Start with a defined trigger
An author marks a code change ready for review.
Pull request-to-review brief
This is a proposed workflow pattern. We confirm data access, permissions, integration options and review ownership with your team before implementation.
Do not claim tests passed unless execution evidence exists. AI review preparation does not constitute approval to merge.
An author marks a code change ready for review.
Collect the diff, approved task, relevant repository guidance and actual validation results.
Draft the change summary, identify potentially affected areas and list unanswered review questions.
The author verifies every claim and reviewers independently assess correctness and suitability.
Save the accepted description and reviewer checklist with the pull request.
Measure unsupported test claims, missing behavior changes, irrelevant commentary and reviewer preparation time.
Keep the input, relevant context, review decision and final result connected. When a reviewer corrects something, use that evidence to improve the instructions or integration, then validate the change against representative cases.
The workflow stays centered on your business. The engagement determines who learns, implements and operates it.
Start with AI workflow training and the Factory Line source package. Workshop support is available when you need feedback.
Explore the $2,500 package ↗Get everything in DIY, three months of workshops, weekly team sessions and direct implementation coaching.
Explore guided implementation ↗Include all the learning and guidance, with ownership of agreed operations and major implementation decisions.
Explore managed delivery ↗Prepare a scoped implementation plan from the repository's actual structure, conventions and test boundaries.
Explore this solution ↗Bring a process, a bottleneck, or an idea. We'll help you decide what to automate, what to keep under human review, and where to begin.