A stack, not a checklist. Pull the bottom card out and the clever architecture above it does not hold weight.
Drawn from AI That Pays for Itself, the book's operator-first method for making AI produce measurable value.
Lean, Six Sigma, ITIL, Agile — enough operational discipline to know where the waste is.
Assess → Illuminate → Accelerate → Sustain.
Quarterly re-validation so agents do not quietly drift into liabilities.
It goes into Kit so follow-up can match what you actually asked for, not some generic newsletter fog.
Use this before a vendor meeting, before a pilot, or before asking a board for budget. The point is to force the operational questions first: what moves, who owns it, what it costs, when we stop, and how we keep watching after launch.
The operating stack only works after the real work is visible. The Operations Overview maps people, process, data, systems, risk, metrics, and ownership before any tool decision gets oxygen.
Identify the workflows, handoffs, approvals, data gaps, and control points that decide whether AI can produce measurable value.
Score AI opportunities by ROI, readiness, risk, implementation difficulty, and executive ownership. Useful beats interesting.
Turn the surviving work into owners, baseline metrics, governance notes, and a 90-day execution rhythm.