agent-team-driven-development

You can execute complex implementation plans by orchestrating a team of persistent specialist agents that work concurrently in waves, processing 4 or more independent tasks spanning multiple specialist domains to achieve high development throughput.

A two-stage code review in a parallel agent workflow means each completed task undergoes both a spec compliance review and a code quality review, ensuring correctness and maintainability before the next wave of development begins.

Yes, you can use pipelined TDD with parallel AI agents by assigning Quality Assurance agents to write tests for upcoming tasks in parallel with current implementation, creating a continuous delivery pipeline.

You should use wave-based parallel execution for software engineering tasks when your implementation plan contains at least 4 independent tasks spanning multiple specialist domains, allowing persistent implementers to maximize throughput without context loss.

Persistent specialist agents maintain domain knowledge by retaining their context across multiple tasks and execution waves, which reduces context loss and improves implementation efficiency throughout the project lifecycle.

Orchestrating parallel agents is limited by task independence; it is designed for plans with 4 or more independent tasks, meaning tightly coupled tasks lacking specialist domain separation are not suitable for this wave-based parallel execution approach.