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Orchestrations are pre-built workflow patterns often with specially-built executors that allow developers to quickly create complex workflows by simply plugging in their own AI agents.
Why Multi-Agent?
Traditional single-agent systems are limited in their ability to handle complex, multi-faceted tasks. By orchestrating multiple agents, each with specialized skills or roles, you can create systems that are more robust, adaptive, and capable of solving real-world problems collaboratively.
Supported Orchestrations
| Pattern | Description | Typical Use Case |
|---|---|---|
| Concurrent | A task is broadcast to all agents and processed concurrently. | Parallel analysis, independent subtasks, ensemble decision making. |
| Sequential | Passes the result from one agent to the next in a defined order. | Step-by-step workflows, pipelines, multi-stage processing. |
| Group Chat | Assembles agents in a star topology with a manager controlling the flow of conversation. | Iterative refinement, collaborative problem-solving, content review. |
| Magentic | A variant of group chat with a planner-based manager. Inspired by MagenticOne. | Complex, generalist multi-agent collaboration. |
| Handoff | Assembles agents in a mesh topology where agents can dynamically pass control based on context without a central manager. | Dynamic workflows, escalation, fallback, or expert handoff scenarios. |
Next Steps
Explore the individual orchestration patterns to understand their unique features and how to use them effectively in your applications.