orchestrate

Automate parallel task execution by decomposing complex multi-file features into independent tasks using DAG-based scheduling and coordinated agents. This approach manages concurrent workflows and ensures verifiable task completion across isolated environments.

DAG-based scheduling organizes decomposed code generation tasks in a Directed Acyclic Graph to establish an efficient, logical execution flow. It coordinates multiple agents to execute independent parallel tasks while maintaining robust error handling and dependency order.

Git worktrees prevent conflicts during parallel workflow automation by creating isolated working directories for each concurrent task. This ensures developers can execute multi-agent code generation independently and integrate multi-file features cleanly without overwriting changes.

Yes, you can use multi-agent orchestration to implement user authentication across multiple files. It decomposes large requests like JWT token and refresh flow integration into independent parallel tasks executed and tested concurrently across backend and frontend components.

Workflow automation with coordinated agents handles error recovery by applying robust error handling mechanisms during parallel task execution. It verifies task completion within isolated git worktrees to ensure complex multi-file features are integrated safely.

DAG-based scheduling for parallel code generation is limited to tasks that can be decomposed into independent, non-circular dependencies. It is not suitable for tightly coupled multi-file features requiring strict sequential execution or shared mutable state across agents.