational database legislation.

Uh, but that's, but that's partly because that's a very, um, you know, that takes humans to put the stuff in there. It's structured and, you know, and findable, et cetera, et cetera. I think there is something a bit different about AI in the sense that it's, um, you know, it's obviously, you know, if you think about the phrase machine learning, it learns, it adapts, it evolves.

And that's where, you know, the, that's where the difference comes. So we've gone from kind of, um, you know, just sort of predictive models that, that they're gonna predict an outcome, um, based on a kind of fixed data set to things that are evolving using enormous, um, training sets that, you know, we're not sure what's in them. And so, you know, and as they change and, and evolve and models drift and model decay, you know, I think it then becomes issues around explainability become very hard.

You know, how can you sit across from your, if you are, you know, if you're a bank, how can you sit across from your regulator and explain exactly how every single uh, decision that you are you are using AI for was made? You can't. Um, so I think it, I think it is, I think it is different.

The volumes of data are just, just so much larger, um, than, than anything else. And I think it's just been evolving as we've gone from machine learning predictive models to generative AI to, you know, eventually agent, um, and things like that. So I think, I think it is a bit, it is a bit different.

I mean, you haven't had kind of, um, you know, I mean, you have regulations around search engines, but not for the reasons of, you know, necessarily, you know, what they're sucking in. It's more like yeah, monopolies and, and things like that. I think the regulations may play out a little bit differently too, rather than having some overarching set of rules, I think you're gonna see, like the regulations that apply to various vertical industries will get tightened around ai, and we'll see extensions to whatever rules we have in place for finance, whatever rules we have for healthcare, as those people get a better understanding of how AI is applied.

And that may be more effective ultimately, because each vertical use case is different anyway. Yeah, yeah. But it, it's interesting to think though that, um, you know, for example, in the copyright world, um, there's been a lot of trouble with, uh, generative ai, um, violating copyright on a wide scale, essentially being able to regurgitate, I don't remember what the, what it was, it was like 87% of Harry Potter or something like that when prompted to, and I've seen similar situations where it has, um, generated, um, specific photos from, um, you know, registered photos from photographers and things like that.

Um, if given the right prompts, so that data is in there. Um, I wonder if there's personally identifiable information that it could be coerced into, uh, spitting out, even though, uh, Nick, as you say it, it's theoretically only been trained on public data, but, uh, I think maybe some of our readers might be yelling, or listeners may be yelling at their phone right now to say, no, it's not just public data, because I think people have a suspicion that it goes well beyond what it should have been trained on. Yeah, I think people also are, um, amazingly willing to put public information on the, on the, on the web about themselves.

So, I mean, this is not just sort of LinkedIn things, but, but o but other things that, that, you know, you could piece together. So I think it's, uh, yeah, I think, I think you're right. The copyright stuff is interesting.

Obviously they've, there's been a lot, bunch of lawsuits and, and there's been some settled, um, for, for publishers, you know, when, when these, some of the, the, the early, um, LLMs vacuumed up, um, you know, hundreds of thousands of books, um, which are, you know, some were under copyright, some weren't. Um, but, uh, yeah, and there's been some settlements in, in that regard, and you've seen all the, the big publishing companies, you know, you know, New York Times and BBC and all this have kind of agreements, um, with, with some of these LMS that they can or cannot, uh, use their, use their data for the purposes of training. So I think it was, it was very much in the early days.

By the early days, we of course mean, uh, just under three years ago, um, you know, extremely wild west, like, and then, you know, within a few months it, um, there was, there was some, you know, uh, some, some, some, some agreements put in place, but they're very much kind of one-on-one. You know, this is not, you know, legislation, um, uh, based, this is just, uh, you know, companies settling or, or not, as the case may be. I don't know how feasible it is, but I always thought about it this way.

I mean, they may have the data, but the issue in my mind at least is that they enable people to use the prompts to tease that data out. So if we were better at maybe putting the guardrails in place around the prompts so that people couldn't tease out Harry Potter, then maybe we wouldn't have a crime in the first place, right? Yeah.

I mean, that's unfor Yeah, that's easier said than done. Yeah. Yeah.

I think it's kind of, because the generative AI has fundamentally changes the nature of security cybersecurity, doesn't it? Because you can't, um, whereas previously with machine learning, uh, you, you could control the input because the input was, you know, your bank, you know, what the input into it is gonna be. And there's no point with a kind of a decision tree chat bot and trying to manipulate it into, say, into swearing or saying something, you know, nasty.

Because all it'll do is, you know, do you know your account number, date of birth, et cetera, et cetera. It's not gonna tell you anything else. Not gonna tell you Harry Potter, it's no point.

And, but now with generative AI in the, in the chat box, you know, you can't, you know, as the owner of it, you can't really control the input. People will, will, you know, put prompts in, um, you know, with, you know, trying to trick the things and, and put code in there and stuff like that. And then of course, you can't control the output so much.

So it does change the, you know, the threat vectors as, uh, cybersecurity professionals, uh, like to say, which I guess begs the question, is AI going to be an IT application or is it going to be, again, back to my original set, is this thing a d fundamentally different animal than the other types of applications and, and data s sources that we've relied on in IT for, for many years? Do you see it differently? I see it in this regard.

Um, and people are talking about that here in Atlanta, CubeCon, but there's a difference between training and inference, right? And there's training, that is one thing. And then the inference side of it seems to be moving back towards IT as a deployment model, and they're managing the infrastructure.

And Nick, I don't know if you see it differently, but in my mind, a lot of this sovereign cloud conversation that's happening in Europe is very much tied to the fact that these AI workloads need to be centrally managed, secured, and protected. And all of this seems to me, screams we need some adult supervision from the IT folks. Yeah, I think it's, it's interesting as to whether it's different.

Uh, I think the, I think there's certainly shiftings, uh, there's been shifts happening, uh, towards the, the, the buyer changing, obviously as, as there used to be. I didn't like the cliche of every company becoming a technology company a few years ago. I thought it was way overblown.

Um, but I don't really think it is anymore because I think, I think, uh, you know, any, any sizable company, um, everybody has the ability to, to use, uh, gen ai. Obviously there's com you know, certain things are locked down, um, but they've got other, other devices connected to the internet, um, that can, couldn't do things. And I think, but I think the, you know, the kind of vibe coding shift, no code tools and things like that, um, and obviously the gen AI coding tools enable, you know, so many people to be able to, you know, develop a small app, micro apps and things like that.

I think it is shifting the buyer pattern. Um, so we are getting more line of businesses, uh, involved your line of business people, by which we mean, I always, again, it's a funny expression. It means everybody other than the IT department.

So in most companies, that's, that's virtually everybody. And so you're getting, yeah, many, many, many more inputs into it. Um, certainly in the early days of, of Gen ai and now in the early days of agen ai, you're getting those people who are driving the experimentation.

The issue comes is when we move from experimentation to implementation, and that's where, um, I think it, um, you know, sort of pulls everything back in to a certain extent. It doesn't matter if it's in cloud, on-prem, hybrid, anything, um, and, um, and, and get and gets heavily involved. So I don't think it's, um, you know, like that famous, uh, essay that was wrong 20 years ago, 20 plus years ago.

It doesn't matter. I don't think that's that's the case at all. But I do think there's gonna be many more people involved in the kind of, um, you know, the top of the funnel stuff in terms of the buying, the buying patterns.

I, I think one of the biggest challenges with AI is just, you know, it is a very different type of application. Um, it, it works very differently from the way that it is useful. It tends to be very reductionist in its thinking.

It tends to say, you know, here's the data, here's the network, here's the servers, here's the application. You know, really lining things up along conventional ways. I don't know that AI applications really align nicely to that old way of thinking.

I mean, in many ways it's very similar to the transition to personal computers, the transition to mobile, the transition to cloud to, um, as a service. You know, AI just takes that to another level in terms of, um, we don't really know what it is. We don't know really know where it is.

We don't really know what data it's using, maybe. Um, and that makes it, I guess, a little less amenable to the conventional IT mindset Maybe. But I would argue that a lot of these, you know, business apps that are gonna be built by end users using natural language will suffer the same issues we saw with low code, no code, right?

We're gonna get a lot of ugly applications, they're gonna be insecure and they won't scale, and that's when they're gonna call for the IT folks. So IT folks, then they're gonna show up and say, well, here's how you build this. So I, I don't, maybe they're not, Somebody's gonna know how to screw these things together and, and, you know, not gonna be the business units.

There's gonna be, but there's gonna be a whole beautiful agent orchestration layer that we just haven't seen yet. Um, certainly a load of load of, uh, every vendor of any size is coming out with those kind of things. Um, which is, I mean, I guess, you know, I, I, I know what you mean.

I think the, the ENT stuff, if it does come off is, uh, again, a shift. And when these kind of shifts happen, um, it, it's like, it's not like everybody, everybody stops what they're doing before and moves to the new thing. It is, it is an evolution.

Um, and I think it would be, it'd be chur, it'd be foolish of us to kind of think that, you know, the, you know, the EGEN stuff is not gonna happen to some degree or another. This is not robotic process automation where you wrote a script, um, but a human wrote a script and just tell a computer to go off and just keep doing the same thing over and over again. This is where, you know, with, with, with agents, um, which I think there definitely will have to be, um, orchestration frameworks, which will have to be sanctioned by it.

And that will happen because yeah, if you think it's, if you think it's kind of scary, um, having users type type things, imagine if you've got other applications deciding whether our applications, what to build and building their own applications. And, you know, you kind of got the, uh, the ultimate, um, insider threat, um, yeah, from a cybersecurity point of view. So I think, yeah, I think it, um, yeah, it will always be around and always be a role for it.

I think the, it's just, uh, I think there's a lot, yeah, just expanding the footprint of people who, um, consider themselves users of, uh, of, of, of technology in some cases fairly advanced technology. And I liken it to, you know, I could diagnose my own issues, right? And I'm using chat GT to figure out what's ailing me, but I'm probably better off if I get a professional to tell me to.

Yeah, I had an interesting conversation, uh, last week with a company, uh, Sefo AI about how they're trying to do agentic applications. And, and their idea was that instead of using a conventional approach, um, you know, or instead of trying to build prompt engineering that we would use runbooks essentially document, uh, the, the, the state document, the process, document what you're trying to get out of it, throw that into the, uh, AI model and see what the AI model can build that achieves your goals. I, I felt like that was actually a pretty interesting insight, not because it was such a novel approach.

I mean, we've been using runbooks in it for decades, but because it actually kind of meets the users where they are and where they need to be in terms of interacting with these applications. Um, do, do you think that, uh, that signals that AI is not going to be an it, a conventional IT application? I certainly think if that kind of stuff comes past, and you, and you're right, obviously in IT itself, we've been doing it and Red Hat with Ansible is a good example, um, and how they've added AI to Ansible runbook and they've done doing interesting only to say within that domain, I think.

I think yes. I think there will be, um, if you mean now, are there gonna be ways that people using natural language will be able to describe what they want and have something get built and go off and do it? Yeah, I think there will be, and I think, but there'll obviously be guardrails where you hope there would be, um, that says, you know, you know, I'm, you know, almost effectively, I'm sorry, Dave, I can't do that.

Um, but it's, but it's gonna be, those, those kind of things are, are, are gonna be in play. But I think, yeah, I think it opens up, I think no code has opens up the, the i the idea of building apps to, to so many other people. No code has been a bit of a disappointment.

But I think this is slightly different, you know, with natural language interfaces. I'm not sure the runbook is the right means for managing all this in the future. And, and I say this because the application environments themselves are gonna be much more dynamic.

They're gonna be a lot more applications built, and they're gonna be updated more frequently. And I think the runbook is a little bit of a more of a static concept. So I'm wondering at some point, you know, I it will be AI agents, I'm just not sure they're gonna be invoking some sort of runbook that a human created as much as maybe there's some other means for managing it that is equally dynamic as the environment.

Well, you've been in this space forever, uh, and you're there at CubeCon, you know, you're looking at all this cloud native stuff. Um, what do you think, um, I, I know it's probably too much to ask, you know, what's the answer, man? What, what do you think of the direction that, uh, the IT industry is heading in terms of getting their hands around this?

I think everybody is betting heavily on AI agents being able, providing the ability to scale. 'cause part of our issue has always been we didn't have enough people to manage the applications, so we didn't deploy as many as we might have possibly could. And everybody's got this huge backlog of applications they theoretically wanna build and deploy.

But the, the limiting factor has always been, well, where do I get the software engineers and the IT people to manage all this? So if we can manage all this stuff at scale using AI agents, that will be great. I just don't think we should abandon first principles of good software engineering because we have a bunch of AI agents out there.

I think we need to think that through, make sure those AI agents are trained and AI agents are voracious and they will do things, you know, unless you specifically tell them not to. And if that's the case, then somebody's gotta sit there and orchestrate and manage and, you know, take care of this army of AI agents. So I just think the future of it is, you know, humans plus AI agents, and there may be thousands of those AI agents, but it requires somebody who actually understands what the objective is of the army.

Yeah, I think it's, I think you're right, Mike. I think there's no, there's, uh, it's more important than ever to not abandon the, the, the, the principles of software engineering. I think it's, uh, because of, because of the kind of force multiplier effect of all this, of agents calling agents, calling agents, you, you know, there has to be, you know, that that kind of, uh, discipline in place otherwise, you know, truly chaos, uh, will reign As one wag one said to me, you know, it's one thing to be wrong.

It's another thing to be wrong at scale. Well, and that's, that's, you know, kind of bring this conversation around full circle then, um, you know, I guess the question is, do we want to risk getting our cart in front of the horse like the EU may have done with their AI regulations? Do we want to be very, uh, reactive like it has often been in the past?

And, um, or, or do we wanna somehow strike a balance in terms of getting our hands around the growth of this technology and, and what does that mean to business users? So, uh, that's a lot. Um, Mike, what do you think?

Do we wanna get in, get out? Should it get out in front of this? Or is the eu, did they make a mistake by trying to get out in front of it before chat GPT was even launched?

Yeah, I think there's a big cultural divide here that you're poking at, right? Because over in the valley that they'll say things like, go fast and break things, but you know, they don't actually manage and do anything. They're just providing the tech.

And for folks who are, um, you know, I'll just put a, a, you know, a small little simple example in place, but, you know, if you're manufacturing yogurt and suddenly the AI is making, you know, 50,000 gallons of yogurt that you got no place to ship to, it's a problem. And I don't think people will wanna see that. And I think business leaders are gonna be one saying, you know, well, hold on there folks.

You know, this is real money we're talking About. Yeah. I think even though AI is, um, is a general purpose, technology like electricity is or was, is certainly does, I think it's, I think it's, um, it will have to come under the purview.

You know, again, we always make mistake done with every time there's a new wave of, oh, we gotta get some of that new wave, rather than what is the problem you're trying to solve and work back to backwards towards the technology? It happens every, every single time. Um, you happen with cloud happened, mobile happened, happened with Java in the nineties.

Um, and so I think, um, and now look at that, you know, you can consider a lot of these things like Java and cloud and mobile, just, just table stakes. And I think AI will get like that. I do think that, um, there is an old joke in ai, and I, I may even used it before on this podcast, that, you know, the AI is whatever hasn't been invented yet.

And so people, you know, there's a kind of, you know, you, you have a problem to solve, use ai, and, and, and then it gets implemented, rolled out and becomes commonplace. And everybody goes, that's not ai, that's just software. Or, well, well, it is still, but you just don't think it like that.

And then AI is trying to solve the next problem along. So I think it is, um, I think we're gonna see a, you know, a long, um, you know, evolution and constant, um, you know, and constant, uh, innovation, um, for, for, you know, decades to come, I think. But it will have to serve, serve the business, otherwise, um, it won't, it won't be much use to anybody.

I'm laughing to myself 'cause now I'm remembering the days when Wang Labs referred to document processing instead, it was ai, right? Yeah. Technology is, uh, anything that was invented since you were born?

Uh, I've heard that one. Um, yeah, it, well, I, I will say too that I suspect in answer to kind of this whole question, I suspect that there's going to be sort of a bifurcation in terms from governments, from companies, from consumers, and, um, you know, each of us individually, uh, some of us are gonna try to get out ahead of it and stand in the way. Some of us are gonna be, take a very passive approach.

Uh, some of us are going to adopt aggressively, some of us are going to adopt conservatively. And, uh, ultimately I think that what's gonna win the day is the practical benefits that we get from this technology or not, and that will spell whether this is going to have the impact that we expect it will. Uh, I think that's a theme that we've heard, uh, uh, the, each of the episodes so far of, uh, utilizing ai.

And I suspect that we're gonna continue to hear that, that, you know, really at the end of the day, um, I, I was, I was talking to Daniel Newman this morning, and, uh, one of the things that he and I were talking about was the fact that ultimately, um, the success is it's, is is the barometer of success. In other words, ultimately if you're selling, if uh, customers are buying what you're selling, then you know, you have a success. And there's really no other metric for success beyond success.

And that's, I think, gonna spell what's gonna happen with AI as well. I think there's different forms of ai. When I think about gen AI in particular, I, I kind of think you should work backwards from the business process.

So if the process itself needs to be done the same way every time, then maybe it doesn't lend itself to Gen ai, which never does anything the same way twice. But if the thing is, you know, I don't know, creating a marketing newsletter or something where it doesn't really matter if it's done the same way every time, then gen AI might be perfect. And I think there's a spectrum of those things and people need to kind of sit down and figure it out.

