Draining the COBOL moat, cybersecurity inequalities, and Claude’s retirement home

**Ben Lloyd-Pearson** (0:05)
Andrew, what do you think about this whole open claw moving from the self-hosted Mac minis to the cloud now, like all these cloud services that are popping up?

**Andrew Ziegler** (0:14)
I've seen so many of them pop up in the last week. It feels like ever since there was the open AI acquisition, there's a lot of people tackling the problem and trying to get a piece of the platform pie with agents first.

**Ben Lloyd-Pearson** (0:27)
It's like, can we beat open AI to the punch or something?

**Andrew Ziegler** (0:29)
And the answer is probably not, or you're just gonna get different punches, frankly, but I think it's actually a really interesting phenomenon because it's really what you're saying in that world is I don't trust myself to host it on my own device securely, so I'm going to trust a stranger to host their device securely and then pay them to hope that they're not reading my information. It kind of flies in the face of, it makes OpenClaw feel even more dangerous to me because you're basically putting it in a phenopticon.

**Ben Lloyd-Pearson** (0:59)
Yeah, with proper protections maybe, but man, who knows who's prompt injecting your OpenClaw agent without you even knowing.

**Andrew Ziegler** (1:07)
But that said, if you're hosting one of these things in the cloud and you have a really strong case for why or you have a really interesting experience, I'd love to hear from it. I was thinking from just the experience of having tickered with the only in a local host kind of setting, I couldn't imagine putting it in the cloud, so I'd be curious to learn more.

**Ben Lloyd-Pearson** (1:23)
Yeah. Well, welcome to the Friday Deploy. I'm your host, Ben Lloyd-Pearson.

**Andrew Ziegler** (1:28)
And I'm your host, Andrew Ziegler.

**Ben Lloyd-Pearson** (1:30)
All right. What do we have in this week's news? We've got the Cobalt apocalypse and what it says about how AI is impacting software companies. We have something straight from a Silicon Valley episode of AI assistance taking down AWS production. Dev productivity studies meet reality. Seven takeaways from the AI safety report, and we'll close out with the retirement home for Claude. So, Andrew, let's get right into this Cobalt apocalypse. So what's going on here?

**Andrew Ziegler** (1:59)
Yeah, so the IBM stock took a huge dip in the last week. It lost 13% of its value after Anthropic announced Claude Codes Cobalt modernization capabilities, basically scaring a bunch of investors away from the moat that IBM has around mainframe computing and languages like Cobalt. And Cobalt is one of those languages that, you know, we talk about and joke about, but it's hard to understate the amount of impact in the world that it powers. I think over 80% of all ATM transactions run on Cobalt. So we're talking about a huge surface area where IBM is, you know, the supreme de facto experts. This is kind of the latest example of AI news announcements taking a big bite out of preexisting companies and their valuations.

**Ben Lloyd-Pearson** (2:46)
Yeah, you know, this story actually hits really close to home to me because my mother actually worked in tech with Cobalt for many years. In fact, she actually built herself sort of like a niche in migrating these like legacy Cobalt systems to the cloud. And I'll never forget when she told me many, many years ago that I should learn some of these legacy techs because they were actually like lucrative jobs, you know, just understanding these old systems as the people who maintain them sort of aged out and retired. But you know, it's kind of strange, it's kind of crazy to think about how, you know, right after I started using AI on a daily basis a few years ago, I had a conversation with her about COBOL again, and we basically came to the conclusion that it was gonna get killed off by AI. Like it was almost inevitable, it was just a matter of time of the tooling catching up to this. And you know, and I think really what we're seeing here is something that represents one of the sort of biggest challenges that a lot of legacy enterprises in particular face with AI adoption. And that is a lot of these legacy code systems just don't have nearly enough public training materials to teach AI how to work with it in a consistent and successful manner. So companies like this that want to be successful with AI adoption will have to train their models on their internal code base and norms as well as their technical requirements to move beyond the general purpose AI capabilities to something that's more highly adapted to them. So yeah, it's really interesting because I know one of the big challenges with COBOL is just understanding the end-to-end data structures because you really have to understand the entire picture before you can start to replicate components of it. And that's something that AI is actually like really, really skilled at doing. So I mean, it makes sense that like the investors are, I can understand why they're scared. I don't think it's going to be an overnight disruption, but I absolutely do think that these models are going to get really good at eliminating COBOL systems from legacy companies. But yeah, what did you think about this, Andrew?