Navigating AI and Cybersecurity: Insights from MacStadium’s Chris Chapman

Hi everyone. Welcome back here to Techstrong tv. My next guest is Chris Chapman.

Chris is the CTO Chief Technology Officer over at MacStadium. I was telling Chris off camera, I haven't had a a Max Stadium update in a while, so I'm looking forward to this one. Hey Chris, welcome to Tech Drunk tv.

It's great to have you on. Great to be here and I'm glad we get to catch up after all this time. I'm excited to tell you about what we're doing and what's going on in the world.

Fantastic. Hey, before we do that, tell people a little bit about you, Chris. Sure thing.

Uh, my name, my name's Chris. I am the CTO of MacStadium for about seven years now. Uh, I came in through acquisition MacStadium iss, a 14-year-old company that is really got its roots in starting cloud and data center, but all based on Apple infrastructure that was primarily to help serve developers and software engineers who built Apple Platform services.

Um, it's evolved since then into quite a bit more than that. And what I did when I came here is brought in a software practice as well. So we've created a flagship product that's really now the focus of the company called Orca that really helps go not only in our own data centers, but beyond that and to the edge and the AWS and everywhere else.

Um, that really defines sort of operating Max at scale and what we call a Mac Ops capability. Max billet. That's a great way of describing it.

com. Pretty pretty straightforward. Cool.

Absolutely. I just wanna kinda get it out of the way so we could dive in here, Chris. Yeah, absolutely.

You Know, you're right, MacStadium, I mean it really started very much centered on Max Right. And, and Max in, you know, specifically exclusively almost. And I, you know, I remember in previous discussions it was really sort of about maybe, you know, running Max in the data center Yeah.

Which was not a, a common thing back then, but, um, and it really isn't one of the Apple sort of core constituencies, but, you know, I know like a lot of my team here are running, uh, is it the Max studio? Is the M four double O the M four Ultra chips? Uh, yeah.

The, well, the, uh, MM two and M three studio Ultras are the big ones. And then M four, yeah, M fours are the master Next gen, but they're usually in the mini, mini form factor right now. Right.

That's the mini we we have both here. Yeah. You know, 'cause we obviously doing all the video we do.

Right. It's, it's a good thing for us. Yeah.

But you know, as you mentioned, max Stadium's mission has expanded, you know, beyond just that and, and for good reason. The world is a crazy place. Um, you know, we're living in and perhaps could, you know, in hindsight be the greatest revolution we've seen yet in computers.

Yes. The Arrivaling, the internet, even the, The two letters that permeate all conversation now, AI for sure have started disrupting all things, and Mac is no exception to that. Whether it's Apple themselves and what they are or aren't doing with Apple versus, you know, what we serve, which is enterprise and business and, and how I think everybody is scrambling A, to keep up and b, to figure out what it means to them specifically as an enterprise.

And as, as you said with MacStadium, we, we've evolved not just from hosting, but to really, how do you do scale enterprise, cloud capable stuff, software defined, and that's, you know, our ORCA platform. But as we get into AI as really start to see with ai, and we've seen it also with our partnership with Citrix on the VDI side, Mac is starting to drag sort of what we would call not just development concerns or creative concerns into the business. 'cause you always had creatives or developers who wanted their Mac to do their thing, but now you're starting to see, oh, it's, it's a core business functionality driven by an AI database with company data stored inside, or it's a remote worker access platform and it's the desktop that the customer's using for, for VDI or for, for day-to-day knowledge workers.

So what that means for us, and what that means for Mac is, is that we're really starting to pivot beyond just specialized infrastructure into core common business infrastructure that has to go everywhere from the iPhone in somebody's hand all the way to a cloud, which most companies don't even still know today that you can do Mac in a cloud. Absolutely. Let, let's, let's zero in on what AI's role is in that though, Chris.

Yeah. Um, you know, I I think like everyone, it's changing by the minute. Um, but what we really think is starting to evolve is that AI is becoming a woven integral part of business.

