Techstrong TV June 12, 2025

Hey, everyone. IBM's building crazy new quantum computers, but they're not blue. You're watching Textron Gang.

Hi everyone. Welcome to Thursday on Textron Gang. We've got a lot to go over.

I mentioned IBM's new quantum commercial grade quantum computers. The, they're all shiny and silvery from the pictures, but, uh, we've gotta discuss that. We've got some Cisco news and, and some cyber news on this bed box botnet, interesting stuff.

But first, let me introduce you to our lineup of gang members for today that we're gonna be discussing this with. First of all, sporting a shiny new haircut, looking good out there in, in the valley. He's our, uh, valley editor, John Swartz.

Hey, John. How are you? I'm good.

Welcome back. I haven't talked to you for a while. I hope you had a great time in Italy.

Um, and it's good to be here. Good. You know, there's something to be said about Tuscan, but, uh, we'll discuss that another time.

John, welcome. It's good to see you. Next is our Cyber Beat Reporter one and only Terry Robinson.

Hey, Terry. How are you? Good.

How are you? I'm completely jealous. You were in Italy, but I don't blame you.

But I did come home kicking and screaming, but they, they got me home. And then, uh, from our neighbor up north, she's runs the, well, I don't know if she would, I think she runs the Canadian DevOps community as well as a bunch of other stuff. Garima Bal.

Hi, Garima. It's good to see you and it's great to have you here on the gang. Hello everyone, and great to be back here.

And then last but not least, our favorite Yankee fan. Mike Ard, chief Content Officer here at Techstrong. Hey, Mike.

How's it going? I'm good. I'm in Midtown Manhattan today in a hotel directly across the street from Madison Square Garden, otherwise known as the crime scene.

As the crime. Well, you, you're still talking about your Knicks. Knicks.

Yep. Yeah. I I, I wouldn't have fired Tom, but whatever.

I, you know, I think there's a Dolan curse on the Nixon Rangers. Mm-hmm. You know, they, he's like, bad luck, schlepp Rock.

And as long as he's involved, I don't know if we'll ever get anything done here. Anyway, let's, let's talk tech. Um, so Mike, IBM unveiled these big shiny honking stainless steel looking boxes for commercial grade quantum computing.

Yeah. Or, or, or at least something that is a drawing of a box that they're gonna build. 'cause it's not gonna show up till 2029, but here's what they're saying.

But here's what they are saying, and it's kind of interesting on two levels. One is they're saying that, you know, they've kind of solved this issue where it's now an engineering problem rather than a computer science theory. And they think that they're gonna actually build these quantum machines.

And the two things that they're also saying is that the mechanisms for harnessing qubits and the software and the coating that they created wasn't gonna work because it would require processors that were just large and it wouldn't scale, and it would be too cumbersome and too costly. So they basically went back to the drawing board and they're saying, we designed the way the code is gonna be created so that we can have smaller processors that will drive this quantum capability, and that'll enable us to build this, um, amazing machine. They're gonna have some proof of concepts and some testing machines between now and 2029 with an idea of, uh, creating something they're calling the Starling system.

And that will be housed in a data center that they're building specifically for this in Poughkeepsie, New York, Which yay for Poughkeepsie. Yeah. Yay for Poughkeepsie.

And, you know, for those of you who do not know, it's, you know, Poughkeepsie is in Westchester County, and, you know, that's home turf for IBM. So, you know, rather than building this thing in some other obscure place, they're essentially putting this in their own backyard. So I assume that they're very serious about it as a result.

And they got some money probably from the state and the feds to do it. But Alan, you've been following this space. What's your take on it?

'cause the other side of this coin is, is they're saying that, you know, the other methodologies that people have been talking about won't scale, and they were throwing some shade too. Yeah, they were. Well, so here, here, fundamentally, here's the issue.

You that, and they, and they're not wrong, Mike, we've been hearing now for four or five years that in order for quantum computing to become real, I think the magic line was at a thousand qubits or something like that, we had to have a thousand qubits or 2000 qubits, you know, and we've seen the, the cubits go from 10 to 20 to 40. I think we've got maybe a hundred or 200 qubit processes that are possible now, but not near a thousand. And so, you know, the goalposts, were pretty far out there goalposts, were pretty, we, we were going to need some sort of material physics breakthrough to, to really achieve thousands of qubits, right?

Or it was gonna take a really long time. And, and we've had some kind of exotic solutions proposed, right? Microsoft inventing a different form of matter, whether you buy into that or not.

Uh, Google has their willow architecture, but still, Willow was not going to get you to this level of commercial availability. And then recently, an interesting thing, much like the, when we first went to Linux supercomputers, right? How did we get those Linux supercomputers?

We put a lot of machines together in parallel, right? So a Linux supercomputer really had literally hundreds, if not thousands of Linux cores running. And from what I understand, it's a similar thing here.

They figured out how to run these qubit relatively lower qubit, uh, quantum processors in parallel. And so you have sort of that quantum supercomputer, if you will, if we can call it that. It's what I'm calling it.

I'm sure it's, there's a real dur. And, and that's what this is about. Now, in doing that, you know, this is like cloud native stuff where you gotta go to microservices architecture.

You need now to have your, your, your, your quantum software be able to run multithread in a, in a parallel processing type of thing. And we're not even sure, you know, prior to this, the, a big problem with quantum software was separating out the software calls that would be need to be done on the quantum side of the house versus other processing tasks that would need to be done in a conventional bits and bytes type of processor. And, you know, and how do you, so how do you separate that, then bring it back together into something that works for you?

Now we're adding another level of complexity, which is I need to separate out the quantum from the non quantum, and I need to put that quantum into a, a serial type of, you know, microservices, multi-threaded architecture to use a parallel processing, then bring that back together. And then we still gotta join it up with what comes outta the regular processor processor. This is a very, this is not a simple thing, right?

Let's be clear. However, this is to IBM's credit a path forward in reality that may get this, as they say by 2029 in good old Poughkeepsie. Um, we'll see, I, I don't, I, I'm sure others will, will go down this path too before they have to resort to, you know, inventing new forms of matter and energy and, and defying the laws of physics.

Um, the other thing is bully on IBM, right? They, they've been leaning the quantum computing charge for a long time, when a, when it really was pie in the sky. And, you know, you look at the history of IBM Watson was AI before we knew ai, what it would do or could do, right?

IBM has taken the lead in so many from, from PCs to so many things where, and then they just kind of stood by and watched others claim the, the rewards and the, and the glory and fame. I'd love to see IBM take the lead in quantum, they deserve it. Garima, when I was listening to the press conference for this, the thing that crossed my mind to Alan's point about the complexity, I was like, so is there gonna be like a compiler and an SDK for this?

Or how am I gonna actually program to this thing? And what's your take on this as you kinda look at all this? So as Ellen said, that it's a double-edged sword, right?

So it has opportunities and threats. So opportunities, uh, definitely it'll help us, you know, solve, uh, complex problems, which couldn't be solved by the limitation of the hardware, right? And the processors.

But on the other side, it's also creating opportunities for the software professional because, you know, if you think about in advance engineering and the scalability of a modular architecture, uh, there is a lot of, uh, you know, action on the software open source as well as DevOps community. Um, Alan mentioned, uh, quantum software. I would also mention quantum DevOps because I wanna kind of, uh, get this into the mix.

Uh, this will create a lot, a large set of, you know, uh, revolutionary evolution in that software and DevOps space. I mean, interoperability, for example, becomes a big thing as well, because, you know, there is traditional ecosystem of quantum technology as well as, you know, the advanced engineering techniques. How do you make it work?

Then there is SDK toolkit, you know, there, there are several toolkits available, for example, from Azure, from Amazon, but you know, there will be new toolkits required for this kind of a modular architecture. And this whole claim is unsubstantiated right now, right? So we'll have to prove it from a software practitioner's perspective.

You know, if you think about, you know, scaling it and industrializing it and commoditizing it for, you know, general purpose needs, I think there is a lot of action needed from a software professional. You know, the entire set of CICD pipelines, the DevOps tooling, um, observability error correction and error, you know, in, uh, auditing of error corrections and all that, that needs to be kind of in place at quantum, uh, engineering scale, right? So there's a lot of, uh, you know, action for software practitioners to kind of lean into and look at it from a different perspective altogether.

And one of the things that keep talking about is the comparison to classical computers. It's not like development of classical computers is gonna be at a standstill for the next four years, so we will see them get faster too. So it'll be interesting to see what use cases actually lend themselves.

I Know, right? That that's the key. My, I don't think it's a question of speed of classical computers versus quantum computers.

I think what we've gotta remember is quantum computing, at least as we understand it now, solves some very specific use case problems, a lot exponentially faster than classic computing ever will, right? That that's the bottom line. There are some things, like encryption is a great example, right?

We could brute force 512 bid encryption if you had some sort of monster machine. And for all we know the NSA does, um, but it'll still take months, years, whatever, to to brute force that encrypt, break that encryption, where by the very nature of quantum, it can be done very quickly, relatively speaking, right? You're talking years and decades versus minutes.

So that's a great use case for it. But I don't know, you know, other things I've heard, weather forecast, weather forecasting another great potential use for quantum computing because just the, the amount of variables in there make it such, um, but we don't really have, what are, you know, what are the other killer apps for Quantum? What are the other killer use cases for Quantum?

There's tons of stuff in the field of chemistry that will lend itself to quantum, because when you think about Quantum, and what they're saying is that they're trying to mirror the way nature computes and the way that nature pulls these things together, and we know haven't cracked that particular code, and that's what they're trying to do. And so there are probably lots of use cases that will lend themselves to Quantum, but I guess I keep pointing them, the quantum people keep obsessing about, uh, what they can do versus classical computers. And the thing about the classical computers is they too get faster.

And a lot of times so far, every time Quantum said we could do something that classical couldn't do, the classical guys showed up six months later and said, here's our new processor that can do those things slightly faster or with much capability. But to your point, I think it is gonna be a hybrid, right? It's gonna be, you know, when even IBM is talking about using high performance computing alongside Quantum to kind of go build an, an application.

So it will be a set of microservices that you're invoking and, and calling on a quantum to, to run specific classes of workloads alongside a classical computer. And that, that's how that feels to me at least. But there is another aspect of this thing that I wanted to bring Terry in.

Uh, uh, people have been talking about Q Day for a while. Q Day is when we're allegedly gonna break all these encryption schemes. And, um, I guess what IBM is kind of saying here is that will happen no later than 2029.

And it might happen sooner still, but at least we have some sort of date that says that, you know, those encryption codes are most likely gonna be cracked starting in 2029 or sooner. I don't know how solid that date is, but I mean, that's what they're gonna do this by 2029, then I, I guess that's it. Um, or at least it gives us something that fixate on right now.

I I, the best advice right there too is to start preparing for that. Don't just wait till 2029, you know, um, to, to see if it happens. Um, there, I mean, I think that is the, it's the, you know, the biggest concern probably with Quantum is that there, that that, uh, encryption will be broken.

And, uh, we talked about this a couple of weeks ago, I think, when we were talking about prime numbers, right? Um, not being as random as we thought. And, and really the, the idea there though is that Quantum was gonna pose a bigger issue when it comes to Yeah, but, but we have quantum proof theoretically from what NIST tells us.

We have quantum proof algorithms, digis cer, and many of the other certificate providers are already incorporated that, that may turn out to be a big Y 2K thing, as far as I'm concerned. This Q Day. What may be more troubling is all of these bad guys who are sitting on tar balls full of hashed personal information that they've not been able to crack to date.

And now using Quantum, if they had access to Quantum, they'd be able to crack it. But of course, that information goes stale over time too. So the longer that, you know, if you wait till 2029, a good chunk of that's gonna be useless anyway.

I think it's gonna be an issue though. And I think, I mean, you're right, Alan, because NIST is on the case, right? They've been working on this and, um, I mean, it's not like people are sitting still, but I, but I really think you need to, you know, as an organization, maybe start looking at what this might mean for Yeah, no, you gotta make sure, have you adopted quantum proof certificates?

What's your, how often are you changing your certificates? Where, where are the, you know, where is your encryption, what, what data is encrypted and what encryption you're using. Yeah.

Yeah. And, and be sure to keep your security audits and, and everything and risk assessments on point, you know, um, you're gonna have to be constantly, uh, vigilant, I think. Um, but all that's gonna be hygiene anyway.

John Schwartz, what's your assessment? That the Chinese come up with a quantum computer that's similar to this sooner? Yeah, that's, that's, that's likely probably, you know, can I, can I just interject a bit of skepticism into this, because I like to do that.

Um, 2029 is a long way away. You know, by the time we reach the, this date to have a fall tolerant quantum computer, the Summer Olympics in LA will have come and gone. We may have a new president Nopes, unless we change the, unless we change that.

Um, I'm just thinking that I bully to IBM for getting our attention, for being at the forefront of something. Again, I am a huge fan. My dad worked at IBM for 20 years.

He was an engineer. They, they were the leader in the, up through the seventies, eighties, even, you know, into the partially the nineties. I do la them for what they're, what they're trying to do.

And I think it's really cool, and I think it's good that we're great that we're talking about this, but a lot of things are gonna have to happen between now and then. And I and I, I think about this within the context of what happened this week. Remember Monday, apple had the ww DCA year after they announced their big Apple intelligence we're still kind of stuck in the mud.

And I'm thinking later today we're gonna have Tesla talk about the robo taxis, which we've been hearing about for years. So I think sometimes it, it's, it's important to kind of step back and look at the achievability. I I actually asked a couple of people about what IBM was up to, and they said, uh, they don't even know what's gonna be happening in 2026, let alone 2029.

So I just want, I just wanted to say that. But again, going back to this whole discussion fully for them, for, for doing something that's exciting on the cutting edge and, and for being a little bit arrogant and they need more arrogance, they, they've been missing it. They've been missing their swagger.

So I do compliment them for that After many decades of swagger. I agree with that. They, they are definitely missing it.

I, I actually, uh, worked on an IBM account, uh, in a brief stint at an ad agency many, many years ago. And, uh, one of the guys, and they were starting to get a little whipped by, uh, some of the other companies that were out there that were a little sexier. The technology was a little more appealing, at least on the surface.

And this guy just looked with me Hope con expression and said, why can't you know, why can't we get the love? Why can't people, you know, see what great things we do? And I'm like, you know, I felt a little bad for him, but I also wasn't his therapist.

But, you know, it's, uh, I think it's, it's nice for IBM to, you know, to kind of get that swagger back and, and maybe well deserved. Well, they have, like, they have a whole wing of their indentions at the Computer History Museum in Mountain View. I mean, literally, uh, section is devoted to IBM.

