Unlocking Quantum Computing & Its AI Connection | TSG Ep. 941

The Nobel Committee goes Quantum. You're watching Textron Gang. Hi everyone.

Happy Thursday, man. This week's flying by Earth Thursday, Mike, you're still, but you're still in Barcelona, right? I am.

Last time I checked and let me look out the window, but yeah, I am. Alright. It's a week in Barcelona.

Good for you. Um, guys, we've got a, a great show for you out there today on this beautiful Thursday. We are gonna talk a little quantum, a little ai, a little, a little Atlassian, Atlassian.

We've got some good people to talk about it with. Let me quickly introduce you to him. I mentioned Mike is joining us in, uh, Barcelona, Mike Ard, happy with the Yankees win the other night.

We've got John Schwartz out in Silicon Valley whose voice is a little sketchy, so we'll try to go easy on them. And of course, joining us, my friend Jeff Rech. Jeff, Jeff Re Jeff is the CEO of the IDSA.

And always a pleasure to have him on here. And we found out today Jeff was a quantum, uh, not quantum, a physics major school. Yeah.

Larger than Quantum. Yes. Much larger.

Billions and billions. But, um, so how Apro Pro to have you on here, so Mike, the, the, the Nobel Committee awarded the other day, uh, their physics awards to three, uh, physicists who did some really, you know, foundational work in the mid eighties that, uh, kind of forms the backbone, the basis for what we call, you know, quantum computing today, With, which I think is maybe slightly overdue after all this time, but I guess better late than never. But we haven't seen quantum computing machines in the mainstream.

At least we've seen them being used in various use cases in pharmaceuticals and some other places. It's interesting and compelling. But Alan, you wrote this article on Textron it, and, you know, as you were mentioning, it kind of does sort of make quantum feel real.

They got a, they got a Nobel Prize for it. And this is now a, a, a real thing. We are computing with the fundamental elements of nature.

So we've been, we've been computing with the fundamental elements of nature all along, haven't we? Everything comes from nature. But that being said, rumor was they, they were holding off on awarding the Nobel until we did have a, uh, commercial quantum computer, but they were afraid that there would be no one left on the committee.

By the time that happened, they weren't, I'm only kidding. They didn't really say that. But yeah, it is a long time coming.

This was work done as you know, 40 years ago and hard to believe 40 years ago this was done. And we are still waiting for Q day. That's the bad news, the good news.

Two days closer than ever. So they say, um, you know, we, we have, I I think over the last three to five years we've actually made a lot of, uh, breakthroughs in, in qubits and, you know, all the multi qubit machines and of course, post quantum crypto cryptography algorithms are, are pretty, uh, widespread these days. But, you know, I think number one, honoring these three men who did this foundational work on, which all everything we're doing now is based, is long overdue and congratulations to them.

Secondly, I do think it's another drumbeat in the steady drum roll of quantum being real and Q date coming third, I think most of our people out here are not really sure other than post quantum cryptography, right? Breaking down encryption, what are we going to use quantum computers for? Jeff, if you don't mind.

Well, sure, I'd love to expound on this because quantum computers, I think in the long run can be used for everything. But, you know, just like every other computer, it's a matter of cost, resources and availability. But I, I think from a, a security and technology perspective, you're gonna see quantum computing further embrace what we do for connectivity be, because keep in mind, quantum particles can pass through objects there, there is no physical barrier to them.

Um, now that's an abstract for most people, but we're going to get there with computing, however, and our, our second topic coming up later on with ai, it's directly tied to that because both of them require a whole bunch of cooling and a whole bunch of power of, of electricity. And we haven't solved that problem yet. I would offer, let's target AI and quantum towards solving our energy issues so that we can get more quantum computing.

And Q day can be sooner. But the sort of things you're gonna see coming out of this, I think when you talk about artificial atoms, I think you're gonna see, um, depending on ethical, how it's looked at by different organizations. I think you're going to see gene therapy come out of this.

I think you're gonna see new, new drugs that can target specific, um, issues and ailments and conditions without having other side effects come out of this from a technology and computing perspective. I, I think what you're going to see tied to AI is a faster implementation of whatever it is we need to do with computing. And I know that's a very broad statement, but there really are no bounds.

