AI’s Economic Impact, Platform Engineering, and a Chilling Cybercrime Report | TSG Ep. 887

Hey everyone. It's the C-Suites dilemma, AI cut bait or double down. You're watching Techstrong Game.

Hello everyone, happy Thursday. Welcome back here to Textron Gang. We've got a great lineup of stuff to talk about, topics to talk about here on the Gang, and we've got some really, really interesting, fun people to talk about it with.

A lot of 'em, of course, have already been here before. Uh, let me intro quickly introduce our gang members. Today we have Terry Robinson, Garima, Bal, guy Courier, and you have Geni Caram, and of course, our Dean Mike Ard, gang members.

Welcome Mike. You know what, what is a poor old C-suite to do? They're dropping like flies.

Should they, should they double down on AI cut date and run? What? What's the deal here?

It seems like there's this kinda hope in the C-Suite at least that ai, somehow or other, is gonna change the economics of doing business. And, and they've all seemed to grasp it. It's kind of becoming something of a religious moment.

But when you go after the average worker and including a survey also from other senior leaders, for that matter that PWC just did, it suggested, we don't really trust AI agents for anything mission critical. We're using them for support functions. And that seems akay, but that doesn't add up to math.

That says that the economics of the business is gonna fundamentally change. And I know you have a post over on Techstrong ai Alan talking about that same issue. So, I mean, what is your real assessment of what's going on here?

Because I think we're setting ourselves up for a bit of a fall. Yes and no. Yes and no, right?

Because, you know, if, if you are A-C-E-O-C-T-O-C-P-O, whatever, you're c-level leader of your organization, you have a fiduciary duty almost to use what's out there to make your organization the best it can be, as profitable as it can be, as successful as it can be, whatever the corporation's goals are, the organization's goals are, AI is certainly a tool that can help. It could, it could save overhead, it could reduce labor costs. It can make you more efficient.

It could automate more. It could do make you better. On the other hand, as we've seen in stories coming out this week, it could delete your production database, cover it up and make up information too.

So, and when it does that, you know, blame the poor ai or who gets the blame? Well, ultimately the buck stops here at the C level desk. And so if you're a C level, the dilemma here is, do I, do I go all in, put my chips in the middle and say ai, damn, you know, damn the torpedoes full speed ahead.

Or do I say maybe risk being a laggard. Go slow old school and let someone else fall on their sword before I try to walk through this minefield. Now, the article, we, we we're citing here up on Techstrong AI is one I wrote, and I, I try to give a blueprint, a roadmap for C-level people to, to kind of look at and, you know, make Nexus decision points as they roll through this.

But, you know, uh, there's another article on, on the Textron ai well as well that, you know, according to a p WC survey, they're not giving, uh, trust. They're not trusting AI and AI agents in high stakes mission critical use cases just yet. That might be prudent given news this week.

But, um, but the, you know, when you're a C-level guy, either you're going for it or you're not cautious people. I mean, you know, cautious CEOs who lay back and let others go first generally are not, are not the, uh, you know, they don't have a long lifespan. Most companies wanna seize the moment.

So I, I don't know what the right answer is. My tendency full speed ahead, damn, the torpedoes, right? If you're gonna go down, go down fighting.

Rob, I think we got a little break there, hopefully, but Guy, Go ahead, Guy, you wanna jump in here for a second? And, you know, what's your assessment of what's going on here from where you, where you sit? ai.

Um, uh, it's called Cut Beit or Double Down. I really recommend the article that he wrote published yesterday about this, because it is quite practical and it names five ways that, uh, the C-suite or management can, uh, make sure to, um, to approach and adopt and use AI effectively. I do think one thing continues to be missed or misunderstood, um, and has been since the beginning.

Um, and if, if you'll forgive me, let me just say that it's sort of human nature to, to run with anecdotal evidence instead of, you know, uh, uh, what, uh, you know, um, objective or empirical or whatever. Like, there's a lot of words for trying to understand in the aggregate or statistically speaking, what's going on in this case, what the benefits of AI are. Um, everyone's personal experience with AI is something that used to take me an hour or two hours.

