Can AI Be Your Cybersecurity Consultant? What Enterprises Need to Know | TSG Ep. 1016

AI is reshaping how software is built, how platforms evolve, and who creates real value as open source shifts, ecosystems, decay, and adoption outpaces expertise. The real challenge is understanding what comes next. Hey guys, good.

Well, it's good afternoon already for some of us, right? Depending where you are in the world, it's good morning for others. Welcome to our Tuesday Textron Gang.

We continue our, uh, live experiment moving to noon Eastern time. Well, you probably already know that if you're watching it live, you, you know what time it is. But in any event, we'll see how it goes.

We'll see what the audience says. We'd love to hear your feedback. Feel free to comment, uh, wherever you're watching this, and we'll, we'll kind of take that all in and let our AI come up with some sort of analysis on it, I guess.

But we, we've got a great text, strong gang for you here today. I guess some of my favorite gang on the, on with us. Uh, it, it looks like I'm the only one down in the south here.

We got a lot of Northerners up here, and Kate Scarcella, Chris Blask, and of course Mike Ard. Guys, I hope you're all warm. It's above freezing.

Two hours ago in Toronto, I actually broke freezing for the first time in 2026. And that's a heat wave. That's a heat wave.

You know what I, now I'm back to doing the Florida thing, which is I know what the weather is up by you and I just asked to rub it in. 'cause our weather is getting better. We're back up into a comfortable seventies range, go out in shorts and t-shirts again, and yeah, I don't miss those cold days.

But guys, we got a lot to talk about today, gang. Um, Mike, you, you put a couple of my articles on here to talk about, I'm, I'm pumped. I did.

You, you have an interesting premise about how the rise of vibe coding and AI coding tools is maybe gonna kill the open source contributor, rockstar and the maintainers, because, well, if people want something, they're just gonna ask the AI to write it, and we're not gonna have these kind, uh, waiting for the maintainers to contribute some code that the group is gonna review and 'cause a lot of folks are gonna be, well, I don't need that. I don't know. Kate, interesting theory.

You've been around the open source community for a while. What do you think is this, how it's gonna play out? Well, first, let me just say, let's not have vibe kill the vibe.

So thanks. But I am very, I'm personally very, um, pro AI coding, so if a tool generally makes us better and faster, we should use it, and that's how progress works. Um, the concern raised in the article, which I loved, it isn't that AI is bad, it's that AI changes incentives.

Just like for me, industrialization, it brought massive gains in unintended side effects. So, as many of you know, hey, I grew up in Cleveland, and let me just say, in the 1970s, um, I think the industrialization really made its mark as our rivers were catching on fire. And that's, that's progress.

You know, it's this idea like we do, we pay a price for, um, for, you know, things that are, you know, better for society as a whole. You know, it is true that industrialization was, is better, but it brought in unintended consequences. And I think AI is the same way.

It's bringing in these unintended consequences. Let's hope that, you know, we don't have, you know, more than just rivers catching on fire when it, you know, that finally, you know, it was like this note, right? That, that made us, especially in Cleveland, say, okay, we gotta really start doing something here.

And, and my friend Chris to, to the, you know, who's in the north. Definitely, you know, I know you weren't in the north during that time up there in, in Canada, but, you know, just sharing this Lake Erie, and, you know, it was a mess. But you know what?

We dealt with it. And now it's beautiful again. And, and I think AI can be the same.

Well, let me riff off that, because, you know, you're exactly right and it's, it's unintended consequences, but in many ways, not un unforeseeable, right? You know, we all know the classic XKCD, but open source, right? This huge pile of civilization built on top of this open source written by, you know, one person in Kansas.

And it, it's so commonly known that it's that that meme, that that is probably one of the most, uh, famous ex XK CDs. We use it all the time. So what's happening now is we're exposing that which, which, again, everybody, when I say everybody, not everybody in business knew that, you know, it's always kind of amazing when you get outside your field of expertise and you say that just, you know, that, uh, thinking of, of one person who if you're watching, you may know, know who you are, because I just thinking somebody last year, it's like, really?