You know what I, I, the irony of history is that Apple, if they don't, if they're not careful, they're gonna start getting into that IBM kind of conversation where they're kind of an an afterthought. I'm not, I'm not, I'm not, you know, the, the half-life of the Apple products is, is pretty long, but, um, there's more and more attention being paid to what they don't do and what they're not doing well. And that's something that every tech company is, goes through inevitable.

So let me, let me end this. Let me end this, uh, segment with this right here. You know what that is the smallest violin in the world playing hearts and flowers, because all those people complaining about IBM, all the people I know who've worked at IBM and are sitting on IB m's stock are doing pretty damn good.

The IBM stock over, you know, you could look at it short term, but over the long term, their IBM stock has seen them through. And the same goes for Apple. Poor, poor Apple, just a couple of trillion dollar cap.

So, you know, talk about first world problems. Let's take a break here on Text Drunk Gang. We'll come back.

We're gonna talk more first world problems. Cisco, you're watching Text Drunk Gang. Hey folks, we're back and we're talking about Cisco, which had one of their Cisco live events this week.

And they announced, I think I haven't seen this many new product launches from them all at once in a long time. I think this would probably rank as one of their most ambitious, uh, Cisco Live events. And they basically came along on two themes.

One is they've created their own LLM that has been trained to, uh, create agents that will automate the management of networks and a few other things alongside of that, anything related to infrastructure for that matter. And they're pushing along on that, and they showed some previews of that capability. And we should expect to see that later this year in terms of, you know, actually finding its way into some mainstream IT environments.

The second thing is that they're saying is that the rise of AI is gonna create a massive amount of data that's gonna have to flow through our networks, and the current networks are not gonna be anywhere near fast enough. And that will lead to essentially a massive refresh of all the networking infrastructure, starting with the core, and then working your way out all the way to eventually access points. Um, of course, you know, Cisco has a vested interest in that occurring 'cause they make a lot of that equipment in that gear.

But it did seem talking about swagger from the previous episode that Cisco was kind of feeling its oats around AI finally, and that they felt like they were in this game and have something to say. And John, you're out in the valley. Cisco's been awfully quiet as of late.

What's your take? Yeah, that's, that's a really, that's a really good summary, Mike. And it's, and going back to IBM is kind of the same situation.

These, these behemoth that are legendary parts of the framework of technology, not just in Silicon Valley, but the whole world, and they kind of get forgotten or, or taken for granted. And Cisco, in a sense, what I think they're trying to do, and I talked to a couple people there about these announcements, is that they get criticized for the breadth and depth of what they do. Like they do too much, or they have too much.

That actually puts them in an actually interesting advantage in terms of ai. So they got the pipes, they've got the, the pieces, they've got the Lego blocks. Actually, a couple of their executives refer to the Lego blocks that their customers are freaking out about over ai.

So what Cisco, if you really oil it down, is they want to build an infrastructure for the AI era. There are three areas that they mentioned to me. So they're, they're, they're locked in step on this future-proof workplaces, AI ready data centers, and digital resiliency.

So they were hammering home that idea, and they're, they gotta tag phrase for it, make AI work for you. If, if you'll see the signs somewhat what they want, what they wanna do is they wanna bring calm to the chaos because given all the AI agent announcements in particular, you've got CIOs, IT managers, semi freaking out over what they're gonna do, um, maybe for the next year or two. Some of them lean on consultants, but that's not gonna last long, I don't think.

Um, so, so this is what the, what they're, what they're trying to do is they're trying to orchestrate, this is what Cisco wants to do, is help you orchestrate. And you know, it was interesting, they kept referencing the chief product officer at G two as the guy who's basically in charge of this massive undertaking to make them relevant in the AI era. You know, and, and, and I, I think I, I give them credit, I think they, they do have legitimacy because they've been through all the other previous eras, and I think for the first time in several years, you're seeing a little bit of a strut from Cisco.

I mean, usually you write about their layoffs, their retrenchments, their, their, their acquisitions to, to try to move into other areas. But I think now they have kind of a cohesive coaching plan that they put into place, and we'll see if it works. But you know what I get, again, I'm gonna give them credit.

Like, like IBM they're trying to establish themselves in an area, and I think they're off to a, a promising start if they're able to do this. So, again, I'll, I'll play hearts and flowers for all those people sitting on Cisco stock. Poor, poor, poor people.

But, um, but look, you're right. G two Patel is who you're referring to, I believe John. And you know, I've, I've had the pleasure of interviewing Gito a few times, and you know, he's always been a rockstar there.

He, and he's always, you know, look, this isn't 1999 Cisco where they controlled the entire network, right? And everyone else was on also Rent. It's a different Cisco, but they're also not just about network switches and routers anymore.

They have huge software. They have huge security tele, uh, you know, WebEx, that kind of thing. Um, they're, they're all over the place, including ai.

But if you look at many of their successful endeavors over the, let's say the last seven years, you'll find G two Patel behind them, including they made some great acquisitions in the security space over that time. Duo security was one, my, my, a lot of friends at Duo. Uh, Splunk, of course is another Splunk, they, they, they really playing up the Splunk aspect of it.

Yeah, well, for good reason, they paid a lot of money for that. Um, but, you know, GG two was the man behind a lot of that stuff. And so he is, I I, you know, I think of him as the number two guy there.

Now it's Cisco. And, and, uh, I, I, I see this as, this has his fingerprints all over it because he still does have that vision of Cisco Silicon Valley's royalty, right? Them in hp, where in many ways the royalty out there, well, besides you, of course, John, but, um, you know, this is, this is, uh, I, I think there's a great move on their part, You know, so you mentioned something, Alan, that I, I didn't, that I'm glad you did, um, that they were just known, I mean, fairly or not, is the company that acquired a bunch of other companies to try to play catch up.

Um, they were, I wouldn't say, I would just say it's, it, it's just, it is just, they, they get criticized for trying to do too much with too many products. But I think in this weird way, this may have, this may help them in at this era right now. Yeah.

Well, they got a lot of, a lot of boats in the water. I, I'll tell you something though, John and Terry, you probably know this. I, I'm, you know, I'm in cybersecurity 25, 30 years for the majority of that time.

And it may still, well, I don't know today, but for the majority of that time, what vendor derived the most revenue from security, even before we called it Cyber, when we called it InfoSec. What was the biggest security vendor in the world for probably 10, 15 years running during that time? Cisco right there, firewalls said, where are the firewalls, Terry, you know this.

Yeah. And I actually was gonna say, you know, some of the things we've been talking about in recent weeks about AI and Agentic AI and, you know, and the, the security concerns, right? The shadow ai, uh, you know, tools that, security tools in the hands of the bad guys.

I mean, those are all valid. But, you know, Cisco's in a real position with their sort of security underpinnings to, to counter a lot of that and, uh, and mitigate, you know, some of those, those issues. I mean, they do have a very strong security story.

Uh, And this is before Duo and before Splunk, right? Exactly. Before Splunk, all of that.

Yeah. So they definitely, um, have sort of the source Infrastructure for that source fire or another one they bought Patter. You probably remember Sourcefire, Marty Rush.

Um, So there's, so there's an aspect to this that I'd love to get Garima's opinion on. 'cause I'm torn on the one hand, everybody shows up and says, I have these AI agents, and it's gonna make the technology more accessible. And you, you won't have to lean so much on specialists.

And so, we'll, it's kind of part of this mass democratization of it. And then the next breath you go talk to people, and especially some of the more senior folks who actually are practitioners and they go, this stuff is awesome. I don't need any more of these junior kids around here.

I got these AI agents that will just automate all this stuff for me. And the, and they're going, you know, it's gonna benefit them more than it is the democratization of it. So, I mean, when you look at all this AI stuff, what's your reaction?

I think software as a profession has always evolved, right? So we as practitioners are up for that evolution. We do not want to do the toil work.

So if somebody wants to automate this for us, that's great. You know, we will, uh, we have a lot of other things to do. You know, quantum AI is coming and the AI stack is kind of producing a lot of work for, uh, the practitioners.

But having said that, I think I also come back to the point which was being discussed with the Cisco, uh, you know, the, the new products, they're kind of, you know, uh, coming up with. And what I am seeing is this new breed of AI data centers, right? And I'm not alone in this journey.

So what we look at it from an enterprise perspective is that we want a tech stack that works end to end, right? So, I mean, they can say that we don't have, we have Lego pieces, but I don't know if the industry is ready for the Lego pieces yet. We need the tech stack at full, at the data centers.

So now what they're playing around with is AI infrastructure as a service, uh, components. Like if you see, uh, the recent announcements they have made, like the infrastructure components, the security components geared towards the infrastructure side of it, right? So what I would like to see more from Cisco is like how they are partnering with platform guys, the application guys, you know, how do you make this as a neutral space?

Because, you know, if you look at the geopolitics, it is very hard to kind of also scale this ecosystem beyond North America, right? So if we don't make it a geo neutral, geopolitical neutral place, and how do we do that? You know, do we have consortiums?

Do you have partnerships? Do you have alliances, right? And how do you steer the talent pool?

So there's some, you know, more work to be done in that area. These Lego pieces are great. It's a great start, but I think there is more work needed to be done.

And you know, Mike, to answer your question, I mean, um, for us as software practitioners, we probably look forward for that evolution of AI agents, but I think we also look forward for like GPU as a service or infrastructure, AI infrastructure as a service. And we have to have a neutral space to play around with. Fair enough.

Alright, let's take a break. We're gonna come back and, uh, we have C blocks here. There's a, a new botnet out there.

Bed box two oh, uh, wreaking havoc. Terry will have some news, hopefully. First on that, you're watching Textron Gang Join Cruise Con Virtual on June 17th in 2025 for breakthrough strategies to address advanced threat intelligence, proactive incident response, exclusive bonus material and regulatory adaptation fear here from our keynote speaker, Admiral Michael S.

Rogers, former director of the National Security Agency, and an outstanding lineup of industry experts as they navigate emerging threats, the core principles of crisis management and the evolution of CISO Leadership Register now for free. Hey, folks, bad box. 0 version that's meaner and darn right nastier than ever.

And it turns out that it's twofold. Uh, the FBI put out a warning saying that it bad box is a botnet that attacks, uh, a lot of senior devices, especially ones made in China. And historically it was installed at the point of when those devices were made, but now it's being installed not only when they're made, but it can be downloaded too onto these platforms.

And the FBI is saying it might be in as many as a million devices or more. So that would just mean, it's just about everywhere, Terry, we, we see a lot of threats over the years, and this one seems to, you know, be pervasive more so than any other. But what's your take?

This sort of emerged right, a couple of years ago, um, and the, the, uh, German authorities, uh, put the kibosh on it, but here it comes back again. That's not so unusual though, uh, when it comes to, um, um, threats. I mean, we often see 'em come back, but this one is coming back, uh, you know, batter than it, than it was.

Um, so they can, uh, the hackers can access the devices and networks, um, through Android devices. Um, and I, I think, you know, we're, I don't wanna say we've ever abandoned the idea of talking about, uh, the issues with, you know, IO ot. Um, it seemed like it was a hotter topic, uh, you know, a few years back and maybe is gaining some steam here.

I'm actually working on a piece on maybe how zero trust could be the, the, you know, answer, uh, to this kind of stuff. But, um, yeah, it's, uh, now it's, it's, it's multiple groups that, um, have joined, uh, uh, forces here and bad bot. And I think it's, you know, including like the sales tracker group, um, mo mo u is that, I guess that's how you pronounce it in the Lemon group.

And they all have sort of different facets of this that, um, they're, uh, that they bring to the table. So, yeah, it's, it's a comeback batter than than ever. I'm, I'm glad to see the FBI doing something besides persecute trump's enemies.

I'm surprised they had time for it, to be honest with you. So some, some intrepid, some intrepid agent decided to, you know, put the alarm out. So, I don't know, I, I'm, I am getting a little paranoid about all this stuff, and I'm like, every time I leave my house to go log into something out there, I'm like, well, is this thing infested?

And then of course, I think twice about it, and I go, well, my router at home's probably infested too. So, um, at what point, Alan, do we just kind look at all this and throw up our hands and say, well, there's nothing to be done about it, and it's just the way life's gonna be. So I, I, you know, I think that's what the bad guys want, want you to feel, right?

And I think there was a time where the FBI and cisa and, and you know, these governmental agencies were trying, were, were making progress against that, the right software supply chains and SBOs, you know, but you got executive orders undoing recent executive orders as we discussed yesterday on the show. You know, it's every man, it's every man and woman for himself these days, guys. Yeah.

But I think there are two, uh, things to take, uh, away from this, right? So the first thing is that the DevOps professionals, uh, the boundaries are kind of, uh, also, uh, stretching a bit to hardware. You know, it's not only at the software level, you, you kind of stop looking at it.

So during manufacturing, you know, deployment, post-deployment, how security professionals can play an important role, right? And the second aspect is also user awareness, right? You know, what is your app store hygiene?

You know, are you downloading stuff without knowing, right? If you're doing a firmware upgrade, you know, as a user, I'm responsible and accountable, uh, to a certain extent to protect my devices, right? So this, this is like, you know, um, an extension to how we look at security from different perspectives and different persona types, right?

But, you know, I, I think a lot of security people or teams within organizations still don't know what they're dealing with. They don't know what, uh, technology you or I are using beyond, maybe they, you know, they know about our phones maybe, but do they know we have a toaster someplace that's, you know, talks, you know, pass the data through our network? I mean, no.

And that, how do you get a grip on on that? That's been the, the question for a really long time. And, and I do wonder if, you know, there's some aspect of zero trust that that really can help hear the fact that you just don't trust anything.

You know, I, I did give half a thought to, you know, going through my house and just getting rid of everything that was made in China, but I decided I didn't really wanna live in the stone Age anymore. So that, So you just, you just hit it right there, Mike. Is that, is that why the F FBI's involved here?

Is this, the cast shade on anything made in China? Could, could, that could be a piece of it, no doubt. Yeah, there are a lot of unbranded, unlabeled, uh, you know, hardware as well, which are questionable.

And, you know, think about this as well, like, you know, when you're downloading firmware, I mean, from a manufacturing perspective, yes, if it is pre deployed from manufacturing, you know, and you probably can't do anything. So maybe from a user point of view, look at like the white labelling or unbranded things, and then you also have to be careful about marketplace, right? I mean, the hygiene of the marketplace is very important.