If you wanna focus on how quickly can we, uh, encrypt something, um, how quickly can we transmit it? How quickly can we calculate what it's gonna be? All of that's gonna come out of it at or around Q day.

I also think, uh, quantum entanglements, which aren't necessarily mentioned in the, um, prize notification, at least I didn't see it when I read it, uh, are going to give us a security, uh, condition that we haven't been able to achieve before. And if you don't know what a quantum entanglement is, and this is some of the work they they did 40 years ago, you, you have two elements. Um, not chemistry elements, but, but two objects.

And they are quant. There is a quantum entanglement between the two. Anything you do to affect the first will have the same effect on the second.

And anytime you make any change to that entanglement, including simply observing it, the entanglement breaks. Now isn't that a wonderful way to have a secure connection that says anytime it's even observed, it breaks. So This, now, this is where I, I need, I need a little mind expanding, you know, mushrooms or something to help me out here that the, the, the quantum entanglement thing, right?

Because it could be a particle in another galaxy or another, you know, star system, but yet the, the, the entanglement is instantaneous. But of course when it's observed, the entanglement is broken. So how if we can't observe it, how do we know it was there?

And I know they've gotten experiments that show this, but, you know, I stopped smoking dope a long time ago and I just, I can't wrap my head around this. Well, maybe you stop too soon. That's the problem.

There you go. There You go. But, um, if you go back to Heisenberg, who really started the whole concept of quantum mechanics, the Heisenberg Uncertainty PR principle, really that's where it came from.

There is a cat in a box. I know I'm going back to, I think many people have heard this sure metaphor, right? There's a cat in the box, there's a cat dead or alive.

Well, you won't know until you open the box. You observe it, therefore you break the entanglement that was there that said, is it one or the other? Both conditions were true because you didn't know what it was.

And then as soon as you observe it, you know it's broken. You know, which one now exists. I don't know if that helps.

But with the entanglement, the, the good news about quantum entanglements is, as I said, it can, um, they can go through physical barriers, uh, space and distance means nothing. So you can have a quantum entanglement with two particles, uh, different sides of the universe. And anything that affects one affects the other.

And any time any change occurs to the entanglement, it's done, which means you've opened the box and looked at the cat. Does that help? Hey, can I mention something that it's, it's, maybe it's a parallel, but what, what I find so interesting about this in this, in terms of what these folks, of these three gentlemen have done in terms of, i, I, I think a, uh, Alan, you mentioned the artificial atom, which bridges quantum theory and, and yes, uh, quantum theory and engineering hardware.

The thing that kind of I see a parallel is a couple weeks ago I went to Stanford. I was at this reception basically about the semiconductor industry and the found the members, the guys who made it all possible. And I think I see this parallel here too.

And I remember at this Stanford ceremony, they were talking about the fair children and what begat the, from the fair, fair children like Intel, a MD alter, et cetera. And I think this kind of marks that same type of moment where you acknowledge the work of the people who build the construction of the house, the foundation of the house, and makes everything possible. And it seems like this was long overdue, but you know, it's kind of gives me the sense of dejavu about what's happened in terms of the long forgotten people decades from now when AI takes off.

So for those who were, um, under 60 Fair children refers to Fairchild semiconductors. Yes, yes, exactly Right? Yes, yes, yes.

Sorry about that. No, I'm dating myself and Mike, I know in all of us. But I'm thinking about Robert Noy, Gordon Moore.

I mean, these were giants. You all know who they are. Sure.

And I think I wish more people knew who they were, right? And I think these three guys, maybe they will be forgotten, but their place in history will be in the firmament forever. Yep.

So I have questions. Am I, do I need all this current AI stuff? If someday I have quantum computing, will quantum supersede AI or will these two things Myself?

No, I, I think, I think AI becomes the catalyst for quantum, right? And, and, and so, you know, you've got power squared between the two of them that, you know, because for a, some people say for AI to reach its ultimate goal, and if you believe the ultimate goal is super intelligence or a GI or what have you, you're, you're truly going to need quantum kind of, uh, power quantum kind of computing resources for AI to reach that goal. So they actually are very complimentary and feed off each other.

