team-implement

Parallel implementation with AI agents works by decomposing an approved plan into independent tasks and executing them concurrently in waves. This approach manages task dependencies automatically and significantly speeds up the development cycle.

Wave execution manages code generation task dependencies by grouping independent tasks into concurrent waves. It waits for preceding waves to finish before starting dependent tasks, ensuring context is gathered and agent prompting is handled correctly.

Yes, automated build and test verification is integrated as a final execution wave. After parallel code generation tasks finish, the system automatically runs build and test checks to verify the implementation before final reporting.

Yes, you need a detailed implementation plan located in a markdown file before starting. The tool reads this approved plan to decompose it into manageable tasks, assign them to an agent team, and orchestrate their execution.

Orchestrating an agent team for feature implementation is best handled by automatically breaking down plans into parallelizable tasks. This method handles context gathering, agent prompting, and wave execution monitoring to streamline development.

Parallel execution waves are used instead of sequential implementation to allow multiple agents to work on different code parts simultaneously. This dramatically reduces development time while still managing dependencies and verifying builds.