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📘 Agentic AI Delivery Playbook

The playbook I'd hand a CEO on day one of agentic AI adoption.

Built for: Head of AI · VP Engineering · Director of Delivery

Why this exists

Most "agentic AI adoption" advice is either consultancy fluff or model-pricing comparisons. Neither helps a delivery organization actually ship.

This playbook is the 30/60/90, the operating model, the KPI tree, and the platform decision matrix — in the shape a delivery lead would actually use them. It's deliberately short. Every section answers a question a real executive will ask in the first month of an agentic AI initiative.

The frame is non-negotiable: workflow before model, evidence by default, human control at risk boundaries, platform consistency, measured scale. Every page in this site flows from those five principles.

What's inside

  • ✅ The Playbook — executive summary, delivery principles, and the adoption pattern.
  • ✅ Operating Model — team topology, delivery flow, and platform decision matrix.
  • ✅ 30/60/90 Rollout — phased plan with go/no-go gates per stage.
  • ✅ KPI Framework — measurable success framework that distinguishes capability KPIs from impact KPIs.

How to read this

  • If you have 3 minutes: read The Playbook — that's the elevator pitch.
  • If you're evaluating a candidate for AI delivery leadership: read Operating Model → 30/60/90. That's where judgment shows.
  • If you're asking "is this measurable?": KPI Framework is the answer.

What this proves

For Head of AI roles: I think in operating models, not org charts. Adoption is a delivery problem, not a tooling problem.

For VP Engineering: I distinguish capability KPIs from impact KPIs. Most candidates conflate the two and end up reporting model accuracy as if it were business value.

For Director of Delivery: I write playbooks engineers can actually execute — short, scoped, with explicit governance cadences.

Isaac Maya — QA · Agentic AI · Data Quality 📧 theisaacmaya@icloud.com · 💼 LinkedIn · 🔗 Source · 📝 Essays