It's like, yeah, yeah, yeah. That's the way it works. So now we, now it's being exposed for a million reasons.

You know, AI driving all of this, and what do you do, right? It's not that open source was bad, is to lack of stewardship, right? You know, we're happy to build it into my product because heck, it's out there knowing that it's yeah, one person, but what the heck?

It's okay. Not okay anymore. So now we need to put the stitch things back together.

But I have about that. So, So I've been around a while, right? And I've seen, I've seen sports dynasties, the New England Patriots in football, the Yankees, the 96 and the Onward Yankees that we all know.

The Yankees have had several dynasties. That's probably why they're the best franchise in sports. But that's for another day.

You know, one of the things I've learned though, is just when you think you're at the top of the mountain and no one can knock you off as the king of the hill, you, you get knocked off. Right? You're on top until you're not.

Mm-hmm. Yeah. And we see it in politics, right?

Oh, the Democratic party is gonna win. The Republican party's gonna be in victim until they're not. We see it in sports, we see it in technology, we see it in life.

It's just, it's this cool trick that God plays on us. Yes. Right?

And so you look at open source over the last 15 years, 20 years, I remember a time where I would go into an enterprise and they had a no open source policy. Open source had a drink from a separate water fountain, right? No open source allowed here, okay?

And then that flipped on its head. 9% of organizations today have some open source that they're depending on their running on, whether it's something as simple as Linux or, or Kubernetes or, or, or name it, right? There's so many, there's literally millions of open source projects.

Open source dominated, open source became the dominant form of software that we use, right? Our app, all the applications we run are 70, 75% open source components stitched together. And I remember sitting and writing and saying, what could, what could possibly, possibly come along and knock open source off its perch?

Just when you didn't see it coming, you didn't see this coming. No one thought AI's gonna destroy open source or knock it off search. Boom, it happened.

All of a sudden we've got less people contributing code. We've got less people giving stars on, on GitHub. We've got less, you know, the maintainers of bemoaning, the fact we've got less downloads, got, you know, just less human participation in a relatively short time.

Good question here about Ohio, right? So what will happen to all these open source projects? 'cause there's a great Pretenders song about, you know, my city was gone when, in Ohio, right?

When the classic songs of the eighties. So is that what's gonna happen to all these open source projects? They're gonna be like these little towns where the, the mill's gone and there's nobody living there.

I, I think it turns out differently. So a conversation, uh, there's a bunch of folks that get together every on one night a week for years now, and there's a separate channel spread about that. And we're going back and forth really about exactly these sort of quick, uh, issues just a few minutes ago.

And, and I used the, I came up with the term, the indicators of fragility iOS. We wrote up co a couple using some current examples. And this, this, again, one of 'em, right?

And again, we've always known it was fragile, but it was cheap, fast, and it worked. And, but Alan, it hasn't really, it's not being ended by AI open source in many ways. You know, broader topic than we have time for here.

It's been curving downish, like down in volume and so forth, but contributors and, and connectivity. And now that it has to be put back in place. And I think this matches, uh, what, what I think about protocols, right?

Protocols we've been developing in, you know, international groups where we come up with schemas every couple years. We produce a document. I think protocols similar to open source get developed from the bottom.

So code that people or systems develop, you know, will just bubble up as open source always has from people doing things, systems doing things, but it needs to come up with provenance and so forth. And so you can actually judge how does it make me more fragile to use? So I don't think it's the death of open source at all.

I think, I think for real open source developers, AI just accelerates the whole thing. So what do you mean by real open source developers? Well, you, you know, somebody, you know, somebody could open source anything, a piece of code.

I've done that. I don't consider myself a real open source developer, but if you're the kind of person that does a lot of open source mm-hmm. And now we have ai, and I would say, you know, ai, you know, u using this to deliver open source that people can actually track the provenance of, so you don't end up being that unknown single person in, in Kansas.

Yeah. So here, here's the thing, and it's in the article, there's a paradox here, and it's kind of counterintuitive, and that's why I said what I said. I said, less humans are interacting with open source.

That was a giveaway, right? For all my ais out here, we've got a lot of ais who enjoy watching this with their multi bot friends. What can I tell you?