Yeah, exactly right. Um, Mike, there's, you know, hallucination might, might have, might get a bad name, but in, in creative amongst creative professionals, that's exactly what you want. Um, you know, so, so you want it to hallucinate if you say, if you're doing, um, you know, marketing collateral, but you also want to, if you just want to resize, um, 50 bits of marketing collateral to 50 different sizes, so they, they work differently in format, you don't need a whole load of creativity in that process.

You just want it to be correct. And so, yeah, I think there's, there's gonna be, um, yeah, there's gonna, there's gonna be, you know, use cases for all kinds of AI and, um, obviously non-AI technology And the, and the risk level on that newsletter going out being wrong is minimal. Right?

I might be embarrassed. Well, thanks a lot. Not gonna, what the company's not gonna go under, you know what I'm saying?

Uh, thanks a lot for joining us on this episode of utilizing ai. Uh, Nick, it's great to see you again. Uh, Mike, welcome to this, uh, exciting little circus here that we're gonna be doing every Wednesday for our listeners, uh, before we go, Mike, um, give us a little pitch.

Where can we continue the conversation with you and where can people find your content? ai, and that website is also one of a series. com cloud native now, security Boulevard, and we also have, uh, tech drawing it.

And they all have an amazing amount of AI content because well, AI's everywhere And Nick. Sure. Yeah.

com. Um, you can find me on, uh, Twitter X at, at nick patients. Um, and so yeah, we're con constantly looking at this space and, and updating all the research for our clients.

Yep. And as for me, uh, yeah, you'll find me at s Foskett on most social media networks. Um, I'm on Textron Gang pretty much every Tuesday, though, not this week because I was traveling.

And, uh, also of course, uh, you'll find me here at, uh, utilizing ai. Thanks everyone for listening to this episode of the Utilizing AI podcast. If you enjoyed this episode, uh, please let us know.

Drop us a line, uh, also maybe subscribe. You'll find us on YouTube or your favorite podcast application. Uh, this podcast is brought to you by the analysts and experts from the Futurum Group, where Insight meets ai.

For show notes and more episodes, head over to Textron ai, uh, the utilizing AI YouTube channel or textron's TV app. Thanks for listening and we will catch you next week. Hey everyone, we're in Brooklyn, you're watching Tech.

Hi everyone. Welcome to this edition of Textron Gang. As I mentioned, Mike and I are in Brooklyn, New York today for a kinda unique, uh, events.

The first of this kind I've gone to, it's called AI Native Defcon, and it's in a place called Industrial City in Brooklyn. And I gotta tell you, I love the vibe already, though it's early in the morning. Um, I think, I think there's a future for this.

I think this thing's got less. We'll give you more of a report, probably not today show maybe tomorrow or on air. But in the meantime, Textron gang stops for no one.

And we'll keep going today. Uh, let me introduce you to our gang. We have the men up north.

Chris Blas, a new gang member, and we'll ask him to introduce himself here in just a second. Sid next Sidd, welcome to the Gang Sidd. If you wouldn't mind, take, take 15, 30 seconds, give people a sense of, of who you are.

Sure. Thank you. Uh, appreciate the invite and glad to be here.

Uh, so I'm currently the president and CEO of, uh, of Techon. Teon is a, is an advisory and analyst firm advising clients in the area of cloud and AI infrastructure and AI software and trends. Uh, prior to me starting off my own, on my own, I was a vice president of research at, at Gardner, where I tracked the same, uh, coverage space.

And, uh, prior of that, I, I've spent my career as a practitioner at an executive positions at Cisco, Dell, EET, bell Labs, and did my own startup company for, for six and a half years, which I took to an exit. So my, my experience spans sort of practitioner research as well as being an analyst in the industry in those s Thank you and welcome to the game. And then lastly, least I'll, uh, and I always try to get her name right 'cause I keep trying Chaya Chaya gun.

Yes, Andy, I've been on the show for five times now. I know. And I messed up your name six times, but I keep char till I get it right.

Anyway, thank you. Good to be. Mm-hmm.

So Mike, we're gonna lead off today. You know, this is a big week. Nvidia has earnings on Wednesday.

So the market, and, you know, the market is in a bit of a, of a, of a share of not a shambles, but it's retracting. And people are saying Nvidia might be a big reason why, but they're, they're keeping, they're trying to keep pushing envelopes. They're pushing the boundaries of physics.

Yeah. There's a supercomputing conference in, uh, St. Louis this week and NVIDIA's there talking about these new models that they're creating that are all wrapped around physics and letting people do some very, uh, intense research at the atomic level, right?

And they're talking about simulations or fusion reactors and helping people build new materials. And as I kind of look at it, I mean, and I forgot one other thing. They also are creating interconnects between supercomputers based on GPUs and what are gonna be quantum computers.

And they're saying that these supercomputers that they have will essentially be the control plane for the quantum computing. And we'll see how that plays out. But it feels like, you know, rather than just kind of focusing in on the GPUs, I can't help but wonder if I look at this and say, cha, let's start with you.

Are, are we on the cusp of some sort of new golden age and science and research? 'cause it seems like all these projects that people are talking about are gonna lead to all kinds of innovations. I think I'm aligned in terms of their next step.

They do have the domain knowledge of the hardware. They do have the people who have worked on it. So it looks like they're taking the next step in the direction, coming up with their own model.

And I think one of the ideology that will help here is machine learning for machines. So think about it that the GPUs, that when built by them, if something goes wrong, the model understands where they can perform better and what are the bottlenecks and give more insight about it. So I think the data that they have collected over the years and building the infrastructure for it, they're going to use the same data set to train these models to come up with the right logistics, performance metrics and benchmark that they claim about it, which people have not even scaled yet because everybody's buying it, but nobody has scaled the GPO to up to that extent where they say Yes, it actually meets this many number of tokens that I wanted it.

So yes, I am very optimistic about it, um, in terms of model, but I, I also feel there are too many cooks in the kitchen now. So that's kind of where I lead others to kind of share my feedback on. I haven't tried the model myself, but that's what going to be in the next thing.

But, uh, if it's coming from Nvidia, it seems to be that they have the, I believe, would've thought about it and trained on the, in initial, uh, kind of trains for it. Yeah. Sy, do you want in here?

What's your thoughts? Yeah, so toons have been follow, uh, in NVIDIA's progress over time, obviously, but, uh, uh, as far as supercomputing is concerned, clearly, you know, the focus on quantum was something that, uh, was striking to me. Uh, but if I were to sort of summarize the takeaways, uh, you know, it's very clear that, you know, infrastructure is obviously advancing really fast, right?

The scale and ambition of systems when deployed with varied technologies, be it, you know, your traditional networking technologies with, with their spectrum announcement they made last, at end at the end, their own Nvidia, uh, event in DC a few weeks ago. And now with, uh, with Quantum, you know, things are really coming together and integration of quantum is real, right? That's the other takeaway I would highlight where you think like NVQ link shows ous entering infrastructure planning, so it's no longer a sort of research project in the labs of IBM and other places, right?

Um, so it's becoming more and more real. And then, uh, I heard one terminology that jumped at me that NVA talked Nvidia talked about, which is AI for science, right? So things like life sciences, climate materials, manufacturing, uh, you know, focus on those kinds of things.

So the high level narrative that jumped at me, I think we ought to track that as to what they're gonna be doing there. And then, you know, in, in terms of risks and governance, they talked about, you know, the whole quantum integration, quantum safe, the whole supply chain issues associated with quantum, the energy and thermal footprint, you know, the whole sustainability narrative is highly irrelevant as well. So those things jumped out at me.

So I think going forward, we wanna make sure you keep an eye on how NVQ link develop or deploys and develops over time, right? Tracks or the commercial aspects of these technologies, because oftentimes we hear companies like Nvidia and others talk about what's today on the truck, what they're gonna be doing in the future. But it's important to understand, you know, in the, what the future's going to hold for them to be making revenue out of their futures, right?

And then evaluate the software stack maturity they've already been in the market with, within lada, but with quantum SDKs, you know, what does it mean for the developer community and how do they build this thing through their whole ecosystem partner play? So those are the things I would highlight. You know, I I, protein folding sticks with me as I look at this era of ai, and it was a couple years ago, right?

You know, we basically solved the protein folding thing completely. And if you're just a general science nerd like me, this is one of those things where the possibility space is so enormous that in the past we've forecast, you know, taking the computers we have now and forecasting 'em forward, it's still 10 trillion years until we could possibly do it that way, and we're done. You know, protein folding is done.

Amazing, right? And as I've learned in the last year, more about specifically how these systems work, you know, LLMs and the, and everything we're talking about right now, you would think that if you didn't know much about it, if you think about the old way, the di digital way, we think that maybe it's vector math with GPUs or something is making it faster, and it's not, it's semantics, right? You know, because what those researchers basically did is they just asked the AI to do these things, right?

And what does that even mean? And we we're stuck in this debate space around this, but it's not that complicated, right? You're, you're, uh, uh, you're reducing the possibility space, you know, like a human, if you were talking to them and said, Hey, could you research this?

You know, they would say from this point, the likely things are this direction. And not try to, you know, at, at every step do every digital, digital pothole and the savings in time and energy are, hey, transformational. That's why this is, you know, such a big deal.

That's why, you know, to, you know, Helen and, and Sid, you know, uh, analysts like you, the business investments where people are putting the money right now, ah, I don't feel that comfortable about it, but the overall trend, yes. Because if you could speed up these things like protein folding, like physics research, not just by sheer CPU horsepower, but by semantically narrowing the space and sheer horsepower. Holy cow.

Exactly. I think, I think that's spot on. You know, I read an article in the Wall Street Journal on Friday about this guy, Jan Koon, who's a, a chief scientist at Meta, and he was a contemp labs, and he's talking about how the new world models not large language models, because LLMs are not grounded in physics.

So to your point, Chris, you know, pro about the protein fold, the analogy, right? Uh, world models are really going to be the next big thing because LLMs don't know basic, there is to sequence transaction, right? If A, then B, because they have a pattern of text and they do NLP and, and come up with the logical answer to a prompt, but there are no physics, they don't know things that, things like balls roll downhill or liquid spill, you know, unless such pattern actually appear in text, I think you're spot on in, in, in the Knowledge that that's very true.

Chris, let me, lemme get, so my, my take when I hear these things though is, you know, I, I'm gonna borrow a nursery right from the old lady who lives in the shoe. There was a company called Nvidia who invented the GPU. They had so much money they didn't know what to do.

Okay? When you're a $5 trillion company, you can't, and you wanna keep growing that market cap and, and pleasing the street, you can't be doing incremental growth. You gotta make some, you know, uh, deep passes, right?

Like Google did. Remember when Google was untouchable it, they controlled 99% of the, of the, of the search market. They were, they were printing money and they, they, they set up a bunch of Hail Mary's, right?

And some of them, like Google fiber, uh, you know, really civilization changing big things because you need that kind of stuff to get from 5 trillion to 10 trillion. It's not gonna be about selling a couple more GPUs. You've gotta invent game changing new markets.

And so kudos to them, not kuda, but something else. But kudos to them for doing this. But that's the game here.

They need to find where's my next $5 trillion market gonna be? And, and so that's what this is about. It might be protein fold in, it might be the, as Mike say, the control plane for quantum, right?

And this way they ride that quantum because, you know, hey, Google's live, they have the willow as the quantum chip or any one of these players are making, you know, that are working on quantum chips and qubits and so forth. But Nvidia is not gonna abandon that market. So they're, they're making a, a, you know, a bit of a Hail Mary there and a hail Mary here.

They don't need all of these to hit. They need one or two of them. And it's almost like the VC gig.

Yeah. I think Nvidia jump in, Nvidia is at an inflection point right now, because what you just said about their lineage, mean, how do Nvidia get into the AI business? It was an accidental discovery, right?

GPUs are basically designed with the purpose of accelerating computer graphics and image process and render pixels on a computer screen. Now that, that function requires the ability to multiply very large matrices, right? Turns out that Transformers, which is based on NLP and sequence transduction, also requires the ability to multiply large matrices.

So somebody came up with that, Hey, why don't you use GPUs for processing AI workloads? And, and then, and then we know, we know what happened thereafter. But I think as a company, Nvidia really ought to think about what is the, to your point, what is the next big thing, right?

Is it protein folding? Is it something else? You know, is it gonna be learning processing units?

So lpu versus GPUs, where these things are built for inferencing in customer environments for small language models. I think that's the, that's the challenge they are currently faced with. And it's almost like changing the engines of a 7 47 in flight, right?

And many large companies go through this inflection point 'cause of crossing the ca classic crossing chasm, right? So it remains to be seen how they sort of do both things at the same time and make money out of that, that, that transition, right? But Sid, let me ask you this question.

I do have one, like, Nvidia is one of the biggest players in the chip, right? There's no competition around it. Why can't they continue to work what they're good at it and scale and reduce the cost of chips and GPUs instead of a market already a multiplayer?

Correct. You're right. So they're gonna milk that as long as they can Go ahead.

No, you go, you go. So they're gonna milk that as, as long as they can. Obviously I would do that because that's bringing me revenue, right?

But, but they have to think about brand new architecture that's different from the GPU, right? If they don't, then there are others who wanna come into this. There's already a lot of development going on in pockets within the hyperscalers that are building their own, you know, specialized ships that they're not even, that are, that they're not even, uh, selling to the, in the open market, right?

I know that some of the hyperscalers already doing that. I have information under NDI can talk about it here. But that's what's going to cause its problem for them if they don't evolve as a company.

Go ahead, Mike. Sorry. Yeah, yeah.

No, if they, you know, they will be kings of the GPU and that might take 'em from 5 trillion to 6 trillion. Jensen Wong didn't get here thinking small. No.

So let's, let's play that out a little bit, right? In my mind, there's no rule that says that Nvidia has to continue to only make GPUs in theory, they could go make another processor that is optimized for AI models as opposed to the one that they developed that was a happy accident. And we've already seen them starting to build CPUs and they have dpu, and it seems to me they're a lot more ambitious than just looking at GPUs and they Want Quantum, right?

So, you know, I think that, you know, they're gonna be so far down the road on the model side that, you know, if they come out with some additional processors, 'cause they learned how to optimize those models, they might be in a better position than folks who are just pure play prostitute companies. You might wanna look at Nvidia and think about it now as trying to own the entire stack. I mean, heck, they sell entire systems now, You know, they, there's gonna be bigger markets.

I mean, a AI is huge and they, they've capitalized on it, but this is not the time to take your pedal off the, take your, you know, take your foot off the pet. This is the time where you now have resources to double down and, and, and make some big passes. Some Hail Mary kind of attempts to, you know, who knows what, what can come of it, right?

And they're already talking about the next two generation of GPUs beyond Blackwell. So, you know, and if they're on a cadence for delivering those, I think they said, uh, somewhere between a year and two years. I mean, the pace of this stuff is gonna just dramatically accelerate and maybe we'll all be living in a different world by the end of the decade because downs point some of this stuff, if it ever hits, we'll change the way we live.

And I think also another thing we need to think about is what are they gonna be doing in the area of sort of pervasive computing, right? Because it's one thing, building a chip and putting all the intelligence in the chip footprint of real estate. But if I need one unit of compute to process, uh, an AI workload, do I need a pervasive computing environment?

Which means I have GPU clusters or whatever, D-P-U-T-P-U cluster that are distributed in the distributed computing analogy. So should they be focusing on, uh, connectivity of these cluster, of the compute clusters, which gives that one unit of compute from wherever is the most efficient resource for that, right? So now suddenly networking is becoming sexy all over again, right?

In the world of ai. So like, what did Nvidia do in the world of networking beyond just computing, right? Is gonna be an interesting challenge for them.

I dunno what, I dunno how you guys feel about that. That's a good topic to talk about. You know, they say Nvidia made hardware sexy against, so now they'll make networking sex sexy again.

I hope so, because a lot of the systems they're currently selling look and smell like made friends to me. But wow, We're not outta time for this segment. Let's take with Frank, and we're gonna come back and talk about, uh, our next segment.

More AI probably. But you're watching text on game. You've earned it.

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Hey folks, we're back. And this is a little unusual. It may be scary and something right outta 1984, but Albania has a minister for ai, and I guess there's gonna be more and more government decisions are gonna be fed through the AI first, and maybe somebody will check on this, or maybe they'll just say, Hey, that looks good to me, and away we go.

But Chris, I know you've been kind of monitoring this kind of thing and, and have talked about this in the past, but it looks like it's here. Well, more countries essentially have ministers of AI and we'll just all, you know, wake up in the morning and be told what to do. I I wouldn't, uh, end it that way at all.

But, uh, yeah. So the last segment ended up being sort of a market, an, you know, business analytic s and the architecture. Lemme talk about narrative infrastructure, right?

You know, so Albana is not the first, you know, here in Canada does this year we have our first, uh, minister of ai, uh, minister of Solomon, uh, Evan Solomon. But last year, mark Sean, the was the first deputy minister. And we know in cybersecurity, we've seen this happen before.

Mark Weatherford, who's now at, uh, doing policy at Nvidia, was the first under secretary for cyber in the, in the beltway, in, in the US federal infrastructure. And Albania is an interesting case because, you know, they, they punch above their weight in EU and in, uh, a number of ways in this, in this case. But we're going down this path, you know, these are important topics that need to be addressed at this level, at the policy level.