You know, what kind of, uh, regulated marketplace you have, because there are malicious apps, uh, you know, every day, you know, we see that, right? There are backdoor entry points, uh, in every kind of, you know, uh, updates or firmware updates or any, any kind of, you know, um, software you are downloading from the global system, right? Yeah.

Well, I think the Chinese government requires anybody who makes anything in China, and they put a backdoor in it. So we just, you have to kind of assume that that's there. I mean, Mike, where why are you spreading propaganda?

Yeah. A again, though, too, I mean, God, when you look at, of course, like, you know, I think things should be regulated or there need to be firmer controls. But again, you know, in the rush to get things to market and the fact that people want devices and things that can, you know, take 'em out of the stone age, Mike, you know, and, and, and put them here in 2025.

There's a, there's a lot of, um, if not pressure, there's a lot of encouragement to maybe not, uh, get these things secured before they hit the market still. And I, I don't know that that's gonna change. You know, I would like to see some sort of effort regardless of where the devices are made that requires them to be, um, I guess something you can inspect to see what's in there and, and find that malware and maybe even mitigated yourself, would, hopefully, without breaking the thing.

But One, one person's malware is another person's remote controlled support, right? The last I checked, I think it was the US government that was trying to force Apple to build back doors into iOS. So there, this, this knows no borders.

I mean, when, when I was selling to the federal government in the nine oh, early two thousands, mid two thousands, the rumor was, don't you know, the federal government wouldn't buy checkpoint? 'cause the Moad had a backdoor nonsense. All nonsense.

Anyway, all right. Hey, I think that's gonna wrap our show for today. We're about outta time.

It's a great Thursday. I hope you've enjoyed it. As usual, we've got a lot of tech drunk TV immediately following this, so stay tuned for that.

But, uh, Garima, Terry, Mike and John, thanks for joining today. Thank you for watching. This is Alan Shimel for Tech Drunk Gang.

We're out. Hey, everyone, back here at Tech Drunk tv. I'm really happy to have back on with us today.

Harry Wang. Harry is the Chief Growth Officer at Sonar. I'm going to hear all about it.

First. Let's welcome Harry. Harry, it's great to have you back on.

How are you? Good, good. Thank you for having me again, Alan.

Ah, it's a pleasure. A pleasure, Harry. So Harry, as we were talking off camera, a lot of people here, the Chief Growth officer and their, oh, this guy's a sales guy, couldn't be further from the truth.

In your case, give people a little bit of a sense of your journey, how you came to be Chief Growth Officer, and it's kind of a unique position that you don't see at every organization. Tell us about it and why you are the perfect person for it. Yes, and happy to share.

Um, so everyone here, I'm being with the Sonar for a year and a half. I came from engineering background. I was a software engineer by trade.

And, uh, for me, chief Growth Officer is really trying to, at a company, at Sonar, in this case, in my case, about leveraging, finding the levers, finding the growth drivers that really help the company to grow, right? So that can range from m and a, from investment perspective, looking for adjacency spaces, looking for technologies and companies and team where we can acquire and make them part of sonar, or can be actually internal innovation in the new areas, whether it's a security, whether it's actually ai, where we leverage our own internal r and d and then define a new product, define a new market where we can, we can grow and innovate. Um, and then somewhere in between which we could really be actually working with the partners or working with our customers and really finding the new growth drivers.

So it's, uh, I'm very excited about this spectrum of, uh, flexibility I have and my team have as owner. You know, if you think about it, it really is, it encompasses what, what we used to call, uh, so I, and I, back in the day when I was founding co-founding companies, I was always chief strategy officer, so I was responsible for corp dev m and a and, and partnership, strategic partnerships, that kind of thing. Yeah.

Little bit of biz dev, right? Yep. Yep.

And then in, in your case, in like when I was Chief Strategy Officer, also help had a hand in driving product strategy, go to market strategies. Um, it, it really is a, a little bit of a, you know, jack of all trades, but you got your hands in really driving the company forward. And, uh, yeah, it's an interesting way of looking at it.

Good for you. Very, very true. I mean, the, the title was to me is really just actually a, a kind of a way of communicating what I do, what my team does.

You know, a number of years ago in the, during the, the mobile transformation, we have people talk about, uh, growth hacking, right? So, um, it's a little bit continuation to that where we're trying to find growth. So we are looking for ways, different ways of finding growth and do what it takes to find that growth, uh, just happens in this paradigm.

In the case of sonar, we are really, this is sitting in between product and, uh, go to market. Absolutely. Now, Harry, a lot of our audiences, a lot of our audience have heard of Sonar.

You know, it's a company that's been around, but not everyone has, and, and even a good percentage of those who have, may not really know the whole picture. How would you describe what sonar, you know, the company and what you guys do, where you play, what problems you solve? Yeah, so Sonar is a Swiss based, uh, uh, company's been around for 16 years, uh, since founding we of the core of our missions to help, uh, developers, software developers to build better software and build it faster.

And we provide a number of tools in the, as part of the CICD part of DevOps, as well as in the ID as extension to finding quality issues as well as the security issues, and providing recommendations on how developers can, uh, can, um, address those. Um, and obviously in the last couple years, uh, with AI being introduced, uh, into the software developed lifecycle, our mission is adapting. So we not only helping software developers, we are also helping the companions, the AI systems, and the AI agents out there trying to do a better job of helping the software development teams out there as well.

Sure. So, Harry, you, you, we, we made it three minutes and we got into ai, right? You can't help it AI's everywhere today, and, and it promises to be disruptive across so many different industries, but I would say that for whatever reason, an inordinate, an extremely inordinate amount of attention around AI has been focused on AI's ability to do coding to make our code better, to code faster, to replace developers, perhaps do better software testing, right?

That seems to be such a huge focus of AI today. I mean, even like absolutely Atropic, the last version of Claude. Mm-hmm.

It was really optimized for co-generation. Yep. Yeah, absolutely.

Right? Yep. Why the fixation on AI and, and software development, you think?

Yeah, I think, uh, so my, my own view of that is really a two part, uh, question. On one hand, AI engineers and scientists behind AI are the primary driver for this innovation. And, uh, you know, they, you, and we all have the tendency to look at the 40 areas where we are familiar.

Web, in this case, uh, software development is very familiar, uh, to these in set of, in innovat, uh, behind ai, right? It's natural to start in that particular application area. And secondly, I think it speaks to the growing share of economy that's driven by digital transformation.

And, and what is the underlying digital transformation in this case is really short software, right? So if from a pure ROI, from a pure, uh, impact standpoint, it makes sense to start with the software development as a key focus. And, and there's an amplifier you can do that.

If you can do build software better with the ai, it means it transcend, it can translate into the GDP impact much faster than maybe some other functional areas. Yeah, I mean, make no mistake, I eventually, AI is gonna disrupt and impact multiple verticals, disciplines, et cetera. But certainly, you know, software development is, is front and center right now.

Now, you know, we had this discussion, I was on text drug gang this morning, Harry, we talked about this Apple paper that came out. We were talking about it, but we also talked about living up to the hype, right? A lot of companies are saying, let's go small.

Let's play small ball with ai. Let's, let's, let's highlight some very specific limited type of functions or jobs that we're going to give AI to do. It, it, so it's not, you know, it's not an open-ended thing.

These are very specific. Yeah. And whether it's generative or agent Yeah.

Very specific tasks that lend themselves to ai. Yeah. Yeah.

Is that, at least for now, the prudent way to go about this? I, I think so, Alan, I actually remember our last conversation we're clunking about a distinction between gen AI and, uh, uh, Gentech AI just actually that was only seemed like a two months ago, and things are moving so fast. Uh, AI agents not everywhere, right?

Uh, maybe in two months, uh, from now on that we will have a different conversation. Um, but I think the approach generally, uh, many companies out there taking is a more measured approach. com era where we actually seeing a dramatic productivity booth.

We're not fully there yet, but I think the time for productivity will will come in terms of that improvement. Um, but taking, uh, embracing the ai, but taking a measured approach in both in terms of, uh, where we deploy AI in our work and, but also actually what type of a task going granular on what type of task we can delegate to the ai, right? Um, the nature, they're actually, uh, widely of, uh, wide conversations, uh, in the industry about how you choose the task as appropriations, right?

There are tasks which is really, um, both actually high impact, but also quite easy to codify, think like in software development, think about unit tests, think about documentation, think about issue remediation, let's say in the area of, uh, sonar, right? We did detect it, not only detect issue, but also helping our user to fix those issues, right? These tasks, high impact, highly repetitive, and quite frankly, developers don't always enjoy doing that task, right?

And also, it's a small tangible things, it's easy to reverse, right? So it's not like, uh, if an AI makes a mistake, it has the consequences on the actually the entire output. You, you could, as an organization with the right measurement to whether it's right type of assurance, the security to like so cube, you could detect those mistakes and then reverse it easily, right?

So I would say start with those tasks, and then as the organization build more confidence in ai, as the AI itself is actually evolving, you can start growing, expanding the horizon of the deployment. It sounds like very prudent advice, right? Because you give it a specific task, but at the same time, you also limit the blast radius, if you will.

Exactly. If something weren't to work out. Yeah.

And, and to back it out. Mm-hmm. You know, Harry, for as long as I've been in tech though, people always want to know, well, what's the ROI?

Right? And so in my background in security, it was near impossible to figure out the ROI because what you were measuring is something that didn't happen, right? If, if you, because in security, if nothing happened, you did your job.

Um, well, one could say that AI a little different, but how do we measure what, what's the right yard stick even to use to measure the ROI here? Yeah. I, I, I think that the, on the, as a whole economy, um, the, I remember, um, it was, uh, in the, I forgot in which, so maybe DA, that was in one of those conversations, uh, people talk about the prospect of ai, uh, for the society.

Eventually we need to see AI impact showing up, uh, in the GDP growth, right? So that's the ultimate litmus test, uh, for, for the economy. Um, are we seeing productivity gains as a society?

Are we seeing the GDP growth, right? Um, but specifically to a particular industry, a particular company, let's just take a software development as an example. Um, the ROI can be in dollar term.

It means actually, hey, are we building software with a lower cost or higher return in terms of, uh, the impact of that software delivered to the, the company's, uh, um, uh, revenue, uh, and then bottom line on top line growth, right? But oftentimes it's not necessarily a dollar term. It could be more macro measured impacts.

That could be productivity, could be happiness in, in the case of software, it could be developer satisfactions. It could be actually the churn on how fast you actually generating new features, delivering on those features and the quality measure. In the case of the sonar, we measure the quality of your code base.

We measure actually how many issues that you're able to address, either by the development team or by the ai, right? So those, uh, leading indicators also very important in addition to just simply a dollar ROI, uh, measure. Absolutely those.

And that again, good solid advice. Harry, if you don't mind, I wanna focus in on, on sonar. Yeah, absolutely.

We've, we've given advice to the whole world, but are you eating your own dog food or drinking your own champagne as some people like to say? How sonar using AI and, and how are you measuring its effectiveness? Yeah, it's almost like across the board.

Um, I would say from the experimentation standpoint, we are trying experimenting AI in every single function at sonar. Whether it's actually software development or it's our community engagement, customer support and marketing, you name it, right? Um, but I would say we do identify internally these several areas where we, um, put more wood behind it.

And, uh, that's a software development itself. Not only it's really actually helping our Sona sourcers to, to be more productive, but also it's actually gave us more ground, um, more concrete, how we build our own proactive, better work with ai. So that shouldn't be a surprising answer.

In software development, we use actually multiple, uh, AI tools as well. Copilot, um, cursor. We constantly experimenting new market coming to the market, and that's some of that coming from our partners, some of that, those really just for commercial reason we decide to use, um, outside software development, we do quite a bit, uh, experiments in marketing from a content generation perspective, from a market research perspective, it's tremendously helpful.

Again, back to the task I was talking about, these very concrete task, we can handle the ai, collaborate with ai, think of AI almost like our peer workers, right? But also in case AI is not actually delivering on the right type of, uh, output, we can easily reverse and that it doesn't hurt. Um, and we can always having our marketer to really gate keeping the quality of the content and also for, uh, in strategy functions.

In my own growth, uh, initiative, we often use research, uh, Google Gemini, deep research, fantastic capability in case, uh, you and your, the audience haven't tried. Highly recommend either deep researcher from Google or equivalent function from, uh, open ai. They're all just actually, um, very, very thorough.

Almost you can treat 'em like a research assistant for a topic, uh, you can throw at it. They Really, and Me too. Yeah.

And then also just, uh, in ana analytics functions, finance, uh, sales operations, we start doing more, um, AI assist analytics. Uh, one example actually, I personally tried is really AI generated SQL queries, right? So to be able to look at the business analytics and, uh, generating business reports out of, Hey, how, how we doing in online growth, uh, in the last seven days, uh, what is our returns?

What is our new signup? I no longer need to actually write a course myself or go to a analyst to do it. I can just actually use natural language to generate those, uh, curries, uh, on the fly.

It is, uh, it's a fantastic product they booster to, to myself and to my colleague Again. Me too, me too. Imagine, especially on my side of the house now in media.

This is, this is an amazing tool, amazing tool in that regard. But Harry, there's a dark side to AI too, right? Or potentially a dark side.

And that is misuse of ai that certainly the bad guys in the security world are no strangers to that. But sometimes, you know, what they say, the road to perdition is, is aligned with the best of intentions and even, you know, trying to use it for the right reasons. We can go off track.

How do you make sure that doesn't happen? Harry Yeah. Has the right level of, uh, policies and toolings, uh, uh, at the starting point, right?

So for, uh, back to the software development, back to the DevOps, um, having the same level of policies and measurement safeguards we put in place, uh, for traditional software development lifecycle still applies. But what we do need to look at at this moment is actually the sheer skill, the sheer volume of things that need to be vetted, right? So for example, in aerospace owner, we help detecting the quality and the security issues that in the past is really simple function of a number of developers and the size of the volume, size of the code base.

Um, but that's going through exponential growth. When AI start churn through the code, the churn is going higher, the volume is going higher. At certain point, this has actually become very, very problematic just in terms of how you look at the different team have a different policy and some tool, some development team may adopt on queue, for example, other team in organization may not, right?

So it's very important for the company as an organization established what is the output, automate, safeguard and compliance requirement for software development and what's the right policy in terms of uh, what type of AI tools is allowed to use at what stage of the software development lifecycle and what type of, uh, uh, verification tools you have on the model, on the software itself, and then finally through the test, right? So having established that practice and being able to give a very clear guidance to the software development teams is very important because ultimately that gave them the peace of mind so they can actually be more on the venturing side and taking more risk and then going faster. Um, and, and this, that life cycle, uh, to me is that is actually very productive in terms of it driving the increasing adoption of AI and not trying to restrict it.