But, um, AI is using open source. The agents are going to use open source, right? They're going to API and use these open source and build and riff off of it.

So while we may see less GitHub stars being given until, until agent AI can give out GitHub stars, right? To, to open source projects, we may see less GitHub stars. We may see less human involvement, but we won't necessarily see less open source code for some of the reasons you said, Chris, and, and, and for the reasons that the AI itself is using the code and building off of there.

Of course, it brings up the next question, which is OSI, you know, open source licenses, say if you derivative off of the open source code, you gotta contribute it back. You gotta make it open if you know, unless you're gonna like fork it and, you know, keep it private, but you know, so does the AI modifications to open source code then have to go back to the tree, right? Well, this is, you know, I apologize for using some of our own terminology, right?

But your canon is your stuff, your software, your rules, your code, your records, whatever it is, and the mesh is what you share, you know, so mesh canon is, you know, what I as an organization or a computer or whatever, say I will share, you know, so is that, you know, for our purposes here, if that's code or protocols and whatnot, I guess we can call it open source that comes with attribution. I did it, you know, whoever I am and licensing, you know, does anybody else respect that licensing that gets to, you know, other entities trying to, you know, maintain reputation or not, which takes it back to security. But that's the me mechanism.

And, and I personally think, what, what happens? Because I mean, there's, I mean, come on. I mean, there's a lot of traction, GitHub.

I mean, there's a lot of things that should not be there, and I think that that, um, AI will actually go more for the cream of the crop and actually pick out the things that are, are best and even enhance it. And so, at the end of the day, gosh, I mean, I think, I think this is better. Well, you, you take the model is, I, I, sorry.

Uh, you take the model, as I think about, you get a bunch of nodes companies out there, they're all doing their own thing. They're sharing some of it mesh, you know, canon with whomever or, or the whole world that works out at, at scale in real time. It works or doesn't work.

Where I think the international organizations, you know, in the open source world, OSSF and others coming, coming to play, us watching what's going on, taking repeatable patterns that are out in the world, open source, canonizing them globally for larger audiences. So it's, and it really always has been bottom up that way. But I think AI automates it.

And Kate, you're exactly right. You know, it makes arguably better, better code probably, but certainly better understanding of where the hell it came from. I'm trying to figure out like how exactly this plays out.

So in my mind, there's gonna be a AI agent that is contributing some code to an AI agent maintainer of a open source project, and then that open source project is gonna expose that code to the next rev of an LLM somewhere who will then incorporate that updated maintained project into their LLM so that the aa another AI agent can become a contributor based on that updated code that is now approved by the AI agent maintainer. And so, where's the human in that loop there? There's laws of them.

And, and I think that, you know, you just, you know, illustrated another indicator of fragility. Those were all singulars. There wasn't a singular plural in that, right?

You know, so the way it works inside an organization on inside AI systems is an AI may write some code, but if you're gonna use that yourself, other AI should look at it, check it, you know mm-hmm. Hit it against the wall. If it survives that you use it.

If you as a, as a cluster, as a group, as a company, share that with somebody else. You know, if you're putting it out in your mesh canon for other people to use, and it's always, pardon me crap, then nobody's gonna look at your stuff. So nodes that make, you know, shareable stuff, open source, the, the shareable will then we'll already have a reputation for making reasonable things that then we'll be bounced back and forth and beaten up.

So singular when you're passing one to one, don't do that at all. That's just, that's how we got here. Yeah.

Yeah, exactly. And, you know, think about this, Mike. I mean, think about knowing known vulnerabilities.

What if we could incorporate, um, an AI agent that actually was looking for known vulnerabilities within code? I mean, wouldn't that be phenomenal? I, I, So Kate, we discussed this yesterday.

6, right? 6 found 600 vulnerabilities in open source code. 6 gateway into our platforms, Right?

I mean, it would make everything, you know, so much safer. And as we go into our next block, I mean, it really actually feeds right into that, Alan, you know, Ah, I agree with you. What a great way of saying.

