subagent-driven-development

Automating multi-task implementation plans without context pollution is achieved by delegating each independent task to a fresh, isolated subagent, ensuring no inherited session history interferes with the current execution. This approach eliminates manual context switching and maintains consistent execution quality across all tasks.

Running automated code reviews after each task is handled by built-in review gates that check spec compliance and code quality immediately after subagent execution. The system automatically generates fix loops for any identified issues before moving to the next task, ensuring quality control throughout the development workflow.

Progress tracking for multi-task development workflows uses durable tracking mechanisms that persist across context compactions, ensuring no task state is lost during long execution runs. It automatically parses the implementation plan, updates task completion status, and manages brief generation without manual intervention.

Using isolated subagents to execute a 12-task feature plan without manual coordination is the primary use case for this approach. It manages plan parsing, dispatches fresh subagents sequentially, runs per-task review gates, and delivers a final merged, reviewed branch automatically.

Subagent delegation supports model selection optimization to balance cost and performance for different task types within the implementation plan. This allows you to assign appropriate models based on task complexity, reducing overall execution costs while maintaining the required code quality and spec compliance.

Manually executing multiple development tasks causes inconsistent quality and slow iteration because developers juggle multiple workstreams while inheriting unrelated session history, leading to context pollution. Automating task delegation and isolated execution eliminates these inefficiencies by enforcing structured, focused reviews after every task.