TAG

# hands-on

2026-07-16

I handed AI about half of my PM job, and there are a few things I still don't dare hand over

This year I handed AI roughly half of my day-to-day PM work — first drafts of documents, digging up competitor research, sorting hundreds of pieces of user feedback, turning meetings into action items, building clickable prototypes. It's fast and it never complains. But a few other things I haven't dared hand over, and I don't plan to. Not because AI can't do them — the opposite, some it does more smoothly than I do. It's because once you hand those off and they go wrong, you can't catch it, and by the time you do it's already too late. This piece lays out my 'hand over vs. keep' line, one item at a time, including the pits I nearly fell into after handing things off.

2026-07-15

AI-Era PM Interviews: How to Answer the 5 Questions They Love Most

I've interviewed a lot of product managers these past two years, and been interviewed myself. One pattern jumps out: the moment an AI question comes up, eight out of ten people start reciting concepts — what RAG is, the difference between fine-tuning and prompting, how Transformers work. The smoother the recital, the more certain I am I won't hire them. Because these questions aren't testing what you memorized; they're testing whether you can think. This post breaks down the 5 AI PM interview questions asked most in 2026: what the interviewer is really weighing behind each one, how I'd answer, and the answer most likely to sink you. Not a bank of templates to memorize — a way of seeing which part of you each question is measuring.

2026-07-14

A Day as an AI-Era PM: How I Turned One Sentence Into a Prototype You Can Actually Tap

One afternoon last week, I turned 'I want a little thing that tracks what I spend' into a prototype my coworker could actually tap on his phone — record a real expense, see a real pie chart. Not a single line of code. Everyone thinks the AI era means PMs have to go learn programming. It's actually the reverse: the skill that's worth money now is getting your words clear enough that AI gets it right on the first try. This isn't a lecture — it's exactly how I did it: how to make AI interrogate me first, how to change only one thing at a time, why the very first version should run on real data, and how to use 'can you tap through it?' as your acceptance line. Includes the potholes I stepped in.