build-full-stack

Multi-repo feature delivery is coordinated by orchestrating specialized AI workers that decompose tasks, implement changes, and group coherent pull requests across repositories. The workflow respects dependency sequencing and enforces CI testing before opening review-ready PRs.

Automating multi-repo pull requests requires an orchestration workflow that enforces CI testing before PR creation and groups changes into coherent, review-ready PRs. It spawns specialized AI workers to implement features while respecting strict dependency order like backend before frontend.

AI workers can be spawned to decompose and implement tasks for multi-repo features by delegating work to specialized domains such as frontend, backend, specialist, and ops. This eliminates manual coordination and ensures consistent PRs across all affected repositories.

A feature spec is accepted as input to guide the end-to-end feature delivery workflow, though tracking issues can also be provided. The orchestrator uses these inputs to guide domain-specific AI workers through implementation, testing, and PR creation cycles.

Dependency sequencing for multi-repo PR lifecycle management enforces strict ordering, such as backend before frontend or specialized domains before integration. The orchestrator iterates in cycles, ensuring CI passes and grouping changes into coherent PRs only after dependencies are satisfied.

AI workers for multi-repo feature orchestration are not suited for single-repo changes or features without clear dependency sequencing requirements. If your workflow lacks strict CI/PR lifecycle needs or does not require cross-repository coordination, manual implementation is more appropriate.