Multi-Agent Orchestration

You coordinate multiple AI agents for task automation by decomposing complex problems into subtasks, delegating them to specialized agents, and synthesizing the results. This orchestration supports horizontal, vertical, and hierarchical decomposition patterns.

The best way to decompose large problems for AI agents is to break them down into smaller, manageable subtasks assigned to specialist agents with clear instructions. The orchestrator then combines the results into a coherent final output.

Automate multi-stage software development workflows by delegating specialized stages like research, API design, code implementation, and code review to individual AI agents managed by a central orchestrator agent.

Yes, multi-agent orchestration supports coordinated execution within IDEs like VS Code. It addresses scenarios requiring specialized agent roles to execute sophisticated workflows directly inside the development environment.

Use hierarchical task decomposition for AI agents when complex workflows require structured delegation and specialized roles. This pattern allows a central orchestrator to manage subtasks and synthesize results effectively.

Outputs from multiple specialized AI agents are synthesized by combining their individual subtask results into a coherent final output. The orchestrator applies synthesis strategies to resolve differences and merge the workloads.