Now it took me five minutes, whatever it is, looking stuff up on the web, drafting an article, whatever it is. So the, uh, you know, how many folks on this panel here in this show, um, think that or believe that the market thinks that the main benefit from AI is productivity, that one worker's gonna be able to do what two used to do or more, or that, uh, each worker's gonna be able to produce more. That is the general consensus, and I have been maintaining since the beginning.

But that is not the benefit or the metric you should look at. The two you should look at are, uh, quality and reliability. Quality sounds dumb, right?

Because AI makes mistakes, hallucinates, and a lot of AI is actually getting worse at the moment rather than getting, getting better in terms of accuracy, let's say. But quality goes up when you have a continuous companion, whether automated as an agent or at your command in a chat or something. When you have a companion, even an artificial one to help you do your work, it's still your work.

And you can go through more review cycles and add things that you might not have thought of and construct things in ways you might not have thought of thanks to your AI companions. So the quality of your work goes up, the reliability goes up, because all those things that you have to do, like research or whatever, that you sit there putting off and, oh, maybe I'll walk the dog now, or maybe this is the perfect time for me to clean the kitchen. Instead, you have your buddy, your enthusiastic buddies who just go and do it for you.

If CXOs, if, if CXOs or business leaders are thinking in these terms, not in terms of, oh, now I get to fire half the marketing department, but rather I can get better results and I can measure those results, that I think is the, the, with Alan with great respect to what you wrote. 'cause I think it's really useful. I think that's the one thing you were missing.

What are you using this for? Not, not to you, you, you tell people, you, you're providing the, the guidance to identify that that's true, but we are sort of lacking in general in the market with nice, strong points of view. Like I just gave, and you can disagree with me, but it's a pretty strong point of view as to what you should be using all of it for.

And I would say for ai, it is quality of work and reliability that the work will get done on time as well, and productivity flows from that. Evgeni, you raised your Head. Yeah.

Yeah. So guys, thank you very much. I think it's a very important point.

I want to add a couple of ideas here and maybe kind of have a small debate. 'cause you mentioned helper. When I think about a helper, helper, somebody helps me.

So basically, each of us now have a helper, or two helpers or three helpers. But in the environment, when we are going in a manufacturing or hospitality or anywhere else, we're talking about C-suite, I'm thinking about a mechanism, an AI that help my customers or help somebody externally. So it need to be doing multiple things.

This could be customer success. This could be providing advice, this be potentially booking flights, constant flight, whatever it is. And what, where my mind is going is not one or zero working, not working is what's happening in between what happened when the AI make a mistake or we found a bug.

Because if it, it's a thing. The AI is a human, or like, as a human, it make, make mistakes. But when a human making mistakes, it's case when AI make mistakes, it's working at a hundred times thousand times faster.

So the mistake can escalate much faster. How do we debug this? How do we create this?

How do we have high availability? How do we fix the car on a fly while we're driving? Do we have another LLM AI that we take this out and put to somebody else?

What do we fire our entire booking department for travel and put the ai and now we need to fix it. So let's take that example, let's take that example. It's a very good perspective, AIAN, thank you.

But let's just take that one example of you're right in the case of, uh, a customer service, a chat, or whatever it is, you're, you are providing that buddy, i, i described to the customer, if your goal in use in creating that aspect to your interactive application with the customer is to help the customer get a higher quality result more reliably, then you'll develop that AI in, in a better way. In my opinion, in my opinionated opinion, the usual goal for putting AI in those scenarios is that you can have fewer employees on your side. It's your benefit, not the service benefit.

And that's a fundamental problem. And, and it affects how you measure ROI, Alan, which is your number one thing to make sure of, and I completely agree. How are you measuring that?