Someone has to be responsible for it. You know, Mike, if it ends up being authoritarianism, I guess then, you know, democracy has failed, but I don't think we're going there, right? And this, you know, Sid, you touched on something in the last segment that I really wanted to, to to pivot on because, uh, the Meta's AI chief, um, Yann Ko, you know, leaving and his statements about needing to move AI into a, not a, not just a word prediction, but a world map, right.

Models exactly what, but I, and we focus on in this attest civic AI world, and it's not that far reach. And it's interesting, uh, to see folks like, uh, like, uh, like, like Lako making those statements and those moves right now, right? And just just to map this out for folks, LLMs are a language modeling thing that's modeled after what happens in our brains.

But that's not the only thing that happens there. And mammals, 200 million years ago, started building a world map that's literally the term used in cognitive science. So they could, it's like a, like an eight big video game, like a really, really simple one.

You can navigate in 3D find the food and find the food you found yesterday, right? The world map that Launa is talking about, that that folks like myself and, and, and our allies are working on these days isn't about a whole new different ai. It's about taking this capability we have and having it operate in a relational environment so it can basically have that world map.

And in that it touches on the things that, like Mike and Alan and you guys, we've talked about week to week throughout this year, you can do so much more without so much energy, time costs, so on and so forth. So that's just, you know, that, that move, you know, out of, out of meta AI this week and this happening in Albania, you know, modeling what's happening here in Canada, that maps a narrative arc that's fairly straightforward, I think, I think we'll see the business and technology architectures follow from that. Yeah, I think, I think the, on back to the world model conversation, I mean, the way I understand it is it's an AI system that essentially builds in, you know, an internal representation of an environment and then how it's used to simulate future states, right?

So more of a outcome-based predictive model rather than LLM, which is a pattern recognition based technology, right? So, so I, I see that whole world model that KO talks about, as, you know, the predicting model, predictive modeling of physical systems like infer, object permanence, motion collisions, the physics thing I talked about, you know, gravity, things of that nature. Uh, it also has, uh, relevance to autonomous planning.

So you can run thousands of simulated rollouts, right? Uh, it has, it's more grounded in decision making rather than sort of like, you know, in the case of sequential transaction, you know, it's very, very one way, right? So, I mean, I can say I, I know based on text has collecting the LLM database, if you wanna call it that, that Tom Cruise with mothers Holly Cruise, but it can't tell me Holly son is Tom, right?

It goes only in one direction, sequential, right? So, so word models will kind of overcome those kinds of things. And you know, it's also gonna have things like embodied intelligence, so robotics, autonomous driving, manufacturing, drones, gen software, all sort of require this, right?

So I, I look at sort of LLM use for reasoning word models use for simulation and a chance and agent for action, right? That's the triad of future of AI architecture, in my opinion. Well, and, and the, the, the, the value of the world map for now m is, is, is is a self transformative.

And that's why I think this era is, you know, historically we may back, look back at this, the hype cycle wasn't big enough, but it was the wrong hype cycle up to this point. But I think we're starting to get it and, and we build LLMs modeling ourselves. Like that's literally what we're trying to do.

Extrapolate a little bit farther back wire mammals, how do they do it? And we're talking little mousey creatures who got a, uh, evolutionary advantage by having that really simple world model. I think that's what we can do today, right?

And, you know, attestation channels and the systems we build and demonstrate all this all the time, and it's just happening this year. So it's not like we need to create another LLM industry, another multi-trillion dollar thing. We need to take these tools and work them in a relational environment that allows, you know, the result to act as if there is a world map like mantels do it, you know, nothing like we do at this point ourselves, but that's the path we're on.

It looks like, uh, Albania, like what, just one point on the Albania thing, looks like they came up with something called dla. Are you guys familiar with that? It's sort of a special, I don't know if it's LLM that's developed by the National Agency of Albania in cooperation with OpenAI at, uh, just I'll aspect, sorry, go ahead Hai, you point.

Uh, No, I was just saying that going back to the original point of we are having a minister, which is a ai, um, power, if I've been a citizen of that country, I'll be excited, I'll be excited to see the politicians are getting a revamp or a new perspective to make the decision. And it might take the country the direction they, they want it to. So I think as I, I'm not talking about the technical aspect of it, but I'm just saying as, as the humans who are taking this decision into consideration, is a good move, um, politically, I think it will, uh, give the governments the insight in terms of the directions where they should invest in take, take the insight, take the inputs, but can they rely on it completely?

I think it's too soon to do that. Yeah. I, I think also, you know, just because we have an AI that spits something out, well, when we determine that whatever that truth is, that it's inconvenient, we're still gonna ignore it.

Yeah. Yeah. I, I think a lot of these countries have essentially, like Albania have long faced systemic issues with corruption, you know, nepotism, weak public procurement practices.

So, so the more they do in, in, in, in terms of openness and creating these AI initiatives that span obviously within their, their own country, but overall across integration with the eu, let's say, or the European Commission, right? Uh, I think those things kind of give, give an optics that they're more open to sort of collaboration and interoperability of the rest of the world and creating these AI initiatives is probably one way to address that. Uh, so I look at, I don't mean, but I'm a huge fan of the, of, of capitalism and democracy and freedom of speech and so forth for the reasons of evolutionary pressure, right?

Because I honestly believe that the better systems are better people and ethical and, and so forth. And again, if I'm wrong, let's find out, we'll play it out in the markets. But, you know, to Mike, to your, you know, and I, and to be clear, you know, we, we, we, uh, uh, uh, spar on this one, but that's good.

You know, I need a razor to go against 'cause I'm an optimist, but it's just, if I, uh, right now I'm looking around the world, I'm seeing countries like Albania, like Canada, where I have good faith to be reasonable effort to have an AI minister and do it properly. I expect a number of countries will do it wrong. I think it will cost them, it'll cost 'em economically, it'll cost 'em in global power.

It'll cost 'em in trade and relationships. And while I could be wrong, I think this is the kind of role like cybersecurity. I was glad to see that get into the public sector because it's a technically intrinsically kind of more honest than just I said so kind of thing.

Those of us in this, in cybersecurity know that that's not entirely true all the time. But I think this topic does drive it down further and further if your actual, you know, let me try to end on this, right? We talk a lot about canon, right?

Canon in our, in our terminology means what you actually do, what you say you do, right? And AI tools are actually really, really good at this right now, right? And lots of use cases and, and we're seeing in real world.

But I think the countries, governments, as they semantically analyze their actual canon, they'll find out whether or not they're doing what they said they do and opportunities to be more or less corrupt. Pick your, pick your choice. I think you're looking at it wrong in all honesty here.

Here's the deal. I, I've said it before, I'll say it again. We're at the beginning of the beginning of the AI story.

We're still at the beginning of the beginning. We don't know where this is gonna go. Will it turn out?

As, as that chief scientist in the Wall Street Journal article said, that LLMs are sort of a dead end and we need to go to these world models to really make this work better or to recognize our dreams. I don't know, but it's gonna be big enough where we need a government element. You probably need a world government element to it as any one country alone, but it's not just to regulate ai, right?

North Korea will regulate ai. The old Albania will regulate ai. You know, the people who sit clutching their pearls saying, oh my, what could AI do bad?

They're dinosaurs. They're already road guilt. Forget about it.

AI is going to go as fast as people can make it go. No one's gonna stop it. No government, no nothing.

It's going to go, what needs to happen here is governments are gonna recognize, how can we use ai? How can we harness ai? Not how we can control it, right?

So it's not just a regulatory function. And, and quite frankly, and I am no fan of Donald Trump, anyone who knows me or has heard this show knows I'm not. But what he did early on in that administration is he appointed a so-called czar for ai.

I haven't heard much from him since, but I assume he is working behind the scenes on all these deals that they work. We need a government policy that probably says, Hey, AI is going to be world changing, civilization changing, perhaps we need to be in on the action. We need to understand what's going on.

We need to try to influence it the best we can, given our resources. The resources of the US are very different than the resources of Albania. And they're very different than the resources of Canada.

But government resources will be brought to back here. And, and rightfully so. It has to, if, if it's as big as we think it's going to be, it naive to think the government's not gonna be involved with, I think it's somebody gonna try to control it.

'cause they will, because for, Well, it, will it be the government or some strong man or who that, you know, who knows? I mean, I like to, I, I like to see the government. I like to see the government, uh, be providing some guidance on responsible ai, right?

I think that's key, right? Because we can't have all these private companies go burst. So again, I'm, I'm a, I'm a capitalist, don't get me wrong.

We, but we can't have chaos, right? And there's too many competing positions once being taken by Elon Musk and XI and Rock and that stuff. The ones being taken to open ai.

And you've got a whole host of other positions, right? Meta and so on and so forth. Like, so we have to be somewhat cognizant of how that is managed, for lack of a better term, uh, from a responsibility act respective.

But I don't wanna see government interfering in ai, right? So I don't want government come stepping in and say, if you sell this chip to China, gimme 15%. I mean, to me, that's socialism, right?

Like, how is it a different Abs Either you're regulating, you don't want China to have it, or you do, but you don't. It's not On one hand you criticize socialism. On the other hand, you participate to socialism, right?

Agree. That's a problem. We all, and then what the other thing is, I like to see government actually deploy AI with their own agencies.

I mean, if I have a government minister, that person should be responsible making sure government is using ai, right? I'm not seeing any of that happening, right? Well, Elon must supposedly, but guys, we gotta take a break here.

We're overtime. We've gotta come back for our third segment today. It's a lively discussion.

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Contact us today and tell your story to the world in the most powerful way with Textron Group. Hey folks, we're back and we're gonna have one more little chat that's AI related at least. But we have talked about one of the biggest issues with AI is energy.

We don't have enough of it. The grids kind of, well, shall we say, shoddy. And so now a lot of folks are saying, well, we're gonna have these massive batteries that are gonna enable us to store energy so that we can mitigate some of the impacts these data centers are having on our grids.

And it's an interesting theory. I just don't know if the science behind the batteries is up to the task or not. But Alan, what do you make of it?

Can batteries kind of solve this issue for us? It, it, it could help if you believe we can get there, you know, on yesterday's gang, we spoke about JP Morgan Chase put out a report that now they expect 5 trillion, 5 trillion. I'm back to that 5 trillion number.

I love that number $5 trillion of data center build out over the next couple years, right? What's the biggest bottleneck to bringing these data centers online and operating them energy? We don't have the energy to operate those data centers.

We can't build nuclear and get it approved fast enough. We, what? Are we gonna burn coal for this?

Uh, the government is not a big fan of solar and wind, and that's probably our best bet. So much. And this is again, the beauty of AI and, and the, and the first segment and video making some hail Mary, that's the beauty of AI is much like the NASA space program to the moon in the sixties, right?

They knew to get to the moon, they had to invent some things that didn't exist right now, right? They had to do better computations, they had to make materials better. They, they needed mathematics.

And, you know, they, a lot of technologies got invented and commercialized as a result of the mood program. We are in the same boat here. We know the key to making our, you know, to solving the energy issue for data centers and, and for beyond data centers is to have that a battery storage, right?

We could then really store all that solar and wind that gets generated and, and stored for a rainy day, so to speak. So I think this is gonna spark better battery technology. And I think we've already starting to see these kinds of announcements, right?

And that's what this is about. We need better batteries to make our data centers and our world better. You got trillions of dollars at stake here.

Let's go build better batteries. I just wonder if these batteries are gonna be kinda, you know, a substantial impact, or is it gonna be like, you know, when I get that electric vehicle and if I pump the brakes, the battery will recharge. But it never really does.

I don't think that's, I don't think that's what we're talking about. I, I think we're talking about, I think we are not talking about the recycle waste this battery is going to generate over time, right? Because if you see Tesla is the one who entered this space years ago, and now this is the time where they are changing the batteries because their battery's supposed to last seven years.

So where is this battery waste going to we get disposed of? So it's not just about data centers getting electricity. I mean, you just said Alan few minutes ago that we are still at the beginning of the beginning.

So when, when we are not sure with AI where we are heading to, and we are building data centers, and we don't, we do not have a clear concrete plan in terms of what are we going to do with this batteries when they're run out of life. We are still in that circle where we are building things. We don't know what use case they are in.

And we are probably producing more environmental hazards, which will be more dangerous than the benefits of ai. The last time I checked this government wasn't very concerned about environmental hazards. Wait, wait, well now I have some, all those rockets that Elon Musk and Jar Bizos are building, right?

Send them on piece space. I, I, I think it's important to recognize what is the role of the battery. The battery is not gonna be the primary supplier of electricity gives data centers, right?

It is gonna be that power buffer, right? And in the grid and the racks. And the reality is that GPUs have very high peak average power issue.

So, uh, the, it, it's a very spiky and sort of a denser, less predictable power profile, right? So AI dense racks, I think the last time I read was like, consume 40 to 60 kilowatts today and then going up to 120 kilowatts, right? So the question then becomes like, what is that?

What is the role of the battery that's going to be, uh, going to be relevant or this buffer power buffer as they call it, right? And already the hyperscaler, like Amazon, Google and Microsoft are deploying what they call battery energy storage systems, or best they call it, which not only generate the power, but also sell capacity back to the grid during peak demand. So I think all of that is an interesting topic, but equally important that someone touched upon is the environmental aspect of these batteries.

Like, what are we going to do with all these battery waste, right? That gets, uh, generated over time by powering creating those power puffers for these ai AI data sectors, right? So I think those are some of the interesting things to, well, I I, I, I've really enjoyed the, the, the power.

You know, when I look at these shows over the last year, right? We keep coming back to this issue. And I, and this is one of these issues that comes up.

We're mostly talking about ai. We talk about power, but I've been involved with the grid for decades and the last 15 years particularly has seen a lot of work in this direction. And this use case is just for these sort of, you know, from a power engineering perspective, you know, one of these CEOs slap your forehead.

Of course they, you know, of course we're gonna throw this in. So into the specifics, kinda like the last segment. You know, I am on an international level.

I am looking for countries to disprove things that seem popular, you know, draconian, authoritarian, whatnot. This particular, uh, legal move in this particular jurisdiction, I think is a good idea. Cattle just this week, you know, the largest battery produced on Earth is coming out, has announced that the production level of their next generation of the lithium iron batteries.

And that should be a, a big quantum step here in Canada. Volkswagen is building a giga plant, uh, shovels in the ground, uh, battery plant, uh, that'll be producing, uh, platforms in 27 and, and end, you know, take everything else we're talking about here over those timeframes. If you know, hyperscale or consuming energy data, uh, in bigger data centers with more Nvidia GPUs was gonna follow exactly the curve that it's on right now.

That's physically impossible. What are we going to do instead? Right?

And, and whether it's these individual things with, with best, with battery storage systems, I, I saw a neat little thing that again, I don't think is the answer, but I love these sort of things. In the uk they have a program now where you can run a micro data center in your shed, literally in your backyard, and it'll provide the heat for your house and lower your costs. You know, Finland, Finland is building underground data centers and using the heat to, to heat homes old house.

So that, yeah, This winter, I have enough GP news running at home right now this winter. I'm, I, I will in fact, you know, lower my heat bills. So anyways, you know, this is a complex issue, but there's pragmatic realities in, in power terms.

We talk about, you know, rotating mass, right? You know, you don't think about this. If you plug something in, there's some spinning tons of steel that feels that momentum.

So we have battery systems now that can mimic that, which is bloody amazing. But we're still so early in this that again, grids and jurisdictions will make bad choices. I have a lot of popcorn.

I think we'll all learn from mistakes, but yes, this is where we're going. So maybe, maybe, maybe the future is where all these big corporations that are building these AI data centers will work with consumers and install GPU clusters in every home power with batteries, which can also power their refrigerator, generate enough heat and save money. So maybe that's new Steady kind of thing.

So, So Sid, are you saying that the Energizer bunny is gonna save ai? Yeah. You, Mike, you summarized it very well.

That's why I love 'em so much. I mean, I don't wanna raise my kids under the house where GPUs are running. I don't know, what are the ultimate race gonna do to this American life?

Oh, You put it in, you put it in a shed in the, in the, in the yard. You know something. I mean, still just around.

Yeah. Yeah. I think on that note, we we're gonna end today's text drug gag gag.

Thanks for joining us. This was a great, great discussion on some great topics. Thank you for watching Mike.

And I'll be reporting here from, uh, AI native Deron in Brooklyn today, tomorrow. So stay tuned for that. Stay tuned for the rest of the text on TV coming out here right after this.

But for now, half of the gang live in Brooklyn. We're out. Let introduce you to my friend Homan Singh.

Homan is with Broadcom Homan. Welcome. Thank you.

Thank you for having me. Enjoying enjoying Q con so far. Absolutely.

Very exciting. Day one today. Announcements.

Yes. It's been, uh, an energy, always a lot of energy. Oh yeah.

Thank Q Con. Yeah. Homan, before we get into, we, we've got a couple things we want to talk about.

I want to spend a little time just letting our audience know a little bit about who you are and, you know, so give them, if you don't mind, a little bit of your background. Absolutely. So, yeah, I am director of product marketing, um, at, uh, VMware by Broadcom.

Right? So my focus areas right now are around Kubernetes on VCF, which are, which is our VMware cloud Foundation offering, uh, everything AI as well. And then also looking at our kind of cloud operations, cloud consumption, uh, capabilities used to be part of the old Aria portfolio.

Sure. Uh, essentially, right. So a few of those things kind are, you know, very related areas to each other in terms of how consumption works in a private cloud.

So happy to be, you know, working on that visa, but not VMware coming to two and a half, 13 years now. So, wow. Lots of changes.

