ai-collaboration-workflow

To manage AI coding workflow scope, you must define allowed and prohibited modifications upfront. This approach locks the scope, requires executable plans before step-wise delivery, and prevents rework from uncontrolled edits.

The best way to structure handoff documentation for AI agent code review is to include clear manifests, patch notes, output file locations, and main changes. This ensures the delivery is verifiable and traceable.

Serial skill generation works by supporting one-Skill-at-a-time generation to satisfy independence and scope constraints. It applies phase identification to ensure historical rules do not block current modifications.

Yes, you can use this collaboration workflow for Sprint iteration planning with AI. It applies to requirement analysis, serial Skill refactoring, and planning to ensure the process remains controllable and auditable.

AI applies incorrect phase constraints when it misidentifies the current phase and treats historical stage rules as active limitations. Identifying the phase based on current context prevents this boundary error.