AADP-Ops

Move AI-assisted work from ad-hoc prompting toward governed execution with explicit tasks, evidence, verification and human authority.

The problem

AI agents can accelerate work, but speed without control can introduce drift, unsupported claims, incomplete verification and unclear responsibility. AADP-Ops explores how disciplined controls can be embedded in day-to-day AI-assisted execution.

What it brings together

Task discipline

Define scope, acceptance criteria, dependencies and stopping conditions before execution.

Evidence

Connect claims and completion states to observable artefacts, checks and repository history.

Verification

Separate implementation from independent checks where useful and make failures visible.

Human authority

Keep consequential approvals, policy decisions and owner gates under explicit human control.

AADP and AADP-Ops

AADP provides governance principles and discipline for agentic-AI execution. AADP-Ops explores the operational application of those ideas in real development and workflow environments.

Current status

In active development. The approach is being exercised and refined through governed AI-assisted project workflows.