Reviewing a PR delivered by an AI agent is the wrong time to ask questions. What was it meant to change? Where did its context come from? How was it implemented?

We will show an AI-SDLC used to bootstrap greenfield applications and work safely in established systems. It starts before an agent touches code. A person defines the change, its acceptance criteria, and the evidence a reviewer will need. Commands and skills carry it through refinement, proposal, implementation, validation, and review.

We will run a feature and then an urgent hotfix. You will see the Definition of Ready, the proposed specification and task plan, CI, tests, screenshots, PR evidence, merge, and the review that improves the next change. Only two steps wait for a person: approving the plan and reviewing the diff with its checks.

AI makes code cheap enough to expose gaps teams once absorbed as hand-offs, ambiguity, and rework. Engineering becomes the work of turning a business decision into safe, verified behaviour in production.