orchestrate

Multi-agent workflows are coordinated by deploying specialist agents with clear role definitions and robust prompts to align inputs, outputs, and decisions across complex tasks. This prevents misrouting and uncontrolled agent behavior.

Multi-agent orchestration is the coordination of inputs, outputs, and decisions across multiple specialist agents. It is needed for multi-domain projects like research planning, coding, and documentation where diverse perspectives require governance and synthesis.

To synthesize findings from multiple AI agents, the orchestrator aligns inputs and outputs from diverse perspectives across domains, producing a unified briefing that consolidates the analysis from each specialist agent involved in the workflow.

Multi-agent orchestration supports cross-functional problem solving and research planning by deploying agents for review, analysis, writing, and data tasks, ensuring complex multi-step workflows are managed with proper governance and clear role definitions.

To prevent data leakage and misrouting when managing multiple expert agents, the orchestration process enforces robust prompts, clear role definitions, and strict governance over the multi-agent workflow to control agent behavior.

The best way to start a multi-step analysis is to provide the orchestrator with a task description such as planning a multi-step analysis of a specific topic, which triggers agent deployment and initiates the unified briefing process.