Excellent. Alright. It's always a pleasure talking to you, man, 'cause I learned stuff, but I also see myself reflected in many of your views.

I think we share a common outlook at things. Maybe that's why I was a good chief, uh, strategy officer and you're a good chief growth officer. Um, if people wanna get more information about Sonar and about what Sonars doing around ai, where would you send them?

com. Uh, it's easier to remember. com.

That's our homepage. And, uh, we have, uh, you know, uh, constantly on LinkedIn, so follow us on LinkedIn as well. Uh, Katie and the colleague and our part marketing team is sharing our latest news pretty on a daily, pretty much on a daily basis.

Great, Harry, I hope to see you soon and in person, maybe at an event we're both at. Until then, keep up the great work at Sonar, come back and keep us informed. Okay, Thank you Alan.

I'm looking forward to it. Thank You. Harry V, chief Growth Officer Sonar here on Textron tv.

We're gonna take a break. We'll be back in a moment. Hey guys, thanks for the throw.

We're here with Chad MedCAP, newly appointed CEO for continue. They are a provider of a AI coding tool, and we're gonna be talking about what's going on in this market. Chad, welcome to show.

Hey, Thanks for having me. Right? There's already no shortage of AI coding tools.

So a what attracted you to continue and from where you sit, what differentiates who these days? Yeah, so I met the continue founders at a meetup in San Francisco in like summer of 23. And so this was kind of post pandemic meetups.

Hadn't really come back to San Francisco. It was one of the first that I had been back to. And I went to go visit my friends at alama, um, and I know them from Docker days.

And there was this startup that was demoing, uh, an AI coding assistant on top of Llama. And I saw it and I had this like little tingle in the back of my neck about like, oh, that's, that's pretty cool. Um, and so I reached out to some friends and I was like, Hey, have you seen this yet?

And then I met Nate and Tai and I started just trying to be helpful however I could. And, uh, that started with some introductions, uh, to some investors. Then that sort of went on to like, Hey, maybe I could advise or something.

And so then a little bit of advising, then a little bit of, uh, consulting and then a little bit more and a little bit more. And at some point they, uh, they asked, Hey, you know, if, if this was to happen, like would you be interested? And yeah, I I thought like, well, there's probably only one startup in the world that could probably get me to do it, and this is probably the one.

So, uh, my career has been a long time in, uh, open source and in enterprise and in dev tools. And so sort of the, the perfect world. So, which probably goes in a little bit about differentiation.

So I think if you go look at a lot of solutions out in the world, those solutions are all like very vertically integrated, not a lot of choice. Uh, you know, sort of very, this is what you get. And I think in the beginning that's a great way to get started.

But if you look at the trends in our industry over time, eventually the open solution wins. And so, uh, continue is open source. It partners with model providers.

We don't make our own models. Uh, and when it comes to, uh, our developer side, lots of our developers want to use local models or they want to use open models, or they want to use the latest models and they want to tinker and toy with it. And on the enterprise side, they want all of the same things that enterprises always want.

They want choice, they want security, and they want governance. And so for them, where do you want the models to run? How, uh, what, what models do you want to use?

How do you want your developers to use it? And sort of the consistency and control that generally goes with enterprise product. And that's just not generally available in the tools that exist today outside of continue.

So I think that's the, that's sort of the bright line for how we think about ourselves. How disposable are the models gonna get, do you think? 'cause they all are accessible via API and I might have different tasks that I'm trying to do at different times, or is all that gonna happen in real time or am I gonna swap them out every couple of months?

How does that work? Also, I, I think if you look at our, like open users, they do swap them out. They, you know, we'll release a new one.

Somebody will, will add support for a new one and they'll, they'll tinker and toy. But I also think over time models will specialize. And so certain models will be good at, at certain languages or, uh, other tasks.

And one of the things that continue allows you to do is when you specify one of our assistants, you can pick and choose different models and you can have many of those assistants. And so that's something that I think in the long run, like somebody could have a model that's just fantastic at Java or at Python, and then be small, fast, cheaper to run. And you could have, this is the way we do Java, this is the way we do Python.

And those things can use different, different pieces or parts. Or speaking of like a llama and local runner, you could run some of that com, some of that compute locally and only go off onto the hosted models for very large things. Like, uh, I want to do reasoning model with, uh, I wanna ask a question of a reasoning model, but for everything else, uh, a local open model is, is fine.

So I think, um, if you look what's happening with like the Quinn family and the deep Seek family, you know, the, the gap between them and the frontier is, is narrowing. And it, it'll be a really interesting time to see what happens. Where are we on the spectrum of the quality of the code being generated?

'cause I'll talk to some folks and they'll say, well, the machine generates Coda, right? But it's not tuned for my environment and I have a hard time debugging it 'cause I didn't write it in the first place. So where are we kind of in the maturity cycle of developers using these tools and, and how much further do we need to go?

I mean, I think we're probably at the, uh, I read a a, a spicy blog post about this from the folks at Fly, uh, and they described it as we're at the intern level in terms of like the level of code quality that you would get. And one of those things is, you know, if you, if you just say, you know, Claude, take the wheel, um, you're gonna get what you're gonna get. And so I think, uh, this is still a, this is still a point of, you know, the code that you check in the code that you, you know, you're still responsible for that.

And so, you know, it's not a magic bullet where you're never gonna have to look at curly braces again. It's time to like, you know, you get the machine to, to do something, you review it and just like any other code review, you know, you need, you need to make those small incremental changes so that it's easy to understand what's happening in 20 lines and not be dropped with like a 2000 line change and try to reason about what that, what that change is doing. So I think it's, you know, you see a lot of, like on the vibe coding side, uh, it's great for prototyping, it's great for like getting something going.

It's great for seeing what, what's like possible. And then on the, the side of the house where you've got existing code bases, it's pretty good at doing drudgery. And you know, I, I love writing software.

Matter of fact, you know, I, I stopped writing software when I converted over into the, into the, the go to market side of the house. But These tools have like knocked the rust off me so that I can go back to writing software again. And I think in that case, like I use them as like a, like a partner in this.

And so like, I'll, I'll direct them for a very specific change. And I think if you use it like that, that's fine. But if you're, if you're just trying to throw at the wall, you're gonna get, you're gonna get what you're gonna get.

I also think that it's really difficult for, um, very large code bases. You see a lot of where, you know, it's great for series A startups that don't have, you know, large code bases and no technical debt yet. And then around, you know, series D when you've got established code bases, things start to come off the rails.

And so it, I think it just depends, like any other tool, what are you using it for? Uh, I remember there was an, an interview early on where they interviewed some woman and she said, you know, I don't want AI to create art. I want AI to clean the kitchen so I can create art.

So, um, there's a lot more that goes into building applications than just writing codes. So how will you know, AI kind of evolve to take hand or take care of many of those tasks? Yeah.

So developers can do the part of the thing that they love. Yeah, I think if you, if you look at, it's interesting, if you look at what a lot of open source, or sorry, if you look at a lot of, if young startups that are in this space, they talk about how fast the tool enables them to write code. And if you look at how Amazon and Microsoft and others describe it, it's a very different story.

Like Amazon talks about the Java eight to Java 11 migration and how many centuries of engineering time, uh, using tools like this saved them to do that migration. Um, there was a, a pretty cool, uh, Airbnb use case where they were updating, uh, a react testing framework and they estimated that that team, it was gonna take them a year and a half, and they wrote an agent for it, uh, spent about four hours doing that, and it got about 80% of the tests. They spent another four days doing that, and it got another 17% of the test.

So in five days of using a tool, they migrated, you know, 97% of those tests, and then they had 3% left, which they just decided to body. And they, they used the team and the team went and ahead and just migrated those tests manually. 5 year process, and it's up taking about five weeks.

And I think when you look at that, that's where, at least in my customer base, where I think you're gonna see a huge amount of the early value in this, where if you think about the average enterprise spends, what, over 50% of their time maintaining their existing portfolio of applications versus innovations, and some of that can be much higher than 50%. You can knock a bunch of that loose and have, yeah, migrations and tooling and, and other things that takes the drudgery away of like, oh, I need to update this from Java eight to Java 11, and that's going to be a lot of work. Versus I need to supervise this to update it from Java eight to Java 11.

That's a much more tact, uh, tackable preg, I think we all agree that there's gonna be a lot more code and moving through our pipelines and heading into production environments and the code bases might get larger. What are the implications of all this for, say, DevOps teams or the, or, or the folks on the back end who support all these developers? Yeah, so I was, uh, I was, uh, very, I I used to do operations.

Uh, I was at Puppet, uh, before, and I used Puppet as a, as a an end user, then joined Puppet. And then after Puppet I went to Docker. And I felt like Docker really accelerated this, uh, years ago where it was much easier to get, uh, code shipped into production.

And there was lots of difficult feelings about like developers lobbying stuff over the fence and just saying, Hey, it's ops problems now it's in a container. They can deal with it. Uh, I have a sneaking expectation that, that this is going to, uh, make those sorts of problems worse.

Because what's inside of those boxes, if they're, if they're boxed at all, is going to be much more varied. It's gonna have a lot more tech stacks in it. And I think that, you know, you're gonna see, one of the things that we see a lot is the folks that come to buy Continue Enterprise are often platform teams and architecture teams that are looking to drive some amount of consistency around the way that software's done in their organizations.

And they're looking at continue, like, can, can we help, can sort of the multiple coding assistant sort of style where you, you specialize an assistant for a specific framework or a specific language, can that help sort of minimize some of these complexities, uh, where operations is just gonna get random tech stacks and just tossed over the fence. So I, I think it, it, it really is gonna be very similar to Docker and like, you're gonna want to put some amount of control around how this works, but that'll be an organizational, it will be an organizational challenge. So what is a reasonable expectation for AI and coding?

'cause you'll see these, uh, grandiose statements sometimes made by people that are like, oh, we reduced the number of developers we have and we're cutting them back. And, you know, it almost seems like it's generally aimed at say, wall Street investors, but from your perspective, you know, what does the future of software development teams look like? Well, I think it's interesting if you go look at the companies that are talking about selling products where you can eliminate the developers and you go look at their career pages are quite large as they basically try to hire all the developers they can.

Um, you know, I think, I think there's just a lot of marketing right now, and I think, you know, when you, uh, when you look at sort of the naysayers, uh, I'm not convinced that they're necessarily naysayers is that it's, it's just so oversaturated with claims and hype and, and everything else. Uh, you know, there is definitely impacts. Like we, we see it amongst, um, certainly very like entry level or, or fresh out, you know, hires are definitely down.

I think the industry will pay for that. I think in some number of years when this all rationalizes and those entry-level folks should have been mid-career folks. Uh, and we regret that there's a sort of a pause in that and potentially a, a long live pause that we will feel this, uh, in the years to come.

But, you know, I think that a lot of folks are trying to understand it. It is, I think the, what's really interesting is the process of writing software has absolutely changed like that. I don't think that that's up for much discussion, at least in my, in my set of folks.

I think though, however, the business of writing software has not changed. And so, you know, what the company still needs is that it needs to bring an application to a customer and yield a value exchange. And that that's still true Now, you know, uh, whether or not that's gonna have a reckoning whether or not that's gonna have a realignment.

Um, but this was, this was coming this, you know, if you think about like even before this rush, there was all of this push from enterprises to try to understand better about how their engineers were working and engineers pushing back and saying, Hey, you can't measure us like sales because it's not as clear as that. So I think what you're seeing is the bubbling over of tensions that have been building in enterprise software for a long time. Uh, in part probably because things have gotten so much more complicated.

Uh, when I first started as a developer, I feel like it was much easier, and this was a long time ago, but I really just needed my language, which in my, that particular case was c or c plus plus, you know, the tool, the, the particular editing environment that I used, and then our version control. We didn't use a ton of external libraries. Uh, we wrote our own network library, our own file system library.

We had one big repo. We didn't use a lot of open source. Uh, we targeted sort of Linux posics sort of APIs, but other than that, we didn't take any dependencies.

If you fast forward today, there's many frameworks. They're rapidly moving. There's Docker, Kubernetes, the clouds, and so like all of this complexity has had a cost.

And I think what you're seeing is actually the, the, the business which wants to ship applications to a customer and wants to do that faster is struggling for anything to do that. And this is a, this is a highly hyped and marketed way where they, they are hoping that this is going to be the, uh, break the log jam that they've had for, you know, a decade. All right, folks, it remains to be seen exactly how much of an impact all these AI coding tools will have, but it will be profound.

However, it may not be the silver bullet. Everybody thinks it is. Hey Chad, thanks for being on the show.

Hey, thank you. All right. Come back to you guys in the studio.

Hello, my name is Chris Blas and I'm your host again for another episode of the Inevitability Curve. And with me is another long-term friend Ken Wick. He was currently in Krakow Paul.

And how you doing Ken? Doing well today. Thanks Chris.

Uh, thanks for joining me. And I didn't mention this in the green room because I, uh, there's a weird little fact. Blas is a very, um, unusual name.

There aren't a lot of us. Uh, my grandfather, my paternal grandfather was born in Germany and went to his deathbed, swearing to God. It was not a Polish name.

Um, it is, and interesting, I learned this in the early nineties when I saw the movie Shine, um, was, uh, was, was listed in Poland as blak. So blak, I mean either shine or brilliance secular sort of thing in, in Polish, which is, uh, very flattering. Uh, the only other place I find in linguistics is in Swedish where it means dish water.

So I think one of our polish is better. Yeah. One of our agent ancestors p****d off of Swed somewhere.

Um, so we've been dishwater ever since. But, so you and I have been doing this stuff for an awful long time as we're talking about the green room, you know, the, the policy nature, right? You know, policy hacking after, you know, a couple decades of, you know, configuring crypto systems is kind of all that's left.

You know, why are we doing things? Why are things done that way? Where have the policies been?

Where are they now? You know, when is the last change? Who changed them?

Why? Right? In, in my, you know, building and sailing boats up and down the Florida coast in the last, uh, three years, I found that the most interesting thing, you know, not how do you get solar power or how do you get starlink or how do you connect the iot to the A, B, C, but what are the rules in this section of water?

Why are they there? How did they get there? When was the last time they changed?

Who changed them? You start to understand that and you can design the systems around it, right? And, and as as usual in this series, we look way back, right?

And, and you were talking about the green room a little bit. We can, anybody familiar with human history can look at, you know, these last several thousand years of documented civilization. And these see things like trade in Mesopotamia with all the clay tablets and all the codes and policies that have been developed since who changed them, why they changed them, how that worked.