You know, I, I did two interviews with the, a, a father and daughter, the daughters of PhD outta Stanford, actually her page PhD's in ai, but she's CEO of this quantum computing company called Q Secure, QU Secure. And her dad, Dave, who's also very well versed in, in quantum. And the, the, the thing that blew my mind is when you, when you look at cubits, right?

And, and which is the fundamental bite of the quantum world, of the quantum computing world, right? In conventional bytes, computer bytes, it's zero or one, right? So if you have, let's say a 64 bit processor, you have 64 different bits that could be zero or one.

So how many permutations of that can you have? Well, 64 times 64, excuse me, 64 times 1 28. 'cause each one could have two different states, right?

64 to 1 28 a qubit, 64 bit qubit, let's say has more computing permutations. There's more computing power than what we compute in a year in traditional computing, basically, right? Because it is, because it could be both or neither, right?

There's actually three. So that the amount of computing power that a quantum computer brings to it, and I, I didn't do this justice. Go back and look at my interview with Dave.

I think it was a black hat. Um, but the amount of computing power that it brings to bear virtually equals the compute, the entire computing power in the world for a year right now. So, you know, what's that gonna do to ai?

But if I could offer in, in aeronautics is a term I'll force a no vector, that means you have a whole bunch of power, a rocket or a jet takes off, but you're not steering, you don't have navigation, you're just going, to me, that's quantum computing. AI adds that guidance and altitude and direction. Excellent.

I mean, so here's the bottom line though. We've mentioned some of the uses, protein folding pharmaceutical, you know, and, and biomed kind of things. Of course, post quantum cryptography and, and you know, cryptographic kind of stuff.

Um, modeling, uh, uh, weather modeling and, and, and you know, what, what those kinds of things. I mean, just anything where, you know, you, you, you need that massive amount of, of ability and, and, uh, of, you know, of computing power in, in on the head of a pin. You know, quantum does that for you.

However, let me also say, and I, it's in my article that we haven't solved all the issues quite yet, right? Basically for the qubits for quantum computers to be working now, they've gotta be like flawless or something like that. And we are developing what they call fault tolerant qubits, which will be easier to manufacture, easier to maintain, right?

The work these guys did in 1985 is they had to have things in a superconductor kind of environment at damn near absolute zero kelvin's, and there's a locket junction or something where the magic happens. Um, I'm, I'm leaning over my head there, but in any event, right, fall tolerant cubits make it a little easier for, for quantum computation to be done without all of those things. There are, Jeff, you mentioned power, the power consumption and cooling and all of that stuff to bring it to absolute zero and all that huge, right?

So this isn't the kind of thing you're going to just run because you feel like doing, you know, you want to do some basic trigonometry, right? You could use your slide ruler. Thi this is, this is an expensive proposition.

And, and so the, the rewards have to be equally as valuable. Does anybody know? I mean, maybe Jeff, like, so how exactly do I write software for this thing?

I mean, is there isn't a traditional compiler, right? So there's gotta be something that I'm using to in access those cubits that Alan's talking about. But what is that?

So first of all, it's, it doesn't really exist yet, so it's hard to say what's actually gonna work. But I believe what you're gonna see is rather than, I think compiler can be a very quaint term when we get to quantum computing, because you're going to, I believe what you're gonna do. And once again, I think AI and quantum are tightly coupled.

You are gonna be able to take a concept and say, here's what I wanna be able to create. I believe AI can create the programming that you need to run on quantum. In fact, I don't think right now a human can comprehend writing a program that can truly take advantage of that advanced speed.

That's why I think AI is gonna have to be the very next step, if not permanent step to doing that. Wow. All right.

So you're telling me the universe is right here on my thumbnail, perhaps, right? A little, a little animal house there. Animal House.

Yes. Yeah. All right.

Hey, we're a little overtime though. We need to take a break. Let's come back.

And again, we're gonna talk a little AI now. Uh, I, big news from, uh, IBM, you're watching Textron Gang. You've earned it.

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And yes, as Alan alluded, we're gonna have a little chat about AI this time. It's IBM making some news with a partnership with Anthropic, and they're gonna integrate the clawed tools into their software development projects, gonna show up in mainframes, all kinds of fun stuff that John covered. But John, um, do you get any sense irony here that, you know, the folks that gave us Watson are now reaching out to get some help from Anthropic?