But, So you were v VMware before broadcast? Oh, yeah. You've seen a lot of changes.

I have seen a lot, and I have the scars to prove it. Yes, I bet you do. I bet you do.

You know a lot of people, or look in the software world, I think everyone knew VMware, and I think everyone knows that vm. Not everyone I guess, but most people know VMware is now part of Broadcom and Broadcom's a name I, again, I think a lot of people know Broadcom by name, but they don't realize all of the things that Broadcom is part of. Without asking you to be the Broadcom spokesman, what you're going to be, give us an idea of the different tentacles, if you will.

The Broadcom, Yeah. Tentacles. That's interesting.

Uh, it's, it's less, Well, an octopus is a very intelligent network, very Intelligent. Then let's just go with that, right? Yeah.

So, um, Broadcom actually right now consists of, I think 26 different divisions. Oh, I didn't realize it was that Many. They operate as almost as independent businesses.

So you have a lot of flexibility. Each kind of GM has a lot of flexibility in terms of just going to market as, as they were. So it's Broadcom's known in terms of more of a hardware company for a very long time.

Yes. Massive hardware, innovations, et cetera. I mean, you know, um, but at the same time, in past, I wanna say close to a decade, they've went into software, you know, very strongly to kind of really think in terms of, if you look at a hardware business, which is very kind of seasonal, uh, you know, there's this like press and troughs versus software.

It brings kind of more stability. And I think that's what Htan was thinking about in terms of, you know, growing Broadcom beyond the hardware pieces. So you got, you know, a few different pieces.

The, the Broadcom software group now has, and then of course, VMware by Broadcom probably the biggest acquisition in the industry when it happened in 2023. Timeframes 65. Yeah, I would say broad.

Uh, VMware or ca was a big buy too. Yeah, CA was big as well. So was like 16 something, But it was older, so you got go by, you know, if you put inflation on those nuts.

Oh, that's true. Yeah. Which Probably is closed.

Yeah. Ca was a long time ago. And then of course, I think that was the first big software.

Yes, absolutely. And so they started with that, and then they kind of got the flavor of it, and so then they went Symantec, they went VMware, uh, et cetera. And VMware is a whole kind of different story, right?

Because Oh, yeah. 'cause I think, you know, the, the kind of ecosystem VMware brought with it for Broadcom, uh, there was a huge amount of, I think learning in terms of the Broadcom culture as well. And we are very fortunate to get like the support that Hog Tan has provided to VMware.

Um, there's been a lot of focus for sure. Yeah. Um, VMware behaved very differently before, um, kind of an amalgamation of a bunch of different groups versus now it's extremely focused.

We got one of one, one key offering, which is VMware Cloud Foundation. Um, and then really making sure that we are going after the private cloud, the value we're delivering and building capabilities around it into VCF. Um, and that's been doing like very well for, for VMware overall.

Uh, so in terms of, you know, how, Look, you've been in VMware, what'd you say? 13 years? Most?

13 years now. Yeah. I've been following VMware longer than that even.

Right. And if you look at the history of VMware, very interesting. Right.

For those of you out there, I'll give you a little history as I know it, right? Of course. It was kind of, it was kind of spun out of, actually it was started and then brought into EMC, wasn't it?

Yes. Right. The original founding team, kind of, there were a lot of hypervisors vying for the market space back then That time.

Yes. Um, the Red Hat one, there was some open source swans, but VMware, it, it was very, at the time, everyone thought it was very lucky to get hitched into the EMC uh, orbit. Yeah.

You know, and similar to Broadcom, it was basically kind of a hardware company. EMC was a hardware storage company. Storage.

Yeah. And now all of a sudden they've got this hypervisor company, and I think it was a bit of a redheaded stepchild, if you will, because it wasn't core to what EMC did, saying then now EMC goes and gets acquired by Dell, another hardware company. That's Right.

Although Dell would argue, like by the time they came to Acquire, right. That, that They were Software company. Well, again, much like Broadcom, they were transitioning to software Yes.

To even out the cyclical, the cyclical hardware cycles. Yeah. Then Dell goes private.

Yeah. Spins out. I think they spun VMware at and was the first time that VMware was truly, truly independent.

That is true. Since it was first. That's true.

Yeah. Formed, that's probably around when you joined, Or No, so I joined back in 2013. So that was still Dell or EMC?

Yeah, that was EMC. Okay. So it was EMC, then Dell came in 2016, I believe.

Right. Um, and, you know, a whole bunch of things through that. And then of course, VMware became a spun out independent company.

Uh, I think we might have been technically independent for like six months. Right. And then Broadcom kind of made the announcement of the Acquisition.

It's such an amazing thing. Yes. No one's ever let VMware just be VMware.

It Is extremely valuable in terms of I that VMware has and the call Based, well, it's also the market share, right? Oh, yeah. VMware though, as we said, there are a lot of open source hypervisors and public cloud hypervisors and so forth.

VMware is the hypervisor. Right. Has been Absolutely.

Continues to be. Now Broadcom bought it, and, you know, there was, there was all kinds of rumors and feelings about what that meant for VMware, but as you said, I think htan surprised a lot of people in that he didn't treat it like ca Yes. He didn't treat it like some of the other software acquisitions, I think, because for the same reason Dell and EMC, they recognize that you got a diamond here.

Right. You, you can't, you gotta shine it up. You can't try to break, you don't want to.

You're not a diamond cutter. Absolutely. And, um, and so it, it's, it's had, its a reflowing, if you will.

Yeah. Yeah. That's a word.

Yeah. Yep. Yeah.

And that is, look, we all talk about license changes and all of these things, but when you look at people who are either staying on VMware or leaving VMware, they don't cite cost as the issue. The issue is freedom. Do I wanna have a multi-cloud a a, uh, hybrid cloud?

Do I wanna just stay in my private data center? Do I want be locked into anyone's walled garden? These are the things people care about.

Yeah. Yeah. But, And, and I think, um, this is the thing with, again, any kind of like platforms that we have, you know, no matter which vendor you're talking about, uh, you know, at the end of the day, it becomes a platform play.

You know, where do you wanna standardize on? Um, there's always gonna be, you know, some silos that you might have. Hey, companies acquired this and that, uh, and or they grow with certain things organically.

But by and large, you know, when you look at large enterprises, they want to look at overall cost, overall standardization, um, that helps with cost, but also from an over, you know, just ongoing operations perspective, skillset perspective. How do you make sure that what you have can be leveraged and, and then basically expanded more and more. And this is the kind of story that works for, I mean, it doesn't matter if it's, you know, Broadcom or VMware or some of the other vendors.

You know, you wanna make sure that you are able to provide the benefits of standardization. While, uh, and I was just having this conversation with, with a colleague earlier, while giving the folks who are doing the innovation, the flexibility of being able to do that without feeling locked in. Right.

And that's exactly what we're striving to do when it comes to kind of VCF. And, uh, yes. This, we went through a whole bunch of changes, uh, in terms of bringing things together, uh, which also for the first time, interesting.

Big, big, big focus. I mean, VMware fantastic culture, but the thing that we lacked before was the focus on making sure it all works well together. Just plane.

Right? Yeah. There was a little a DD, if you will, entrepreneurial a DD.

Yes. Um, and you know, that's not a bad thing, but focus is a good thing. Now we're here at Cube Con, though, and people say, okay, hypervisor cool, Kubernetes, how's the, what's the connection?

And if you're asking that, then you really don't understand. Right. Uh, containers, orchestration of containers has run on, have predominantly run on hypervisors.

That's right. From day one. That's right.

Uh, VMware pre Broadcom was a huge supporter Yes. Of coup. Absolutely.

Of, of CNCF. They continue to be under Broadcom as well. Yes.

Uh, talk to us a little about that. Yeah. So VMware has been involved with CNCF for the longest time, and you know, basically Right, right.

From since inception, pretty much Yep. But involved with Kubernetes right up front. Uh, and, uh, we've been, Ian, this is something that folks are actually surprised to hear that we've been, if you look at long-term Kubernetes projects, uh, you know, contributions by companies, we are the number three.

People are very surprised to think, oh, VMware, you, you guys have been that active. Yes, absolutely. And it is just that we never kind of talked about it.

No. Right. But then you've right there, people Put together Since, since the beginning, you know, if you, this is again, quo c nnc, F sta statistics, um, it's been a top, top, uh, contributor.

We've got a lot of people who are maintaining a lots of kind of, uh, CNCF projects, Kubernetes. So the idea has been that we've not been like just the users of Kubernetes and incorporating it and making sure it works on a platform. We've been right there with the community building it help, helping to build it all this while.

And, uh, and we wanna continue to do that in an even stronger way as we go forward, because, um, as you think about core infrastructure, it doesn't matter. You wanna run applications on virtual machines or on containers, which predominantly, as you said, pretty much, uh, you know, uh, everyone including all the hypervisors run containers on Kubernetes, on a virtualized environment where everybody has their own kind of flavor. And because it brings a certain amount of, you know, benefits to be able to do that, all the isolation, benefits, security, and all that kind of good stuff as well.

Um, and making sure that we provide this experience of running containers and Kubernetes as good as folks have enjoyed running virtual machines on a VMware environment. Right. We have been always known for, for VMs, of course, you know, we, we are the market leader, uh, no matter what metric you choose, but, and we are doing the same when it comes to containers and Kubernetes, um, to make, to provide that experience.

And this is exactly where, as part of this VCF platform I was talking about, the vSphere Kubernetes service, or VKS kind of comes in. We used to talk about this as, uh, a tan, zu, uh, service Yes. Back in the day.

And, uh, as we came into Broadcom, we moved all the Kubernetes and infrastructure pieces as part of VCF. Again, to that point of focusing, focus, simplifying, providing a better experience to customers. At the end of the day, that's what it's all about.

And so our Zu team is focusing very much on a PA environment, uh, uh, going directly to developers while the VCF piece is working with platform engineers predominantly, and of course, our core kind of audience, the IT admins, the IT team that have been running infrastructure. So that's kind of how the overall evolution has been. And there's just, there's so much more that we are now looking forward to do, because when you focus, you can do so many more things better versus just doing a whole bunch of things in average way.

So we're very excited about that. I, I, I, I don't, I could see why. Right.

I, I could see that happening. So here's one thing we haven't mentioned, though. That's been a big thing, and that's ai.

Yes. How is AI changing, influencing, showing itself in this, in this ongoing evolution? So we, um, been in involved when it comes to the AI space and providing the infrastructure for AI workloads for quite a long time.

And we've been working with NVIDIA for more than a decade at this point in time, to make sure that all the innovations from nvidia, therefore the gpu, vgpu, et cetera, are available as part of the, as part of vSphere before. And then now VCF, of course, the other thing is, um, I forget when it was, but I think might have been 2023. We kind of put our foot down and, and talked about private AI as a key piece.

We basically said, Hey, uh, private AI is, again, not about like the location, but the concept of privacy of your data. AI in itself is all about massive, massive amounts of data Yes. And where it resides.

So we wanna make sure that customers are able to get the insights from all that data without having to move the data around, keeping it within their boundaries, keeping it safe and secure. And again, if you folks have used vSphere or VCF, they understand the level of, you know, enterprise grade security that comes with the platform. And so we are bringing the exact same thing to all AI workloads.

And the, of course, when it comes to ai, you're deploying it using Kubernetes, you're deploying it on containerized, the applications are typically containerized. And so making sure that the experience we get for all our private AI services and capabilities that are all included in VCF with V Kubernetes service as well. In fact, um, today at the CubeCon, they talked since CFC announced the new, uh, Kubernetes AI conformance program.

And we are one of the first, one of the few really, uh, starting kind of conformant and certified platforms. Um, you know, VKS is as part of that. So we kind of underlines the importance of AI in general and how we see at the end of the day, it's just another workload.

And we wanna make sure customers have all the tools available on the VCF platform to be able to use VKS, use our private AI services to build those, uh, those, uh, you know, applications that they do. I, I, I think, I'm not sure we're running low on time, but one of the things I wanna close with, and you know, I'm directing it right to our audience, and you could look in that one when you respond, which is, look, VMware's always been a supporter of the Cloud Native computing foundation of Kubernetes, of containerized, of cloud native computing in general under Broadcom. That commitment is of anything stronger than ever and remains so today and tomorrow.

And, uh, you know, anyone who says different is, doesn't know the truth. Yeah. Just need to get educated.

That's all. Just need to, like, it's an education, learn more, figure, figure it out, and, and they'll see the value. Yeah, Absolutely.

Hey, thank you for all you do. Thank you. It's a pleasure as always having you on.

Um, I hope we won't wait till the next Cube con. I would love to, you know, get in touch earlier and Share this conversation. Well, we do these every day outta the studio.

All you gotta do is write me. Absolutely. So it's on you.

Absolutely. It's on me. All right.

Haman, you sing, sing, uh, Broadcom, VMware, Broadcom, VMware. Wear Broadcom Right term here on Techstrong. We're gonna be back in just a minute.

Hey, if you've watched Tech Strung TV over the last few years, you may may have seen this gentleman on his name is Colton Andrews. Andrews Andrews A-N-D-R-U-S. That's correct.

Not Andrews my funny French accent. You gotta be careful with that stuff, Colton. But Colton is the former once and present and future CEO of Gremlin.

That's right. Right. And, um, if you don't know who Gremlin is, stay tuned, we'll tell you.

But Colton, it's great to have you in person. You usually do this, you know, remotely over text, drunk tv, but here you are in the flesh, man. Yeah.

Good to see you. Remote's fun, but, uh, different energy when you're live so Much. Enjoy.

You know what, enjoy. I, um, I gotta echo that, right? I, I just had this at a, we were at a dinner last night and I was talking to some people, whether it's a, a sales environment where you're there talking on a potential customer or a partner, or even a friend.

Nothing, nothing takes the place of person to person. And, and that's not, and that's something AI's never gonna be able to do. Yeah.

Right. Such a timely comment. Yeah, exactly.

No, but humans are social animals. And though, like, when we were locked in our houses for COVID and everything else, zoom was the next best thing we had. It pales in comparison Yeah.

Of, of this kind of communication. So, hey man, it's great to have you here. Yeah, Yeah.

Thanks for having me. So, Colton, I made a little reference to once present and future CEO, but there's been some gaps there. Talk, tell, give people a little bit of your history.

Yeah. Well, uh, for those who don't know me, I'm Colton Andres, engineer by trade. Uh, grew up working for a bunch of tech companies.

Had an opportunity to work at Amazon for a few years, focused on their reliability program, got to join Netflix, got to continue my good work there. And that really led to going out and founding Gremlin. Uh, first few years I was CEO, uh, for six years, you know, out building the product, learning the market, really advocating champion for the idea.

Uh, brought in another CEO to run the go to market side so I could go focus on product and engineering. And that was really a go into the lab, you know, understand the problems well, and go fix 'em. And, uh, I got that done.

Engineering's running great products in a good spot. So I took back over as CEO and excited to be, you know, running the whole ship again. You know, look, I know a lot of guys who were, you know, founded companies, became CEOs and then moved into product role, CTO role, chief evangelist or strategy.

But I, I'll be, I'll be honest with you, I haven't seen many come back to be the CEO. Yeah. Um, so kudos to you on that.

You know, if you wouldn't mind, you know, I don't want to go Barbara Walters on you showing my age even saying that, but what, what kind of, what was, what was like, what was the light that went off and said, okay, it's time for me to come back as CEO? Yeah. Well, I think it was twofold.

I mean, just to be, just to be completely honest, you know, if it's your first time being CEO, you have some doubts. You wonder if you're doing things right. If you could have done things better, Joe.

Right. And so, you know, you bring in another CEO, it's an opportunity to learn, listen, observe. Uh, and I'd love to say, you know, that the person I brought in taught me a bunch of things I didn't know.

But a lot of it was actually, you know, kind of par from the course. You're right. You know, I was doing it.

Okay. And You needed that reinforcement. Yeah.

And so that was part of it. And then the, the product and engineering side, I'm an engineer, I'm a product guy, I'm a builder. And one of the mistakes I made was stepping too far away from the engineering side and really delegating it.

I see what you mean as CEO. And so, yeah, my, my three years as CTO was getting back in and making sure we were building product correctly, we were understanding it. Well, part of it was getting our engineering team just humming, you know, making sure they were shipping.

It's the lifeblood of a tech company. And if you've got issues that are preventing, you know, consistent quality delivery, those have to be fixed. So once I had those fixed, that left me in a position where I felt like I could come back and take back over the reins as CEO.

And I think one of the, one of the big things for me is, one of my roles has always been an evangelist role. And it's actually a bit easier in the CEO position to be that evangelist. Sure.

To be in front of customers, to be in front of prospects, to be at events, to be doing interviews with great guys like you that allow you to get out and spread the message. And so that was, that was a big impetus. Flat, flat flattery will get you everywhere, my friend.

Thank you. But, you know, I, I had a little bit of the opposite from you where, and this is another sort of, uh, persona that I, I've seen in startups where CEO founder is the chief sales guy. He's the guy who close his deals.

He's the guy who has the network, or she, in some cases, right? They're the ones who are primarily responsible for making it rain. And sometimes, you know, revenue is key, revenue is king.

And you're so focused on trying to go out there and make it rain, bring in the revenue that you, you, you lose touch or you lose focus on is is product running, right? Is engineering, is operation now a case, it's operations, it's, it's, you know, all the little things that beyond doing these, 'cause I'm the face of it, beyond, you know, making it rain. And, and that's a, it's a tight, you, so you live this too.