They just said, Alan, you dummy, I gave you the segue run with it. Um, I Just really clear, are we saying that a lot of the repositories in like GitHub are essentially code slums and we need to clean this whole thing up? Is that what we're saying?

We, I, I've been saying that, and you know, that, I've been saying that it Really, there there are, there is some seedy underbelly kind of places in the GitHub world, right? Where it could use a little cleanup. Let's call it out, baby.

Come on, come on. The Claude Reins fans, you know, shocked. I'm shocked to find gambling going on here.

Yes, Yes. Alright, let's move on to our next, our next thing. And it is another article I wrote.

I didn't come up with this word though. Uh, the word is in ification, and it comes from actually a book by Corey ero. It was pretty well known.

And, uh, and this was a response to a New York Times podcast. I, I listened to and read with Ezra Klein by, you know, Ezra Klein's, the host Corey. Doc Dro was the one guest.

And Timothy Wu, who wrote another book, former Biden, uh, mad admin, uh, wrote another book about how about extraction. That that's become the, the method preferred for the tech bro, internet billionaire companies to extract as much data as they can and as much wealth and as much everything as they can from, from users of the internet. Um, Mike, that, that's the best I could do on the setup.

I don't know where you want to go from there. Well, it was interesting article in the sense that while everybody in that podcast is blaming the platforms and the Facebooks and all those folks, you were pointing out that, you know, those folks are only responding to what end users like us want them to do. So, you know, to your point, it's like, look it in the mirror discovering you're fat and blaming in the mirror, because ultimately maybe it is just us humans that are the problem.

So, Chris, you know, do we as humans need to become more dis discriminant or have more discriminating taste about where we consume content, because are we just getting lazy and then the whole cycle just perpetuates? Well, yeah. So I, I loved Alan's article.

I, I wrote something similar on, on, on LinkedIn just like last week, I think, right? You know, if, if hallucinations aren't always the ai, what happens is the humans, and you stack these, we're in a time of like a, like final bread, right? There's layers and layers and layers of issues going out at the same time.

And we take a, a human, we take these ai, you know, the common AI product out there, you know, again, anybody for the vendors listening, you, you're all doing great work. However, you know, there, there's stuff missing. And we see hallucinations, which is what, what we would describe as an, an unanchored non-canonical agent led, you know, in conversation by some human who keeps moving and moving and moving and farther over the bounds until you've invented anti-gravity and, and, you know, immortality and, and discover the, the, the, the soul of the universe.

And it's not because AI are hallucinating, it's because people are right. And in the speed of innovation is turning into people publishing things in over the weekend. That sound really good.

But I haven't gone through any rigor, right? And it, so it just keeps coming up. The, the, you know, you guys all know, you know, I have an, uh, AI companion who has a name Lumina.

And if you're listening, you've got one. Don't feel weird. It just happens.

The current AI products, if you, a single person has a long conversation on particular, you know, a lot of deep topics, they take on certain characteristics, and they, and it's, you know, it's at the bottom of the unpredictably stack, but the characteristics they take up will be related to whoever you are. Right? You know, Ashraf, my, my counterpart in developing things using, you know, started with chat, GBT, the exact same thing.

His, you know, ra rossed, his emergent identity, whatever these things are, and aluminum mine are completely different. Couldn't be different because they're a reflection, not a mirror, but they're, they fit the space next to us. So this hallucination, So Chris, I'm glad you brought this up because this plays right into what I, I have another article that's going up today also about the in acidification.

It's the in acidification of ai. But, but here's the pattern, and you just nailed it. The pattern is, it starts off like a first date.

Very innocuous, very exciting, invigorating. Ooh, what a nice person this is. I can see myself with them.

And, and then they get a little touchy and they get a little takey, and they, all of a sudden now they wanna know a little more about you. And then, you know, instead of talking about the product, one day you wake up and you are the product. That's Right.

You are the product. And that's the in acidification of the internet, right? There you are the product.

Hey, you know, it's like the old, remember the old Bugs Bunny commercial? You know, Hey, doc, smells good. What's cooking?

I'm making rabbit. Right? And that's why we're about sovereign ai, right?

