subagent-driven-development

To prevent context bleed when dispatching multi-step plans, assign a fresh subagent per task. This approach isolates contexts entirely from the main session, ensuring deterministic task execution and preventing unwanted state carryover.

The best way to automate code review for subagent tasks is to apply a two-stage review loop. This system evaluates spec compliance first, then checks code quality, ensuring structured workflow outcomes and high-quality code generation.

To structure task prompts for deterministic AI agent workflows, provide per-task prompts to a fresh implementer subagent. This isolates execution contexts and accelerates iteration by maintaining clear, structured workflows for each dispatched task.

Dispatching isolated subagents for TDD does not slow down iteration speed; it accelerates iteration. By using a fresh subagent per task, contexts remain isolated, preventing main session bleed and enabling faster, more reliable task work.

A two-stage review process is used for AI agent code generation to separate spec compliance from code quality. This staged review ensures the implementation subagent meets both the exact plan specifications and high coding standards.

Yes, you can execute complex plans using subagents without losing main session state. Dispatching a fresh subagent per task keeps contexts isolated, preventing context bleed and maintaining the integrity of the primary workflow.