ROI, that ROI may not be in terms of lesser salary or what have you. It could have to do with like a better brand, better perceptions, higher, uh, a net promoter score, like that sort of thing. Agreed.

Agreed. Well, look, I it's not though it's a a, an exciting time to be a C-level person and what AI can do for your business. This ain't a slam dunk, right?

This is not just full speed ahead, this real right? This is a time, it's a little choppy. The water's out there right now.

And, and, and I, you know, a little caution may go a long way though. You don't want to be the laggard, I think, I think there's a, there's a lot of room for fact checking in the world. We need to hire fact checkers now for Ai.

A fact, AI fact check. Let the AI fact check the ai. Hey, we're gonna take a break here on Textron Gang.

Let's come back to our B block today, which is about platform engineering. Nice topic to talk about. You're watching Textron Gang Discover Textron Group, the epicenter of tech innovation.

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Hey folks, it's Alan said, we're gonna talk about platform engineering. com. We invite you to check that out, but it says that sometime after the turn of the decade, this platform engineering market will be worth, I don't know, I think it was $40 billion.

Is that the number, Alan, right? But Garima, let's go to you. I mean, here's my problem with this whole report, and I, it's my problem with any of these reports, but, um, so we were investing in other things in IT before platform engineering came around.

So we just double counting here because some of this was our DevOps spending and our IT infrastructure spending already, or is this actually on something called platform engineering that's net new, above and beyond what we were already spending? Thank you for that question. And again, um, I'll start from basics and then we go onto this question.

So I was reading this report as well, and there is another, um, uh, report from, uh, Gartner, which says that in 2026, around 80% of large software engineering organizations is expected to have a dedicated platform engineering team. And, uh, if you look back like this moment of somewhere started in 20 20, 20 21, and then, uh, it has picked up from there. But what is, uh, uh, to your question, what is fueling this growth, right?

I mean, of course, uh, there's a plethora of tools and applications, but I will actually, uh, uh, identify two, uh, two areas which is fueling this growth and it becomes more exciting for investment per, uh, per se from DevOps and SSRE practitioners. The first aspect is, uh, AI and the interest of AI native workloads, integration of AI and advanced technologies. And when you talk about commercialization of generative AI technology and other advanced analytics, this is pushing enterprises to upgrade their infrastructure, for example, including data structure, uh, centers and networking storage.

And I'll come to some of the recent announcements which will prove this point. Um, another, uh, growth, uh, example, and this is again, uh, based on, uh, you know, my findings is there's a substantial amount of interest in vertical powerhouses like banking and financial domain when it comes to platform engineering. So we have often talked about, you know, how lucrative it looks, uh, from large or enterprise level, this platform engineering, because it, of course, it cut downs the overload.

Um, it also has, uh, streamlined developer, uh, workflows. It has substantially contributed to developer productivity. But there was one thing which I was watching out for, what is it in for small companies or mid-size companies?

Because it was not proven that platform engineering is, uh, providing benefits because it becomes a limitation to a certain extent if you, uh, look at small companies, uh, who have to invest four, five people into, uh, upkeeping the platform. But now there's an interesting development because of this AI integration or AI native development. And this in, uh, interesting development, I will quote some of these cloud providers.

So, uh, cloud providers have jumped into the bandwagon, right? And the platform engineering has become an essential component for cloud service providers. For example, if you see what Azure has done, they have launched this dev box, which is basically, um, ready to code environment, which is cloud based development environment.

And it is primarily targeting like small companies, right? So this is an, uh, substantial amount of kind of, uh, in, uh, has gained substantial amount of interest from small, uh, companies and even solar printers. Uh, another, uh, interesting development which has happened from a cloud perspective is let's say Azure arc.

If you look at Azure arc, what they have done is that they are not talking about interoperability the same game which they have done when they explored like beyond Microsoft, right? So Azure ARC is exploring multi, uh, cloud environment and how, uh, this platform would enable multi-cloud environment. Of course, they, uh, see the need in the AI era, right?