Yeah, I know, I know that, did you know that that's a pretty big, uh, thing there, symbolism, right? I mean, exactly. IBM claimed that they were the beginning, the forefronts, the builders of AI in a sense that they brought it to commercial use in a sense, they're going to anthropic and Anthropic is gladly gonna help 'em.

Uh, so yes, it's an interesting deal in a, in a sense that IBM greatly expands its AI capabilities through a startup. And it also for Anthropic, I think it's incredibly significant and plays into this narrative that Anthropic has been pushing very hard lately to get into enterprises. Um, there are a lot of companies trying to get into the enterprise through AI capabilities with large language models like Claw becoming more central to business software platforms.

In a sense. Anthropics been making this push into the market of enterprises, um, as kind of the go-to vendor for large organizations. In fact, they've been courting corporate clients since they launched Claude Enterprise in September.

They claim they have 300,000 business customers. And one of the biggest, I think the largest enterprise agreement to date was announced Monday of philanthropic, and it's with Deloitte. So that would bring Claude AI models to nearly half a million employees at Deloitte.

Um, it's also on top of that, anthropic has for ties with Databricks and a partnership they announced, I believe in March, which is targeting businesses looking to develop their own AI agents. You know, this kind of this divergence between what Anthropic is trying to do. They claim they are now like the enterprise go-to solution versus OpenAI, which is, uh, stressing the consumer side.

But, um, it is interesting that IBM chose to work with them given the history of Watson and whatnot. And, um, I think we're gonna see more of these types of deals between the legacy and between the startups. Uh, it's just really gonna be, uh, almost like a weekly occurrence, I think.

Isn't it refreshing to see an AI deal where there's not a couple of hundred billion dollars thrown around? Remember? So like, hey, I, I've got my shimmy says this afternoon at two 30, uh, and it, and it, and, uh, it's Shimmy says, uh, when the bubble bursts set to the, to the tune of LED zeppelins when the levy breaks.

And, um, and there's also a companion article to this up on Textron it that I'll send you too as well. Great. Everybody, you know, to me this sounded a little barish.

I don't know if the guys were in purple when they were up on the stage. You know, we're all working together. It, it is ironic that the folks who brought Watson, you know, the first kind of AI we thought about are now put, put IBM's like that, you know, they'll, they'll put anything in their chin.

They got the pipe. If you give them product to put in their pipe, they put it in their pipe. Um, but here's the real question, guys, and I don't want to, you know, stay tuned for my shimmy says this afternoon, but when half of the growth in the US GDP for the year is due to data centers and AI deals, half of the, there's more money being spent on data center and AI deals this year in the US than consumer spending.

Consumer spending's, usually 70% of our GDP. But there's more of that being spent on data centers and ais as, but here, the, the, the downside is, if you look at the amount of money we've spent on data centers and ais, it roughly equals the entire GDP of Singapore, which is a pretty sizable GDPI think it's 500 billion plus dollars or something like that. The amount of revenue that AI has generated roughly equals Somalia, okay?

Single port is Somalia. com bubble burst, and they haven't lived through the real estate market crashes. And they maybe have been through the great recession, though we, in tech, we kind of skated that, right?

This is a bubble and everybody's jumping on making Barney announcements and, and pledging hundreds of billions of dollars that they don't have because they're getting hundreds of billions of dollars from another company who doesn't have it. And that company gives it to this company, and this company gives it to that company. It's Enron all over again.

Yeah. You feel like you part of Go ahead. It's gonna be, it's gonna be interesting.

We hear these projections of what they're gonna spend on data centers, and it's like more than a trillion dollars of the next four years. And when the reality rubber hits the roads, when we finally get to that point, we're gonna find that it's a fraction of what they said, because it was impossible. These numbers were just being thrown out there randomly.

Well, to Jeff's point, you don't have enough power to run 'em or enough cooling to water to cool 'em and come on. And that's assuming that we're really going to use it 'cause it's really gonna generate money. But he, here's an interesting thing, and again, stay tuned to my shimmy says, for this Past bubbles were funded by debt, brought down the savings and, you know, the savings and loan crisis, right?

com, it was all VC money. This bubble here, it was primarily, at least initially funded by CapEx from the large tech companies who were sitting on billions and billions of dollars. And now they spent it.