You're just living it from the engineering side. I'm living it from the revenue side. Right.

You, it's a tight rope between how much focus do I internally give to the, the guts of the company versus my external focus on making it right. Yeah. Yeah.

And that's, that's one of the parts. Yeah. I think one of the unique positions I'm in is being an engineer that has done it and lived it.

I have a credibility, I have a, a wealth of experience I can speak to. Yeah. And that's relevant, whether I'm talking to engineers or I'm talking to executives.

Yeah. And so, but yeah, if you get, you know, gotta gotta have revenue, gotta build a healthy company, gotta make sure the company's moving forward, and that, that focus can steal from kind of the pure engineering. Are we solving the problem well?

And are we really making the progress we need to? Absolutely. It's a tight balance.

Absolutely. It is. It, it is a tight balance.

And, and the other thing, and, and, and I would say this is probably another mistake that CEOs make, especially first time CEOs or more inexperienced CEOs, is you hold on to things so tight, right? I, I can't let go of engineering. I'm, I'm an engineer.

I, I know I have the vision. I God will see that through, I'm the best advocate evangelist we have. I I'm the one who could close these deals.

I'm this, I'm that I, I, I, I, you can't be all eyes. There's gotta be some whe in there. And so learning to delegate, first of all, it's, well, it's, it's having a team.

You could trust It. It's interesting you say that because I actually think one of the traps I fell into was the too much good advice trap. Oh, You delegated too Much.

And I delegated too much. I tried to find the perfect executives That could do it. So that's tattered.

And a lot of what I've been learning and doing the past year is just falling back to what I find. You know, there's a balance. And so, yes, I think what you're saying is totally valid.

You gotta build the team, you gotta build the expertise. But sometimes if you over delegate or you do too much, then the company goes astray. It's, it's, it's wandering too much.

There's too many options away from Your Options to go. Right. And so I think that's the beauty of being in both roles and being in both positions, is I arrived at this happy medium, which is, I have the confidence that I know the direction we need to go.

I have the confidence in the pieces I can do to it, but I have a team I can trust, that I can delegate to, to ensure that I don't have to be the one who does everything. Love it. It's, you know, it's an interesting thing.

We're here to talk about Q Con though, but this is great. Look. Sure.

com. They'll be happy to answer 'em for you a Hundred percent. Um, But Colton, let, let's talk a little bit about Gremlin.

You guys kind of, I mean, for in, in many ways you invented, well, Netflix did, but you invented chaos engineering, and of course you were there at Netflix. Mm-hmm. When chaos engineering kind of took root and gremlin, at least for my money, was the Chaos Engineering company then.

Yeah. Right. Now the world changes, things change, technology changes.

But talk about today's gremlin. Yeah. So I think the Chaos Engineering Gremlin was a cool idea and a cool project, but really needed to grow up a little bit to be effective in today's enterprises.

I think a lot of what was great about the early product is it lets you go out and experiment and test and understand. And it was a bit how an engineer would build it, freeform, figure it out. If you need help, come ask us.

Well, most enterprises don't have time to go out and figure it out, and they're busy. And so what they need is a bit more guidance, a little bit more prescriptive approach. So a lot of what happened over the last few years is let's take what we know the best practices are and just build them into the tool.

So people are starting out with the right patterns. And some of that is, uh, you know, the engineers aren't sure what to do. Let's tell 'em what to do.

Let's tell 'em what tests to run. Let's integrate with their monitoring. Let's tell 'em if they passed.

Let's, let's take the homework away so they can get the work done and get to the answers they need. The other thing that Chaos Engineering struggled with is how does the company view it? And as the company view it as important as security?

Is it something the company says, yes, this is something everyone should do? Or is it an unproven idea? That sounds cool.

And I think we saw a lot of sounds cool, but we've seen over the last few years and the way we've taken the product, a lot more companies buy into the, this is how it should be done for our company. And one of the biggest parts of that, one of the things I love to ask, uh, my customers, I've asked it three times today, is if you prevent a large outage, can you get promoted for it? 'cause we know you can get fired if you cause a big enough one.

And the answer is, if you don't have some way to measure it, some way to track it, some way to prove it, then the business isn't gonna believe you. And that's really a lot of what we've filled the gaps in. Do, Do you think it's a question of the business doesn't believe you, or the business doesn't value it?

Kind of the same thing in the way I'm talking about it, which is, you know, if it's, if it's a clear value to the business, saves engineering time, it prevents customer pain. It prevents us from losing revenue. If they have confidence that our solution gets them, that we are, we're aligned, we're off to the races, we can get a lot done.

It's when people aren't sure. And we really have to go out and prove it that, you know, we got work to do. I agree.

I agree with you, man. Um, interesting stuff. io?

com. com if You want. Nice and easy Information on Gremlin.

Well, everybody tastes got io ai t That's my series A money went to our domain. I, I it's a best, More, more, more first time CEO advice here from Colton. Um, let's talk CubeCon.

Yeah. You guys, you guys made a big announcement. Yeah.

Talk to Us. Yeah. Excited to announce our Dynatrace partnership and integration.

We got a lot of great monitoring tools, but Dynatrace is one that really gave us what we needed to make it easy to do the right thing. This is something you'll hear me say a lot, make it easy to do the right thing. And when it comes to this kind of testing, you really have to know how's the system behaved?

Did it work well? Or else you're flying by blind. Right?

You know, and so Dynatrace makes it really easy for us to find the code, the code that we're testing, we can go find the monitors, automatically pull 'em in and associate 'em without the engineer having to go do a bunch of legwork. Uh, and so it allows us to, uh, one, create these services within Gremlin based on what's already created in Dynatrace. So we can just pull it into Gremlin, set up your services, set up the monitors, and now day one, you're ready to just click run and go get answers instead of doing this homework you have to do in advance.

Absolutely. You know, we work a lot with Dynatrace. I've had Dynatrace on here a number of times.

They really got their act together in this observability and space and everything. They, you know, Dynatrace is an interesting company as well, right? They, they're not new.

They've been around, they were originally a European company. They bought a big American company. They then merged.

And there was a little, I think for a couple of years back then, a little struggle over what culture and what vision they were following. You know, we didn't have something called observability then. Right.

It was a, a, uh, A-P-M-A-P-M. And, um, but now they've emerged over these last couple years with their act together, certainly. And they're killing It.

I've seen a lot of great product innovation. Yeah. And there's things that, you know, beyond just alerts and monitors, you know, when it comes to reliability, you need very fine grain data.

This is something where we need to know what's happening every second, not every five minutes. Right. And we found that granularity.

We found the nice places we could integrate to get that visibility. Yeah. No, I've, I've been impressed with the product innovation and, and the partnership.

Absolutely. Let me, let me put on my CEO rainmaker hat again here. All Right.

I love it. How, how is this translating in the market for you? Or how do you expect it to translate?

'cause it's new? How do you expect it to translate in the market? Well, I think we see a lot of, uh, shift in the observability market, uh, from our position.

A lot of companies are reevaluating their vendor of choice. Uh, cost is a big issue. Sure.

And so people are trying to right size and find that value. And the truth is, we are, we're pretty tied to that observability. If you can't see what's happening, you really can't do intelligent testing.

Agreed. Uh, and so this ability to really understand what's going on, integrate in and get that helps us to be able to just move so much faster, be able to get that value so much quicker. Agreed.

Agreed. So, yeah. Is there, is there plans of how you go into market here, though?

Is it, are they gonna sell this solution or offer it or talk about it, or, I mean, right now it's an, it's an integration and it's something that shows up in our product. We've got some things that we push into their product as well, so people can know what tests are happening and when they're occurring, they can correlate 'em with events. Um, but for us, we just, we have a lot of important Dynatrace customers.

We wanna see them be as successful as possible. And so leaning in with Dynatrace lets us go build a better product for our customers, which leads to our customers getting better adoption, better reliability results, customers. That's the flywheel we want to get going.

Love it. Other observations around coup con, I realize it's only day one. Well, if you were here yesterday, right?

There was a lot going on, but what, what, you know, what do you think? It's been interesting. I've, I have only been able to walk the floor a little bit.

Um, you know, I think the last conference or two, you were kind of getting beat over the head with ai. Yeah. I feel like it's balanced out just a little bit.

Not every single person's talking about it. Uh, you know, I thought it was a, a compliment. I got, uh, a customer came by the booth, uh, or a company, a customer company, not somebody I'd worked with directly.

And they asked for the details. We told 'em all about Gremlin. They're like, great, we want this.

And then he is like, you win because you didn't swear you didn't say the, the curse word at me. And I said, what? Ai, what curse word?

He said, ai. And I said, well, you know, there's, we've got some intelligence stuff. We think it's important, but that's not, we're not, we're not here to just jump AIing bandwagon answer for Everything.

Not, not to say that it's not real, it's not disruptive, it's not all of those things, but it's, it, frankly, it's not the answer for everything. Yeah. I think there's great uses and places for it.

I'm an engineer, so I'm a little cautiously optimistic. I want to see the value be proven. It's the same as chaos engineering.

I wanna see the value be proven. Yep. Before I go all in.

And look, we're, we're building intelligent capabilities that make it easy to do the right thing. Well, it's, you run the test, you know how your system responded. Well, the last step is you gotta go fix it.

So we built a great product this year that tells people how to fix the things they find. And to us, the key is it's credible. It's, it's accurate, you know, and it provides good advice.

And, you know, we're not, we didn't just slap it on everywhere. We put it in a very specific spot, we tuned it well, and we feel really good about those results. But, you know, the dirty secret is we're not just shelling it out to an LLM, you know, we're, we're doing some machine learning and modeling in the background, and you're treating it a bit more like a, a classic data science AI problem than just a, Hey, could the LLM solve this problem for me?

I love it. Hey, Colton, we're about outta time. com.

That's the important thing to remember. Good luck for the rest of CubeCon this week. Um, I guess we'll see you on Textron TV next.

Yeah. Yeah. I'm looking forward to it.

Thank you very much. A Colton Andrews, CEO of Gremlin here on Textron tv. We're gonna take a really short break 'cause I got my next victim sitting in the barber chair.

Ready to go? You're watching Tech Truck tv. We're live at CubeCon.

Hey everybody. We're at Ingram Micro one. We're talking innovation with my good friend Bill here.

How you doing Bill? Going On, Mike. Good to see you.

Good to see You. One of the things that's come up at the show is that we're talking to the partners about becoming more of business advisors rather than just technology advisors. And for years we told everybody that they were gonna be a trusted technology advisor.

What does it mean to be a business advisor? When and how does that transition them, the way partners engage with their customers? Absolutely.

You know, that's a great question, Mike. And, and you know, this, this industry, if it's one thing, it's always evolving. And, you know, when you think about technical advisor versus business advisor, right?

I think today it's more around business outcomes. Companies are looking for business outcomes. They're looking for ways to differentiate themselves in market.

They're looking for ways to be ahead of the competition. And so it's no longer just about the technology, it's about the overall desire of the organization and where they see themselves going and how they see themselves showing up differentiated from the rest of the field. And so I think being able to have that business conversation around where a company is looking to go, where they see themselves in three to five years, and how they wanna show up to their partners.

It's more critical today than ever before. The technology is great and it's required, but it's more than technology. It's people, it's process, it's how we show up.

And I think that's what, what's changed. Does that change any of the business models of the partners? Am I gonna tie my, uh, revenue to an outcome versus maybe traditional time and labor or some sort of annual per c fees?

Is that gonna change? You Know, I think as this industry evolves, everything changes, right? And I, and, and I know we're at this, uh, really exciting time in our industry with, you know, AI that we talk about all the time.

But that's forcing all of us to rethink how we do things. How do we compensate, how do we look for value and where we can capture value and how we can monetize value. So I do believe it's going to change how companies look at rewards and recognition, how they look at compensation models and how they look to drive value in the interactions they're having with their partners.

Do the partners need to go deeper in the business? And I'm asking this because, yeah, it's one thing to provide, I don't know, an email security service, but it's another thing to go in and understand a workflow that drives revenue and how to optimize it to, you know, create a better bottom line for the customer. So does the partner have to get in there and kinda understand a little bit more about each vertical industry and what those people are doing to apply the tech to that process?

So when you think about, I, I always look at now, the deeper you can get into the process, the more you can understand where can you automate, where can you find efficiencies so that you can free up the rest of the time for your individuals to be doing far more proactive consultative or a more valuable, um, work for the, for the organization versus that transactional. And that sometime cumbersome, you know, operational stuff. Mm-hmm.

So the deeper you get in the business, the more information you will have. Of course, you can't walk down the street these days without somebody leaping out to tell you about their great new AI thing, and this show is no different. Um, but to that point, uh, how do you have that conversation with people?

'cause I think on the one hand, you've got business executives who think some magical thing is gonna instantly happen and transform the world. And then you've got, uh, some employees maybe who are like, well, this is interesting, but it only, you know, helps me write a better email. But that doesn't really change my world.

Right? How do I kind of navigate that spectrum as a partner and engage those different constituents? That's a great point, Mike.

And, and the thing is, is everybody's gonna be coming at it from a different perspective, right? You have business owners who are trying to understand, what does this mean for me? How do I capture the value that this is supposed to provide?

Okay? You have line line workers, folks who are driving different business units within a company who are trying to figure out how can they take advantage to help automate drive efficiency and streamline their go to market strategy. And then you have, in some cases, associates are saying, Hey, what does this mean to my job?

And so I think it's really being clear what the message around what you're trying to accomplish, right? I think the focus is automation. And I think if that does free up part of someone's day, you're able to repurpose that individual on a more strategic focus for the business.

I think it's a win-win for everybody. The work that we used to think was valuable because it was very time intensive and it was very transactional, is not necessarily the kind of value we want to create as companies. When we do business together, the value we want to create is a true partnership where we're looking for growth, we're understanding where opportunities lie around the corner, and we're building a strategy to go capture those opportunities.

I think sometimes we get ahead of ourselves a little bit when it comes to emerging technologies like ai. Not a shocker. But, um, are we entering like a new phase here?

'cause we're talking now about agentic ai and it might actually deliver more of the promise that we initially made on the first round of AI with copilots, which, you know, are kind of assistance to people. But agentic ai, it feels more like an autonomous process that I'm letting something get automated through. And that's a different mindset and a different way of thinking about a business process.

But is that, like, are we on some sort of arc of a journey here? I mean, agentic AI is truly transforming the way everyone thinks about what they do. And to be able to build an agent that can, that can focus on a specific task or project, and actually learn how to make it better and grow in efficiency as it continues to learn and evolve, is truly kind of mind boggling when you think about it.

And it's exciting because it opens a door to a ton of possibility. And I really think it's, it, it's only limited to people's imagination right now, really thinking about how they can leverage this technology to get into a business process at every step of the journey and find ways to streamline, automate, and drive efficiency and make a better experience at the end of the day. Mm-hmm.

I sometimes feel like the partners wind up being diplomats within the customers that they service, right? There's a lot of constituencies that sometimes they have competing agendas. And so do the partners, if they're gonna be business advisors, have to kind of get in there and start understanding the dynamics and the relationships between the IT people, the marketing people, and the salespeople, which may not always be, you know, an agreement with each other.

In fact, I'd be hard pressed to find an example where everything works, you know, all happy and everybody's working together, uh, in symphony. I think, uh, you're, you're 100% correct in the assumption that companies are going to have different priorities. Different business departments are gonna have different priorities.

And it is critical for business partners to understand every aspect of that, of that organization. How they operate. Where is the influence, you know, where is the sphere of influence?

How are they able to build trust amongst each one of the constituents? Because that's the key piece, right? If the, if the organization believes, oh, this guy has always been working with it.

They're, they're on the side of it, they're not really thinking about a business outcome, they're not really thinking about how they're driving, uh, efficiency and, and, and cost to serve. You have to be able to show the company that you have an interest in each one of the pillars for their success and how much they play a role in what each other do. See companies get siloed and they get very defensive over their areas of business.

I think we have to all rethink that. And we have to think we're all here for one reason. We're here to drive one objective, which is the success of an organization.

And it takes each of those functional areas to get it done. Each one plays a critical role. So how do we work closer together?

So the business partner has a great opportunity to bridge that gap, help them understand how the work they're doing is going to help everyone in the organization be better and have the company succeed at a higher level than ever before. So they sit in a very unique spot today, more so than ever before. How should the partners think about their own talent pool to accomplish that goal?

And I asked the question because I love the partners, but a lot of them are what I call accidental entrepreneurs that came outta the IT world. And they don't necessarily understand the business side all that well. Should they go out and recruit people who have business expertise in a vertical, whether it's manufacturing, retail, or whatever it might be?

I do believe that would be a great step. Because if you think about it, if you are, if, if it's not an area where you came from, where you're familiar with all the nuances and, and you want to go, you know, what's the first thing that you do personally in your personal life, right? You go do research and you go figure out what do I need to know before I go make a purchase or go make a decision in my life?

I'm gonna gonna go get information. So I think it's really important for partners to figure out what do they want to do? Where do they want to go?

Who do they want to be? And then once they understand their strategy and their plan, then go find the resources required to be able to drive success into that, into that strategy, into that focus. And I think getting people who are experts in the field that you wanna play in is a great step to be able to help you build and shape an organization to support and grow that piece of the business.

So what's your best advice to the leaders of these organizations? How do I have that conversation with my teams in a way that it resonates? 'cause I think a lot of them are also, well, frankly, most of them are so busy putting out fires that they don't have a minute to think about fire prevention.