Um, if you, uh, look at other cloud providers, they are still kind of, uh, pivoting, uh, carefully. For example, Google has this, uh, GK first, um, perspective on their development platforms as well as, uh, AWS, uh, it's also trading cautiously. But what the most important development of the week, and this is, was also covered by Techstrong TV, was Broadcom and the announcement, uh, by vm, uh, like Broadcom that VMware, this platform, VVCF nine.

And what VCF nine is kind of doing is that it's enabling platform engineering concepts, uh, uh, to a certain extent for private cloud, right? So then it's changing the game a little bit here and Hawaii again, why this whole interesting development is happening is to a certain extent, it's fueled by AI and AI native software development. We can talk a little bit, uh, more about MCP, for example, and MCP marketplace, which is another exciting development which is happening.

And I do believe that MCP marketplace will be a new feature in platform engineering or platform engineering space. So it has a lot of potential in that, uh, regards, but I will give it back, Mike, to you for more perspective on this. So, so yeah, I, here's my take on this, guys.

Mike, to your original question, Greenman was a great answer. Platform engineering needs a Statue of Liberty. And since we don't seem to believe what's written under the Statue of Liberty anymore in this country, maybe we should give it to platform engineering.

And it says, send me your, what does the Statue of Liberty say? Send me your homeless. Send me your, you know, poor people send me poor your huddle mass, right?

Yeah. Your huddled masses, all that stuff. The deal with platform engineering is, it's not nearly new.

When you look under the covers, the name platform engineering is sort of new. And the, the title a platform engineer is sort of new, but the, the, the things that platform engineers do is not new. We've been doing them for years.

We had CIS admins doing them, and we had, you know, ops people doing them and what SREs do today and all, you know, so when we look at that $40 billion, a lot of it was money that we were already spending. Maybe it had, it was under different tents or different titles, and we're now pulling it under the umbrella of platform engineering as it pulls all these disparate un huddled masses of people and gives them a place platform engineering. So are you saying, Alan, that the, that the growth projections and, and total available market refers to the total available market for a marketing term, a new marketing term platform Engineering, not, not a new marketing term.

That would be a first term, but it's a new, it's a new grouping of existing dollars. And, and when you look at the history of modern platform engineering, you know, since we coined the term, well, originally it really referred to can I manage Kubernetes? 'cause it was really tied into Cloud native and Kubernetes.

But, but it's, it's morphed a little since then it's grown. It's not only now can I manage Kubernetes, but what's really driving platform engineering today is I need to manage my i internal development platform, internal developer platform, my IDP and the IDP is what's driving our platform engineering team. And, and that lends itself, gima, to your point, that lends itself to large organizations where you need an IDP 'cause you've got dozens, hundreds, thousands of developers.

If you are a little shop with a half a dozen people coding, you probably really don't need an IDP. And, and then hence, you maybe don't need a, a platform engineering team. So if you are an insurance company, okay, you are only doing insurance, are you a platform or you still have one function?

If you are a bank, you may become a platform because you may do multiple things. If you are a cybersecurity vendor like Palo Alto or McAfee used to be, when you have multiple products, you have a platform. So I guess we need to also think about the idea that if I don't have a very big development shop, as you're saying, or many different products, I'm not gonna be a platform then no, you, If you don't have a big development shop, you may not need an IDP and hence you may not need platform engineering.

Is, is, I'm, I'm gonna go a step further though, because I think that this is a, the beginning of something larger and great that we're talking about IDPs and centralizing application development. But let's be honest, the management of it and the enterprise is a frigging mess and has been four years. We have all these different silos.

We spend a fortune on the cost of labor to manage all that stuff. And mainly because we're spending a huge amount of time trying to integrate and maintain this stuff, it is fundamentally economically insane. Platform engineering is a step towards centralizing that in a way that makes it accessible, right?

I have the notion of self-service, so people can take care of what they need. And I'm not beholden to some autocratic CIO somewhere to do every stupid little thing that I want to do, but we have to get back to some fundamentals of the economics of it, which right now is kind of a disaster. So this is a step in the right direction, Right?

