Sub-Agent Delegation

Sub-agent delegation enables parallel execution by dispatching multiple AI agents simultaneously. You define self-contained prompts with deterministic task definitions, expected outputs, and success criteria to maximize workflow throughput and reliability.

Sub-agent delegation handles error handling and result validation through built-in guardrails against failures. It ensures correctness by validating sub-agent results against defined success criteria before integrating outputs into the parent workflow.

Yes, you can use sub-agent delegation for multi-step codebase analysis and build/test pipelines. It applies parallel dispatch patterns and recursive delegation to decompose large problems into manageable, concurrent tasks for faster processing.

The best way to prevent prompt injection when coordinating multiple AI agents is applying context management guardrails within the sub-agent delegation framework. This prevents data leakage and secures self-contained prompts during parallel dispatch.

Yes, you need deterministic task definitions for recursive delegation and task decomposition. Defining clear expected outputs and success criteria ensures that sub-agents execute decomposed large problems reliably and validate results correctly.