Um, and quite often how that didn't work out on the end. Right? So, lemme see if I can put any of that form of a question.

Um, looking, looking back over your career, you know, either in the time of your career or the, the history you referenced, how's your path towards policy hacking evolved? Well, it's interesting. On the beginning of my career, I thought they were an impediment, you know, start, I started on the technical side, starting on the, uh, the grunt side, so to speak, and policies, procedures, they were sort of an impediment to getting the job done in a lot of ways.

They weren't, you know, perhaps that would, that was just my vision of it. And, and it wasn't too bad. But as I evolved, especially when I, uh, my experience at Citibank started to shape that, when I learned, uh, the most important thing there was learning how to deal with bureaucracies, the technical aspect of the job was one thing, but my God, learning how to deal with the people and the different groups and the unholy bureaucracy that that corporation had had, uh, built, I think was almost sucking only to the US government, but the learn to see the value of it and why these things, why the policies were in place and what they were for.

So it was a huge, to develop that governance to understanding why that was important or why it was so critical. Because the technology, as you said, that the how to do it, the little things, the bolts, that can just be anything. As technology evolves, it's replaced.

Those things change. So knowing the technical details of how to do it isn't important to understand why you need to do it and what needs to go there. So what needs to replace it and why, as, as time evolves, because you, you, you have those guidelines and rules in place for a reason.

Sometimes it is bs, sometimes it's, uh, developed by those who don't know what they're doing or shouldn't be doing it. But most times, hopefully you gotta, it, it's developed by those who have been there, done that, and know that it's there for a very good reason. You know, one of the, you know, now that I'm not spending all my time in the boats, you know, um, you know, I think about all the things that I, that I've learned along the way and the problem markers.

I, I think that the, the analogy of bubble mar bubble markers fits no, no better than this conversation because out on the water, if you're anywhere, but let's take the, the shallow waters of the Florida East Coast and the keys, you apply, you know, you, you sail down the Intracoastal and across the Florida reef, and you'll see a lot of policy markers, you know, literal, you know, telephone pole kind of thing with this nice sign on it that says, this is the right side, this is the left side, you know, you know, no swing or whatever. It's, um, and you see a lot of, and those, those are expl explicit policy markers. You know, there's a formal policy that's written down, agreed by somebody, somebody took the effort of, of, of expressing the policy in the physical environment.

So the people who were there know there's a policy, and then you get these little white posts that stick up out of the ocean all over the place. And those are referred to, um, by, by the people who know has riz, which is basically someone who goes back and forth here, you know, either hit that shool or couldn't find that, uh, that gap in the shool often enough, they finally came back and they stuck a post in the water. And when you spend time in an environment, um, as I've done in that specific environment, you know, being able to see the reason and logic of those, of the implicit policy, why are people doing things?

You know, why did someone take their time and express this policy in this place, uh, at this time? It tells you so much practical information. I literally about where you drive your boat, you know, and when you do and how you do, and it's, it is the, and it's, it's practically fascinating, right?

Because the, the, the patterns of these people, they're sponge fishermen in this area, or whatever it is. Yeah. I think it, it reflects hard lessons that were learned often fatal lessons that were learned, Right?

And, and the analogy to the corporate environment and, and the international environment in which we, we, uh, really wanna get, you know, to talking about is act. Right? You know, companies die, you know, people lose their jobs, you know, uh, countries go into conflict, wars happen, right?

And kinetic things happen in the real world. It's all the same patterns, all the same policies. And you know, we can't, you know, with, with your involvement in, in everything you're doing and, and mine and my work, you know, if we can't talk about all this without looking at the international policy state that we're all in right now, and I, you know, I make no bones about my position.

I think, uh, like my country, I think, uh, the US is making missteps in policy, interpretation, implementation, um, and that has long-term effects, immediate effects, and long-term effects. And in, in the same way these policies were developed over long time, for lots of good reasons, that was Stop this way. I've ever heard you talk about that.

Right? Um, and, you know, maybe, maybe that marker shouldn't be there, right? But, you know, why is it there?

How did it get there? What was, you know, walking around pulling markers out and expecting to be able to implement new policies on grand scales is naive beyond words. I agree.

I mean, I, I agree that there's questions of whether they should be there or not, but perhaps the way it's being implemented now to, uh, change things is not the best way. And, and it's, you know, I, I think, you know, again, trying to play my Alex Rebek role here, not just soapbox, but you know, there are competitive advantages here. You know, I, I'm wearing a Canadian shirt, you know, I'm in Canada, you know, my, my wife is Canadian, my kids are Canadian.

We've lived in both countries. You know, I'm currently a US resident, changing Canadian resident. We've been playing that for like couple years, not related to the current, uh, international situation.

Yeah. But I spending a lot more time looking at this policy stack, you know, that's called Canada. It has its own rules and regulations and reasons for having them and how it responds to current conditions, I think is an indicator of what healthy policy structures, you know, uh, why they're better than poor ones.

I think the evolutionary forces are in favor of structures like this. Again, whether that works or not, I think the odds are better in the, you know, here, if no are reasons, simply because the policies are more seen and robust, what do you, what do you, and looking around the world, what are your thoughts on, on that? And say it as hot topic as you like.

Well, God, it's interesting. The first thing that came to my mind, at least the last part, was think about the evolutionary concept of the, uh, policies and robustness of it is obviously the human body. And life in general is a reflection of it.

There's a lot of waste and, uh, things that should have been done if engineered from scratch should have been done better. But they evolve, they work, therefore they stay. And a lot of that same thing.

We see that in the governments today and policies of, there's a lot of crap and waste and b******t. But because it works, it has stayed. Whether it's the best, whether it's the most efficient is not necessarily the reason it's it's there.

It's because it, the, it was the whole learning evolutionary process. So I agree there, from a, a standpoint of internationally, it's very interesting to, to my perspective, is to almost have like a paradigm shift in how things work. And it's, uh, I see things through a different lens out here.

So especially over the last year, well, actually the last couple years, it's been interesting because in, in different ways. But that's getting a little bit political. But, um, that's okay.

I mean, just, I mean, one of the things I I've found very interesting since I moved here, and this is I'm getting outside of policy a little bit, is, and I had some conversation with friends about this is the, uh, so-called freedom of America. You being land of the free able to do things that you can't do, uh, anywhere else in the world, which is a little bit true and also may be true governmentally. But the infrastructure that built up around it, like to say the civilian infrastructure with the legal infrastructure has created such tight constraints legally that everyone's in America is really more constrained there from, and I'm not talking criminal law, I'm talking civil law, lawsuits, liabilities, insurance seems like that, that I see in here, specifically in Poland, people being a lot more free than in the US in some many ways.

Uh, the, there are ramifications of that, which is if you f**k around, you find out if you do something stupid and get hurt, you know, it's like tough s**t. You did that. Why'd you do that?

Like, guard, right? You go up a, a steep hill. Uh, there's a, got a wonderful monument here to, uh, God, I'm embarrassed, I can't think of his name.

He was part of the re a Polish, Polish soldier, famous man, uh, part of the revolutionary American Revolutionary War. He did so much in, in America to help Americans gain their independence. And I can't think of his damn name here, but wonderful thing, huge mound.

But you go up this trail, and I'm thinking the entire time going up this thing, which is pretty high on the sides, you fall down, you're going down, gonna get hurt, if not killed no guardrails. You won't see that in the us. The it in front of the castle here, wild castle.

The, uh, the babo dragon breeds fire every couple minutes during the summer. Kids are climbing all over it, and it's breathing fire. I'm just thinking, my God, I can only imagine the women screaming about, oh my god, little Timmy, oh no, you know, this is too dangerous.

You know, I'm gonna sue you. You can't do this. They could hurt, you know, that granted, it's safe.

But at the same time, there's a lot of, and those are just small examples of just little things where just it's, the guardrails aren't here. It's, you're more free to, to do things and make mistakes. And the way the US used to be now, it's so tied up in the court system with all the, the log laws and procedures that you're yeah, free in theory, but at the same time tied up.

You know, let me, I'm gonna, I'm gonna, uh, uh, agree with that and, and, and see if I can tease it out. And it's interesting 'cause you and I have have discussed politics and spurred politic, you know, dis disagreed, you know, vehemently and had our, had our positions. Um, you know, I have belonged to all three major political parties in the US and, you know, Fadden believed on, on behalf of each of them in their own time.

Um, so, but, you know, but, but it's, it's the policies. And, and so here's, here's, you know, this, you know, most of my left, my friends of my mind to the left will pick me for this. But I think you have a point.

And as an interesting example, there are apparently two individuals, um, who are behind the playground safety movement, you know, started in the US in the sa 1970s, you know, we all like to joke boomers, like, you know, or Gen X folks like us, like the joke that, you know, we hung upside down from, you know, steel monkey mirrors over concrete, which we did. Yeah. Right?

Yes. Right. And what's interesting is that in the two thousands, 2010s or whatnot, one of those individuals, um, turned around and started, uh, um, working on projects to basically make sure that there were broken glass in playrooms, right?

And, and because it, it was interesting reading his point on it. It's like we lost something, right? You know, and, and each of these policy choices we make, and this is, this is, uh, and I do get it.

I get get these conversations with my left-handed friends quite a, quite a lot because I understand, you know, it's like that child fell, you know, got hurt. That's a tragedy. It is.

And if we had that rule, got this policy in place, that won't happen. And that's true. Now, is it a good thing?

Well, obviously the kid didn't get hurt. It's not that simple. I'm sorry, it just isn't right.

You know, that bubble market made perfect sense, right? And it worked there for years, and then there was this storm, and there was this one time, and we found out that, that it's, that it was just a terrible idea or whatever they, you know, they, they can't develop a great analogy for that. But you make a good point.

You know, we have sort of incremented our way into safety, right? And to be clear, even in this, you know, interesting world we're living in today, we live in the safest world that has ever existed by orders of magnitude, you know, each of us individually, that's on, on every bloody level. But we're terrified and we keep trying to come up with the next rule to keep us that much safer.

I think, I think the international affairs going on right now are a good reflection of the, the error in that. Because when you take that view, as I think is happened in, in, in our country, in the states, now you have somebody who just disagrees and comes back and takes your same argument to 11. Right?

You know, we can't say these things. Guess what? You can't say anything or you can't say this.

Right? Exactly. And it, it, it, it aligns up more than people in opposition of the current administration would like to think.

Yeah. Uh, many years ago, a friend in the, uh, listserv going back in time here, um, al probably many people might have been on it to listen to this DC stuff. I used to run my Shipley.

But I was talking about that, about how some of the downfall that the world started to change the, with the Nerf world, you know, we're, we're looking for safety. And that started when with the medical advances with children, it was expected, you know, some, you didn't even name the children until they were a few years old because they're expected to die. A certain percentage of them, right?

Graveyards are filled with children from a hundred years ago, 20 years ago, because of and beyond, because they, the life expectancy was low. And those who survived, learned to survive. Part of childhood was learning how to survive and to not do stupid s**t.

When you are still young enough and small enough that the stupid s**t you do is gonna be fairly safe in general, there's gonna be a learning curve. You're gonna break bones, some might die. But that was expected because you, I won't say toughen 'em up, but learn how to be human and not to do those stupid things.

But as they started to survive and be the health and the medicine improved the attention to 'em to keep 'em that way, to keep them healthy and keep 'em alive, which obviously is a good thing, but it became almost over obsessive to the whole north world to put the bubble wrap around 'em and never let anything bad happen to 'em. And as you mentioned, the Gen X and and beyond, we grew up just like learning those lessons. Yeah.

Of see when the street lights come on, do whatever you want. And we learned, we broke bones, we did things, we got hurt. Kids these days aren't allowed to learn those lessons of what not to do and how not to go.

I mean, hell, we, when you fall down as a child, you get banged up and scraped and ah, you no big deal. You do the same thing. Now as an adult, that's a bigger fall.

You're a lot more mass and bad things happen, kind of, especially the older you get. I'm still recovered from a fall. So it's the kids, those lessons important, those are important lessons of life that just, that these generations aren't receiving.

And you know, I, I have a parent, you know, I, I've got three kids, my oldest turns to 30 this year. Um, you know, I, they're wonderful human beings to be clear if in case they happen to watch any of dad's boring, you know, work stuff. Um, so I don't have any regrets of my parenting, you know, that, you know, the result work speaks for itself.

However, right. You know, I've wrestled with these same issues and I've tried to, you know, we, we, uh, uh, our youngest Terry was born while we're living, you know, here in Canada on a lake, and we had our own beach, you know, right by the house. And our friends from the city would come, would come up, and no child was allowed to be within say, 17 miles of the water, unless there was a phalanx of at least, you know, 25 competent adults sober, staring at them the whole time.

And family would toddle outta the house naked by herself and go down to the beach and play in the sand. And, you know, you know, the, the social pressure, you know, that we had friends, you know, long time friends, you know, getting extremely angry and, you know, voice that in great length. And my point was, you know, I want my kids to grow, you know, not being terrified of everything, right?

Yeah. Be able make decisions and think about how that works out. Um, but, you know, I, and I, you know, I am old, you know, we're gonna find lawn.

Um, I, I love the generation. I think they're gonna solve a lot of problems that our generation is not structurally wired to. I think they'll be fine.

Um, but, you know, they carry that legacy from our generation, you know, we just tried so bloody hard, even parents like myself who may have, you know, taken laziness and tried to make a virtue of it and let the kids figure things out themselves. Yeah. My kids are raised in that same culture.

A To worry about, and I wanna try to turn this into a, you know, to border our topic, but because it is the same thing, countries and economies and ideologies and societies, you know, compete in an evolutionary fashion against each other, looking for nutrient grads of belief or economies or whatever. It's Right. And I think what we're seeing right now on the international policy scale, you know, on behalf of my country in the United States is, you know, a frame wreck, failure of policy proportions, right.

Taking this sort of thing and, and, and, you know, taking the, the, the slow erosion of policies or accretion of policies and abusing them without restriction because the policies weren't that good. Right? And, and the, but the evolutionary pressures, again, I I think Canada is actually in pretty good shape.

I think a lot of parts of the world will get advantage out of this, you know, because Oh yeah. Their policies are more conducive to, to taking advantage or surviving or, or, or not having the same problems. So yeah, I, I see a lot of the same thing where there's, uh, whatever you think of some of the policy decisions being made now, there's gonna be a lot of change that's gonna benefit a lot of people in other parts of the globe, I think.

