Field Manual

Field Guide

A compact framework for making AI systems auditable, governable, and provable.

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AI Identity Control Plane Field Guide

Everything you need to understand and implement the control plane. Includes the architecture map, DiFilippo's Law, reference requirements, a governance checklist, and three metrics that prove maturity.

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Who It's For
  • AI platform owners and architects
  • Security and GRC leaders
  • Identity and IAM architects
  • Engineering teams shipping agents and tool-calling
  • Anyone responsible for AI governance
Contents Preview
PDF · 3 pages
Page 1: What Just Broke
The identity gap in AI systems
Page 2: DiFilippo's Law + Requirements
The law statement and control plane requirements
Page 3: Outcomes + Metrics
What success looks like and how to measure it
What You'll Learn

The Problem

Why current identity infrastructure doesn't work for AI agents, and what breaks when you try to use it anyway.

The Architecture

The three-layer model: execution, identity control plane, and provenance. How they connect and why each layer matters.

The Implementation

Concrete requirements for identity binding, token governance, policy enforcement, audit events, and provenance stamps.

Quick Start

Step 1: Download the Field Guide and read DiFilippo's Law.
Step 2: Review the control plane map against your current architecture.
Step 3: Run the agent receipt demo to see the concepts in action.
Step 4: Use the governance checklist to identify gaps.

Next Steps

After reading the guide, explore the demos to see working implementations. Use the map as a reference when designing your own control plane. Share the law with your team as a conversation starter.