I agree with Mike and Alan, both of you, because I, I wanted to kind of, uh, also shed some light on, uh, you know, why platform engineering becomes very important for DevOps practitioners, because history reminds us why DevOps was, uh, important for us. We were lean, right? And with the plethora of tools, which we see, the complexity has, uh, uh, increased tenfold, right?

So platform engineering is streamline those, uh, developer workflows. This is like providing some kind of, uh, value for money for companies and investments, even if it was investments in 10 different directions. I think platform engineer is giving that lever or tool to ensure that the return of investment is secured by, you know, investing in the right kind of tools.

I'm also following some of the talks. One of the great talks this, uh, week was on DevOps, uh, Munich, uh, there was a conference there where they were talking about graveyards of tools because there is a lot of tools which are being ob becoming obsolete. So I mean, there, there is a potential of looking at it, uh, from a platform perspective, a very different, uh, different with a different lens.

And to your point, actually, you mentioned that if you're an insurance company or a banking company, I would say that every company is in a software company today. So this is very, very important that we, uh, ensure that we take our software workload developer experience very seriously. And why it is important, essentially becoming important for smaller companies is because, uh, it provides you the capability to exponentially scale, Right?

And scale is what it's about, and scale is what platform engineering's about. But hey, we gotta take a break. We, we ran outta time for this topic today, I apologize, but we are gonna come back.

We've got some cybercrime investigations, and we got a couple of cybercrime sleuths right here. com is the leading resource for news analysis and education on challenges facing the cybersecurity industry. com covers all aspects of cybersecurity, including data security, DevSecOps, cloud security, application security, network security, security threats, and more.

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Home of security bloggers network. Hey, folks, we're gonna shift gears a little bit and talk about cybersecurity because, well, it looks like the bad guys have figured out how to hack into the surveillance state and are using it to well commit murder. But Terry, you wrote this story for us in Security Boulevard, and is, is this kinda like some weird way of where the infrastructure that we created is now being hacked into by the bad guys for illicit purposes?

Well, yes, and, and not surprisingly, right? We've talked about this before, how the bad guys take the good stuff and, and use it as, uh, for their own nefarious, uh, actions. Um, so, so what basically Happened, they're like committing murder, by the way, like Literally this time literally, committ committing murder we're not figurative.

Yeah, Yeah. The way, Mike, the way you said that it was like committing murder, you know, like, uh, like, like the kind of metaphor my mother used to use. No, we're talking about literal murder.

Sorry, Terry, I just, This Yeah, no, no, no, that's okay. This is, you're, you're right, it's literally murder. Um, so what happened here is, uh, so this all stems actually from an IG report, uh, for the FBI that came out, uh, last month, that they're just, they're actually trying to, uh, audit like, uh, the FBI's efforts to mitigate the effects, um, of technical surveillance, which is just ubiquitous now, right?

It's everywhere, not just in Singapore, which we've, I think we've discussed Singapore, how creepy it seems sometimes that these cameras are all over the place, but they're, they're everywhere. And, um, one of the, the stories that they recounted in this audit was, um, about in Mexico City, um, there was a hacker affiliated with, uh, El Chapo's cartel, or one of his cartels, and, um, this person or group or whatever, um, actually surveilled the FBI, uh, building there, or the embassy in, uh, Mexico City. And they identified like an attache and, uh, other, other people.

And then they focused in on this, this one person, and w they were able to access his or her phone records, location data, contacts, all of that. And then they used the, the web of cameras in the city to trace, um, informants, like track them and then in some cases kill them. Uh, other cases I think they probably just put pressure on them or whatever.

But yeah, so literal murder, um, and it was a like, sort of this interesting combination of tech. And then that old school kind of, you know, you used to see in the Rockford files or something where somebody, you know, is, is uh, is uh, casing a building, uh, and, and watching people, you know, like literally a person out there observing people. Now they're not a hundred percent sure that this hacker was a person sitting out in, in front of this building watching people go in.

