subagent-driven-development

You can isolate context in multi-step AI development plans by dispatching a fresh subagent for every task. This approach prevents context leakage and ensures each task receives focused execution.

A two-stage review workflow enforces spec compliance review first, followed by code quality review, ensuring AI-generated code meets both functional specifications and structural standards.

You manage task status transitions using defined states like DONE, DONE_WITH_CONCERNS, NEEDS_CONTEXT, and BLOCKED, which guide collaboration, track progress, and handle escalation for dispatched subagents.

Yes, you can run parallel execution for independent tasks within multi-task plans. Dispatching isolated subagents per task supports parallel execution while maintaining strict context separation.

Inconsistent results often occur when a single agent handles all tasks due to context leakage. Dispatching a fresh subagent for each task isolates context and improves focus, resolving inconsistencies.

You should avoid dispatching fresh subagents per task when tasks are highly interdependent and require shared context, as this approach is designed for largely independent tasks needing isolated execution.