And it's, uh, I, I'm seeing that here in, in Europe, the conversations around especially, it's was fascinating just last year seeing the, to take the Ukraine, Russian War into, uh, as a topic here, old 50, 60-year-old NATO equipment, US equipment. But some of it was, you know, from many o any many other areas of, of, of Europe as well, uh, Swedish, German, et cetera, was kicking the ass of the Russians, just destroying their equipment and the people and just doing an amazing job. Just a, a limited amount because there wasn't a hell of a lot being sent over there.

But this old stuff that was actually built to fight the Russians that are finally fighting the Russians, and you see high Mars and Patriots and the, the, the way they, and, and, and the way the equipment and the drones that the Ukraine is just developing on the cutting edge, the way they were getting through Russian defenses, that Russia was, you know, a leader that was one of their, their besides oil was arm sales. And so they were selling a lot of arms and here's our top tier equipment, it can't be beat, no one can do it. And here's this 6-year-old equipment just beating the crap out of it, you know, like the rest 400 and so on state-of-the-art Yeah.

Getting hit by a, you know, $50 drone being blown up. It was selling the hell out of us manufacturing weapons manufacturers. I mean, it was just like, here, fire cell.

Just like, wow. Everyone wanted to go and get by the US manufactured weapons because of how well they were doing. That was just last year.

This year there was a switch. We, wait, wait a second. US equipment comes with a huge, uh, cost.

Actually, no, this guy actually does. I, I, I've gotta be fair, this goes back actually the last several years too with under the previous administration where Biden imposed the restrictions of, no, you can't use, if this is USAID equipment, you can't use it in this way. We're dictating how you, we, you, yeah, you have it, but you have to do the way, use it the way we want you to.

It comes with rules and restrictions. European equipment, Hey, you, you have it, do whatever you want with it. And this administration is sure showing the same thing of just that, but in some ways it got even more harsh with what you could do with the equipment.

And we're just show that yeah, maybe while it's superior, we can go with something a little bit not as good, but has no strings attached to it whatsoever. And now the, you know, the French arms manufacturers are just going like crazy. German is starting to go and ramp up, or Germany should say.

And it's just been, it's been a huge switch between fire sale from the US to now just, eh, it's, it's toxic. We don't wanna do it and buy, we, we'll buy some because we have to right now, but we want to get off of that. We want to get rid of that.

So it's, Take, take that I just look forward, right. You know, 'cause the, you know, I, I have to admit right now I'm, I'm having really concerns that I might be addicted to the chat GBT, right? Because only the last really two months, you know, have I just been actually trying to use this tool for purposes.

And I kind of love it. It's kinda amazing. And it's doing, you know, some of the things that I've been looking for over the last decades, you know, over the last five, six years in supply chain, um, uh, possibly in there.

And that I'm fully aware that I'm probably in this little, you know, pop culture friend phase where, you know, I'll look back and say, yeah, you know, can't believe I thought I could do all that. So that big fat caveat out there, I think what we're currently referring to is ai, um, actually does give us the possibility to get the visibility in policy environments that we've never had before. 'cause whether it's disinformation, misinformation, influence campaigns, or just normal, you know, difficulty in, in dealing with, you know, life and policies and, and those evolutions, um, one of the things working against us is it's impossible to see, right?

You can't tell you, nobody knows, you know, law, you know, you, you're all in favor of law and order. Uh, you want everyone who breaks the law to immediately get charged and fined and arrested for it. You're breaking the law right now.

We all are somehow. Yes. And we don't know because there are some bloody many, and it is physically, literally impossible to understand where we fit in the policy and environment as individuals, as organizations, as nations.

Um, just because of the sheer volume and complexity of it. I think that's going away. I think the kind of, and again, we'll just say a ai, we get to say Moore's law or horsepower or anything we want, but I think we're getting to a level of tech that is able to interpret our policy environments well enough and fast enough to allow us to make decisions based on more than everything else.

We just talked about this sort of reactionary policy evolution over time. Um, so first, am I being outrageously optimistic there, or does that make any sense at all? Yeah, I'm not sure.

I'm, I'm trying to place where you're going with how you think AI's gonna help with that a little bit. It's, uh, I, yeah, it's, it's time to, time to transparency, right? You know, in, in supply chain, you know, every, every time I look at these sort of issues, um, and supply chain is just such a, a great cartoon of it.

All of the information I need to solve, problem A exists now, you know, the only burden I have is my time to actually get that information. You know, if, if I really, really, you know, we're looking at a plane crash or whatnot, we can find out that yes, you can find out what software was running on the radial plasma forge that made an individual blade inside a turbine if it's crashed and we're spending, you know, a couple years and millions of dollars to find that information. So the information already exists.

So the time it takes me, and I think this is happening in supply chain and threat intelligence, cybersecurity at large right now, is that we're collapsing the amount of time it takes to do things that would previously just be inconceivable. Like you just say, yeah, that'd be great if we had a thousand people and, and 10 years, but we don't. And I think the same, and again, without, you know, defining what ai, and again, AI is a terrible acronym, but right, but this mass, you know, there's this mass pattern matching, you know, policies are written documents that can be interpreted that, that act like code, that in fact, our code policies are all executable in, in the, you know, real time runtime environment we call life.

And I think we're getting tools that can literally read our codes and help us understand them fast enough for us to make more intelligent, you know, decisions at each level, you know, personal, organizational, and national. I agree, except for the caveat that right now it's the limitation with the AI in general, as I, you know, I agree with the term as you just said, there's some issues there, but it, the, the trusting the data, I think it does a great job of, of gathering the data. I think it does a great job of giving you the correct data, but it also gives you incorrect information.

And that that's the issue of trying to discern what's correct and what's incorrect. You know, as an example, getting into a policy and the ai, I was recently just trying to discern what was in, um, asking rock about, uh, Alaska Bill one 30, was it, uh, 1 34 dealing with cybersecurity and it had some other issues to it. And just trying to get some very specifics there about exemptions.

And I kept asking it, I'm comparing the PDF of the actual literal bill to what it was spitting out to me distilling. And it kept on giving me incorrect information. I called it out on it just like, what the hell?

This not here, you're hallucinating. And then finally, oh yeah, I guess you're right. This was early iterations in the bill and associated documents that were associated with it that I got this from not the actual final bill.

It's like, but unless I knew that, and unless I checked it, it was dead on and everything else, but it was just, it had some incorrect information. And I see that a lot where it can be very confident in its answers. But unless you actually are also knowledgeable in the subject, which you know, is a problem when you're not, because you use it when, when you're not knowledgeable to gain the knowledge, it, it's, that's gonna be an issue unless it gets resolved.

And that's gonna be a tough one because of all the, uh, the information it's trained on, and is it gonna, is it gonna have the current information? Is it gonna know what's correct and what's not? Correct.

It's a lot of disinformation out there. Well, You know, I've, you know, I've used this knowledge all the time and it still makes the most sense to me, is I see all of this stuff as a really good intern. And if you're, you know, I, I'd love to, if you're a graduate student out there and you wanna learn a lot of things, you know, I love, you know, good interns and so forth, and I'll take you seriously, and I'll take your research and I'll read it.

And as you're saying, Ken, I may point out exactly where you're wrong. It's like, that was beautiful, however, right. There was more work and you know, more so it's the same sort of thing, you know, as, as I use these things myself, like I say, like I say in my daily life, you know, just, you know, it's practical.

I'm feeling how it works and as I'm advising others, yeah. This is not in a maturity level where you let it do a lot of things. Um, and the humans still need to be there to make the decision.

And I mean, and, and I don't, I, I can't recall right as I'm sitting here, if you gave an exact example, but I've, maybe I was just picturing in my head, but it all comes down to the individual. How important is it to me? And if I'm not certain, I mean, you know, I am certain if I got it from the internet that it may or may not be true.

Whether it's Google or Grok or chat GBTI know it said it, it says it right there looks good. And if it doesn't matter that much, I'm probably acting on it. Why not?

You know, I got other things to do. Yeah, exactly. Yeah.

It's more important. It's up to the user, you know, I know it said that. Let me ask it differently and again and again.

So if you do those things, and if you don't do those things with a, a good postdoc intern, then you're gonna make bad decisions anyways. Same thing. A hundred percent agree.

In fact, that's sort of funny. I actually did use, uh, did do an initial, uh, chat, GPT, uh, tryout with writing a thesis and even with references, right? You start looking up the references and it was just like, what?

This doesn't exist. It just made 'em up whole, I mean, whole wholesale, just completely just, here's, here's the paper, here's the author, here's pages. It's like, this doesn't, this isn't real.

Well, I'd love to, you know, this, you know, I don't think there's anybody even, I can put this on topic, but I do love this, right? You know, I love the hallucinations and that, and it's eagerness. It just wants to please, right?

And just, just like an intern or you know, somebody you're working with is like, that's a warning sign. You know, I think you're probably willing to say something 'cause you think I want to hear it and you catch it doing that, like literally doing just that. So A hundred percent.

But I agree with you. It is, it is amazing tool at aggregating all that disparate and huge amounts of information down to something that's at least you can work with, Right? We, which, you know, thank you.

That takes us back to our, our, you know, my, my positive, I think, I think savvy individuals and organizations are doing this now, but we're ly very early now. This is one of these fast moving things. Three years ago, the answer is no.

Even a year ago, I'd probably say the answer is no. I say I today, I might be a little early, but I think folks are starting to understand this, that you can use these tools exactly like that. You can't trust 'em.

But, and when it comes to, you know, this particularly, you know, the policy, again, we're talking politicians, right? You know, you, I think it was Win Schwartel who gave the first talk to the US Congress about cybersecurity at all. And as a community, we, you know, we spend the, the intervening couple decades complaining about how politicians don't understand this stuff.

They're never going to, that's not their job. They don't have time. I agreed.

But maybe they'll have time as they evolve to understand how to use these tools for this exact purpose. You know, putting their policies they're arguing against or proposing in a, in a richer context with better results. Well, here, lemme scare you a little bit.

I didn't tell you this the way I was able to live here in Poland. I came here a student visa po you know, policy hacking as you say. You know, I came here, it was like looking for ways to stay here and get a permit.

I came here a student visa, so I'm getting my master's, master's degree, business in finance at Y and university, one of the oldest universities. Very cool. But especially coming back at my age.

And so I'm in there with all these children, you know, twenties, thirties, children. But it was culture shock and seeing how good they are. A cheating.

I mean, it's amazing. I mean, I, I, it's like they could teach classes. It just, it's mind blowing.

I love that. And AI chat, GPT, et cetera, is one of the main tools. Oh, on a test, you know, on the phones, whatever, figuring these answers out or doing the homework and everything is just, you know, using AI to, to bypass the system and to cheat the system to get the good grades.

On one hand, I applaud them. On the other hand, I mean, I've been, I see, hear stories about it too with medical students and others passing their classes and their degrees based purely on AI and not actually knowing the underlying, which is, that's, to me is the scary part. It's just a, a huge current generation of people that don't understand the underlying rules and are relying completely on these tools to do it for him.

Well, and I, I'll, let me, let me, you know, as, as is my want, um, acknowledge that. Well, well, you know, looking at the other side, you Yeah, it's a, it's, it is, I think the tactical term s**t show, right? You know, we're, we have all sorts, the problems are coming out of this, however, right?

Yes. There's a, however, seems Like, it seemed like about 2007 perhaps, but right around that, that period, maybe 2010, I noticed a phenomenon where up until that point, if I'm on a, on a work call, you know, with a bunch of people and somebody says something I don't know anything about, and I'm not talking, I will Google it up, read about it, learn about it before popping in, you know, three minutes later with my thoughts on the topic. And it felt like cheating up until that point it felt like cheating.

Like you, you know? Yes. And then I found out you could say that I just looked this up and then say your thing, and everybody's fine with it, and we're all doing it.

And in fact, at right about that point, it became, you know, I, I remember getting annoyed and it sort of went away since, but there were people, you know, say, I'll get back to you on that and everything else. It's like, look, you, Bob, you haven't talked for 17 minutes. You know, you have like, can just contribute to the conversation now and instead expecting us to all get together in an email over the next three weeks and get your thoughts together.

And I think we may be, you know, again, acknowledge all the downsides, what you're talking about, you know, lack of expertise. You know, we got you, you got whole new generation from hacking the, the certification system with all those downsides. But maybe we were wrong in the first place, maybe expecting everyone to have memorized all these things to get this, this certification was wrong.

Don't, because in the real world that they're gonna be living in, they're going to have these things all the time. So, well, I, and that's, I have no issues with the helping as a tool to bring up stuff to not to memorize, because memorization, of course, that's whole other discussion about the loss of ability to memorize and remember things these days. But just to say that you can outsource that, no problem.

But you still have to understand the underlying fundamentals of how to use the information and why it's important and what part's important, et cetera, and how to interact with it. And that's the part that I think is the problem. It's not just pulling up an answer and just like, aha, you know, I didn't, you, you know how to get to it like we did.

You mentioned Google, you know what to look for, you know how to get to it. You, you understand the fundamentals of how to use that information here. It's just, Hey, what do you do?

This is, you know, it's everything. It's not learning the rules. It's not learning how to do things.

It's just learning how to use, uh, AI more effectively. Which, if it could be trusted, outstanding, but, and it is good in some respects, but you have those caveats. You had a, I think that's something to be wary of.

Well, I, I think this is one of these, you know, things that are right smack in the, in the, you know, 10, 20 year inevitable building curve. But this is gonna happen. You know, we'll see a lot of these cases where, you know, they got that far in their career without knowing anything.

Um, but we'll see, you know, our, our qualification certification, education, uh, evolved to keep that from happening. 'cause it, it is a massive problem that's gonna happen everywhere. I don't, don't know how we'd fix it in advance and it's too late.

Right. But I, I still see it like, like Wikipedia, my kids were of that generation where I get these notes saying, you know, you know, or talking to my kids who were working on a project and my teacher doesn't let me use Wikipedia. Like, that's cute.

Here's Wikipedia and here's what it says. Now if you copy and paste that, and now you're an idiot, um, but if you don't at least look at that, you're also an idiot. You know?

'cause that's, yeah. It's, it's a jumping point. That's, it's something to start with.

And so how to work with it. Exactly. Right.

You know, and, uh, yeah. So we, we've moved past that conversation. We're right now having this conversation, and we will in fact, 'cause 'cause there were people actually copy and pasting Wikipedia and, and submitting it as papers for a while, um, until they, you know, realized that's a way you could lose, uh, lose your, uh, your, uh, your, your college degree.

