The AI Agent Control Playbook: A Practical Guide to Managing Autonomy, Access, Actions, and Risk

AI agents are moving from generating answers to taking action. The question is no longer only whether the output is correct. It is what the agent can access, invoke, change, communicate, spend, or commit, and how that authority is controlled.The AI Agent Control Playbook gives business and technology leaders a practical framework for managing AI agents as operational systems rather than treating them as prompts with tools attached.Inside, you will learn how to: - distinguish capability, autonomy, authority, and consequence;- classify actions using five Agent Action-Authority Levels;- assess impact using four Consequence Tiers;- define an enforceable Agent Control Envelope;- control identities, permissions, tools, data, and delegation;- protect instructions, context, memory, and trust boundaries;- design meaningful human approval and escalation;- test agents before they are allowed to act;- monitor actions, reconstruct incidents, and contain failures; and- build a practical 90-day agent-control roadmap. The playbook follows the fictional Northstar Customer Resolution Agent from initial scope through permissions, approvals, testing, monitoring, incident response, and change management, showing how the framework works across a complete agent lifecycle.The paperback also includes a 24-page Agent Control Quick-Start Toolkit that helps you apply the method immediately to one real or planned agent.This book is designed for AI product leaders, business executives, founders, consultants, IT and automation leaders, security and identity professionals, governance and risk teams, and organizations moving AI agents from experimentation into real workflows.Useful autonomy needs boundaries. This playbook shows you how to define them.