3 posts tagged with "AI"

In our previous post we walked through deploying an AI-generated Educates workshop on a local Kubernetes cluster. The workshop was up and running, accessible through the training portal, and ready to be used. But having a workshop that runs is only the first step. The next question is whether it's actually any good.

Workshop review is traditionally a manual process. You open the workshop in a browser, click through each page, read the instructions, run the commands, check that everything works, and make notes on what could be improved. It's time-consuming and somewhat tedious, especially when you're the person who wrote the workshop in the first place and already know what it's supposed to do. Even this task, though, is one where AI can help.

The way we direct AI coding agents has changed significantly over the past couple of years. Early on, the interaction was purely conversational. You'd open a chat, explain what you wanted, provide whatever context seemed relevant, and hope the model could work with it. If it got something wrong or went down the wrong path, you'd correct it and try again. It worked, but it was ad hoc. Every session started from scratch. Every conversation required re-establishing context.

What's happened since then is a steady progression toward giving agents more structured, persistent knowledge to work with. Each step in that progression has made agents meaningfully more capable, to the point where they can now handle tasks that would have been unrealistic even a year ago. We've been putting these capabilities to work on a specific challenge: getting an AI to author interactive workshops for the Educates training platform. In our previous posts we talked about why workshop content is actually a good fit for AI generation. Here we want to explain how we've been making that work in practice.

In a post on my personal site I talked about the forces reshaping developer advocacy. One theme that kept coming up was content saturation. AI has made it trivially easy to produce content, and the result is a flood of generic, shallow material that exists to fill space rather than help anyone. People have started calling this "AI slop," and the term captures something real. Recycled tutorials, SEO-bait blog posts, content that says nothing you couldn't get by asking a chatbot directly. There's a lot of it, and it's getting worse.

The backlash against AI slop is entirely justified. But I've been wondering whether it has started to go too far.