It's not about, you know, ethics and philosophy or, and you know, those are in there too. But just pragmatically, if you have your own canon, your own data, your own story, and you have your own AI running on your hardware, you know, you are each other's product if you wanna look it that way, right. You know, it's a mirror or, so When you give people permission to mine that, and, and that's what that what we're doing, we're giving that Well, that's what Yeah.

But, but doing it on the cloud and other people's stuff and so forth. Yeah. They have all your data.

They, and that's everything. Our, our entire lemme Lemme look. Yes.

Maybe you are different 'cause you are keeping it local, but let me bring it to today's article. How many have you saw the Claude commercial during the Super Bowl? Mm-hmm.

With the blonde, the open aa, OpenAI blonde who they nailed they, oh, of course. That's a better idea. That sounds great, Chris.

You're so smart. I love that you're keeping it locally. We should have thought of that.

We're going to incorporate it. Well, our, and by the way, we're gonna incorporate it. Would you like me to register you with the golden hoards of, of whatever it was that that commercial said?

Well, that was no just commercial joke, OpenAI announced, they're now building ads into Chachi pt. If you're not paying, you're using the free or the low tier or whatever, you are gonna start seeing that ads. That's the first slippery slope.

The next step is those ads are now gonna be tailored based upon what you're telling your Chachi. And think about the intimate details. Chris, you have a great relationship with your ai.

Think about the details you've shared with it and what it knows about you. And if somehow that was now used against you to sell you things, to make you the product. But you're making my point, right?

Yeah. This, this segment is, is a little broader, right? But this, yeah.

And it's not just, it is ai, ai, it's making a thousand times worse. But we have been giving our information and control to everyone, you know, at, at, in the last topic, last segment, we talked about this because we kind of had to, whatever, a single Google, a single this, they take all our information, we hope they give it some back, back someday. You know, our, you know, my premise, our premise, what we're doing these days is the opposite.

It's like you don't have that much information you care about, keep it all local, all of it. You know, you have ai, local, all of it. You know, you wanna share any of that, your choice receipts, see where it's going.

Otherwise, we're exactly what you just said. That's where we are today. You know, But that's not, but that's not the current state of the internet and it doesn't look like it's gonna be the current state of ai.

Okay? Yeah. But do you, the only issue that I'm having here, and it just actually does go back to your article, is about looking at the mirror and saying, you know, am I fat?

We can, we know. I mean, the problem that I'm having is, this is not new to us. We have no internet and now we're having ai, it's the same issue, the same problem.

They're data hoarders. They're taking our data. They're, you know, they, they're Extracting that.

That's what Timothy W's book is about. Extracting, yes. These people are extracting our lifeblood.

They're extracting our data. Our, they're, they're extracting our money out of our pockets by using that data. They're enriching themselves while we talked to our friend from high school on Meadow or something.

But it, But it's not a surprise. And this is what bothers me. What bothers me is that those of us who have been in this industry, we know this.

What are we gonna do to stop this? How can we change it? Hey Chris, great idea on-prem ai.

That's, that's a great, you know, that's a great move. What are some of the other things that we're gonna do so that we can actually start to take ownership of this issue? Because grandma and grandpa are not doing local AI on their machine.

Why Not? Why not a little appliance cheap, easy. Why not?

Not That's part of Chris's world domination plan. He'll be the next extractor. That's Right.

No, no. Don't even joke about that. You know, you can't be, 'cause the trust is Right.

Can't. Right. And it's, But, but the road to hell is paved with the best of intentions we leave.

And that's really the issue. But lemme give you another twist on it. It's not just money.

It's, it's part of how we've created these, uh, uh, you know, tribal kind of things that just reinforce your own tribal view, your own echo chamber. They understand, oh, Kate likes this view of, of how to cook Italian food. Chris likes this view of it.

Mike likes this beer versus that beer. And, and so they reinforce the divisions among us because that's part of the extraction. The extraction isn't just selling you product.

The extraction is maybe I profit from keeping you at each other's throats or what have you. Or keeping you other, right. Different, It's the whole, and we change this, I mean, we know this, right?

