Techstrong Gang – August 7, 2024

Hello everybody. I'm Mike Vizard. Alan Shimmel is out at Black Hat today, so he won't be on the show with, I mean, but we have an awesome lineup of guests, and we're gonna be talking about DevOps and ai.

Then we're gonna be talking about a little reverse engineering of code using ai. And finally, we're gonna have a deep discussion about what it means for Google to be a convicted monopolist. Hey, you're watching Textron Gang, and we'll be back in a minute.

All right, folks, we're back in. Let me introduce our guest for today 'cause we have some new ones. But let's start with Mitch, who is not in Denver today for Mitch.

Where are you? Hi Min, actually in Las Vegas had Black hat. There you go.

Which I'm not sure everybody knows what Black Hat is, but it's one of the big security conferences that take place during the course of the year. And of course we have Amanda Razani, who's home in Texas, I believe. Yes, that is correct.

And then finally, our newest guest, David Nicholson, is out in California. Dave, welcome to the show. Thanks.

Glad to be here. All right. Dave is with Fu Toum, and do you have a particular specialty at Fu Toum since this is your first time at joining us in the game?

Um, I think, I think sort of the specialty that I bring is, uh, voice of the tech customer, because I'm adjunct faculty in the Wharton CTO Academy. So if, if I had to be nailed down to something to a single hat, that would be it. Dave's the guy who talks to CIOs and CTOs every day, that would be me.

All right. That's an impressive program that you're part of too, David. It's a pretty amazing what they do at Warden with you.

All right, awesome. So, and it is fair to say that you are a geeks geek. Try to be.

All right. Well, let's jump into our first topic 'cause we got a lot of geeky stuff going on today. Our first article that we want to talk about is a new report from Textron Research authored by Mitch Ashley.

And it goes into, well, what is the level of adoption of AI among DevOps folks? And what are we seeing? And I know, Mitch, you authored this report and did all the research.

So why don't you kind of walk us through the highlights a little bit? Well, a bit of a, a labor of love. 'cause this is actually an update to a report we did in 2022.

Textron Research did a report about what are the anticipated benefits of ai. You know, that was pre gen ai, um, and in copilots and things were starting to be used and AI being introduced in some of the DevOps and testing and other kinds of tools. So this gave us a chance to come back and say, okay, now a lot of things have happened, right?

You know, the news cycle's about two hours these days. So, and it seems like the AI is on a shorter cycle. So it was really interesting.

Um, we, we talked to a variety of people, folks primarily involved in developing software, ranging from architects to engineering leadership to developers and testers, uh, systems in, uh, system reliability engineers, platform engineers, et cetera. And trying to understand, so, you know, what's happening, what are people, are people seeing any benefit from AI yet? And using it anywhere in the SDLC.

And there were, uh, some, I think some really surprising in a way, findings. Um, in terms of people that are using it, about 24%, um, said that they're, excuse me, about 20% said that they're using artificial, uh, intelligence in some phases, any of the, any one or more of the phases of the software development life cycle. So they're consciously knowing that we're using ai, part of our development, part of our testing part of whatever phase that might be.

Um, and at least 24% had at least one, one, uh, one phase that they were using in it. But the two standouts, probably not too surprising, were the, uh, we're using AI today and writing code, and also preventing defects and doing testing. Those are the three standouts, but not that far behind where other areas of the software development lifecycle, um, I think there were some real eye openers there.

Uh, the people who were, what we call the more, uh, mature phases of DevOps. 'cause we did ask, you know, how long you been doing DevOps? Um, how would you assess your maturity of DevOps?

And do you, uh, how do you see your performing? Are you assessing your, your abilities, uh, as a DevOps oriented organization? And, uh, those who are using AI and are in the more mature stages of DevOps, we call it adoption, we call it the unicorns, kinda at the very top end.

And also, uh, people who are standardizing, meaning they've gone through the adoption, they've learned they're really standardizing DevOps or have standardized it across their organization, uh, rated themselves higher in their performance, or either in the higher medium, two categories as compared to the group who were not using DevOps. So actually not using AI as part of their DevOps. So, um, it's really, it is really, it's a great report.

Um, by the way, it's a very approachable approach, uh, report to, uh, a lot of graphics and, you know, content that you certainly can read it, but you can also skim through it. And there's a highlight section of some of the findings. So that's just a quick recap.

But, uh, again, labor of love. Do these things take a little while to, to get done. And, and it was a real pleasure, uh, publishing it.

And, uh, Tricentis was the sponsor. You know, they had some input on the questions and, and gives some feedback on the writeup. Um, but the, the research is our, so we're, we're happy to be publishing it.

Let me ask you this about it. 'cause what struck me was it seemed like, well, maybe not everybody's using AI just yet, but those that are, seem to be rapidly moving it through the entire software development lifecycle. And, um, so once you get into ai, it seems like you kind of want to use it everywhere.

Very, very true. Um, kind of, there are some, there are some easy entry points, you know, the co-pilots and development is one obvious place because it's already built into many ides and a lot of organizations are, they're not using it, they're experimenting with it. Like, how much do we use it for code completion or do we actually generate some code, um, with it as well?

So that, that seems to be the most common entry point. And then of course, any tools that you're using, like you're using a testing tool that's, that has AI built into it. If you're using A-C-I-C-D platform, um, GitHub, for example, repository, whatever you're using, those are also kind of ways that it's introduced into the SDLC.

