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Episode 89: Agentic AI

Episode 89: Agentic AI

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 The episode opens with host David Brady introducing a panel to talk about recent advances in AI, kicking off with “story time” from Mike. Mike describes how massive investment has accelerated progress and uses a hotel analogy to explain the shift from traditional AI tools (you ask for a specific thing and it does exactly that) to agentic AI (you describe a goal like “I’m cold,” and the system takes multiple independent actions to solve it). The panel frames this as a major interface change: instead of issuing step-by-step commands, you collaborate with a tool that can plan, execute, and iterate—powerful, but also riskier if it takes the wrong initiative. They then ground the idea in practical software work. David describes using an AI agent to scan a large, messy, decade-old Rails codebase for dead or “zombie” code—surfacing unused files, routes, and even database tables with no activity since years ago—while also noting how the agent can misunderstand intent (e.g., trying to “fix” missing controllers instead of removing obsolete routes). Justin and Matt extend this into security and ops: combining logs (like Datadog/WAF), an OpenAPI spec, and code access—potentially via MCP (Model Context Protocol)—to identify unused APIs and shrink attack surface. A recurring theme is that agents excel at tedious grunt work (grep-style hunting, bash plumbing, awk/sed, git forensics), but they still require review, guardrails, and clear instructions. The conversation widens into “AI fluency” and human factors: prompt skill matters, “prompt engineer” is treated as a real craft, and vague requests can cause agents to take unhelpful liberties. They discuss personality differences among models—sycophancy and overly affirming behavior versus more nuanced ethical reasoning—and how that can affect users, sometimes dangerously. The panel debates whether software creation will move toward natural language: some argue English is too ambiguous for precise specs (hence lawyering), while others think we’ll keep needing discipline and precision even if interfaces get friendlier. They close by flagging major risks—unattended agents with broad permissions, security exposure, and IP leakage—and tease that AI security and governance deserves a full follow-up episode. Transcript: DAVID: Hello and welcome to the Acima Developer Podcast. I'm your host today, David Brady. And we have got a fun panel. And we're going to talk about advances in AI today. Today we've got…on the panel, we've got Kyle Archer; we've got Mike Challis; we've got Eddy, who's down in Mexico now. That's awesome. We've got an AI bot who I'm pretty sure is our coworker, Justin. You're elsewhere now, aren't you? JUSTIN: Yes. DAVID: Yeah, awesome. Well, I mean, it's terrible for us [laughter]. We've got Will Archer. We've got Van…well, you go by Thomas, don't you? Wilcox and Matt Hardy. And this is going to be a good, good show. We always start with story time with Uncle Mike, and I'm not going to break that trend. It's great because Mike did not say in the pre-call that he had a story ready. I'm just putting him on the spot. MIKE: Well, I've been grappling with how to think about or how to express the changes that have happened in AI over the last few months. And if you put, you know, like, hundreds of billions of dollars into something, it's going to tend to move, and that's happened. DAVID: Something will happen. MIKE: There have been amazing, amazing level of money, like, shocking levels of investment in AI. And I'm sure not all of it will pan out, and we'll probably touch on that a little bit, but some things already have. And there are new ways of doing things that didn't exist, like, a year ago, in, you know, any meaningful commercial format. And one of this is this agentic approach to AI. And I've been trying to think about how to express this. If you're like me, you've been to a hotel. And if you have kids and you go to put a bed on the…sorry, some covers on the fold-out bed out of the couch, and you're like, oh, wait, there is no blanket here. I'm not going to have my kids sleep on the springs. And so, you know, you call into the desk and say, "Hey, can we please have a blanket?" Or you walk down there and ask for a blanket. And they'll bring it to you, right? And they'll bring it to you. It's part of the service, and it's covered. But it's very much, I am going to ask you to do this, and you will do it for me. And that's how AI tools have been up until fairly recently. But there's been a change. Now they've got these agents, and so it's more like you call in and say, "I'm cold." And they say, "Okay," and a few minutes…well, maybe actually more like an hour later. It takes longer [laughs] [inaudible 02:43]. You know, they show up with, like, an electric blanket and a comforter. And they go over, and they raise the temperature in your room, and, like, “Oh, this is how you use the thermostat,” because it is...
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