Why Technical PMs Should Get Hands-On With AI Tools

A lot of project managers use AI tools the same way they use any other dashboard: as a black box that spits out a status report or a summary. That is fine as far as it goes, but it leaves a lot of value on the table.

Having a development background changes how I approach this. When I look at an AI-enabled reporting tool, I'm not just consuming its output. I'm asking how it's pulling data, where it could break, and what it would take to extend it. That's the same instinct I bring to any system integration problem.

I've spent the last year building on this deliberately: coursework in agentic AI tooling, cloud deployment fundamentals, and hands-on practice with the same kind of systems I used to build as a developer. The goal isn't to become an AI engineer. It's to be the PM in the room who can tell the difference between a tool that's genuinely useful and one that's just automation theater.

More on this as I keep learning.