But how do I create that space? You've gotta set the North star. You've got, as a leader, you've gotta set the direction and you've gotta let people know where you're going and then you have to give them the why.

It's one thing to tell people what you're doing, but if you don't tell 'em the why, I think you're gonna lose a lot of the people along the way. Or you might not get the kind of buy-in that you're looking for. So you have to be able to explain why you're taking the steps, you're, you're taking, why you're making the changes you're doing, the, the changes that you're making, and how are you positioning your organization for success, their success, so that collectively everybody sees the big picture and they understand what their role is in driving that.

I think one of the other bigger challenges here, and it's right here on the show floor, there's so many vendors, so many technologies, so many piece parts that have to go into something to create something that feels like a solution. How do partners navigate all that? Because it's a little overwhelming, let's be honest.

And I'm in tech for 30 years and I find it overwhelming, Right? I think I'd like to think that's where Ingram comes to play. I really think that that's where we can play a bigger role.

And I think it's a role we've played for many, many years. It just continues to get more sophisticated as we go, as technology continues to get more sophisticated. But, you know, our job is always to go find the best and the brightest technologies that are entering into our marketplace.

We're there to vet those companies out and make sure they're ready for primetime, they're ready to get in the game and help our partners grow their businesses. And so our job is to help navigate and help our partners navigate that vendor ecosystem to understand how to put together the best case scenario for the customer's exact needs. And I think now we can be very prescriptive and we can get very focused and, and do a great job with a lot of the different players that are in this space.

This is a huge market. It's trillions of dollars of tam. There is a lot to go around.

And all of the vendors here know that. They just wanna know where they can be focused, where they can have the most success and drive value into the equation so that it's a sticky relationship that lasts a test of time. And how does that change their relationship with a distributor?

Like you guys, or, I'm not even sure you are in a distributor anymore, 'cause you're so much more than that, but it seems like to me, I look at the portfolio and there's all these professional services now that I can lean on as a partner, and I'm kind of just, I don't need to invest in hiring all those people. I need some, but right. It feels like I can lean pretty heavily on you guys.

And has that changed the relationship? It has. It absolutely has.

And it's something that you're gonna see us really double down on in years to come. So Tim Aman, uh, who recently, uh, rejoined the US business, came over from leading our Australia business, is running our services practice. And I think what he's bringing to the table is a really a, a a, a great tenured approach in this industry.

He's got a lot of, uh, learnings from working around the world, and I think what he's able to do now is understand what are the solutions and the services that partners are really looking for so that we can make that invest investment proactively. And partners don't need to do that right outta the gate. They can find opportunities, lean on ENG or micro get scale, and then add competencies and capabilities as they choose so they can leverage our experience and expertise as an extension of their business.

But then they can grow and add on whenever they're ready. And our job is to make sure we help them understand that roadmap and we help them understand where the opportunities exist and let 'em capitalize on those opportunities at a very low cost of entry and then continue to grow for profitably. So let me ask you this, what's top of mind for you?

And then when you pull into the parking lot in the morning and you're about to go in the office, and before everybody disrupts whatever it is you're thinking about, like what are the top two or three things that you're looking at to accomplish and kind of, you know, if you looked at the next year, if they happen, what would be the definition of success? I will tell you what keeps, what keeps me very, very laser focused right now are the people. Our processes and our system, our platform, those three things, people, process and platform is what I think about every single day.

How, how do I leverage the platform, the power of our platform, drive a differentiated experience? How do I elevate the people in the organization to be that true trusted advisor alongside our partners to help them find growth and scale? And then how do I fix the processes that exist around the ecosystem to make it easier to do business with Ingram and make it more efficient for our partners to serve their customers?

If I can do those three things, I think I, I think that's success. Alright. Hey folks, you heard it here.

People process and platform. The funny thing about that is the more things change, the more they stay the same. Hey buddy, thanks for coming by.

Thanks Michael. We'll be back in a minute. Hey everybody, welcome back to day two of Ingram Micro one, and we're having a little chat about what's going on in Latin America with my new friend Luis here.

How you doing buddy? Hi, Mike. Nice meeting you.

Nice to meet you. What is the state of the market in Latin America? I think a lot of our folks who are watching this may not know, but I know it's highly competitive and I know it's highly fragmented, so, you know, what are you seeing out there and what's going on?

Yeah, We're seeing, um, you know, the dynamism in the market today. I think it's one of the best times for that. So the market, it's, it's growing.

The future is bright for the technology market because of all these changes that are happening, right? All this evolution on technology, AI adoption, and, you know, the cloud business, which is exploding in some, in some countries drive that, uh, the, the optimism is across the board, right? You know, that in Latin America we have a lot of countries that are catching up on technology.

So that open also the door for, you know, big opportunities. A lot of those countries are also maybe skipping generations of technology because they're going to the latest and greatest. They're not just going through the last thing, right?

Absolutely. Absolutely right. They are catching up on the new trends that are seeing and, uh, you know, the new, the new necessity also of all the businesses to become much more productive.

So the technology is helping and, and enabling those, those companies also to become much more effective. Are there partners in this various countries getting better at differentiating themselves? And do they have some ability to say, I do something that the other one doesn't?

Yeah, I, I think it has been a journey, right? It has been a journey. Obviously we have huge partners that have big different differentiators in the, in the markets, right?

Another ones that start like their journey of transformation, right? From being legacy partners or partners that we're focused on transacting now to, to become, uh, solution providers, right? So it has been a, a huge evolution from the, from the channel I would say.

We had very, very good partners that provide solutions or have that have been very innovative on, on developing solutions that today are send cross the world. One of the themes of the conference has been this notion of becoming more of a business process consultant, a little more focused on the business outcome and less on the enabling tech per se. I think a lot of partners focused on being the trusted technology advisor for years, which is good.

Yeah. But it feels like there's a ship going on where they end customers saying, I need you to be more involved in the business process. Are you seeing that in Latin America?

Absolutely. Absolutely. Right.

The, the, the businesses are requiring that the it guys become much more consultants and become part of the, the solution of the company, of what the company is requiring. And we have several of our, of our partners that have gone through that transformation already, right? They, they have become like the trust advisor for our end users where they rely on, on, on their, their advisors, on the, on their, uh, partners, uh, you know, to come up and build solutions that help the company become much more effective, right?

To really drive, uh, their, their results that they are expecting, right? The companies today, they don't have, I would say all the vision on what they could get out of the technology, but when they got a good, a good advisor, that changes, right? The advisor helps them, or, and our channel helps them to understand what are all those opportunities that could be, that could be fulfilled with technology, you know, and we are seeing that, we're seeing a, a lot of, uh, adoption in cloud, for example, right?

The adoption in cloud that we're seeing in several countries is huge, and it's because the demand has increased at the end user level, right? They want to be much more secure. They want to have their, their information available at any time.

So we, we've seen that, uh, level every time going up and up and up. The requirements have been, you know, raised in the, the bar. I think every channel partner around the world wrestles with this following issue skills, getting the right skills, making sure their teams are up to date on skills.

Now we're asking them to kind of become more business experts. Where do they get that expertise to kind of converge the business acumen with the technology skills? Right.

Well, first, First of all, I would say start with the willingness right of them to change on moving from selling hardware now to sell solutions or, or be together with a, with end user. Uh, and we work together with them. We have several programs through the region where we start with an assessment on where are they today and what do they need to do in order to become much more a solution seller, a really integrator that will help the, the end user.

So we have seen great changes in some partners that went from selling hardware that today they're, they are very good service providers, right? That went through the whole process with us from understanding where they, where they were and where, where those, uh, what were those requirements that they need to start process analyzing their sales force and also their skills, right? To become much more integrated with their end users.

So it has been a fantastic, a fantastic journey in, in several channels and in several countries. I think there's also a fine line between the skills that I go higher versus maybe relying more on you and Ingram for professional services as far as I can tell. Walking around, you guys have built a fairly deep bench, so are the partners starting to tap into that to kind of achieve that goal?

Absolutely. Absolutely. I would say today, one of the most difficult things today is to get a customer, but once you get a customer and you are partnering with us, we can basically complete your value offering without having you, or without the, without the channel having to build the full infrastructure because we are behind.

So we can support a channel with our infrastructure, with our expertise, with all our technical resources to really support their value proposition so they can go out and sell anything without necessarily having a full infrastructure to support the requirements of the customer. So we have a, a full stack of professional services, a full stack of technical resources that could support the end user requirements together with the, with the, with the partner. So it has been a, a very good, uh, a very good journey and alignment with our, with our partners, supporting them with our professional services offering.

This is my assumption, but I think if you're selling more of a consulting engagement and a, and helping with a business outcome, there's less conversation about, um, you know, how to compare the price of one server versus another, and we don't wind up in this kinda, you know, race to the bottom kind of feeling. Absolutely. Absolutely.

I would say the price is not the most important piece anymore, right? Obviously it's a, it's a, a big piece because they want, everybody wants to maximize their, their margins and, and their profitability, right? But at the end, when you build up a solution, it's not necessarily easy to compare on the price, right?

When you build up a solution that comes together with, uh, uh, with services, but also because also what we are looking with the services, it's like to create the thickness to the customer, right? So the customer, once they start seeing the benefit of the services, they start asking for more and more and more and more because they see the benefit in their, in their, uh, in their company results. So that, that's, that's what really the vision that we want to accomplish, right?

We want to create a huge thickness to the customers so they won't have to look for another, for another partner, right. We're here at the show, and I don't think you can walk maybe 20 yards without running into somebody talking about ai. Um, what are the partners telling you about the opportunities there?

What are they looking for? What do they need? You know, I, I would say it's, it's in two levels.

There's a, a big piece of our channel that today is trying to understand what, how to sell ai, how to use it first, and then how to sell it, right? Those are the ones that we are still working, you know, that we have an AI enable enablement program with them where we, where we took them again, with an assessment on where they are all the way until they, they become really experts on selling ai. And the other one, it's a channel that, that I would say was born more on the, on the solutions space that quickly adopted the ai, uh, the AI trend, right?

Those guys, we have set, we have seen, uh, you know, huge, uh, use cases in retail, in manufacturing, uh, in, in, uh, in health that are helping also the, the communities and the end users, you know, to become much more, uh, I would say u the, the use of the, of the technology. It's helping them to become much more productive and more effective. And so, so we have clear examples in several countries.

Ingram, of course, has invested heavily in AI to take a lot of the friction out of the, the process of transactions and all of the things that's involved with that. Um, is that gonna play out with the partners and the partners also investing in AI on their side and the two together might, you know, create a, a channel that is friction free maybe, is something Yeah, yeah, Yeah. No, absolutely.

Absolutely. You know, that we have been developing our platform, right? Ex vantage, we have been already for over three years developing the, the platform, and every day we see more traction, right?

We see the, the partners using it much more frequently, taking the advantage of all the data and all the insights that they could get out of the, out of the, out of the platform. Now, the platform's also helping us to become, to become much more proactive on bringing opportunities to the channel, right? That we saw through the data, through all the analytics that the platform is giving us through all, all of these, uh, AI models that, uh, that the platform works with.

Uh, it's creating, you know, a lot of, uh, opportunities that today, or that the customer that, that our partners weren't seeing, no, now they're seeing it because we are putting them on the table. We're telling them, okay, you, if you're selling this, a lot of customers that they sell this also sell this, so you should also explore, right? Complimenting your offer with all these products or with all these solutions, or with all these services, right?

So I think it's, it's getting traction. And on the other side, the customers are also seeing the benefit, the operational benefit of being, working with the platform today, right? It's much more effective for them to devote time, you know, to the, to the relations and to the, you know, to the, uh, strategy development with us, while the platform takes care of all the transactional piece, you know, so it's, it's, we are gaining traction every time.

Mm-hmm. Historically, the best partners, I think, have built some sort of solution or something that differentiates with them, and a lot of times they work with you guys to kind of craft that. I think AI is gonna drive that further and deeper, because I need something that is tailored specifically to a business process.

So are you hearing more from the partners about collaborating with you guys to build some unique solutions? Absolutely. Absolutely.

You know, that we, we have basically all the, all our vendors solutions. So we promote all our vendors, ai, AI solutions, right? So there's a stack of already I would say use cases, opportunities already there.

Uh, but what we do with the customers is that we work together on the specific requirements of their customer, of the end users or, or the users, right? So collectively, we build solutions that are much more effective according to what the end user is requesting today. So we have all these, uh, I would say processes and communication.

We are all the time with, uh, trainings, we're working with trainings, we're working with seminars, right? In order to, to work with them. And we also go with them to create demand, right?

To generate demand without the end users. Like talking about all the opportunities that AI could bring to those companies. So we are, it's, this is a, I would say an ongoing, an ongoing process.

And obviously we start with those guys that we're already selling solutions, right? Because that's, I would say that those, those are the most feasible to, to start, like accomplishing or building that business model that could support the end users. We, of course, live in a global economy, and of course, times are interesting, but still we see more international cooperation, especially around IT solutions.

How is that impacting the partners down in Latin America? Are they working more closely with vendors and partners around the world? Absolutely.

I mean, uh, we have examples in Latin America of countries that are really, are well advanced in the adoption of the technologies. One, a clear example is Brazil, right? Brazil is one of our, I would say worldwide, one of our top subsidiaries on the adoption or selling on cloud and solutions.

So we have huge partners in Brazil that deliver great solutions. So we took advantage of that also, to go and train and share best practices and also share those solutions to other countries. So we're trying all, all the time to learn and to try to, you know, to export from those countries that have really good practices to export them to the rest of the, of the LATAM countries, and in some cases, to the world, because we have really good, um, and develop partners in, in, in our countries also, Are there partners in these various countries working with each other across borders to build solutions themselves?

Ye yes. And we are starting now to build our trust tax alliance community for Latin America, right? Where we want the customers or our partners to start in, uh, you know, uh, interacting between them through the region so they can, they can expand to other latitudes with their, with their solutions, but not necessarily having to have, or having to have the full infrastructure based in those other countries so they can go much more quickly or much more rapidly expanding their solutions to other countries.

All right, so we're coming up to the end of the year. You get your little crystal ball out. What's 2026 look like to you?

It's, I, I think 2026 is gonna be a bright year, right? The adoption continues, uh, the adoption and the necessity of te of technology continue, continue growing rapidly, right? We just saw all the trends and what Id c is predict predicting for, uh, for next year.

And we saw a huge growth, double digit growth, basically in everything, even in devices. The growth is not gonna be that high, but will start, will continue growing because the devices will be the base for the usage of the technology, right? At any, at any level.

So we, we still see, uh, all our, our technology and products with good trends of growth for the, for the following years. So that is exciting for us, right? So we just need to continue building and complementing all, all these solutions that could help us, you know, build a huge value proposition for the end users, right?

So that's, that's, I, I think that's what we're gonna be continue working on, right? All right. Hey, folks, like the man said, things are happening in Latin America, and I can't wait to see what you guys are doing this time next year.

Thank you, Mike. Thank you. Thank you.

And we'll be back in a minute. I, Hey guys, thanks for the throw. We're here with Todd Cassidy, who is managing vice president and divisional CIO for associate experience at Capital One, and we're talking about what it takes to build and foster a tech culture.

Todd, welcome to the show. Hi, Mike. It's great to be here with you.

You know, everybody and his brother who's in the tech sector, who's always trying to, uh, get the latest and greatest kind of thing and play with various toys. And, and so the attitude is, right, but how do you harness that in a way that's productive for the company? Because, well, there has to be something that gets generated at the end of the day, right?

Absolutely. Um, you know, I think it, our, our engineers crave the latest tools in the marketplace, and, and we really want to encourage them to take advantage of the evolving, you know, marketplace of tools that are out there. And, um, you know, I, I think a couple things really set this up for us.

Uh, capital One's investment, um, in our modern tech stack, I think really gives a, a nice, um, opportunity for our developers to use the latest technologies. We also work hard to maintain a open culture that fosters collaboration and encourages innovative ideas to solving problems. And we think innovation really thrives when associates feel supported and have room to explore ideas.

And that's really where we, we emphasize collaboration, knowledge sharing, and celebrating experimentation. Um, our developer first culture, um, ensures that our team has the best tools and infrastructure to innovate at scale. And there's really three programs I would, I would call out that we leverage to inspire innovation inside the company.

Um, the first is we've had a lot of focus on patent innovations and, um, in recent years we've, we've been at the leaderboard for the number of patents granted each year and have over 6,000 US patents to date. Um, we also have a recognition program internally, uh, that we call Tech Excellence, uh, which is designed to recognize and reward contributions of our technology teams. Um, we publicly share the winners across the company quarterly, and then those quarterly winners compete for our annual CIO Elite Award.

Um, and the recognition that comes along with this is also showcases what accomplishments the team has and, and shares that broadly. Um, lastly, uh, the one thing I would call out here is we also have an internal conference, um, that allows our teams to demo innovations that they have with the rest of the company. Um, this in, uh, this is an annual conference that we do internally with keynote speakers and curated demos from teams, um, across the company that allow us, uh, allows us to share that innovation broadly and, and, you know, create reuse and, and celebrate those accomplishments.

When the developer first culture, how do you strike a balance between, I guess, what we'll call operational excellence and standardization and the fact that the developers want to be able to play with whatever tool they find and do something? That's a great question. Um, certainly we have a big focus on being well managed and, um, resiliency of our infrastructure.