It's not just a cloud thing. It's not just a, uh, LOM chatbot that you can ask a couple of questions because you don't know the answer, which just kind of evolved search, right? Um, we're starting to see businesses really try to understand how it can fundamentally automate and change workflow and work efficiency for employees, but also do things that matter to the business, sort of become a digital employee to augment their company.

That could be anything from, you know, scanning things real time through visual devices to figure out what it needs to processing it on the back end to gobbling up all the company data and finding patterns and, and efficiency and, and sort of reporting at scale. Um, so we think pulling all these things together means that you now have an interesting challenge in the enterprise because not only do you have to figure out how to run this cost effectively and securely, but you have to figure out how to command a chain of tools that could go everywhere from the desktop all the way back out to the cloud and figure out how the data's moving, figure out how the technology's working and mesh all of this stuff together somehow. So, you know, that that's where we see the challenge and opportunity in ai, but also the, the race to, to get sort of your arms around it, if that makes any sense.

There. It, you know, there's a land grab going on, but there's also a, um, you know, it's, it's, it's trying to run as fast as you can while you're trying to keep your pants up kind of thing. Right.

A Hundred percent. Do you know what I'm saying? Yeah.

Um, and, and so there's, it, it's, it's interesting. Um, I wanna pivot a little bit and talk about AI and cyber. Yeah.

And as it relates, you know, we could relate it specifically to Max, but there's a bigger story around AI and cyber as well. You know, again, it's a Tom and Jerry game there, right? Yeah.

The cat, the mouse. And we're sometimes always a step behind. Yeah.

Well, like I said, you know, you know, you've, you've long had it in cyber, it was the capability of the individual to do certain things. But AI brings a whole dude a mention to it because it's not just automation and speed, but it's intelligence within the automation. So before, if I ran like a massive script to try to find vulnerabilities, that was one thing, but then I had to act on it.

But having a thing in the middle now that can do that and then make its own decisions about what next, what next, what next, that just amplifies the speed with which things are starting to happen. And the same on the defensive posture side. I think, you know, before it was protecting your end point and analyzing the data and making sure that you were secure.

But what I think AI's bringing to the puzzle is, um, an increase in speed and real time decision making. And then it's also sort of forcing this sort of comprehensive mesh. It's not just about one spot being secure anymore, it's about the entire tool chain being secure at speed real time and sort of interacting with what's happening as it goes.

And I, I think more than an arms race that becomes more of a, like, you know, more, you, you have to be almost have a have a proactive and comprehensive solution set around your cybersecurity posture these days. You absolutely do. I I, I think the, yeah, so my background security, let me just say that, uh, 'cause I've been about 30 years in the, we didn't call it cyber, we called it security.

Um, but I, I think the biggest kind of boogeyman for us in security with the AI is, is we just don't know what's coming down next from the bad guys, right? I mean mm-hmm. You know, they're well funded, they're well organized, they're not dumb.

Right. You know, and whether you're talking about nation state kind of threatening or pure, you know, economic stuff or hacktivists, you know, there there's no shortage of vectors. Yeah.

And the other thing is, all of these LLMs that we're using and all of the data we're using, you are consuming or generating all the code we're generating via ai, it all just blows up the attack surface, right. Where we couldn't defend what we had before. Now, now you're gonna tell me, I gotta defend twice as much code, I gotta check code that humans aren't writing, but the AI is, and the AI's not quite up to maybe writing secure code.

How the heck, how the heck do we do that? Yeah. That, that is, that is quite the challenge.

And you know, I think the evolution of not just sort of, um, context writing, but context engineering and how that's starting to happen. I, I, you know, I'm starting to see in code and tools now, not just the right way to prompt engineer, but actually evolving what we would call software development lifecycle processes actually embedded into the cogen tools so that you have the QA guy and the, the project manager guy. And so you're sort of having the AI segment itself up into proper like tool chain.