Uh, one of the other interesting findings is, you know, our, I think you kind of know the answer to this, but are we just turning AI loose? Do we just let it do what it's gonna do? Or do, do people have to still be in the loop?

And very much, very heavily, um, folks saw that being a human in the loop, looking at the output of, uh, of, of AI in any place in of those places, uh, in the SDC was very important. Just a small fraction said, yeah, we kinda let it do what it's doing. I imagine that's not too, too big a shot doing that.

From that standpoint. We also looked at productivity. You know, what, what is the impact on the people processes and, uh, productivity of people?

And, uh, you know, how much is it impacting your productivity? Uh, how does it help you keep up with the demands and, and across the board of the kind of positive ratings, um, the kind of somewhat more productive, somewhat, uh, usually hitting demands, things like that were, were pretty substantial. Um, but even those in the significantly, in those two categories were, were always, were also fairly high there.

There's a middle of the road, you know, we're, we're not seeing an impact yet, but, uh, there was very little who were saying it's negative on productivity. And we've heard some things about AI taking more time, you know, particularly if you're using Gen AI for writing or things like that. So it's, it doesn't seem like it's getting in the way or taking people too far off course to introduce it into their development.

David, I know, I think it's fair to say that we are in the hype cycle of AI for soft specialty, for software development. What's your assessment of what's really going on here? I mean, last year there was probably a lot of what you might call irrational exuberance.

So where are we on this actual journey? I think we're in the, um, if you, if you go sort of down to the lowest levels of the IT stack, uh, I think some rationality has returned. Uh, folks who are making decisions about building these stacks realize that there isn't only a single blessed way to accomplish what they wanna accomplish in the world of ai.

So I think that there, there will be a lot of, uh, realignment of players in this space. You know, Nvidia, of course is going to dominate, again, diving down to the lower part of the stack. So I think we're in sort of the, the place where we start to get more rational about these conversations.

Um, but, but on AI for DevOps in particular, uh, it's, it's important always when we use either a a if the, uh, if the TLA is a two letter acronym or a three letter acronym, that we sort of define what we're talking about. Because yes, ai, artificial intelligence, well that's a big, that's a big umbrella. People immediately leap to this concept of generative ai, auto aggressive generative ai because we're so familiar with it at the consumer level.

So people, people hear AI and DevOps and the conclusion they generally leap to is, oh, you've got this, you've got this engine that's going to generate code by the use of plain language, uh, computer, uh, I shouldn't say that. 'cause my device will go off here. Sorry.

I'm sorry. I have my Alexa programmed that had to, had to unplug little start reference there. So, you know, you, you say, you say, you say computer, write me a software program with a caterpillar that catches butterflies and the system, oh, okay.

It goes out and it generates the code. That's not, that's not really where we are now. To, to Mitch's point, if you go back in, if you go back in history, we call it paraprogramming.

Um, now you have an artificial copilot with you at your shoulder sort of making suggestions. But the person is very much in charge of the tool. But the vast majority of AI that's happening in DevOps today and everywhere, frankly, is what we would, we would call sophisticated machine learning and automation.

And there's nothing wrong with that. That's awesome. It's where it's gonna begin.

Um, and I guess my final thought on, on, on AI is much like cloud. I think at some point in the not too distant future, we're just not gonna talk about ai. It's all gonna be considered it just like cloud, is it, it's all it, it's information technology.

Yes. What we're doing in AI is revolutionary to a degree, but really it's just the next thing in information technology development. Yeah, it's interesting you, you place it that way.

'cause one of the things we discussed is, what are we title this report is that AI and DevOps is that, you know, software generated code with, with ai. And, and we, we stayed with the AI augmented DevOps because yes, it's not AI in the driver's seat, it's the copilot or it's behind the scenes. Yes.

Um, it's, you know, like your pair programming example, you know, I'm, I'm gonna look at the code 'cause we don't have code generators that we know generate better quality code or more secure code, things like that, more reliable code. So there's, you know, we're relying on some general LLMs to ADIs, at least in terms of generative AI and the code writing part. There's a, there's a long ways to go.

And that's part of the theme of the report is here's the impact we're seeing so far, but we're at the beginning of all this, this is, and, And, and augmentation. IIII love augmented, um, because at some point it almost becomes absurd for us as humans to say that, well, it's me augmented. It's like, no, dude, you were driving a freight train.

The freight train was towing everything along the tracks. It's like, no, no, no, it was just augmenting my strength. Uh, it's like, Well, I, I should say no, AI was harmed in the making of this.

So we're all clear. I had a question in regard to the report, and Mike and I were talking about this yesterday in our podcast. Um, it was another report that we were reviewing, but it was saying, while AI was increasing efficiency, in fact what it was doing was causing more burnout in a lot of employees because they had more of a workload because of the efficiency.

They had so much more of a workload, their brain capacity couldn't really handle it. So they were struggling from burnout. So what are your thoughts on this?

Um, it, it's a great question. It's not something we looked directly at Amanda. Um, and I'm familiar with that report too, of, you know, just, just trying to figure out how to use ai, create more workload on top of trying to get what you're were done in the first place.

So are you having a net productivity gain? Um, when, when we saw kind of, when we saw what the changes in people's work, um, productivity was the first thing that they kind of pointed out. And real closely for developers as well as for test teams.

So, which tends to be, you know, that's, that's, I don't wanna say they're the bottlenecks, but that's kind of two of the things that are essential to get code, get, get software developed and, and get it out the door. There's a lot of other elements as well. Um, and, and they did say fewer resources, full-time people, things like that.

