orchestration-workflow

To coordinate multiple AI agents for complex task delegation, you can use an orchestration workflow that analyzes tasks, selects execution strategies, builds agent teams, and coordinates execution with validation and error handling.

Multi-agent orchestration is the process of managing a swarm of AI agents to autonomously complete complex tasks. You need it when a single prompt must be decomposed into manageable subtasks with dependencies for specialized agents.

AI agents share context during multi-agent execution via a ContextBroker, which facilitates inter-agent communication. This ensures that specialized agents can pass necessary data and intermediate results to each other.

Yes, you can use a single-pass strategy for simpler tasks within multi-agent workflows. The orchestration system automatically employs either single-pass or multi-pass strategies based on the analyzed complexity of the task.

The best way to break down a complex prompt into subtasks is using an orchestration workflow that analyzes the prompt, identifies dependencies, and assigns sub-tasks like market research or content creation to specialized agents.

Yes, multi-agent orchestration handles errors during task execution. The system coordinates execution with built-in validation and error handling to manage the workflow and agent interactions autonomously.