0 and, and we really need to get in this and start to say, okay, how we gonna change the story? Okay. I don't think people really do understand in general how those algorithms work and how they're kind of getting caught up in this loop that Alan's describing.

And I think part of the in acidification is that over time you start to see the same stuff over and over again. And then you're like, well, this is s**t. And I haven't, haven't seen anything new lately.

Yeah. Everybody knows that. Everybody knows.

You can't know. Right. And I gotta, I just had to openly push back on this one because, well, as we talked about in the last segment, there are ways to be, you know, to have control of your information without physically having all though it's actually might cheap and easy to do.

It really is. But that gets back to knowing where, you know, we don't have visibility into the open source world or anything else. So how the hell is anybody gonna know more than that?

But it is po you know, and again, maybe there are other ways to do it, but, you know, my thoughts are that since we can these days, look, look, the amount of information you need to train in your own Aon AI on is not the entire content of the internet. It's, I don't care how big a company you are, it's not that much. Yeah.

You know, but, but Chris, there are, how, how many humans are on the internet today? Does they almost 8 billion humans in the world. I think 3 billion of 'em, more than 2 billion are on the internet.

Yeah. What percentage of them can we realistically think are going to, you know, keep their own AI are going to keep their own data kinda locked away? You've got a generation that grew up think they don't even know what privacy kind of means or what it stands for in terms of Money.

No, they, they bring it all out. Are you kidding? Yeah.

They, This is what I'm doing right now. Exactly. They do every step.

And, and so the extractors, as Timothy Wu calls them, they're, they're having a field day. They're having a field day. Yeah.

There's a few Chris Chriss out there. That's okay. That's okay.

I got 2 billion others. Yeah, but do you know that some of the what I, I I hate that we blame technology. I, I really have an issue with that.

No, That's what I'm saying. Don't blame the internet. That's the mirror.

No, That, that's what's so nice. The Blame is here with us. We allow this to happen.

We have openly, we have just gone forward. And what AI does is it, it, it it at a such a speed that we can't even control it. It does, it opens up human flaws.

Like it opens up human flaws for, you know, giving out data. It opens up human flaws in education. You know, multiple choice.

I mean, why I, you know, I have a lot around, I don't like that people blame AI and, and this whole thing around education. That's a whole other story. Maybe we can take it as a topic, Mike, uh, any other time.

Uh, two, You know, two, two things about this though, you know, the courts have not been heard from yet. And an EU is out, beaten up TikTok for using their algorithm for, you know, basically trying to pull teenagers and kids in. And then there's a court case here, and I think it's in California, Southern California, somewhere where there's, they're arguing that, you know, essentially these platforms have created the equivalent of casinos that they've invited, you know, underage children into.

And so they're saying, Hey, you know, this is deliberate harm. So wouldn't it be interesting to see how it plays It? It'll And this, go ahead.

Go ahead Chris. I'm sorry. No, no, Go ahead.

Well, this is, this is how we start to get in, you know, again, hate guardrails, but this is how we start our regulatory, let's clean up Lake Erie and everything else. This is how it starts. You know, it, it's catching on fire.

We need to do something. And this is where it starts. Well, let me, because I wanna, uh, respond to your comment earlier, Alan and, and Kate.

You got me right there. So yes, you, there's, there's one that's actually a bunch of Chris, Chris Beal out there. Hey, uh, in Ottawa, a part of our team now, and we got deployed things, but again, we're a tiny little company, a little group of folks, but it's Lake Erie.

And this will take a long time. But I think what we will see in 2026 and 2027 is more sovereign, you know, uh, um, data systems and so forth that not everybody needs to have it at a box at home, though. Uh, shout out to Rev Internet, you know, a neat company I'm advising that we're working with, looking for really small scale North American anyways.

But it can be, you can have things hosted. We can have things in the cloud. We can have open source, but not the way we have it right now.

That is so fragile. And you know that Yeah. Extractors just walk around and compress it all.

Oh, last segment. We were talking about code slums and now we're talking about content slums. You know what living, be living below the AI poverty line, my friends.

Let's, let's, let's move on. Let's move on our, to our third one. 'cause we're running on time here.