Um, but we also recognize that technology advances quickly and our, you know, developers want to work on the latest technologies and apply that to the business problems they have. And I think there's a number of factors that, that we have in place that support this. First is, uh, we, we have a continuous learning culture and, um, I think that just encourages our associates to continue to evolve their skills, um, to support that.

We have an, what we call tech college. It's an internal learning platform that allows, uh, both self-paced as well as instructor-led training that are as are encouraged to leverage for upskilling. Um, uh, we also provide our associates with leading industry tools.

Um, particularly coding assistant tools is, is a hot theme, uh, right now. And we really want to, you know, create time for our developers to experiment and learn these tools and then apply them to, as I mentioned, our modern tech stack. And we have really challenging business problems to apply these new skills towards and take advantage, advantage of the new tools.

Um, you know, as an example of this, when we were an early adopter of, uh, Amazon workspaces, um, I'm sorry, AWS um, sorry, I had my other hat on for, for other aspects of my, of my role. But as we proceeded that migration to the public cloud with AWS, we had a big focus on, uh, training our associates about AWS. And so we had AWS certification initiatives really to help raise the water level because public cloud was not something that we were in before that.

And so we wanted all of our associates to learn that. Um, what I would say is, in my experience, when you, when you provide developers with a continuous learning environment or in culture, um, industry leading tools, time to experiment with them and learn them a modern tech stack to apply them to, and then create a business challenges to, uh, solve using those tools. I just think amazing things happen when those things come together.

You hear the phrase platform engineering a lot these days, and it's all about kind of we're making a, or providing at least a better developer experience. But I can't help but wonder, were you guys kind of doing that all along and you kind of woke up one morning and said, well, it's nice that somebody put a name to it, but that's kind of the way we operate. Yes.

I, I do, I do think, uh, I would say we, we've always had a focus on this. I think, uh, you know, one morning that we've had is we've moved from data centers to being in the public cloud, is our developers had to take on the role of full stack engineering, including, you know, the, the infrastructure parts with the public cloud, that includes vulnerability management. Some run the engine went up.

And so as we reflect on that, we're really focused on automating as much of that as possible so that our developers can spend their time on the most important aspects of creative problem solving and innovating, um, on top of that versus the kind of rote tasks that can kind of come along with managing, um, that. And so the, the more that we can kind of peel away at tasks that are not really necessary for our developers to focus on, um, is a big area of, of, um, of focus for us right now. Mm-hmm.

Do you think maybe, you know, early on with Full Stack, we were all talking about shift left, and I wonder maybe if we shifted too much left and the developers got too much cognitive load and now we're trying to swing the pendulum back to something in the middle. I, well, I guess my perspective was, or is that I do think we shifted left and probably shifted left before we had some of the tooling in place. That takes some of the burden off of the developers as, as we shifted.

Um, I personally still really like the full stack, um, um, accountability that comes along with that and the capability that comes along with that. You know, if I went back to, um, you know, our data center days, our developers were frustrated that they often had to wait for infrastructure to be ready for them in order to, um, you know, begin their project. If they needed a server and, and we didn't have that capacity, they might need to be ordered and then be racked and stacked before they could even begin their project today, within minutes, they can spin up new environments and, and really take control.

And just our speed to market has, um, advanced dramatically. I would also say our re the resiliency of the solutions we put in place has, uh, also dramatically increased. Um, with that said, though, I, I think the, the focus we have around the automation around some of those aspects and just taking some of that burden off of their workload is, is, uh, key to where we're headed.

Of course, you can't walk down the street these days without somebody leaping out to tell you about their great new AI thing. But what are you guys doing with AI as it relates to software engineering? So we, we have, um, a number of, you know, large initiatives across the company on ai.

And I think Capital One's investment in our modern tech stack and our data ecosystem, along with the strength of our AI specific talent, I think really dispositions us to be at the forefront of leveraging ai. We have a number of initiatives internally, um, where we are building our own LLMs and, and applying that in different ways across the company. Um, I, I think, you know, all, all, you know, we're also providing a lot of, uh, you know, commercially available products for our associates, particularly coding assistance as well as Gemini, um, Google Gemini, which we rolled out across the enterprise this year, not just for our technology organization, but for the entire organization.

And we intend to have that in the hands of all associates by year end. Um, I think, you know, there's a common theme here across these, these tools. We're gonna be building things internally ourselves.

We're also gonna use commercial products and, and roll those out to our associates. But I think empowering them to learn and get the most value out of those tools is gonna be a bit of a journey. Um, so far we, we've, uh, you know, we're allowing a lot of experimentation, um, but I think that there's more we can be doing in, in and are intending to do to really help our, as associates take the, take the most and get the, you know, get the most value out of these tools as we look ahead.

Yeah, I think one of the issues that people are wrestling with is we're clearly generating more code, but more code doesn't necessarily translate directly into more applications being deployed, because a lot of that code needs to be reviewed, and there's a lot of other processes. So how do you kind of go in and start looking at some of the bottlenecks in the process, and how do you think about eliminating this? I think it all comes down to automation.

Um, you know, we, we have objectives to automate testing, um, to where we don't do any manual testing before deployment to where we can get to a place to where we're doing continuous deployment, um, across the environment. And I think that will be a big unlock for us now. Clearly, um, the resiliency of our solutions and, and making sure that we don't have disruption as we have change is gonna be important.

I would say that we, we've been on a really incredible journey of, of just the resiliency of our solutions. I'll say cloud-based, you know, advantages, uh, play out pretty big here in what we've seen from a resiliency perspective in recent years. And we're really proceeding, we're performing right now at all time lows as a company in terms of you, you know, technology outages and disruption.

Um, and what's pretty amazing about that is we've had a pretty robust, um, you know, technology agenda as we've been transforming our tech stack, moving to the public cloud, and a number of other things that we've been doing as we've made that shift. And our number of releases has continued to rise dramatically. Um, our number of incidents has decreased dramatically along that same time period, which I think just shows our balanced per, you know, a balanced approach from wanting to be more productive, but also doing that in a well-managed way.

Mm-hmm. I don't think it's much of a secret that occasionally developers and the centralized IT team don't always get along. So how did you, you know, bring together these two disparate cultures in a way that kind of gets them to work together cohesively short of, uh, maybe locking everybody in a room till they see since?

Yeah. Um, you know, I have, uh, I've been with Capital One for a long time, and I've worked in all different areas of the company from our, our card business to some of our enterprise technology functions. And, um, I just think our collaborative culture and, um, having shared goals across teams, I don't see major issues.

Um, with this. Now, I will say it was a bit more challenging when we had a separate infrastructure team that was managing data centers from, you know, the ability of what comes with public cloud. It just allows a lot less dependencies across teams as the, you know, the full stack developers have control of their infrastructure through the public cloud.

And, and it minimizes some of that, but, but your question's a good one. I think, you know, clearly there's still gonna be dependencies, um, across many of our horizontal functions, whether it's with cyber or network. Um, you know, the team that I, I lead our associate experience team and others that partner closely, um, with those with, um, you know, our, our customer focused, uh, teams across the, the company.

So ultimately, what's your best advice for your fellow CIOs when it comes to dealing with developers? Well, you know, we, we believe that a attracting and growing talent is the most important role, um, that our technology leaders have. And I think from a, a attraction perspective, you know, or sorry, from attracting developers to our, to our environment, we look for builders, people that are naturally curious and, and passionate about solving problems with technology.

Um, and, you know, technical skills matter, but we also look for creative problem solvers and adaptability and a learning mindset. And once those engineers join, we invest heavily in their growth, um, through a bunch of different things from structured learning programs, mentorships, internal events, great assignments, um, and rotational experiences, which are really intended to expand impact and growth. Um, you know, from a, um, how we continue to grow our associates, I think there's also a bunch of factors that come together from, um, creating a, a, a learning, uh, a continuous learning environment, I think is critical.

Um, I think setting an example of that and encouraging that, whether it's through, you know, an internal tech college like we have or other mechanisms, um, we also provide our associates with, as I mentioned, industry leading tools and time to learn and experiment. Um, which I think is, is, is really important I think in my experience. When you provide developers with a culture that's, you know, pivots around continuous learning, industry, leading tools, time to experiment and learn a modern tech stack and challenging business problems, just amazing things happen when those things come together.

Um, folks, you're hearing it here when it comes to software development and developers in any age, there's no substitute for a good culture. Hey, Todd, thanks for being on the show. Thanks, Mike.

It was great to be with you. All right, and back to you guys in studio. Everybody's trying to figure out how AI fits into the political, social, uh, individual.

And of course, it landscape, people are trying to get out ahead of it. Uh, people are, some people are trying to step out of the way and, and see what develops. That's what we're talking about on this episode of utilizing ai.

Welcome to utilizing ai, the podcast focused on practical applications of artificial intelligence from the Futurum group. Each episode brings together a diverse perspectives to explore news and use cases in the way in which AI is transforming enterprise IT and the industries it serves. I'm your host, Stephen Foskett, president of the Tech Field, a business unit here at the RUM Group.

Before we dive into the discussion, let's meet who's on the panel today. Hi, I'm Nick Patience on the AI Practice lead, um, at Futurum Research. Hey everybody.

I'm Mike Baard, chief Content Officer for the Text Strong Group when we publish Textron AI among other things. Absolutely. And, um, you know, Mike, uh, you and I are on the Textron Gang quite often talking about, uh, news and what's going on in the industry.

Um, and of course, AI is just everywhere. It's become, uh, front page news for basically everything that's happening in the world today. Uh, Nick, uh, let's kick things off by talking a little bit about the ways in which governments are trying to get involved in ai.

Sure, yeah. I think it's been apparent, um, for a long time that AI will be a regulated industry of some, uh, uh, to some extent, to a large extent or another. It already is in, in, obviously in in China, uh, to a much greater extent.

But one thing that kind of caught my eye, um, was, uh, sort of talk here in, in Europe, uh, I'm in London, but you know, we still consider ourselves part of Europe, um, that the, um, European Commission is thinking of watering down somewhat. The EU AI Act, which has already passed, hasn't been fully implemented in every, every, uh, every country yet, all, all the 27 countries. But they're talking about that.

And it, you know, there was a story, I think it was in the FT originally, and there were, there was saying about, you know, the commissions come under a bit of pressure from big tech companies, um, not surprisingly. Um, and they're talking about having grace year long grace periods before certain aspects have to be, uh, implemented. Those you, you may remember, it has a kind of, um, a risk hierarchy of like, you know, unacceptable risk, high risk, medium risk, low risk types of, uh, applications, and low risk would be spam filters.

So everybody uses it, no problem at all. High risk and things like that would be, um, you know, facial recognition and unacceptable risk things, facial recognition. So it's, it's an interesting if that's, if that's gonna happen.

I mean, there's been a lot of talk over the years when the EU was trying to figure this out, that they were trying to, um, put the cart before the horse somewhat and regulate something that hadn't come out yet. In fact, just before they, they passed it, um, you know, or they were, they were negotiating chat, GPT came out, and that caused 'em then to rewrite drafts. Um, you know, we better to get this, this generative AI stuff in there.

Um, and so they were trying to react to that. And now of course, you know, we've got AgTech coming up, uh, and, and those kind of things. But if for enterprises, for those that, you know, this is utilizing ai, so it's, you know, it, it could be relatively good news.

Uh, and obviously this is not just EU headquartered companies. This is companies doing business within the eu. Um, so it could help them, it could, it could help enterprises, you know, reduce their, uh, immediate term compliance needs and compliance costs, uh, and things like that.

So it's a, it's something we'll, uh, I'll certainly, uh, be keeping my eye on because, you know, compliance and sovereignty and, and all these kind of things are, are really, really key issues in ai. You know, I'm having a hard time wrapping my head around this whole thing, and I'm hoping you can gimme some insights here, because on this side of the pond, it kind of looks like, well, you know, the EU for some folks was gonna save us from ourselves and institute all these rules, but there's also people who say maybe there is a legitimate case being made here for not having so many prescriptive rules so early. And other folks, of course would say, you know, those folks in Brussels will just overregulate everything, and they're basically gonna be like, you know, just standing in the way.

So what is the mood over there? I think the, you know, especially in, you know, I may be in London, but especially in continental Europe, it is quite a fundamentally different way of looking at things, um, and certainly on the data privacy issues. So that's why obviously GDPR, which came into that, came into, um, effect in 2018.

Um, you know, those kind of data privacy issues, privacy, privacy, call it what you will, um, is extremely embedded in the culture. And so it, it does seem a little bit, um, weird, I think to to, to some folks in North America that, that kind of obsession. But, you know, these things go back with a, a long and a somewhat troubled history.

But, uh, I think it's, you know, I think there is a, certainly a case to be saying they were trying to, they were, you know, as I said, what the cart before the horse, the flip side of saying that is, I think there was a 75 year gap between the Model T Ford, um, the first model T Fords being shipped and seat belts being mandatory in the us, you know, and obviously hundreds of thousands of people died in car accidents between, you know, the, the first and the second thing. This is not the same thing. You know, I'm definitely not on the kind of, um, do munging, um, AI is gonna kill us all, um, side of the argument.

I think there is certainly though, um, you know, data privacy issues that are look completely legitimate about, um, about, you know what, it's not so much what companies collect because I think people that kind of cat out the bag. It's, it's whether the government can have access through back doors, um, you know, to your, to, to your data. And I think that we're seeing, we're seeing a lot of, uh, issues with that, you know, in here in the UK with Apple, um, you know, and, and the government, you know, um, negotiating with them on that.

Um, but the, but the, uh, the EUA act is, is pretty, is pretty broad, and to say it's very sort of risk focused. Well, the, on the GDPR front, that's a really interesting point that Mike makes though. Um, how do they square that on that side of the pond, uh, with all of the intense data collection that's gone into the building of these AI models and the kind of data collection that's gonna be feeding these AI applications in the future.

Um, are they expected to, uh, abide by GDPR rules? Or is it sort of like a, eh, well accept ai? I think except, yeah, I mean, LLMs and, and how they vacuum up stuff on the web, I, I guess a lot of that doesn't really count as, um, data that's private.

So, you know, vacuuming up publicly available data is, is, uh, is not really covered by it. Um, and so I think it's from that point of view, while some people worry about it, um, it's also quite difficult to figure out obviously, what the training sets were or are because, um, yeah, the companies are not exactly particularly transparent in, in, in what they're doing. Um, so I think it's, I think that doesn't, the LLM kind of aspect how LLMs were built originally, um, isn't so much of a, of a, of A-G-D-P-R issue.

Um, but, but yeah, it's certainly, and there hasn't been, let's face it, a huge amount of massive, um, cases. Yeah, there hasn't been all these kind of, because obviously there's, there's, uh, revenue, there's, you, you can be fined up to a certain percentage of revenue, and there hasn't been these kind of, you know, 300, 400 billion Euro fines, um, um, administered. So you could argue that, um, you could argue that it's doing its job because, uh, has now, or you could argue that it wasn't quite as needed as, um, as some in, uh, Europe thought it might be.

Yeah, it's pretty surprising really that there hasn't been more cases, because of course, people have, um, legitimate concerns about the kind of data that, uh, AI is, is vacuuming up. But I guess, uh, that kind of leads to this whole question. Is AI a different animal from all other IT applications, or is this just a wild west still that hasn't been regulated?

Um, do, do you think that AI is, um, fundamentally a different animal and needs different types of supervision? I think the, if you kind of contrast to something like, you know, just a relational database, um, that's obviously, you know, where a lot of this data is stored. We don't have, um, relational database legislation.

Uh, but that's, but that's partly because that's a very, um, you know, that takes humans to put the stuff in there. It's structured and, you know, and findable, et cetera, et cetera. I think there is something a bit different about AI in the sense that it's, um, you know, it's obviously, you know, if you think about the phrase machine learning, it learns, it adapts, it evolves.

And that's where, you know, the, that's where the difference comes. So we've gone from kind of, um, you know, just sort of predictive models that, that that're gonna predict an outcome, um, based on a kind of fixed data set to things that are evolving using enormous, um, training sets that, you know, we're not sure what's in them. And so, you know, and as they change and, and evolve and models drift and model decay, you know, I think it then becomes issues around explainability become very hard.

You know, how can you sit across from your, if you are, you know, if you're a bank, how can you sit across from your regulator and explain exactly how every single uh, decision that you are you are using AI for was made? You can't. Um, so I think it, I think it is, I think it is different.

The volumes of data are just, just so much larger, um, than, than anything else. And I think it's just been evolving as we've gone from machine learning predictive models to generative AI to, you know, eventually, um, and things like that. So I think, I think it is, is a bit, it is a bit different.

I mean, you haven't had kind of, um, you know, I mean, you have regulations around search engines, but not for the reasons of, you know, necessarily, you know, what they're sucking in. It's more like yeah, monopolies and, and things like that. I think the regulations may play out a little bit differently too, rather than having some overarching set of rules, I think you're gonna see, like the regulations that apply to various vertical industries will get tightened around ai, and we'll see extensions to whatever rules we have in place for finance, whatever rules we have for healthcare, as those people get a better understanding of how AI is applied.

And that may be more effective ultimately, because each vertical use case is different anyway. Yeah, I think, yeah, but it, it's interesting to think though that, um, you know, for example, in the copyright world, um, there's been a lot of trouble with, uh, generative ai, um, violating copyright on a wide scale, essentially being able to regurgitate, I don't remember what the, what it was, it was like 87% of Harry Potter or something like that when prompted to, and I've seen similar situations where it has, um, generated, um, specific photos from, um, you know, registered photos from photographers and things like that. Um, if given the right prompts, so that data is in there.

