parallel-agents

Multi-agent orchestration coordinates multiple specialized AI agents to collaborate on a single objective. You can execute agents in parallel or sequential chains, passing context between them to leverage diverse domain expertise for comprehensive analysis.

Multi-agent orchestration is a workflow pattern that assigns complex tasks to specialized agents like a security-auditor or backend-specialist. It enables parallel processing and sequential execution with context passing to build comprehensive feature reviews.

Yes, you can assign feature review tasks to specialized agents. A backend-specialist analyzes server-side code, a frontend-specialist examines UI components, and a test-engineer devises test cases, all coordinated by an orchestrator agent.

Context passing enables agents to share findings and build upon each other's work during sequential execution. The orchestrator agent manages the flow, ensuring downstream agents receive the necessary context from prior steps.

Yes, multi-agent orchestration supports both parallel and sequential agent execution. You can run agents simultaneously for independent analysis or chain them sequentially to pass context and build upon previous findings.

Use parallel agents when a complex task requires diverse domain expertise or multiple perspectives. Orchestrating specialized agents like security-auditors and backend-specialists provides comprehensive analysis that a single agent cannot achieve.