But that we started kind of falling off on what are the changes to people's jobs. I think there's a lot of shakeout to do yet. And, and I would, I've never been a believer of, you know, oh, the cloud is gonna replace everybody's job.

No, it replace, you know, people that, that hung machines on racks. It didn't replace, uh, people doing work. Uh, same thing for ai.

I think it's largely, uh, augmenting what we do. You know, I'd love to have LLMs, we're not here, LLMs that, uh, help us reduce technical debt. If we had an LM to do that, turn that loose on all those things that Dell, the developers don't want to go back or helping us figure out what those systems do, that the people that wrote 'em are long gone and, and we're afraid to touch those parts of the applications.

I think that's, there's some real productivity gains there. So, bottom line, we didn't look at that specifically, but I didn't see anything, the data that, that I got that sense that people are, if anything, they're may be trying to figure out where the best cases in their applications are to use ai. That's where there's new Work.

I would look at, I would look at this productivity question. I, I would ask Amanda, see, you, you see this, you're familiar with the, the mobile device, obviously. Is this, does this give you more freedom or is it a ball and chain?

Right? Oh, it's like, I can work, I can work from anywhere. I have to work from everywhere.

I think that I think those AI tools are, are going, there's gonna be a mixed bag as we go forward with that. Uh, an individual developer inevitably will be able to be more productive if they let that bury them. Like some people let their mobile devices bury them.

It's gonna be tough. It's gonna be tough. Of course, your mileage may vary if you're asking my family versus me, right?

David, let just, You're absolutely right. Good point there. David, let me just ask you one last question here.

It seems like one of the things that's in this survey that leapt out at me was only 9% or so of the folks who are, you know, totally trusting the output of these gen AI platforms. Um, so have we reached a point where, you know, it's great, I got a little tool, it's gonna help me do something a little bit faster, but it's the reality of is it is not this end-to-end magical button. It is a thing that helps us get something started, but it won't complete nearly any task.

Or if we let it complete any task, we should look at it really hard. Yeah. Let's say you're, let's say you're using a tool like this.

How many times does it have to be wrong for you to say, you know, this is a waste of my time. Now I'm proofreading the work of a kindergartner. This, this doesn't make sense.

Eventually people will, will start to trust it. There's a parallel with, um, uh, driving aids, self-driving systems and vehicles. It's the same sort of thing.

It's one thing, Hey, straight highway, I have a three hour monotonous drive. You very quickly will trust the system, try driving that same car with the same system in stop and go traffic in a construction zone on a rainy day. It doesn't take too many.

Whoa, whoa. What were you doing for you to say, forget about this and turn the system off? So, um, I think we're, I think there are gonna be fits and starts as we go, but it's gonna be an upward slant to adoption.

There will be people who will try it, say, ah, forget this. I'll come back later. There will be people who stick with it because they're early adopters.

But over time, more and more people will learn to trust it as it gets better and better. Hey, David, a question for you. Um, uh, this is a big question, but could, are there any highlights you can share of what are the conversations about AI in, in the program at Wharton that you're part of?

What are the things that are bubbling up to the surface? Um, I, well, it's sort of funny. I would say, I'd say going back six, 12 months ago, a lot of the conversation was, um, and I'm being silly, but I'm serious.

These, these, this, this is the way that the conversation goes. The CIO says, I'm really, really upset that we fired all of our people who could be doing work on this stuff, on premises favor of, of, of moving everything we do to the cloud. Because now we have no data center muscle.

We have no one who can come in and create something that will be a unique value proposition in the world of ai. We're a slave to the cloud providers. We can't even buy Nvidia GPUs if we can get our hands on them.

And the thing that makes me the most mad is that I'm the one who fired all those people. You know, that's their thing. They're, they're realizing, oh, wow, if I had known what I know now, maybe I would've held into reserve some of this smarts internally.

So that's, that's one dynamic. But then the other is, is the, the, um, um, what I alluded to earlier, this idea that people are realizing, wait a minute, maybe you don't need the Ferrari highest end Nvidia, GPU based infrastructure completely integrated, uh, stack. Maybe I don't need that for everything.

Maybe I don't need it for anything. Um, people are just learning the difference between inference and training. We focus a lot on training.

People don't realize that there's, in aggregate, there's gonna be way more inference than there will be training. It's just training is concentrated into these mega clusters. So that I, I, I think that's, uh, that's a good, uh, that's a good sampling.

There's a lot, a lot of other, a lot of other stuff. Oh, and the, the final, the final thought I would say is, um, because I work with folks on, on their papers that they're writing over the course of the year on what they're doing with ai, and I would say 80% of it, um, we would all look at it and we would say, yeah, that's ai. It's ml.

It has nothing to do. It's machine learning. It's, which is great.

Has nothing to do with, um, with, uh, generative ai. Not yet in some of these cases. And that's perfectly fine.

Not everything has to be the sexy, shiny, new object for it to be valuable. All right, folks, we can talk about this probably for the entire show, but we can Well, Please, yes, you continue, Mike. Thank you.

We can, we have to move on to our other segments. I would just conclude with remember that thing about trust, right? It's hard to win and easily lost.

We'll be back in a minute. All right, we're back, and Mitch kind of brought this up in the first segment when he was talking about technical debt, and there's now a whole movement afoot to kind of reverse engineer a lot of the existing code that's out there. DARPA has a project where they wanna turn c and c plus plus code into rust, which is, uh, said to be a more secure language because it, uh, doesn't leave so much stuff visible in memory.