But now the second generation of these AI companies, you know, the neo clouds and and so forth, their, their debt, they're, they're funding with debt. And, and when this thing, you know, when the music stops, those people who don't have chairs, it's gonna be ugly. Hey, John, are you reminded of the last time IBM partnered this deeply with a small startup company and how that all turned out?

So, uh, so I'm like, go ahead. Yes, I know, I know you Kelly. You know, can I, can I just go back to something that Alan said, then I'll let Jeff, I'm sorry, Jeff, but it's, uh, in Silicon Valley, the big question is it's bubble or you know, it's bubble or boom, right?

Well, there are more people now anticipating the bubble to burst right now. What they're trying to figure out is where are we in terms of that happening? Are we at 1997 point, or are we at the 2000 point, or are we getting even closer?

And there's several people I've been asking this of, and they're convinced that within 18 months we're gonna find out uncertainty when that happens. Nobody knows, of course, but it's inevitable as Shimmy says. I, I would, I would agree with that.

I I do think that we are, um, it's near, it's near to medium term. It's not a long term issue. Before this bubble burst for a, a number of reasons, real estate power, environmental, downstream issues, finding enough talent to be able to manage all this.

And then getting to the point of now that we're there, what do we do? Because it's, we're, we're, it's all forced, no vector. I'm going to use that one again.

We're streaming towards this and we don't necessarily have an end goal right now. The goal is how much money can investors make? That's, that's what this is all about.

And when that, And it's fueling the whole stock market Yep. And when that breaks, it'll probably break pretty big. Um, it's Gonna be catastrophic and, and the thing about it, but here's the real piece that's missing.

Where's the killer app? What is gonna generate the revenue to justify this kind of spend, right? I need 10 trillion in revenue to justify a trillion spend.

And we're, you know, we we're, we're not sure it really works at that level. It's great for writing, you know, helping you write, it's great for some marketing stuff. It, it's getting better writing code, but geez, geez, I don't know.

Yeah. There's not a lot of logic. There's not a lot of logic applied to this.

It's all pipe dream. And, and, but you, it's funny, Mike, you're mentioning IB working with startups. When you think about Microsoft, I think about even Apple, remember they had that partnership with Apple, with kaleida intelligent, whatever the hell that thing was called.

And it, these, these things kind of went awry for Fraud. You know, the AI train is speeding down the track and companies are afraid of being left behind when it leaves 'em fomo, but they don't know where it's going to end. Is it gonna end at a station or is it gonna end at a, in a mountain at, you know, without a tunnel?

No, It's like that meme, I'm sorry, go ahead, Mike. If you look at the open AI numbers, it would suggest that they are also supplementing the cost of everybody's prompts. So every time you put in a prompt, you know, if they charge you a buck, it's costing them four bucks and they're not Quite figuring it out, they'll make it up in volume.

Sure they will. com days, right? I how many times I heard that in the dot coms, we'll make it up in volume.

It costs, you know, I I charge 90 cents. It costs me a dollar, but I'll make it up in volume, You know? Well, you hit, you hit the nail on the head when you mentioned Enron.

I've been thinking about that more and more recently when I say this, this doesn't, it, it just, it's just like froth. It's hype. It's over expectation, it's b******t.

And it's, it's gonna come back to haunt a lot of these guys. And it's, it's in it's inevitable. That's all I really could say about it.

I, I wanna put a, a positive spin on this if I can, because it is real and it will benefit us. Yeah, that's true. And it will happen.

It's the investment part of it and how much leverage our, our economy has on it, versus is this ever gonna really happen because it will. Yeah. No, look, you know what, Jeff, it took about 10 years after 2000, but we did use up all that dark fiber in all those data centers we built, right?

And we need new ones now. So AI is real, but, you know, this is a classic bubble scenario. And, and what's even worse is you've got the US government, you know, we're already 35 trillion or whatever it is in debt.

You know, our administration's all in on this taking stakes in these companies when no, when those stakes go south, someone's going to, someone's gonna have to answer for santino, Carlos. And, you know, I wanna make sure I understand what you're saying. You're saying that, you know, because we have AI and we can all now write better emails that we're not gonna move the GDP needle.

