Writing

The four conditions that have to be true before you trust an agent with anything that counts.

What the tutorials don't show you — including the part where the AI confidently led me in circles, and why that's actually the most important lesson.

The build-in-public post I wish existed — including the ratio nobody talks about, and what it means differently depending on your role.

Most people treat AI like a search engine. Managers assign. That mental shift changes everything about your outputs.

For leaders who believe their organizations are ready for AI — and haven't asked what they're actually ready for.

For leaders who think AI is making their teams smarter — and haven't noticed what it might also be making them.

A practical guide for leaders who think they're doing AI transformation — but haven't made the leap yet.

A practical checklist for leaders who need AI work to be defensible, auditable, and compliance-ready.

Your AI isn't broken. Your process is. Seven diagnostic signs — with specific fixes for each.

You wouldn't give a colleague a one-line instruction for a complex deliverable. AI deserves the same discipline.

AI won't replace you. But someone using AI effectively will. Here's how to stay on the right side of that gap.

The bottleneck isn't clever prompting. It's structured context — and the teams that understand this are operating at a different level entirely.

AI doesn't clarify ambiguity — it multiplies it. How to define problems clearly enough that AI can actually help.

You can't prompt your way out of a context problem. What to fix instead.

The organizations achieving real ROI on AI share one discipline: they never start with the technology.

The quality of your AI-assisted work doesn't matter if stakeholders don't trust how you produced it. Five language patterns that change that.

When AI makes a consequential decision and no one is accountable, the entire organization pays the price.