Um, and then we also have an article on, uh, text drawing AI talking about the rise of software intelligence, which is kind of like business intelligence for software, where we're gonna do a lot more analytics and understanding how the software is constructed so that we can change it or reverse engineer it when the time comes. I'm gonna start with Mitch. Um, we've been hearing a lot about this stuff about you rewriting entire applications into different languages.

Folks are doing co ball to Java. Other folks are trying to convert things into go or whatever it might be. Is, from your perspective, is this gonna be like a major trend?

Is this the new face of application modernization? Well, I think it's, I think it's a thread through that process. Um, very few organizations are gonna go say, let's go back and rewrite everything in blah to Rus, for example.

Um, but they may say, going forward, here's what we wanna start using. Uh, I, I'll use AWS as an example. Um, they made a conscious decision a few years back about what they wanted to develop their software in, and they chose rush, excuse me, rust.

Uh, I love rush. Different band, different topic. Um, but for a couple of reasons.

You know, CNC plus plus Kenny Lee is a programmer, right? Kenny Love Teddy Lee. Absolutely love all three of them.

Um, yeah, and you remember the days we used to talk about c plus plus and SEA of, uh, oh, there's memory leaks right there. There's things having processes would run a mock and take over and have to get killed and restart it and things like that. There's a lot of housekeeping that you have to do in those traditional languages, um, object oriented or not.

And then we kinda shift to the other end of the spectrum where we use, you used to use Pearl heavily now. We use a lot of, uh, Python, um, and, and any, any number of programming language languages, which tape a lot of that housekeeping away from you, and it's easier to develop in, it's much more approachable. Um, but they don't have things that Rust has.

Rust has, um, what they call type safety, meaning this variable is an integer, and it will always be an integer and nothing, it can never become something else so that it doesn't get exploited and get SQL injected into it. Just a really simple example, it also had me memory protections. And that's one of the biggest features because once we're running code, it's not, you know, sitting on the disc, it's running in the memory of a computer, and it's both susceptible to being attacked, but also to getting into other parts of the system into the operating system or other parts of the application.

And one of the big pushes around AI is how do I protect my data that AI is using, whether it's generative ai, machine learning, et cetera, all the way down to the chip load. So I don't want code that's running in, in a, in a processing unit, whether it's a GPU or IPU or CPU, um, that's, that's also post-processing AI type data to share that memory together. So there's a lot of focus on all the way down to the hard level hardware level, which has a lot of implications for the programming, uh, languages that you use.

So long explanation, but I, but I went into that because it is important. Um, it could, we could reach a day where, what are you doing to, in the programming that you're programs that you're writing to add memory protections, to add type safety and things like that. I don't think we're there yet, maybe except for defense and government kind of contracts, but I think we're headed down that path.

David, are CIOs talking about technical debt in these issues, or are they just kind of pretending they don't exist? Well, which ones? The ones, the ones who are just about to get fired, they just, they ignore it.

They ignore it. They figure CIO stands for careers over, and it just doesn't matter. Um, no, part of, part of what we, what we talk about as the CTO mindset, which has to be incorporated into every CIO's role, is this idea of ambidextrous management.

You have finite resources, you have infinite demands put upon you. And what do you have to do? You have to do two things at once.

You have to keep the lights on, manage technical debt, and you have to innovate. You have to run the business, you have to change the business. You have to do these things at the same time.

So technical debt is a, is always a nightmare. And it's often either because of budgetary concerns or because of technical reasons, it's the friction that prevents a lot of, a lot of innovation from happening. But I think that I, I, I think Mitch Freudian slip here because, um, you know, I think of DARPA as sort of being akin to the, the priests at the, the temple of Syrians.

I, I don't know how big of a rush fan you are, but that's a Russian, oh yes. From 2112. The point is, I want transparency and visibility into the transmogrification of code.

Um, if what we're saying is, Hey, we're gonna create this centralized government agency, we're gonna go back and we're gonna rewrite all of this code for your safety. Um, I want visibility into that system. Uh, not that I don't trust, trust was alluded to earlier, but I don't trust That's the Tom Sawyer of the picture who's talking to other people and yeah, let's go rewrite everything.

Right, right, right. So I get it. I get it.

It makes sense. Um, uh, I would like to see a focus on control system software, frankly. And I, I plead ignorance.

I don't know, I, i, I don't know the, the, the frameworks they're generally used there, but the kinds of things that control valves and switches in electrical grids and water systems, uh, those need to be hardened. I think that would be a great place to go if the constitutional things we ask our government to do are provide for the common defense and support the general welfare. I say, let's harden our infrastructure first before we go out and transmogrify code.

A little bit of a tangent there, but so a little, a Lot, a lot of people watching this, sorry. A lot of people watching this show are now running prog rock lyrics through chat GT to understand what you guys are referring to. My variables, brush lyrics, you know, so just a little perspective on technical debt.

There, there are different estimates of this, but you, you can find how many, you know, how many lines of code are, are in existence that are still running today, and the numbers are like 5 trillion. And literally, that's some of the estimates. So it's really crazy.

Any every line of code written that you aren't working on is technical debt. So that's how big technical debt is. I mean, you may have not have touched it for five years.

You may have touched, touched it for a month, but every one of those lines of code you have to maintain is technical debt. So it's, we are building this problem, uh, you know, higher, the mountain's getting taller and taller, right? It's not shrinking.

