Thinking out loud

Only 7% of companies scale AI enterprise-wide. The reason isn't the model — it's the workforce change management pillar most frameworks skip entirely.

AI adoption is shifting from 'how much can we use' to 'where does it create value.' Here's why the winners are getting selective about cost and impact.

Two experiments in vibe coding — one simple, one complex. Here's what broke, what I had to fix myself, and what it means for developers and teams working alongside AI.

How building a closet from scratch — with an ROI decision, AI-assisted planning, mid-build pivots, and a stakeholder pilot — turned out to be pure PM thinking.

Most AI content teaches you the tool. These four skills teach you how to protect your thinking — and why that matters more than any prompt technique.

I replaced WordPress with GitHub Pages and a pipeline of AI agents. Each handles one stage. I review, approve, and commit manually. Here's the workflow.

Five layers of AI tooling, from vibe coding to autonomous agents. How I decide which one to use — and how much of the work to hand off.

Not for a brand. Writing is how I find out what I actually know — and how I want to be remembered.

20 years in enterprise software taught me what I actually look for in a developer. It's not the degree — and in the agent era, it's not even just the code.

Meeting notes, backlog discovery, product specs — three workflows that compress the distance between raw signal and something I can actually ship.

Not every task needs the same level of AI involvement. Here's the mental model I use to decide when to delegate, collaborate, or stay manual.