parallel-agents

Multi-agent orchestration coordinates specialized agents in parallel or sequential chains to analyze codebases, passing context between them and synthesizing findings into a unified report.

Multi-agent orchestration is the process of managing multiple specialized AI agents to execute tasks in parallel or sequentially, enabling comprehensive analysis and multi-domain problem-solving.

Yes, you can orchestrate specialized agents like a security auditor and performance optimizer to run in parallel, analyzing different aspects of the codebase before synthesizing their findings.

Context passing enables agents in a sequential chain to share findings and build upon each other's work, ensuring downstream agents have the necessary information from previous steps.

Use an orchestrator agent to synthesize findings from multiple specialized agents by managing their parallel or sequential execution and consolidating their context into a single unified report.

You need multi-agent orchestration for feature development when a task requires diverse expertise and perspectives that exceed a single agent's capabilities, such as comprehensive security audits or multi-domain analysis.