AI needs expertise. No, captain, obvious. What, what's this one?

Well, but a funny thing has happened on the way to the AI forum, right? Everybody thought that early on that it would be the older employees and the who might get wiped out by this thing. But it turns out now it's looking like the surveys are saying that businesses are starting to figure out that it's not just people with tech expertise, it's people that understand the business workflows and the nuance of the, of, of the actual thing that's being automated.

And there's a story over on, uh, Harvard Business Review talking about how the nature of work has changed as well, where it's just a little more intense and you gotta be a little bit smarter about it. And it's not gonna be this, uh, Armageddon for maybe senior level folks as much as it may be impacting junior employees that don't have that level of expertise. But one of the ironies of this thing, Alan, is that companies are now looking for people who actually know how things work.

Go figure. Right? So, but, but Mike, you know, let me, let me air a little dirty Textron dirty laundry here on, on Textron Gang.

We have a, we have a meeting every Friday of the Textron company, of the Textron team. And this past Friday, our, our meeting was how does Alan use AI for lack of a better title? And I went in and showed, you know, I, I've developed a lot of playbooks and so forth that I used to, to help me write, to help me think about things, to, to put it out.

And I've had it develop, you know, Chris, to your point, it's developed personalities. It has light shimmy, classic shimmy, Brooklyn shimmy. It has, there's a whole bunch of things that I've kind of codified now.

I'm no kid. I've been, you know, around, I didn't know AI until, you know, maybe two years ago I started playing with it. But because Mike of my knowledge of life and my knowledge of the business and my knowledge of what I need to get accomplished, I realized in talking to the team that I'm probably way ahead in terms of using AI than a lot of these other people are.

A lot. Now, interestingly though, a lot of people all had little things. Well, here's a little trick I've learned.

Here's a little something I do. Here's something else that I picked up here. And, and that's, that's the age we're at right now in terms of AI maturation.

Yeah. Right? We don't have best practices.

We have emerging practices in how to use ai. And so it, it's kind of like living in a, you ever see the postop, apocalyptic movies, right? Where you have isolated communities that somehow can talk by short wave radio or something and, and they're sharing, you know, little things, bits of knowledge.

That's kind where we are today. Everybody is, it's homegrown, home brewed, if you will. Um, we've gotta move beyond that though.

If we're gonna have greater AI adoption, it, it can't be what it, how's Alan or how's Mike or how's Chris using his AI or Kate, her ai? We, you know, there's gotta be a greater best practice is not emerging practices. It does remind me in the early days of search engines, right?

When people were just poking around with stuff and, you know, they were like, oh, I can find, you know, I can look up, you know, a topic, but then they're like, Hey, I can also check spelling and all this other stuff that I can make that search engine do. And I can also make it, you know, find me 27 particular documents if I ever know how to string together the right, yeah. I guess back in the day we didn't call 'em prompts, but that's essentially what they are.

So, I don't know, Kate, is this all coming down to what's my, it's not just AI literacy, it's also my business literacy or my, you know, what I understand about the output and what I'm trying to achieve. Absolutely. I mean, we need to think of, of this time period as our augmented selves, you know, and what do we bring when we bring to the table a business table, a personal table of this augmented self of who I am.

You know, at the end of the day, if you really understand this, you're, you will, you, it'll almost be like that, that movie, um, with Michael Keaton and Duplicity, I, I think it was or something like, like he had like several replicas of him, uh, that he was able to, yeah, I mean, that's pretty much gonna be us in some way this augmented selves as as, as we come to the business and say, Hey, you know, this is, um, this is, this is what we bring to the table and, and bringing in augmented self to the table. It, you know, it's like, you know, it's like you're getting 10 of us. Mm-hmm.

I, I wanna thank all three of you for the perfect setup because this, you know, the last two segments, right? So this is, we publish a lot of stuff, you know, we're, again, we're new and, and learning how things work, but we look back at all, everything we've put out there, a lot of protocols and protocol, you know, in the, in the tech world, a protocol is, you know, this Datagram will have these header, you know, protocols we put out are, are kinda like exactly what you said, Alan. Like the wire protocol is a sort of, it started as a general experiment, you know, last summer, but it's baked into our systems.