Right? Right. Basically.

Yeah. You know, pretty much, I mean, here's the flip side. How bad would things be if we didn't have AI in data centers to spend money and, and juice things up around here?

You know, there was, there was an article in the Times the other day that we really have two economies right now. We have an AI economy, which is booming right on the, on this kind of irrational exuberance. And then we have the rest of the economy, which quite frankly isn't doing so good.

Right? And you know, the, this, this is, it's, it's a scary proposition. It's a scary proposition.

And here, here's another thing, and I've said this before, when I hear people start telling me it's a new paradigm, the old rules don't apply anymore. Things are different this time, man. That's, that's when I keep my hands over my pockets because you're not getting none of my money.

Uh, that it, you know, fools, fools in their money. Anyway, go ahead. Yes, the irrational ex, but this is true.

This is irrational. You know what it was? I think I was younger and dumber back in 2000, right?

And I was like, oh, Greenspan, he's putting his foot on this. He's killing it. I'm, I'm, I'm about to retire, God dammit.

But you know, in retrospect, he probably wasn't wrong then, and we're probably not wrong now. Yeah. By the way, I was in that same boat with you.

Yeah. Then, um, but the second thing is, I, I teach part-time. I've been teaching for a long time.

90% of what I teach hasn't changed in 30 or 40 years. Yeah. So for every new thing we get, we still have to go back to what are the fundamental principles and do they apply or not?

And yes, they do. Yeah. Agreed.

All right. Hey, I think we're outta time on this segment. Let's come back and we're going to get a report from Mike about what he did on his Barcelona vacation.

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Contact us today and tell your story to the world in the most powerful way with Textron Group. All right, folks, as Alan Sain, I am here in Barcelona at the Atlassian Europe 2025 conference. They're talking up their robo AI agents that are gonna be embedded into every piece of software they have, and they're only gonna charge five bucks per user.

So it's gonna be interesting to see how all that comes together, given our last conversation about the cost and the pricing. But, um, what they are saying is that they're gonna use this MCP protocol that Anthropic developed, along with a graph to integrate all their AI agents. And every, these AI agents will all know about each other, and they will suggest and help us all do various tasks across their entire portfolio of collaboration.

Software includes project management software that people use, JIRA, Trello. We are big users of Trello here and, uh, tech Strong group. And it's gonna change the way we work.

But it was interesting with what they were saying is don't go after big projects that were saying. A lot of the issues we're having with AI is, especially as noted by those folks at MIT, is that a lot of companies went out and tried to hit a home run with ai. They're saying play small ball.

They're saying automate existing workflows, just move 'em forward and, and get some AI muscle memory going and understanding of how to use this stuff and when it works and doesn't work. And that's gonna be the path to success, which frankly struck me as, you know, common sense. But maybe that is the way to go with all this stuff, is just give it to everybody and they will find ways to use it.

And then we'll figure out what the big ROI is later. Alan, what do you say? You know, they'll make it up in volume.

Look, so agentic ai, AI agents, I think are gonna be the make or break of this generation of ai, right? I, I think generative AI has its uses and we've explored them and we're going to continue to explore them. But when we look at a, you know, agentic ai, these agents that are gonna like, let's say cello make using our cellos easier and stuff like that, or workflows that will help us, help us publish articles, you know, on our sites.

Mike, it sounds great in practice, but as you know, we haven't been able to get it done in reality. And, and that's where rubber's gonna meet the road. I mean, and now I, I think this is a classic case of Atlassian, you know, keeping expectations low, saying keep it simple, but it also reminds me when DevOps first started, right?

Enterprises didn't adopt DevOps. People adopted DevOps, small teams adopted DevOps, right? For a long time you had the, uh, Spotify squad model, the Amazon two pizza model, right?

And so, you know, it was good for a team of 10 to 12 people. One, you know, there was a huge jump, What a similar message as the CEO of the browser company is here. And the deal hasn't officially closed between Atlassian and them, but he was saying the same thing about this forthcoming AI browser of theirs.

Well, it's forthcoming in the sense that it, well, it works on the Mac today and it'll be on Windows sometime next year. But, um, it was the same thing. It was, he was saying onesie, twosies, people will adopt this to get rid of their tabs on their browsers and have a more, uh, integrated workflow experience.

