From the task you request to the result you check, in one place.

Organize project work as issues and attach the context it needs. Follow AI runs, code changes, and evidence, then have a person decide whether to request a fix or approve. The settlement-system change below is one example of this workflow.

Write down the task and what counts as done.

The project owner records the request and the conditions to check, which sets the scope the AI works within.
See what was executed on one screen.

Compare before and after with test results and supporting evidence. The reviewer checks the required items before approval.
Ask for what is missing; approve once it is checked.

Request changes and run the task again when checks are incomplete. The reviewer records an approval after checking the result. Deployment is a separate decision.

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