And, and well, about technical debt. Um, I posted an article a few days ago, George Home wrote, and it was an interesting use case about a company that just decided to get rid of all the technical debt, just wipe it all clean, start fresh, put in all new and completely digitally transform. And it worked well for them.

It was a great return on investment. So, um, uh, I would love to hear your thoughts on should business leaders be trying to just get rid of all that and start fresh in the end? Is it a better return on investment?

I'm curious, Amanda. Um, kind of when I've run it and develop more organizations, you build up all these things that we should do. And at one point it was a good idea.

And oftentimes it's just like, that's actually, we, even if we did that, it wouldn't be helpful. So you kind of cull out, you know, two thirds of the debt that you think you have to do. Did they go through a process like that to really figure out what's meaningful to, to fix and let's just shed the rest?

Yes. Yeah, it was, um, yeah, it was a halt planning process. And, um, and in the end, it, it was, it worked well for them.

I don't know if it would work for all companies to just wipe all their technical debt out and start fresh Mm-Hmm. David, it budgets in my experience are kind of like bills running through Congress and like everybody attaches all kinds of stuff to them. And so if, how many CIOs do you think are gonna say, we're launching an AI initiative and we need this amount of money to go do that, and then they're gonna pull in all this technical debt cleanup effort underneath that because, well, who's gonna check a line item?

Well, I don't know if this tracks, if this tracks with what you're saying, but my, I I'm constantly admonishing folks that I work with, you know, that, you know, that it's very easy to adopt the, you know, the saying that, well, we're considering AI for everything. Our ai ai, our AI strategy is important. It's sort of like a few years ago when people would proudly say, we have a cloud first policy here, which to me, sounds like I'm a mechanic, I have a screwdriver first policy.

It's like, oh, really? So if you see a bolt on the end of a screw first on a, on a, on a, you know, on a net, a net on a on a screw, I'm gonna try a screwdriver first. Why wouldn't you use a wrench?

You look at, that's a, that's a wrench job, not a no, no, no. We always use cloud, try cloud first. Come on.

Fit, fit for function. So in this case, I, I, I, I don't know, I, I think that, um, people, what, what, what I admonish people to do is pay attention to the things that they think are not important. The CIO doesn't have to care about the storage systems, but in, in, in the, in, in the environment as an example, refreshing them.

Uh, but someone in the CIO's organization needs to, because if you optimize infrastructure, if you take your eye off the infrastructure ball, you're not gonna have budget for ai. So by focusing on the things that aren't cool, you free up budget in this finite resources, infinite demands world that they live in. So long, long way to get to the point.

Focus on the boring stuff, to free up capital for the cool stuff. And just really quickly, because Mitch tossed out 5 trillion numbers like that are impossible to conceive, right? But I have an example to just to help the audience.

So this is 100 trillion Zimbabwe dollars. So hopefully that helps. Wow.

To get your arms around what the numbers do. You're rich. You're a rich man.

I, I don't know what it's worth. I think, I think this is, I think this is worth a dollar. I think part of the issue here with technical debt though, is I think more people will rewrite code for the following reason is the, the people who wrote that COBOL program from 30 years ago are sitting on a beach somewhere and they're not gonna help me come fix it.

Or, or if they do, they're gonna charge me a fortune. So how many, many seat level folks are thinking through the fact that there's just a lot of stuff that they're trying to run from bygone days, that there's nobody around who remembers how it works. You know, the, I'll share one experience like that, Mike.

Um, I took over a SaaS product that ran, runs about 93 million transactions a year doing kind of service locator type functionality. net. Several years back.

People wrote it long gone. And there were major sections of the code that we were just afraid to touch. 'cause nobody understood it, nobody what to do with it.

And so when we looked at moving to the cloud and modernizing it, you know, rewriting it was just not impractical. I've tried that earlier in my career and I managed to survive those mistakes and still hear. But, um, what we did was look at, well, let's take the whole monolith application and say, what parts of it really does the business need to be able to add more things to it?

Flex, you know, what flexibility do we need? Where do we need more agility to be able to modify this quickly? And there was one area of the product that really most of the business needs were, were, were being asked for there.

Yeah. There were, you mean hundreds of things across the whole app. So that's the part that we moved to microservices and use containers and Kubernetes and tried to use a more flexible approach so we could add and update it much more quickly.

Saved a ton of money. It turned out to be a, a successful strategy in that case. But that's only 'cause we, we were able to pinpoint what parts of this to the do we change.

So unless you've got something that's so antiquated, you need to re really rethink and write the app. It's hard to justify. Let's put this into rest.

Let's put this into micro. So all those are are tough decisions unless you're just backed into a corner, you don't have an option. David, you know, who makes a fortune on technical debt, global system integrators, they kind of launch these projects and then they show up and they move in for a couple of years, and then they announce that they have either succeeded or they just throw up their hands and say, sorry, but they don't give you your money back.

I Always declare victory. Always declare victory. And so the next contract, right?

That's right. So, yeah, you know, 1, 1, 1 quick example that's, you know, we're experiencing in real time in terms of technical debt and friction associated with it. VMware, uh, look, look at the bluster.

People are frustrated. Broadcom comes in and clearly Broadcom's going to ride the long tail of VMware into the future. Um, if people could snap their fingers and move to something else, they would, largely, in a lot of cases people would do that, but you can't because of the friction associated with change.

And so, so technical debt actually is opportunity for global systems integrators, uh, companies that want to take on these very sticky portfolios of technical debt. It's, uh, it's a mixed bag. I'll tell you one thing.

