Agentic AI Discipline Protocol (AADP)

A governance framework for keeping agentic-AI work structured, auditable and anchored to explicit human decisions.

Why discipline matters

Agentic systems can act across many steps and tools. Without clear constraints, evidence and decision boundaries, automation can drift away from the owner's intent. AADP addresses that governance problem.

Core themes

Explicit decisions

Important requirements and owner choices are made visible rather than left to inference.

Invariants

Critical rules remain stable across tasks, agents and implementation cycles.

Auditability

Evidence and verification make it possible to examine what was done and why.

Anti-drift controls

Defined boundaries help prevent automated work from silently changing scope or policy.

Current status

Published framework. AADP is part of LAKSAHA's work on practical governance for AI-assisted systems and operations.