True. And the source material you have, it's the same thing as ai, is it? Correct.

Who knows, you know, parts of it. Yes. Yeah.

I, I grew up with, with the encyclopedia Bri Britannica. But anyways, you know, actually getting the monthly right. And Yeah.

Was that accurate? You know, read some old books sometimes, you know. No, True.

But it good enough. Exactly. Was, it was a reference point too.

It's just like, okay, you reference it and Yeah, exactly. I think Wikipedia does offer that. At least.

Here's the, here's the references good to start with. Jump off and look into other places. Of course, I think there's better places to look than Wikipedia, but still, yeah.

Points made. Yep. So I think we've, we've probably beaten that, that horse to death.

But we'll find, uh, we will, like everything else, we'll find out, you know, those of us who live far enough into the future to see how these things work out. It'll be like cobol, I think, uh, Those who know how to do will be called back up. Hey, charging whatever, you know, Like the Voy Voyager engineering, uh, team, you know, that's, those are the folks I'd like to meet.

But, uh, at any rate, I think with folks like you working on it, you know, and, uh, and the, the forces around us will, again, I think we'll find our way through this. I expect, you know, that in 20 years, you know, what we see is how we figured out policy and, and interpreted and used it today as being sort of horribly naive. We will, we'll see be I say that about a lot right now, just like, yeah, let's just wait and see.

Yeah. Alright, well, I will wait and see you again at some point. Um, we, uh, uh, I'd love to get back to, uh, to the Fatherland the motherland, you know, where blasts come from and, and, uh, tour poem with you sometime.

But in the meantime, that'd awesome. Thanks for everything you do, and thanks for your time today. Welcome.

Thanks for having me, Chris. Appreciate it. Right.

Thank you folks. We'll see you again. Cheers.

Bye. Kubernetes pours a sidecar quantum navigation, T SMCs A 14 AI process. We're gonna reset some things to factory defaults.

CCF stops a release, HPE gets even more secure. And then we're gonna take a look at some of Intel's future layoff plans in this episode of the Tech Field Day rundown. Hello everyone, and welcome to the Tech Field Day rundown.

Today is April the 30th, 2025. And, uh, I have a, a confession. It's, it's actually three days in one that are all slightly related.

'cause it is National Oatmeal cookie Day. It is National Raisin Day. You can see how those things are related, uh, and it's, uh, national Honesty Day.

And, uh, honestly, uh, oatmeal raisin cookies get a bad rap from pretty much everybody out there. Uh, so yeah, there we go. Uh, leave your comments in the, uh, in the video below.

If, uh, you believe that oatmeal raisin is a superior form of cookie, because the superior form of co-host is joining me today. Mr. Alistair Cook.

Al, how are you today? Well, today is an awesome day. Uh, there's a lovely storm raging outside, and I believe you've got a storm as well.

So we're sharing weather for a change. Uh, that of course brings us to something that neither of us are overly concerned about, which is National Hairstylist Appreciation Day. This wind is clearly not appreciating your hairstylist, Unfortunately, it is not.

But what we do appreciate around here is a lot of great news stories, and it's, it's been a fun week as we're wrapping up April, and we've had some stories that we want to take a look at, some fun stuff, and honestly, some not so fun stuff. But we'll get to that part towards the end. First thing we wanna do is kick off with some news about everybody's favorite container that isn't named Tupperware.

33 now includes native support for sidecar containers, which makes it easier to manage and deploy them alongside apps. This update also improves routing, pod placement and storage handling while adding some new features for security and resource management. Al, I guess the biggest question that I have about this is, are we gonna be able to find all the Kubernetes lids for these sidecars?

Well, hopefully you'll end up with matching lids and sidecars along the way, uh, as, as we want to keep our containers secure with those lids on, uh, sidecars are, are a really important characteristic of Kubernetes and, and, uh, a really common pattern for building container-based applications, uh, for those who haven't come across them. The issue with containers is that they hold a single process. And so where you need maybe an, an additional process to send logging messages or another process to handle maybe some sort of data delivery, uh, this is achieved in Kubernetes through this concept of a sidecar.

Uh, there's another container that runs inside a portal alongside the one that's running your application. And you can imagine that quite often there's a dependency that these sidecars need to start up before the application starts up. And that's the big change here, is that there's built in support for that in Kubernetes, rather than every customer needing to build their own into their own application.

And that application, having to retry until the sidecar is up and having this dependency mapping essentially inside the pod, is really very useful and reduces effort by, uh, large numbers of customers who are using sidecars extensively. Uh, I think it's a, a recognition that this has been a point of pain for many customers, that dependency management, and it's required lots of customers to solve the same problem, which to me always indicates there there's a feature missing in the product. There's some other cool things in this.

Um, as you mentioned, there's pod placements, things that are, uh, oriented towards places like cloud providers. We have multiple regions and, uh, multiple, uh, data centers within a single region. And there's some awareness and traffic being sent within the actual, um, what AWS would call an availability zone within the data center.

So you're not being hit with charges from moving traffic unnecessarily between those, those, um, availability zones. I would also flag that this continues, um, an interesting challenge that customers have. Enterprise organizations struggle with a pace of change in Kubernetes.

Kubernetes is relatively now for a cloud native application. It's actually slow moving. There's only three releases a year, but there are three releases a year to stay up to date.

And there are significant challenges for organizations that have standardized on Kubernetes, but not standardized on where that Kubernetes runs. And so they might have some Kubernetes and AWS some on premises, some running in Google, some running on Azure, some running on a service provider as well. And there are some complexities around getting everything to be at the same version.

It's not like you can simply apply the same service pack across all of the operating systems because you don't control the operating systems. And of course, new features are only available once the underlying Kubernetes platform has been updated. Now, good news is most of the providers have a pretty fast cadence of catching up with the, the latest release of, of Kubernetes and their underlying platforms.

But then there's sometimes some challenges about getting new versions of the Kubernetes agents or all of of the other components or of the operators and so on, getting deployed out, uh, to all of your worker notes. So although it's relatively slow for a cloud native platform, that three releases a year can be quite challenging for enterprise organizations to get the best value outta these updates to Kubernetes. 33, always like seeing open source products with a one at the beginning of the version number, um, means they're actually fit for use.

Um, Kubernetes of course has been awesomely useful for a lot of organizations for a long time. An Australian company just over the pond from us, or as we like to call it here in New Zealand to the West Island. Uh, an Australian company Q Control has launched Ironstone Opal.

It's a, a, uh, compact quantum navigation system, outperforms GPS, and it uses the earth's magnetic field in some really funky sensing rather than using the geostationary satellites. Uh, highly accurate, really useful in the many GPS denied areas. And we've seen cases of real problems with GPS jamming and, um, provided getting it in the way of our universal expectation to know where the heck we're, uh, much higher precision in in their testing, uh, small enough to be used on drones and vehicles and for defense use.

Uh, Tom, as you are heading out into the backwards, do you think you'll be using Einstein? Uh, I probably can't afford it at this point, and that's probably gonna be the biggest thing we're gonna have to deal with here. So I dug into this a little bit 'cause it had quantum written all over it, so obviously I have to talk about it.

Here's the thing. Um, Q Control took a quantum magnetometer, and they are, that's, that's a little cassette thing. It's, uh, probably about yay big.

I, I don't know what this is in science units. It's, it's this big. And what it does is it detects subtle variations in the earth's magnetic fields at specific points all around the globe.

So essentially what it's saying is, is that if you drop one of these magnetometers anywhere on the planet, it can read the magnetic field and tell you where you are. Okay? That's not true.

The magnetometer can tell you the reading of the magnetic field. What needs to happen then is you are going to have to have advanced denoising capabilities to basically, uh, filter out all the junk. And then there is map making software that crew Control makes that will tell you based on the reading that you got from the magnetometer where you are now, if you read through a lot of the stuff out here, and I'm not talking about the press release that Crew control put out, I'm talking about like the Arix paper that they put out and all the other stuff.

They're not at this time saying that this is a replacement for GPS. It's a backup for GPS. And the key thing that is valuable to them is that it is a passive system.

So everybody I hope at this point knows that GPS works by you walking outside with a GPS receiver. And if you can get in a lock on three to four satellites, then you know where you're at, or more appropriately, your sensor knows roughly where you're at based on the times delay that you, you get going to the satellites, that's great, but you can jam satellites. And we've seen that as becoming a bigger deal now because you've got, um, you know, the US has one, uh, set of GPS satellites, uh, uh, Europe uses, I believe Magellan, which is a different set.

They, or operate a little bit. And then you have, uh, Russia uses its own set of GPS satellites. And a fun fact, the reason why we have public access to GPS is because the 19, uh, 83, uh, Korean Airlines, uh, flight seven disaster, we learned about GPS in like, what, 83.

And it really didn't come become commercially viable, I would say, until the late nineties, early two thousands. So that's 20 something years, 15, 20 years before that technology became commercially viable. We are just learning about this quantum GPS technology.

Don't get me wrong, it is absolutely cool, but the cost is probably gonna be off the charts right now. So here's what I expect is gonna happen because there's already reports that Lockheed Martin is working with Q Control as a supplier to provide, uh, this as an assistance for, um, devices and things that are operating in GPS jammed areas. You should just read that as defense applications and write, uh, neon letters.

These are gonna go inside of Humvees, these are gonna go inside of jets, and these are gonna go inside of things that jets shoot at Humvees missiles, bombs, whatever, because that's important for precision work. We might see something like this, maybe two or three revisions down the pipe. So don't check out your GPS receiver yet.

I'm not gonna strap one of these quantum magnetometers to my, my back while I'm out on a run. Just know that they're working on advancing this technology and making it jam proof, making it cloud proof, making it indoor proof. Um, but remember that just like any good science experiment, being able to buy this at Best Buy is probably still a decade or two away.

TSMC has announced its upcoming a 14 line of chips, which is expected to be publicly available in 2028. They're gonna offer 15% better performance and 30% lower power usage compared to the future in two chips. The company also introduced system on wafer X, which, uh, is not something that they're trying to do to be more extreme, but it's in fact a new technology that combines multiple large chips with memory and optical connections for advanced AI workloads.

Since AI is dominating the, to support these innovations, TSMC will of course be building two brand new facilities in Arizona, and that is gonna bring them into competition with Intel who has already announced plans to build facilities in Arizona as well. Al, is this a 14 process going to drive even more adoption of TSMC silicon for AI applications? Potentially it could.

Uh, one of the big challenges in in building an AI data center is getting enough power and enough compute density, well, it's usually power density, that compute density we can achieve, usually feeding it with power and taking away the heat it generates. And so 30% decrease in power consumption compared to their existing, it's gonna be pretty significant. Particularly also in here is having the obstacle interconnect actually on the chip rather than necessarily dependent on external, um, external transceivers, which are a, a high power consumption item as well.

Not sure just how much that's gonna be, uh, optical interconnect off the chip. The, uh, things that I've read suggest it's optical inter interconnect on the chip between those multiple processes that are on this chip on wafer substrate. So it's multiple chips sitting on, on the wafer and interconnected.

Um, it's a, a little unclear exactly how that's gonna come out. And fundamentally, I, they're saying this technology is gonna Deb to publicly accessible in 2028, and they're, they're still building those, um, fab factories, those production facilities in Arizona, um, as well as, uh, yeah, Phoenix area packaging plants and, uh, there's gonna be a, a lot more construction there. So, as always, there's, this is a lot of promises about what will happen in the future, and we hope that TSMC will be delivering these promises and letting them go a little more toe to toe with maybe Nvidia, maybe, um, other vendors who are providing AI chips and AI accelerators.

Uh, nice to see in there some of their enhancements. So things like putting voltage regulators actually on the chip alongside the processes, rather than having to send voltage, uh, regulated voltage from a distance, which again, requires more power, um, requires thicker traces, more board space. There's a whole bunch of optimization in here.

So this chip on wafer substrate technology was launched in 2024. It is a, a thing that is, uh, has been delivered particularly for high performance compute. And we know that although AI vendors don't like to see this, there is a definite line between how high performance compute works and how AI works.

They're not the same thing by any means, but a lot of the concepts transfer across, uh, I think this will help TSMC continue to, to compete and, um, to compete with both Intel and to, uh, to a lesser extent Nvidia. And hopefully they're gonna be able to deliver exactly those power savings and those increased performance that they're promising. With this new a 14 program process, Convault has introduced a new factory settings feature to its clean room recovery service.

This feature enables organizations to restore critical systems to a secure, well-known good state after a cyber attack. This capability helps ensure that recovery environments are free from malware or unauthorized changes, uh, supporting faster and safer restoration of operations. It's interesting that clean room recovery doesn't quite mean the forensic recovery that I would've previously thought.

So this seems like it's gonna be very important as we continue to see particularly ransomware, uh, attacks and on Linux systems living off the land kind of behaviors of these ransomware attacks, Attacks, attacks. This is kind of the, this is the last resort button, if you wanna call it that, because like you mentioned, there's, there's different kinds of recoveries, right? Like sometimes we wanna recover files because we wanna actually see where they were and what they were doing, the forensic kind of analysis.

Then there's the, we need to get things back operational to yesterday because we need to be able to get things operational tomorrow. And, and that's a little bit more destructive, if you wanna call it that. But, uh, then there is the, I guess maybe we should call it the Ellen Ripley option.

I say we take off and nuke the entire site from orbit because it's the only way to be sure. And that's kind of what we're talking about here. And I love the fact that Commvault offers this as an option to say, we are gonna take a clean snapshot of this system, of this site, of whatever it happens to be.

And when you hit the big red button, or blue or green or whatever color you wanna make it, it goes back to this like we, and, and I'm sure that part of this is going to be that that's an immutable copy. And and maybe you can say, well, you know, every six months, every year, whatever, we're gonna upgrade our factory reset to, to X or what have you. But like I said, this is the absolute vallet.

We are not recovering anything back, you know, that has been made since this point. And that sounds harsh. Like, like I'm sure that, uh, a resident storage expert, Mr.

Steven Fosse will be listening to this episode going, oh my God, they're gonna do what? But sometimes that's what it takes. Like think about when your iPhone is so far gone, or Android, if you're using an Android, if your phone is so far gone that you just, you've gotta wipe it and restart.

I mean, I had to do that to my son's iPad a while back. It was working, but like, it kept, uh, got caught in a boot loop because it didn't have enough free storage because somehow in the whole thing it said, oh, well we've, we've consumed 80% of the drive, uh, for system storage. And the only solution once it was in a boot loop was to restore it.