But he wasn't expecting big companies to kind of sign big deals as much as it was gonna be led from the bottom up. And people are just gonna experiment with stuff and move the bowl forward. I think that too is probably the way to go.

And I, I, I think maybe we're just trying to come up with some sort of prescriptive approach to ai, and we should just let a thousand flowers bloom and see what happens Now who's over 60? Good. I know.

Um, you know, it's interesting. Yeah, this is kind of the same thing that, uh, Atlassian did in, in Anaheim. I remember going there several months ago.

Uh, and it's just a very more practical, reasonable approach. And I think it's, it's the right approach. And I actually think that they, they're onto something and, uh, rather than shoot for the sky, let's just see what happens, right?

Let's see what happens from the rank and file and see how it grows. And, you know, it's that, that whole mi again, by the way, we, everyone is referencing that MIT report, it's like just, it's getting torched by everyone, but who, who, you know, who kind of took it, took it literally for what it was. I mean, but if you read between the lines, it was not no immediate effective, uh, profitability instantly.

And it was, you know, this is gonna take time and agents, maybe this is the year of ai, AI agents. I kept, I keep hearing that. Now I'm hearing some people say, well, maybe next year, um, we'll see, We shall see.

I'm like, I just don't really see yet. Like, all right, let's say we do have all these AI agents and I've got 20 and you've got 10 and the other guy's got 50, and we're all gonna put these AI agents to work, and somehow or other they're all gonna find each other and negotiate with each other, and there'll be some sort of handoff and something magical will happen and it will all get orchestrated. Uh, maybe, but I don't see that happening in the next six months.

The crazy thing is like a company, like, I won't mention a company by name, but there are several candidates then announce, uh, AI agent product only to then change and say, well, in a couple more months, we, we have a new version, and this must be driving people on it. Crazy. I mean, how do you ke stay ahead of this, of all these fastballs coming at you, these curve balls?

Many in many cases, right? And, uh, you know, and it's just, it's, it's, it doesn't, it just doesn't make sense. It's just, again, it is baked into the hype, Especially if you've got a CEO who's standing around telling everybody that AI is gonna change the entire economy and the world that we were living and working, and the, the poor IT guy probably looking at 'em going, uh, I don't know what magazines you're reading, but not in my world.

Uh, you know, I think AI will change our economy as, as Alan referenced earlier, I'm not certain in a positive way in the short term, um, because of the exuberance. Uh, but the, um, but John, to, to your, to your point, so let's go ahead and say we're all kind of admitting our ages, and by the way, I think I win that contest, but, um, the days of how does it keep up with more fastballs coming at them? They have to, the days of No, no, no, slow down.

I can't handle that much. Doesn't work anymore. Um, you know, the days of maintenance did, who heard of a maintenance window anymore?

When's the last time you heard that? But, but that was the law, you know, 20 years ago. Yeah, That Was, so I think speed and volume are going to increase.

They're here to stay. So we need to adapt. And we, and, and it could be that we use Ag Agentic IA to help ourselves to do that.

Yeah, no, it's just, it's, I guess, you know, we, I I'll age, you know, I'll date myself again. When you're talking about Moore's Law, that's like blowing outta the water with this, with the, the current, the current environment. Everything is based on speed, adapt, or die, more so than ever before.

I think that's what terrifies people. The, the fact that they're, they're trying to get ahead of something that they can never get ahead of. They're always playing catch up.

It's interesting stuff. Interesting stuff. Anyway, Mike, thanks for the report from, uh, Barcelona.

How are the topics? Is the paella, The food is lovely, as always. The weather's been great.

And you know, I, I could live here, You and me both. Mm-hmm. Okay.

Adios from Barcelona. Jeff, John, thank you for joining us. Thank you for joining us today.

As usual, we have full text on TV immediately following our gang episode. And a reminder, again, two 30 live on X and on LinkedIn. I'll be doing my shimmy says we'll dive into this AI bubble business and, um, got a lot more to do.

And of course, we'll be back tomorrow with our week and our week wrap up Friday show for Textron Gang. Until then, though, on behalf of John, Mike, Jeff, and all of the gang folks here at Textron, have a great day, everyone. We're out.