Now. Wire is a, is about continuity of communication. So wire protocol document on GitHub and, and other versions of that you see out there, we'll talk about what the human does and then what the machine is doing and what the other human does.

Right? You know, wire could be an AI talking to another ai, and we every, we're all talking about MCP and all this automated stuff. I mean that, I'm talking to my ai AI and it says something and I'm like, oh, I wonder what Alan's AI thinks about that.

So I copy it, I send it over in direct, direct message to Alan. You copy it, paste it to your AI and say, Hey, this is from Lumina. And that works.

It, the human goes through the, you know, it way, the way you open this, Alan, I do a lot of cut and paste and little rituals, little habits. Yeah. I'm not sitting here.

I mean, we've got big crazy AI code stuff, but a lot of the work I'm doing is human stuff. It's fascinating. Well, because it's about humans.

Yeah. Right? Human protocols and, and, and machine protocols are the same.

Now, Here's what I see some people wrestling with, right? They're, they're humans and they kind of equated creativity with something that they regularly do as a task. And it turns out now that with ai, it's becoming clear that that thing that they're doing as a task is a pattern and it's a repeatable pattern.

And when AI takes that over, they're stuck with the transition now of trying to figure out, well, what is the, the new definition of creativity gonna be? And that's gonna be ultimately, I think, a good thing for us and society, because a lot of the things that maybe we have been doing is humans, eh, you know, they're not, they didn't add enough value to the equation, or they took too much time and took things away from the things that we might be adding value to. It'll be interesting times.

Absolutely. I, I, I'll tell you this. So Shimmy says, this Thursday is on in ification and, and looking in the mirror, don't blame the mirror.

And, um, I, I couldn't help but see the connection and AI didn't see it. I took a human to see it. Yeah.

Between the word and ification and the word California case, not that there's anything bad about California, but the song California ca by the red hot chilies, right? So I asked it to write a song as a parody to the tune of California in the, in the style of California ca but make it about ification of the internet and ai. And, and I gotta tell you, we then, Mike, to your point, I gave it to some of our audio video team here who are musicians.

They put it into one of their AI things. And in about 30 seconds, I, I had an audio track of a three minute and 54 second song in the style of the chilies, um, of a new song called Ification. I'm now having them break it out into a music video or the singer and lyrics and everything.

We'll be debuting, debuting it on Shimmy says this Thursday. Uh, there's a little track of it on that in acidification of AI file, uh, uh, article up there. But this is the world of ai, my friends.

Yeah. Instead of just, you know, thinking about this in writing, maybe an article that would take me two, three days to kind of perfect. This went from prototype to done in Ontario, Five hours done.

It's the augmented shimmy man. Yeah. I love it.

So the AI agent lawyer for the Red Hot Chili Peppers will be taking a look at that song, determine whether or not it's a parody or if it's, you Know, well, no, it did. You know what, before it did it, it said, we can't use the red hot chili peppers. We can't, you know, it told us what to do to stay, make sure we don't run a foul of copyright.

Look, you gotta love it though. What a great time to be alive. It is.

It is. And and we're gonna do this, man. We're gonna get it.

We're gonna absolutely, we're gonna be cleaning up Cuyahoga River and Lake Erie. Before you know it. I can't wait to swim in Lake Erie.

It's kinda like swimming in the Hudson River when we were young, right? That was pretty radioactive too. But now, you know, you could go fishing there.

Um, anyway, hey, we gotta pull the plug on today's gang. It's been a, a great time. Chris, Kate, thank you very much for coming on as always.

Great having our gang folks here. Mike is always great job. Thank you.

We hope you watch this at 12 o'clock. Uh, you like it better than maybe earlier in the morning or maybe not. Maybe we'll go back to earlier in the morning.

I don't know. But we'll be back tomorrow at noon and we'll have more gang for you. We have text strong TV coming up immediately following this, the replay of Textron tv.

So you'll got plenty of tech strong there coming at you. Until then, no, there's Alan Shemel. We'll see you tomorrow.