Now, when I restored it, everything came back just fine. 'cause I had an iCloud backup as you should have. But this is that version of saying we have a good data copy from, I don't know, call it January 3rd, and we know that things were working well then, and we backed up the transaction somewhere else.

We're just gonna wipe this thing back to what it looked like on January 3rd and go from there. Um, use with caution though, with all, uh, you know, magic erase buttons. Uh, sometimes you get unintended side effects, but at at least, you know, you've got another tool in the toolbox because if the, the alternative is to restore from a backup from two weeks ago and then go figure out how they got into your systems.

And is this malware persistent and are they able to move laterally? Again, I I, I don't have a good answer for anything other than the l and ripley option. Here's a fun one.

The Cloud Native Computing Foundation is actively working to protect the open source integrity of the Nats project. That's NATS because the company that donated it to the CNCF CEDIA is attempting to remove the project from the CNCF and re-license it under the business source license because they want reclaim control over those assets. Now, CEDIA originally donated Nats to CNCF back in 2018.

They want to back it out because they wanna assert ownership over the Nats trademarks and infrastructure. Now, in, in blog posts that we're gonna put up in the show notes, CNCF contends that those actions violate community-driven governance models and the commitments that were made when the project was donated seven years ago. The foundation emphasizes that the open source projects that are in the CNCF umbrella should remain community owned and vendor neutral, and is taking steps to ensure that Nats continues to operate under these principles.

This isn't the first time that we have seen an open source project create some problems because of the business source license, because this happened to HashiCorp a while back. Uh, al you're a proponent of open source and all kinds of wonderful things. Should CEDIA be able to reclaim that project from CNCF just so they can relicense it?

Well, here's the thing. Uh, usually companies take some software that they've built and donate it to CNCF, uh, 'cause it's gonna help their business. And that they hope that by making it open source, other people will contribute to their project and improve the software and therefore make it easier for them to cont the, the commercial organization that donated the software to continue to trade and make a profit.

Where it starts to fall down is where an open source project is only being developed by the originals owner, and there are minimal contributions from anybody else for whatever reason. They can be a variety of reasons. Sometimes it's about how the projects are governed and led and other times it's that the feature set is just not interesting enough to, to see development.

In that case, the commercial organization looks at it and says, well, we put all of our intellectual property into the software that we donated, and we're not getting a return for our donation. Huh? When I make a donation to a charity I want to support, I expect them to use that donation for their benefit more than for mine.

Maybe there's some altruism that I have as a, as an individual human that doesn't really apply to a commercial organization. And, uh, what we're seeing here is, uh, EDIA seems to want to bring this thing back because they've given away too much value from the organization. They're not able to add enough additional value to the open source to be able to make their own business viable.

At least that's my interpretation of why they're choosing to pull this back. Uh, the other way that this sometimes plays out, and we saw this, um, with the database that AWS released a document DB and it was a, a clone of an open source database or, or it was actually an open source database that they produced a, a service on and some challenges around that. Cloud providers taking open source and just releasing a service, leveraging what's been donated by another commercial organization.

Uh, we do see changes in licensing around that as well. Although there's some, some fun stuff in governance here. I think the CNCF is doing the right thing by standing up for saying you made a donation, you can't take it back.

Um, that's not the way donation works. And that the important, there is a very important element here of, uh, once things have be become open source, somebody has to stand up for the open source and protect that. Uh, but also the whole idea of open source is communal development.

So active projects where improvements are being made, the requirements of customers using the software are being met by these changes. This is an important part of open source. And if it starts to fall down, if there's no, uh, if, if there's no motivation for developers to improve the open source project, this is where we're gonna start seeing challenges.

And maybe we need to see if there is a way for a, a graceful exit. Uh, one of the most common ways we see this is that the commercial organization will fork the original code and will release a new updated version of code with new proprietary code that is not covered by the existing license. It really does depend what license was applied when the, um, NATS project was open sourced.

It's a project that's, that's used and embedded inside people's applications to their message passing between different parts of the application, particularly from on-premises to cloud or across multiple clouds. Um, yeah, we'll see how this plays out. I don't think it's over battles over trademarks and open source are nothing new.

Uh, we reported a while ago on the ongoing WordPress, uh, atomic Mullen work, um, dramas. There's nothing new. Open tofu also recently, uh, joined the CNCF, which was the, the outcome of that.

Uh, earlier Terraform, uh, closed sourcing, more drama to follow. At RSA 2025 HPE announced updates to make its cybersecurity tools work better across different platforms. This includes Integr improved integration of its networking and security tools, smarter DDoS protection using ai 'cause everything's better with AI and new options to disconnect from the internet during threats.

Wow, that would've been really useful about 30 years ago when the first email based threats were coming in. Uh, HPE also added features to help protect data in the cloud and AI environments. Aping aiming to simplify security and make it more flexible.

Uh, Tom security is you tell me what the heck's going on. Um, this all comes down to everybody's favorite Explorer, Dora. Well, okay, not Dora the Explorer, although if you wanna say backpack, say backpack.

Uh, no, this is about the Digital Operations Resilience Act. And if you don't know what that is, that's because you don't live in Europe. Uh, this is a new regulation.

I say new it, it's, it's not brand new. Uh, but this Dora is aimed at financial providers in the eeu and it is designed to keep them online when everything goes wrong. And there's parts of Dora that now need to be implemented, and one of those is a kill switch.

We laugh, right? Because the Morris worm took down all of these systems, and man, if we'd have just been able to unplug 'em from the internet back in the eighties and nineties, we would've been okay. But it's actually kind of more common now for large malware deployments to have a command and control server out there somewhere.

And we saw this, uh, from, uh, a few years ago when, uh, Marcus Hutchens actually black hole, a massive cyber outbreak because he registered the domain name that one of the malware pieces was looking for as a a C NNC black hole. If that domain name was online, then it was gonna stop propagating. And just by sheer dumb luck, he found it and, and created that, and then of course created a whole other mess for him himself with the FBI.

But I'm not gonna go there right now, but this is, this is becoming a more common thing, right? If the, the attackers are assuming that all of these systems are, uh, terminally online. So all they have to do is make it so that when the system checks in with the CNC server, then uh, it'll keep propagating, it'll keep doing all this crazy stuff, and then it can be used to launch DDoS attacks and stuff like that.

And so now what HPE is saying is, okay, we're gonna comply with Dora. We're gonna add these kill switches. We're gonna add policy, uh, that allows you to, uh, you know, take systems offline until the threat passes until a certain amount of time elapses or we're seeing, uh, no more anomalous traffic coming from these things.

It's essentially a way to prevent you from continually reinfecting yourself, but also to shut down the capabilities that these people will have to leverage your networks to do other stuff. Because we've seen that quite a bit in, in the DDoS arena, right? Like CloudFlare is talking about blocking, uh, DDoS attacks that are dozens, if not hundreds of gigabits in size.

And, and that's a lot. But, you know, this is all being integrated into GreenLake. This is all being integrated with HP Aruba Networking because all of this came out of, uh, some of the work that Phil Mara's team over there has been doing.

Uh, you know, it's, it's designed to help people feel better about migrating things into, uh, an, uh, a cloud environment like, uh, HP GreenLake and, and the things that they're doing. But more importantly, uh, for organizations that are subject to dora, which if you do business in the eu, you absolutely are. Um, you have to make sure that you are following these regulations because if you don't, um, then swiper will definitely swipe some things from you.

Let's take a closer look at a story that involves our friends over at Intel, because they're still looking to smooth out their operations under new CEO Lip Bhutan. Last week there was an announcement that Intel was gonna be cutting some more positions and initial reports said that the rumors were as high as 21,000, which would've been 20% of their workforce. And then on Friday, CFO, David Zenner said, uh, absolutely not.

Uh, instead what he said was, each department will assess the structure that they have, and then they're gonna decide whether or not they're gonna cut positions or offer voluntary buyout packages. However, Zenner, who is the CFO, so he would know, said that maybe not all of those buyout offers were gonna be accepted. And if you're one of those older people that's been sitting around going, well, I'll just take an early retirement, not so fast my friend, because Intel announced that early retirements are not gonna be considered at this time.

The stated reason, of course, is that in the long-term, previous early retirement options had led to some long-term problems that they don't wanna repeat again and again. All right, Al, I know that the rundown this year really feels like we have been punching intel to the point where the kid on the Simpson School bus is saying, oh, stop, he is already dead. But I gotta ask the question, are we at the point where Intel can cut more to get to profitability, or are we gonna have to look at other options?

Now? I think the, the headline of more people being laid off after 15,000 laid off, uh, last year with Pat Gelsinger, um, that that headline definitely reflects the fact that there is a large change being made at Intel. Whether that means that it's a 20,000 existing staff or 21,000, if, if those numbers follow up, um, these massive numbers of people leaving isn't necessarily the whole story.

What very commonly happens in tech companies is that the bit of the company that is underperforming, the bit of the company that was awesome five years ago, but is no longer pulling its weight gets cut off and a new bit gets growing that is going to move forward and improve. So I do think there's a little element where, uh, lip bhutan's plan, he says, uh, I'll make it perfect when he speaks of, of Intel. Uh, so he may be following that idea that perfection is achieved, not when there's nothing left to add, but when there's nothing left to remove.

Um, not sure that that gets us to the, the forward space. Hopefully alongside these eliminations of, um, parts of the business that have been underperforming and that are yesterday's intel, hopefully there's a growth in tomorrow's intel because, uh, lip bhutan's there to make a recovery, to make a turnaround, to make Intel, uh, perfect. And you can't do that by continually cutting away.

You will certainly reduce your burn rate on money, but then doesn't increase your income. You've gotta increase your top line. You've gotta produce new products that are competitive in the market, that are demanded in the market, and that are taking on the people who have been eating your lunch recently, specifically Nvidia and increasing the a MD.

You've gotta get ahead of these people and build new products. Tom, do you see Intel building new products, adding more replacement people for some of these? I, I don't right now, and that's part of the problem.

You, you mentioned, you know, lit Bhutan says, I'm gonna make it perfect, and yeah, when there's nothing left to remove it, it, it could be perfect. I mean, I think of the old story of the Zenith. Uh, CEO used to walk down the assembly line and he'd yank a piece off, and then when it didn't break the tv, he'd say, well, you didn't need that piece.

And when you yank off enough pieces that finally you break something, oh, look, we, we found a part we needed. But that's not a strategy for, I don't know, um, survival. Like, here's the thing.

Intel is finding itself in a very hard spot because their plans to become more profitable, or at least stop the slide, require people to do things like you said, but you don't know who that's going to be. And that's the weird thing about this. They've already said that they're gonna have every organization go through and figure out who needs to go and who needs to stay.

That sounds to me like it's gonna be asymmetric. You're not just gonna go in and they're gonna go like you and you and, and 20 people over here, and I guess 20 more people over here. Some of these organizations are gonna get hit hard and they're gonna make sure that the people who are left behind in the areas that they think are going to be their growth areas are not gonna be allowed to take an early buyout, and they're not gonna be able to take an early retirement.

So basically, you guys are gonna be here because we need you. And I wish they would do a much better job of communicating that upfront, because that to me is where Lit Bhutan's leadership really is needed right now. Here are the things we are going to do well, and whatever they are, you're gonna have to double down on those, right?

Because I, I remember recording rundown episodes late last year saying, you know, Intel gout e can't miss, like, like if they wanna get on the AI bandwagon, their GPUs can't miss and they gotta do this and they gotta do that. And here we are, less than a year later going new CEO cutting people left and right, they need to succeed at what, that's the question that I think that Intel has to answer right now. What are you gonna be a fab facility?

Are you gonna build out that Ohio Fab in these Arizona fabs? Like in the story we talked about where you're gonna be, uh, coming into competition with TSMC? Are you gonna try to become the homegrown tariff proof company, then say it?

Because that's gonna take time for you to get those things adopted. But if I don't know what you're building other than making more CPUs, that doesn't give me any, any hope for the future. Because what if you're cutting jobs from the CPU manufacturing and the packaging people and all that other stuff, if you're cutting those from areas that I know you're good at, that's a signal to the rest of the, of the market that you are trying to either survive or that you don't wanna be good in those things anymore.

We have to see what's going on because then what happens then the rumors come out that you're cutting 20% and everybody flips out because oh my God, how can you cut 20% of your workforce and continue to be a market leader leader? You've got to provide guidance. And that, that's table stakes right now, as, as, as I see it.

All right. With that being said, luckily there are some things that are coming up on the horizon of the future, at least from the Tech Field Day side that you can absolutely hang your hat on. And the first of those will be next week because I am gonna be in Silicon Valley talking about all things related to mobility.

We are gonna be having mobility Field Day, uh, 13. We're gonna have presentations from great companies like, uh, Juniper, Cisco, Ubiquiti, Fortinet, Nile, cel, um, Arista and more. com and check out what's going on there.

And then coming up after that, the next week, uh, Steven is gonna be it, uh, tech Field Day Experience at Click Connect 2025. Uh, it is a great opportunity for you to learn more about what Click has been working on since we had our, uh, click Connect experience last year. And I know he's gonna have a wonderful lineup of delegates around the table, uh, enjoying, uh, all the great things that there are to offer at events like this.

And then at the end of May, you're gonna be hearing from me once again at Security Field Day. We have a wonderful lineup of companies, uh, Microsoft, Dell, Veeam and more. com.

Uh, you can also check out the delegates that are gonna be there. Uh, it's, it's gonna be a lively bunch. Uh, luckily nobody's gonna be guessing anybody, pa anybody's passwords 'cause we're all two factor enabled.

And you should be too. You should use all of the factors of the tech field a rundown, whether you are checking out the video on the tech field, a plus YouTube channel, whether you're listening to the audio format of this in your favorite podcast application, or go over to the website and check on the show notes because we link to all the articles that we use for research. Uh, and sometimes we link to some other fun stuff too.

But we will be, uh, producing this episode every Wednesday in the afternoon. You know, once you get a little bit of caffeine and some lunch down, you then it's time to listen to the news and hear what Al and I have to say about it because Lord knows we, we have as much fun as we can with some of this stuff. Uh, but you know, we'll be back next week with some more exciting, fun news.

There'll probably be some stuff out of RSA and a few other things. But until then, make sure that you're subscribed to Tech Field Day, across the board, uh, website, uh, for upcoming events, our newsletters for all the stuff that you need to know. And if you have any news stories that you wanna send our way, you know, make sure you check out all of our social media channels.

Those are listed on the website as well. Uh, we'll be back next week with more great news. And until then, uh, make sure that you stay dry, uh, and enjoy an oatmeal raisin cookie for me.

Will you.