Run your programs on intelligence, not overtime

If you've ever stayed late reformatting a status report that should have taken twenty minutes, or caught a schedule slip only after someone else flagged it in a steering committee, you already know the problem this school exists to solve. You're a capable, experienced PM — and you're spending too much of your time on work that shouldn't require your judgment at all.

I built PM Intelligence for the version of me that was drowning in reporting cycles. Not because the work was hard, but because it was relentless. Status reports, risk registers, executive briefings, meeting summaries — each one manual, each one urgent, and each one pulling time away from the actual program leadership that moves the needle. When AI tools started becoming genuinely useful for this kind of work, I didn't want a course that explained the technology. I wanted a system I could run on Tuesday morning with real data.

That's what this school is. Every module is built around realistic project scenarios — the kind with slipping milestones, vague stakeholder notes, and executives who want clarity in two paragraphs or less. You'll learn how to prompt for PM-specific outputs that are actually useful, how to pressure-test an AI-generated schedule before you sign your name to it, how to turn a raw transcript into a structured action item list, and how to maintain a risk register that stays alive between reporting cycles rather than gathering dust in a SharePoint folder.

I'm also going to be straight with you about where AI gets this work wrong — because it does, and the consequences in our profession are real. The responsible-AI module isn't a compliance checkbox. It's the most important thing in the curriculum, because no credential helps you if an AI error makes it into a board update. You'll leave with a pre-escalation review checklist you can use every single time.

The capstone is where it all comes together: a complete program package — schedule, status brief, risk register — built from real sample data, ready to reuse and ready to show. That's the credential. That's the proof of work.

If you're ready to stop managing the paperwork and start managing the program, this is where we begin.