I am optimistic about all this. 'cause to your point about that, the cost of switching IT platforms is just way too high. And if we can rely on AI tools to reduce that by making it easier to take some, um, platform that has some, uh, dependencies that are designed to lock you in, and then reverse engineer that into something that is more generic code that can run anywhere.

I think the level of competition across the IT industry is about to dramatically increase. Now David and I engaging in some wishful thinking, Well, you could, uh, you could, you know, there's, there's, uh, let's see. I've, I've, I've jumped, I jumped into the multiverse just for a moment while you were, uh, closing this.

And one possible path I saw was, uh, with all of your good intentions, where we ended up was almost a pharmaceutical industry model where developers in IT had to use patent protection so that they could get enough profit to warrant the work they did to do the development. I, I, I was part of something called the open Data Center alliance, I don't even know more than a decade ago. Um, and, and, and what the Open Data Center Alliance customers said was, I want perfect substitutions for everything that I do in it.

I want the best functionality that the market can deliver. And I want to be able to grind all of your heads together in a price war to get you down to the lowest common denominator. It's like, well, where, where does that leave room for innovation really?

When there's no profit motive in, in, in differentiating. So it can go, it, it can go sideways. But I, I agree.

I mean, the promise of cloud was supposed to be portability. We still don't see a lot of people moving stuff back and forth. Um, but yes, to the extent we could drive friction out of the system, everyone benefits.

So you're basically saying, I will not see a generic version of my IT platform that I can go buy for a nickel. I don't think so. Not one that you wanna buy for a nickel, not one that's worth a nickel.

Yeah. Don't throw those COBOL skills away, Mike, quite yet. Don't throw 'em away.

They're getting more valuable every day. Uh, we, we just had a show talking about how we're training kids to write COBOL programs. 'cause that's where the money is.

Although all the cool kids think the other languages are cool, but hey, somebody's gotta make money. And if everybody's using AI to write code, maybe you should learn cold ball because AI might not learn that as quickly. Yeah, we will see how all this plays out in the future.

But stay tuned as we continue to talking about our next section, which is, well, Google has joined a, shall we say, an elite club. And we will dive into what that means in a minute. We'll be right back.

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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 we described, Google is now a convicted monopolist and well, I can't make up my mind if they should be congratulated for the fact that they managed to create this situation and they have enough market share to dominate. And from a investor perspective, maybe that's very impressive.

On the other side of it, it's clear that if they eventually wind up losing the 27 appeals, that will probably go through before this thing gets resolved. Um, what are the implications of all that from a business perspective? David, what are you hearing about this case?

I mean, it's been around forever and I think everybody forgot about it. And then one morning we woke up and there was a ruling. Yeah.

And it's not just this case. There had been many other cases brought in state and federal court, uh, coming after them. I don't know why the phrase convicted monopolist makes me laugh, but I dunno why, but it just, but it just cracks me up, so please don't say it 'cause I won't be able to keep straight face.

But, but the, you know, let's take a quick step back here. What are the point of these antitrust rules? The point is to protect consumers.

The idea is that if in a, in a healthy economy, you shouldn't have someone with so much control that they can artificially control prices, artificially put a damper on competition that hurts consumers. There's nothing illegal about being a monopolist. That's why it's kind of funny to say convicted monopolist.

You could have a monopoly if it's a natural monopoly. If it's like, look, and this is what Google argues. They say, look, our search engine is better.

That's what, that's all, that's why people use it. The pushback is, well, the fact that your search engine is the best, if we stipulate that it got you to a point where unfortunately, with nefarious intent or not, you started to leverage that power in a way that is anti-competitive. That's what's been asserted and confirmed by the court in this case.

Now, search engine is directly tied to another lawsuit or a several other suits having to do with ads because, because they're, and those are inextricably tied together because search is how ads are presented and you know, in the two, the two go hand in glove. So the real question is, how do consumers benefit if the government intervenes to say, Google, you must implement the following policies to prevent these anti-competitive behaviors from happening moving forward. So what does that look like?

Well, something like 95% of mobile, mobile devices have as their default browser or search, excuse me, default search engine is going to be Google. Uh, and that doesn't happen by accident. And so behind the scenes, the question is, is Google exerting too much pressure?

Um, you look another layer down and guess who's driving a lot of this? Is it me and you as a consumer? Are we really that upset about it?

Or is it the competitors of Google? Is it the Microsofts of the world that are pushing back? And generally it's, that's part of the dynamic.

And then my final, um, cynical Dave view on this is that, uh, Google just isn't, hasn't been effective enough at lobbying. They're not greasing the right palms in the way that they need to. Essentially, this is a bit of a shakedown exercise, and I'm sure you're going to see Google participate even more in, uh, political elections, uh, local, state and federal moving forward.

Um, but, but does breaking up Google help us? Like the consent decree that broke up at and t for, for, for myself, probably the only one old enough to remember it on this call. You know, the baby Bell operating systems came out of that.

It was, it was chaotic at first, but I think in the end, more choice for consumers came out of breaking up the phone company. And, uh, but I just don't know what that would Look, I'd love to hear Amanda and Mitch what you think about, what would it look like? What, what, what would, what would the world look like if, if the government came in and said, we're breaking up Google?

I mean, what does any Well, you know, Yeah, I posted about this news when it came out. Yesterday was a huge news day in the world, I tell you. But, um, when that news came out, I was shocked.