Um, there could have been all sorts of, um, technology involved in that. But, um, so First of all, I thought they fired all the, uh, uh, uh, inspector generals. Well, so, and so that's like, you know, when I was first looking into this, um, I had a little moment of satisfaction.

Those igs are really super valuable to government. And the fact that we got Rid of, well, if you don't fire them, they are, If you don't fire them, the fact that we got rid of so many of them earlier this year makes me even more concerned. Now, I mean, about what, With this report, I, I, I, you could probably count his employment on two hits, but, but, but there's another thing here.

Look, the real issue here is in a surveillance state, the, the room for abuse, whether it's by the government itself or people who are hacking into leaky government, surveillance infrastructure is great too. Great, too great. And the, and sometimes you gotta weigh what is the, the, the advantage to the, to the downside of these things and, and make a determination if we're going to have this type of surveillance capability, number one, we've gotta make sure that it legally by government sources has to be extremely supervised and qualified.

Number two, What kind of good luck was that, though? I don't think we're heading in that direction, And that's why we don't have igs the way we used to. But number two, it's ludicrous to think that we would do such a shoddy job of setting it up that would, would allow the, the quote unquote bad guys.

And who's a bad guy today? It's hard to tell when they're all wearing masks, but it would allow the bad guys to, to harness the same, uh, infrastructure that we've set up for this. So it's kind of a double whammy, which leads me to believe we shouldn't be doing this stuff, right until we have guardrails in place.

I think it points to what, how security, at least previously, and hopefully this is getting better, although I can't say for sure, was always like an afterthought when people were setting up or groups were setting up, you know, things like this, right? They didn't really think too hard about security. Well, I mean, that's my own opinion that I don't think they considered all the options.

I also think that the bad guys have gotten so far ahead of, you know, uh, the good guys in terms of how they use technology and everything. But it is a, you know, it is a, a a hard to win battle when you're On the, depends who you think of as the bad guys and the good guys. Like I said, they all wear masks.

There's the ambiguity there is, you know, who are the bad guys? Who are the good guys? It gives me great comfort that the United States Government awards these contracts to the lowest cost of partners with the least amount of cyber cybersecurity expertise.

So I think it's gonna be great. I know, well merit, you know, we're on merit now here, so, um, good to, always good to see. But, um, yeah, so that all that's of a concern.

I will say right here, one of the things that they, they, they do think that maybe there were some insiders, uh, within the agency that possibly shocking, Shocking going on here. That's what struck me, Terry, was, was just as we harp on, you know, uh, AI needs human intervention, cyber needs, human intervention, but it also needs to address the human factor. And, and it seemed to me that hacking into a video surveillance system is one thing.

A lot of these are pretty old and, you know, the, the cloak and dagger of somebody going over to a line and tapping it, like you saw in Oceans 11, which is pretty much mostly fake, but could actually occur in, in, in the case of video surveillance, you could see all that, but it seems critical that they use the same old, usual, you know, pay somebody off method too. Could be, you know, it's, it's a, it's a twisted world, a twisted world. So the IG report also did give some, you know, they, they did offer a few recommendations, although honestly they're fairly basic, so I'm not sure how much help they'll be, but it was good to see the IG active and getting out there on what is an important topic.

Absolutely. Alright guys, I think that wraps up our textual gang for Thursday. We hope you, you enjoyed it.

As usual, we have Textron TV following this, um, on our network. You can also check this out on our Textron tv, YouTube channel, our Textron TV webpage, as well as our Textron TV OTT app, which is available on Apple and Google Play and Apple TV and Roku TV and Amazon Fire. So no matter what you watch on, we've got a text on TV for you, uh, gang members, thank you so much for a lively, great conversation.

Mike. Thanks for leading it. We'll be back tomorrow with more, but until then, this Alan Hummel we're out.