And in that you have the security guy that goes and checks for the dependencies and all the gen to code. And it's interesting how, you know, we're sort of starting to mirror the real world and what the AI's having to do because we're realizing it's not good enough to just say, go build me an app and then watch the crazy stuff it spits out because that's not gonna be compliant and safe and secure at the same time. It's sort of frightening that anybody with limited skill can go into one of these LLMs and go, go look at the interface on that thing and write me an app to see if you can attack the vulnerabilities and anything that's a gap and it'll go do its best to write it for you and you don't have to know anymore.

So there's, there's that problem. But I, you know, I think the larger problem set to LLMs in general, and it's back to the enterprise use of ai, is that everybody's so excited that they're just typing their answers out into the internet everywhere willy-nilly. And, and as you know, the biggest problem in security is usually the human.

And it's, it's a huge opportunity to sort of socially engineer people or have, you know, talkative LLMs on the other end asking questions or honey potting people or doing things like that. So, you know, the biggest risk, I think still is just training people to use the tools correctly and be very aware and cognizant of where their data's going and what they're saying to whom I, you know, that's still the, the fundamental classic problem and security with this stuff. Yep.

Chris, I want to turn to the last kind of topic we had on our agenda today. And that was, you know, an emerging blueprint for managing mixed device, cross platform, remote first environments. Let's define that first and then talk about the blueprint.

Yeah, yeah. You know, you know, again, I, I think you know, what we see at least in the, in the Mac world, and I think the enterprises in general, we've, we've done sort of some recent sort of market research and things like that, and it's, it's confirming what our thoughts were is that Mac is really starting to permeate the enterprise in a bigger way. Apple's always provided it, and people always loved and use their products, but I think with the, the M four Air was one of the big new laptops last year.

They completely crushed the market from like an adoption perspective, and it's a combination of like apple, silicon power and price point. But that combined with sort of generations of people using it because they just felt like it was a really cool device. You're starting to see people demand it as sort of the productivity tool in the enterprise.

So what this means is now you've got Linux users and Windows users and Mac users at scale all over the place in these enterprises. And then with what we've been talking about with ai, you've got all these new and interesting tools all over the place coming into play too. So what you're really starting to see is no more, no more homogenous environment, it's no more heterogeneous environment, it's just all over the place.

Things everywhere, different oss, different platforms, and IT departments are really going to have to get their arms around the fact that there's gonna be multiple device types. They're going to go all the way from the edge because it could be somebody, you know, looking at something with AI with their iPhone and then processing it on their desktop and then asking a cloud to answer the question. Um, so there's this, this big giant mesh of tooling and chaining that has to take place now.

And I don't know that it is quite ready for that yet as far as the, you know, traditional tool perspective. So, um, it's, it's a new challenge. No one's asking their permission.

That is the other problem is that it's a thousand tools all at once, and it's, I'm gonna use this and figure it out. Um, that, that's, that's a really spooky thing. You know, I, I wrote, I wrote an article on, on this, I, it was last week and I ended it with the words of Lee.

I Coker man in today's world with this AI stuff, it's lead follow I get out of the way. It really, really is. Yeah.

Well, Yeah, It is. With, with us, we're, we're trying to, we're trying to suggest that the right way to do that is to sort of integrate and embrace as fast as you can. And then we, you know, kind of leverage, we're leaning into our software strategy with Orca as an ability to sort of orchestrate anywhere at scale.

And we think that's the right way to start pulling tools. And whether it's a cloud or the edge or whatever, you've gotta be able to sort of touch everything real time, get your arms around it, and start to push and deploy. Love it, Chris.

Don't wait so long to come back on here and keep us posted on MacStadium. You know, myself and our audience, we got a lot of Mac fanboys out here and you know, Mac is in the enterprise, right? Yep.

And in spite of what anyone may say. So good luck. Keep, keep doing what you guys do over at MacStadium and come back and keep us posted, okay?

Yeah, absolutely. Thanks for having me. It was a blast.

Always. Chris Chapman, CTO at MacStadium. com here on Text Drunk tv.

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