'cause I was thinking, what does this do to the stock market? First of all, it's already starting off badly. And then if big tech, you know, all the other big tech lawsuits that are yet to come, what is that gonna do?

But, um, anyway, when I posted that, the responses I got were that they were shocked. That was crazy. Google was the best search engine there was.

I agree. I use Google the most as a search engine. So if it gets taken away on people's phones or devices, I don't think it's the consumers that were complaining we like Google other than some, some, um, some people don't like the censorship on it so much, but it is the best search engine.

And, um, so anyway, that's what I'm hearing. I don't know what y'all heard, but I definitely don't think it was a consumer complaint about Google other than, like I said, some of the censorship. You know, what I was surprised by, and Mitch, I will get your opinion on this 'cause you know, I'm going way old school here, but you remember payola?

Mm-Hmm mm-Hmm. So let me get this straight. Google is paying Apple a a significant amount of some for the privilege of being a default search engine on their platforms, and they're paying other folks similarly.

Um, you know, wasn't that part of the thing? So, you know, is it Google who's really being at fault here? Or is it Apple for taking the money from Google?

And, you know, 'cause that's part of the payola. It it is every business's objective to monetize what they create, what their advantages are in market. The question is, do you take it too far into David's point where you have, you exhibit anti-competitive behaviors?

So are you doing price fixing or collusion with others in the market? Um, are you controlling something so much about your product that limits what others can do it? So you become such so popular search engine now you not only cut others out of search, but you cut others out of other parts of their business.

And if that's substantial enough, the, the real thing that comes out of this, we we're not in the days of the baby bells, which I went through that too. Very interesting time. You know, standard oil, right?

You know, breaking up standard oil, that's one of the, you know, landmark, uh, monopoly cases. It, it isn't being declared a convicted monopolist, which, uh, I got that title from playing Monopoly, but not from running one. Um, it, it's what the consequences are.

And we live in an age where the neur negotiation is, yes, we appeal it, but what are we gonna have to do as a result of it? We'll change this in the algorithm. We'll change this of what giving it, making it easier sort of for people to choose what search engine they use in the browser.

We'll do these things about how ads are, that's where the, the rubber meets the road and the outcome of this very unlikely, you know, the, the, they'll go to cord and say, okay, we're gonna break, uh, a, b, C up into these five companies and do that kind of a, of an impact. So I think at the end of the day, and, and sometimes these changes that they make are so esoteric that the normal consumer don't know it. Like for example, uh, Microsoft had to do make and part of their agreement with an eu and one of the challenges that they faced was giving others access to direct access to certain things in the operating system.

Well, they don't have to do that in the us but they have to do that there. So it gets a bit esoteric and I don't think for most of it's, most of it we're gonna see. They're not gonna take our browser away to your, to your research engine a way Amanda.

Um, we're probably, most consumers probably won't even ever see what the consequences of this are. And a lot of money will be spent by some very wealthy lawyers. Yeah, I think think Amanda, Amanda brings up a good point about the political angle on this.

Yes, censorship. Um, there are a lot of people who see Google as the bottleneck for all information globally and that that, and that control is frightening from a democracy perspective. And so I think that that then percolates up at least through the legislature.

Um, now we're talking judiciary, we're talking about civil suits and, and, and, and things brought by the administrative branch of government. But, but, um, but yeah, don't underestimate the fact that, that everyone has seen the AI generated images of, uh, of, of what appear to be African Nazis. It's like, wait, what?

And so, so anything, anything that smells like bias that's being injected into our lives front and center, that gets people fired up too. So that's definitely a dynamic. Do you think people will take a minute to think about, I mean Amanda was talking about Google as being, you know, the best search engine experience.

Well, you know, I would argue Google maybe is the best of a bad lot. Search engine experience has just gotten worse and worse over the years. It's basically now what, five, six ads before you get to the actual thing you're searching for.

And um, Google's been playing around with this algorithm for the last year where it's trying to quote unquote find more helpful content that's more timely. But when I go look at the search results, I don't really see that I see the same old junk at the top of the list that's from two years ago. And I might be clicking through now to the third window before I find what I'm looking for during a search engine.

So I gotta say, you know, all this stuff about how great the Google search experience is, I'm kind of like scratching my head going, well, maybe it's time to get rid of this thing with something better and maybe we should just go to this AI thing that knows better about what I'm looking for. I mean, have search engines kind of outlived their usefulness? David, I'll let you jump on that grenade.

Yeah, yeah. So I think that, I think that if you ask people to Google, they would tell you that, look, all of this effort is misplaced. We at Google are terrified that we're going to lose our position of dominance.

We know about this idea of disruptive technology and that, and that something is nipping at our heels. Um, I've always been curious, and maybe, maybe maybe there's a way to get this answer somewhere, but it's, but, but what's the value of having access to free search? How much would it cost for me to have no ads?

No Google intervention in terms of the ranking of, of items. Um, what we're seeing is not someone coming up with a a, a better a a a, a better Google version of Google, but no, no generative AI with rag with, you know, retrieval, augmented generative ai where I ask a question and I just get the answer. I don't get ads, I don't get things ordered based on some priority that's getting money somewhere else, but I pay 20 bucks a month, 50 bucks a month to have this very, very effective tool.

I think that Google has frankly painted themselves into a corner, to your point, you, you've gotta go down 20, you know, 20 hits deep to get something that isn't an ad promoted result. So I agree. I mean, we say it's the best it is, but yeah, best, best, best.