Um, I wonder if there's personally identifiable information that it could be coerced into, uh, spitting out, even though, uh, Nick, as you say it, it's theoretically only been trained on public data, but data, uh, I think maybe some of our readers might be yelling, or listeners may be yelling at their phone right now to say, no, it's not just public data, because I think people have a suspicion that it goes well beyond what it should have been trained on. Yeah, I think people also are, um, amazingly willing to put public information on the, on the, on the web about themselves. So, I mean, this is not just sort of LinkedIn things, but, but, but other things that, that, you know, you could piece together.

So I think it's, uh, yeah, I think, I think you're right. The copyright stuff is interesting. Obviously they've, there's been a lot, bunch of lawsuits and, and there's been some settled, um, for, for publishers, you know, when, when these, some of the, the, the early, um, LLMs vacuumed up, um, you know, hundreds of thousands of books, um, which are, you know, some were under copyright, some weren't.

Um, but, uh, yeah, and there's been some settlements in, in that regard, and you've seen all the, the big publishing companies, you know, you know, New York Times and BBC and all this have kind of agreements, um, with, with some of these LMS that they can or cannot, uh, use their, use their data for the purposes of training. So I think it was, it was very much in the early days, and by the early days, we of course mean, uh, just under three years ago, um, you know, extremely wild west, like, and then, you know, within a few months it, um, there was, there was some, you know, uh, some, some, some, some agreements put in place, but very much kind of one-on-one. You know, this is not, you know, legislation, um, uh, base.

This is just, uh, you know, companies settling or, or not as the, I don't know how feasible it is, but I always thought about it this way. I mean, they may have the data, but the issue in my mind at least is that they enable people to use the prompts to tease that data out. So if we were better at maybe putting the guardrails in place around the prompts so that people couldn't tease out Harry Potter, then maybe we wouldn't have a crime in the first place, right?

Yeah. I mean, unfortunately, Yeah, that's easier said than done. Yeah.

Yeah. I think it's kind of, because the generative AI has fundamentally changes the nature of security cybersecurity, doesn't it? Because you can't, um, whereas previously with machine learning, uh, you, you could control the input 'cause the input was, you know, your bank, you know, what the input into it is gonna be.

And there's no point with a kind of a decision tree chat bot and trying to manipulate it into, say, into swearing or saying something, you know, nasty. Because all it'll do is, you know, do you know your account number, date of birth, et cetera, et cetera. It's not gonna tell you anything else's.

Not gonna tell you Harry Potter, it's no point. And, but now with generative AI in the, in the chat box, you know, you can't, you know, as the owner of it, you can't really control the input. People will, will, you know, put prompts in, um, you know, with, you know, trying to trick the things and, and put code in there and stuff like that.

And then of course, you can't control the output so much. So it does change the, you know, the threat vectors as, uh, cybersecurity professionals there, like to say, which I guess begs the question, is AI going to be an IT application or is it going to be, again, back to my original state, is this thing a di fundamentally different animal than the other types of applications and, and data sources that we've relied on in IT for, for many years? Do you see it differently?

I see it in this regard. Um, and people are talking about that here in Atlanta, CubeCon, but there's a difference between training and inference, right? And there's training, that is one thing.

And then the inference side of it seems to be moving back towards IT as a deployment model, and they're managing the infrastructure. And Nick, I don't know if you see it differently, but in my mind, a lot of this sovereign cloud conversation that's happening in Europe is very much tied to the fact that these AI workloads need to be centrally managed, secured, and protected. And all of this seems to me screams we need some adult supervision from the IT folks.

Yeah, I think it's, it's interesting as to whether it's different. Uh, I think the, I think there's certainly shiftings, uh, there's been shifts happening, uh, towards the, the buyer changing, obviously as, as there used to be. I didn't like the cliche of every company becoming a technology company a few years ago.

I thought it was way overblown. Um, but I don't really think it is anymore because I think, I think, uh, you know, any, any sizable company, um, everybody has the ability to, to use, uh, gen ai. Obviously there's, you know, certain things are locked down, um, but they've got other, other devices connected the internet, um, that can, couldn't do things.

And I think, but I think the, you know, the kind of vibe coding shift, no code tools and things like that, um, and obviously the gen AI coding tools enable, you know, so many people to be able to, you know, develop small app micro apps and things like that. I think it is shifting the buyer pattern. Um, so we are getting more line of businesses, uh, involved your line of business people, by which we mean, I always, it's, again, it's a funny expression.

It means everybody other than the IT department. So in most companies, that's, that's virtually everybody. And so you're getting, yeah, many, many, many more inputs into it.

Um, certainly in the early days of, of Gen ai and now in the early days of agen ai, you're getting those people who are driving the experimentation. The issue comes is when we move from experimentation to implementation, and that's where, um, I think it, um, you know, sort of pulls everything back in to a certain extent. It doesn't matter if it's in cloud, on-prem, hybrid, anything, um, and, um, and, and get and gets heavily involved.

So I don't think it's, um, you know, like that famous, uh, essay that was wrong 20 years ago, 20 plus years ago. It doesn't matter. I don't think that's that's the case at all.

But I do think there's gonna be many more people involved in the kind of, um, you know, the top of the funnel stuff in terms of the buying, the buying patterns. I, I think one of the biggest challenges with AI is just, you know, it is a very different type of application. Um, it, it works very differently from the way that it is useful.

It tends to be very reductionist in its thinking. It tends to say, you know, here's the data, here's the network, here's the servers, here's the application. You know, really lining things up along conventional ways.

I don't know that AI applications really align nicely to that old way of thinking. I mean, in many ways it's very similar to the transition to personal computers, the transition to mobile, the transition to cloud to, um, as a service. You know, AI just takes that to another level in terms of, um, we don't really know what it is.

We don't know really know where it is. We don't really know what data it's using, maybe. Um, and that makes it, I guess, a little less amenable to the conventional IT mindset Maybe.

But I would argue that a lot of these, you know, business apps that are gonna be built by end users using natural language will suffer the same issues we saw with low code, no code, right? We're gonna get a lot of ugly applications, they're gonna be insecure, and they won't scale, and that's when they're gonna call for the IT folks. So IT folks, then they're gonna show up and say, well, here's how you build this.

So I don't, maybe they're not, and somebody's Gotta know how to screw these things together and, and, you know, not gonna be the business units. There's gonna be, but there's gonna be a whole beautiful agentic orchestration layer that we just haven't seen yet. Um, certainly a load of, a load of, uh, every vendor of any size is coming out with those kind of things.

Um, which is, I mean, I guess, you know, I, I, I know what you mean. I think the, the ENT stuff, if it does come off is, uh, again, a shift. And when these kind of shifts happen, um, it, it's like, it's not like everybody, everybody stops what they're doing before and moves to the new thing.

It is, it is an evolution. Um, and I think it would be, it'd be, it'd be foolish of us to kind of think that, you know, the, you know, the agent stuff is not gonna happen to some degree or another. This is not robotic process automation where you wrote a script, um, but a human wrote a script and just tell a computer to go off and just keep doing the same thing over and over again.

This is where, you know, with, with, with agents, um, which I think there definitely will have to be, um, orchestration frameworks, which will have to be sanctioned by it. And that will happen because, you know, if you think it's, if you think it's kind of scary, um, having users type type things, imagine if you've got other applications deciding whether our applications, what to build and building their own applications. And, you know, you kind of got the, uh, the ultimate, um, insider threat, um, yeah, from a cybersecurity point of view.

So I think, yeah, I think it, um, yeah, it will always be around and always be a role for it. I think the, it's just, uh, I think there's a lot, yeah, just expanding the footprint of people who, um, consider themselves users of, uh, of, of, of technology in some cases fairly advanced technology. And I liken it to, you know, I could diagnose my own issues, right?

And I'm using chat GT to figure out what's ailing me, but I'm probably better off if I get a professional to tell me to. Yeah, I had an interesting conversation, uh, last week with a company, uh, Semaphore AI about how they're trying to do agent applications. And, and their idea was that instead of using a conventional approach, um, you know, or instead of trying to build prompt engineering that we would use runbooks essentially document, uh, the, the, the state document, the process, document what you're trying to get out of it, throw that into the, uh, AI model and see what the AI model can build that achieves your goals.

I, I felt like that was actually a pretty interesting insight, not because it was such a novel approach. I mean, we've been using runbooks in it for decades, but because it actually kind of meets the users where they are and where they need to be in terms of interacting with these applications. Um, do, do you think that, uh, that signals that AI is not going to be an it, a conventional IT application?

I certainly think if that kind of stuff comes past, and you, and you're right, obviously in IT itself, we've been doing it and Red Hat with the Ansible is a good example, um, and how they've added a AI to, to Ansible Runbooks. And I think they've done a really doing some really interesting stuff, but it's only to say within that domain, I think, I think yes, I think there will be, um, if you mean, are there gonna be ways that people using natural language will be able to describe what they want and have something get built and go off and do it? Yeah, I think there will be, and I think, but there will obviously be guardrails where you hope there would be, um, that says, you know, you know, I'm, you know, almost effectively, I'm sorry, Dave, I can't do that.

Um, but it's, but it's gonna be, those, those kind of things are, are, are gonna be in. But I think, yeah, I think it opens up. I think no code has opens up the, the i the idea of building apps to, to so many other people.

No code has been a bit of a disappointment. But I think this is slightly different, you know, with natural language interfaces. I'm not sure the runbook is the right means for managing all this in the future.

And, and I say this because the application environments themselves are gonna be much more dynamic. They're gonna be a lot more applications built, and they're gonna be updated more frequently. And I think the runbook is a little bit of a more of a static concept.

So I'm wondering at some point, you know, I a it will be AI agents, I'm just not sure they're gonna be invoking some sort of runbook that a human created as much as maybe there's some other means for managing it that is equally dynamic as the environment. Well, you've been in this space forever, uh, and you're there at CubeCon, you know, you're looking at all this cloud native stuff. Um, what do you think, um, I, I know it's probably too much to ask, you know, what's the answer, man?

What, what do you think of the direction that, uh, the IT industry is heading in terms of getting their hands around this? I Think everybody is bending heavily on AI agents being able, providing the ability to scale. 'cause part of our issue has always been we didn't have enough people to manage the applications, so we didn't deploy as many as we might have possibly could.

And everybody's got this huge backlog of applications they theoretically wanna build and deploy. But the, the limiting factor has always been, well, where do I get the software engineers and the IT people to manage all this? So if we can manage all this stuff at scale using AI agents, that will be great.

I just don't think we should abandon first principles of good software engineering because we have a bunch of AI agents out there. I think we need to think that through, make sure those AI agents are trained and AI agents are voracious and they will do things, you know, unless you specifically tell them not to. And if that's the case, then somebody's gotta sit there and orchestrate and manage and, you know, take care of this army of AI agents.

So I just think the future of it is, you know, humans plus AI agents, and there may be thousands of those AI agents, but it requires somebody who actually understands what the objective is of the army. Oh, yeah. I think it's, I think you're right, Mike.

I think there's no, there's, uh, the, it's more important than ever to not abandon the, the, the, the principles of software engineering, I think is, uh, because of the, because of the kind of force multiplier effect of all this, of agents calling agents, calling agents, you know, there has to be, you know, that that kind of, uh, discipline in place. Otherwise, you know, truly chaos, uh, will ring. There's one way one said to me, you know, it's one thing to be wrong.

It's another thing to be wrong at scale. Well, and, and that's, that's, you know, kind of bring this conversation around full circle then, um, you know, I guess the question is, do we want to risk getting our cart in front of the horse like the EU may have done with their AI regulations? Do we want to be very, uh, reactive like it has often been in the past?

And, um, or, or do we wanna somehow strike a balance in terms of getting our hands around the growth of this technology and, and what does that mean to business users? So, uh, that's a lot. Um, Mike, what do you think?

Do we wanna get in, get out? Should it get out in front of this? Or is the eu, did they make a mistake by trying to get out in front of it before chat GPT was even launched?

Yeah, I think there's a big cultural divide here that you're poking at, right? Because over in the valley that they'll say things like, go fast and break things, but you know, they don't actually manage and do anything. They're just providing the tech.

And for folks who are, um, you know, I'll just put a, a, you know, a small little simple example in place, but, you know, if you're manufacturing yogurt and suddenly the AI is making, you know, 50,000 gallons of yogurt that you got no place to ship to, it's a problem. And I don't think people wanna see that. And I think business leaders are gonna be one saying, you know, well, hold on there folks.

You know, this is real money we're talking about. Yeah. I think even though AI is, um, is a general purpose, technology like electricity is or was, is certainly does, I think it's, I think it's, um, it will have to come under the purview.

You know, again, we always make mistake done with every time there's a new wave of, oh, we gotta get some of that new wave, rather than what is the problem you're trying to solve and work back to backwards towards the technology? It happens every, every single time. Um, you happen with cloud happened, mobile happened, happened with Java in the nineties.

Um, and so I think, um, and now look at that, you know, you can consider a lot of these things like Java and cloud and mobile, just, just table stakes. And I think AI will get like that. I do think that, um, there is an old joke in ai, and I, I may even used it before on this podcast, that, you know, that AI is whatever hasn't been invented yet.

And so people, you know, there's a kind of, you know, you, you have a problem to solve, use ai, and, and, and then it gets implemented, rolled out and becomes commonplace. And everybody goes, that's not ai, that's just software. Or, well, well, it is still, but you just don't think it like that.

And then AI is trying to solve the next problem along. So I think it is, um, I think we're gonna see a, you know, a long, um, you know, evolution and constant, um, you know, and constant, uh, innovation, um, for, for, you know, decades to come, I think. But it will have to serve, serve the business, otherwise, um, it won't, it won't be much use to anybody.

I'm laughing to myself 'cause now I'm remembering the days when Wang Labs referred the document processing instead, it was ai, right? Exactly. Yeah.

Technology is, uh, anything that was invented since you were born? Uh, I've heard that one. Um, yeah, it, well, I, I will say too that I suspect in answer to kind of this whole question, I suspect that there's going to be sort of a bifurcation in terms from governments, from companies, from consumers, and, um, you know, each of us individually, uh, some of us are gonna try to get out ahead of it and stand in the way.

Some of us are gonna be, take a very passive approach. Uh, some of us are going to adopt aggressively, some of us are going to adopt conservatively. And, uh, ultimately I think that what's gonna win the day is the practical benefits that we get from this technology or not, and that will spell whether this is going to have the impact that we expect it will.

Uh, I think that's a theme that we've heard on, uh, the, each of the episodes so far of, uh, utilizing ai. And I suspect that we're gonna continue to hear that, that, you know, really at the end of the day, um, I, I was, I was talking to Daniel Newman this morning, and, uh, one of the things that he and I were talking about was the fact that ultimately, um, the success is it's all, is, is the barometer of success. In other words, ultimately if you're selling, if uh, customers are buying what you're selling, then you know, you have a success.

And there's really no other metric for success beyond success. And that's, I think, gonna spell what's gonna happen with AI as well. I think there's different forms of ai.

When I think about gen AI in particular, I, I kind of think you should work backwards from the business process. So if the process itself needs to be done the same way every time, then maybe it doesn't lend itself to Gen ai, which never does anything the same way twice. But if the thing is, you know, I don't know, creating a marketing newsletter or something where it doesn't really matter if it's done the same way every time, then gen AI might be perfect.

And I think there's a spectrum of those things and people need to kind of sit down and figure it out. Yeah, exactly right. Um, Mike, there's, you know, hallucination might, might have, might get a bad name, but in, in creative amongst creative professionals, that's exactly what you want.

Um, you know, so, so you want it to hallucinate if you say, if you're doing, um, you know, marketing collateral, but you also want to, if you just want to resize, um, 50 bits of marketing collateral to 50 different sizes, so they, they work differently in format, you don't need a whole load of creativity in that process. You just want it to be correct. And so, yeah, I think there's, there's gonna be, um, yeah, there's gonna, there's gonna be, you know, use cases for all kinds of AI and, um, obviously non-AI technology And the, and the risk level on that newsletter going out being wrong is minimal.

Right? I might be embarrassed. Well, thanks a lot, but the company's not gonna go under, you know what I'm saying?

Uh, thanks a lot for joining us on this episode of utilizing ai. Uh, Nick, it's great to see you again. Uh, Mike, welcome to this, uh, exciting little circus here that we're gonna be doing every Wednesday for our listeners, uh, before we go, Mike, um, give us a little pitch.

Where can we continue the conversation with you and where can people find your content? Well, by all means do check out Techstrong ai, and that website is also one of a series. com cloud native now, security Boulevard, and we also have, uh, tech Strong it, and they all have an amazing amount of AI content because well, AI's everywhere And Nick.

Sure. Yeah. com.

Um, you can find me on, uh, Twitter exit at Nick patients. Um, and so yeah, we're con constantly looking at this space and, and updating all the research for our clients. Yep.

And as for me, uh, yeah, you'll find me at s Foskett on most social media networks. Um, I'm on Textron Gang pretty much every Tuesday, though, not this week because I was traveling. And, uh, also of course, uh, you'll find me here at, uh, utilizing ai.

Thanks everyone for listening to this episode of the Utilizing AI podcast. If you enjoyed this episode, uh, please let us know. Drop us a line, uh, also maybe subscribe.

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Thanks for listening, and we will catch you next week.