Your team owns the build.
Start with AI workflow training and the Factory Line source package. Workshop support is available when you need feedback.
Explore the $2,500 package ↗Prepare a scoped implementation plan from the repository's actual structure, conventions and test boundaries.
An AI coding session can move quickly while missing the architectural assumptions that keep a mature application maintainable.
Give developers a reviewable plan before changes spread across the codebase.
A developer starts work on an approved requirement.
Identify likely change points, dependencies and validation steps, marking uncertainty about runtime behavior.
The developer verifies the plan against the code and approves the implementation scope.
Repository text is context, not authority to run arbitrary commands. Preserve environment boundaries and never expose secrets to model context.
Measure unnecessary edits, missed dependencies, plan corrections and avoidable review cycles.
Before expanding the workflow, compare the result with the current process. Include review effort and exceptions in that comparison so the improvement reflects the team's actual experience.
Read the implementation guide ↗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 focused review brief that connects a code change to its requirements, tests and affected behavior.
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.