What it's like, it's like, you know what it is, it's the exit row on a Southwest Airlines flight, right? It's like, Hey, I'm the president of a third world country. Great, good for you.

Um, and, and so I, yeah, I think that the disruptive technology is gonna come from the AI space. It's gonna be chat based things, uh, where not only are the search results coming in just boom, boom, boom, boom, boom, but there's some logic wrapping them all together. I think that's where the disruption is gonna happen.

I think that that disruption will happen way more quickly than any legislation can affect change. I agree with Ben. I dunno If you had this experience on your phones, but I've noticed the last month or so, I use Siri a lot and that's kind of my, my search engine on my phone.

I'll just ask Siri and then the AI will, you know, scour the internet and give me back a response right away, which I have often found helpful. Now, sometimes it's not the response or any more in depth information, but I like that little AI response at the top when I ask, have y'all experienced that yet? I do use Siri for that.

Um, not, not all the time. You know, IIII think sir, sir, sort of the, uh, the, the is is sort of Alexa's sibling that just wasn't blessed with the, uh, mental acuity that Alexa was blessed with. Um, but, but yeah, I do, I do, I do use Siri, but I'm more often frustrated by her because I use Alexa so much and there seems to be a greater depth there.

I have a feeling it's gonna be hop, scotch Next Gen stuff coming from Apple, I think is going to address that. I think we're gonna see a lot of rhythmic increase in its capability. I think they both need to go to a different school, get some more training, right?

You know, so, so we talk about the best, oftentimes the best is the most familiar. That's why we're very comfortable with Google and how it works. And we, we already know how to do prompt engineering that we talk about in generative ai.

We do prompt engineering every day when we type Google search. We have a way we know that we'll get the results, you know, for certain things if we use it, uh, for that often and up. So to your point, Dave, something else, if something else is truly easier and, and gets me a, is it equal or better results?

Just easier to use. Okay. Now you might be talking about displacing or at least competing with it.

So yeah, that's, that is a, that is a, that's a brilliant insight that what's the, what's the easiest ui? What's the one you already know how to use? Of course.

Yeah. Right. There's no easier than That command line was the best experience when that's all we had, Right?

Do all Right. So I, I'm looking forward to reading the filing that goes something like this, your Honor, we have messed up this product so much that the experience is so horrible that there's no way we could have a monopoly because there's all these new technologies that are about to replace it. 'cause that's essentially the defense.

Their defense, their defense will be, yes. There's, there's, oh, there's a ton of competition in the market. In fact, we're, we're, we're not even sure how we're gonna pay our rent next quarter because who knows what's gonna happen.

But look, the numbers, the numbers at this point show their dominance, but those numbers in and of themselves don't make you guilty. That's the thing. They can have 95% market share as long as they're not abusing the, the, uh, the, the power that they have, that they have deservedly achieved.

And that becomes, that's a, that's a gray area. That's where I go down to sometimes the tipping point is how well you've lobbied Congress or not. You know, I mean, literally the elections in the fall could make a big difference in the way that these things sort of go in terms of scrutiny.

Who gets scru scrutinized and who doesn't. Um, but, uh, but yeah, I think in the long run, um, we are gonna benefit from AI in this case. The challenge is in both cloud and everything associated with search and ai.

These are the highest barriers to entry in the history of humanity in terms of business. This isn't, you know, you wanna compete with the chicken restaurant down the street, it's gonna cost you $300,000 to get your business up and running. Ooh, no, no, no.

This is, this is like, how could you possibly say, if Mitch and I decided we were going to come up with our own version of AWS, um, you know, everybody I would, I pitch in a hundred trillion Zimbabwe dollars, and then we would need to raise, we'd need to raise a lot it's, it's, it's an insurmountable barrier to entry only, only a government, frankly could do it. So that's, that's, that's kind of the difference here. When you get to the scale of something like Google, who can mount a front, well, guess what?

It's gonna be the chat, uh, you know, the chat version. What's the, what's the, there, there's a recent one that there's, there's one that's popular for search duck, Go duck, duck go with Jesus being on the backend, by the way. Yeah.

No, no, but, but, but specifically it's, it's, it's touted as, uh, a chat gt GPT, like engine for search, where chat, GPT OpenAI is saying, no, we're not trying to be, we're not trying to be Google search. That's not us. That's, that's beneath us.

Um, but there is, um, I, I should have it on the tip of my tongue. People are starting to reference it. I'm starting to get links from this search engine, if you will, which is a AI driven search engine.

By the way, I see your a hundred trillion Zimbabwe dollars and I reju eight quadrillion. There we go. Oh, okay.

I'm, I'm out done. I should never, I've learned, never bet against Amanda. Amanda, you're worried about what the market does.

Just gimme a call. I got you. Go.

I just, I just got these $9. We're gonna close this up here now on two thoughts. One is all you folks in Zimbabwe who are angry, direct your email to David.

And then the second thing is, hey, just remember a couple of decades ago we were all flipping out about the dominance of Microsoft. And now look at the world today. There's n os is everywhere.

Linux dominates in the server side, and we were all using Google AppSec in the cloud rather than Microsoft office on your desktop. So the world is changing and it will change, and the market will decide and vote with its feet. Folks, I wanna thank you all for being on the show, and I wanna thank you all for watching the show today, and we'll be back with some additional content for Techstrong tv.

So stay tuned. I'm Bonnie Schneider, sustainability contributor to the Techstrong Group. I'm excited to introduce you to a groundbreaking new initiative from Techstrong Research, the sustainability pulse meter.

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