agent-teams

Multi-agent orchestration coordinates multiple AI agents to work as a cohesive team. You need it when managing complex product, research, or operations workflows that require rapid, adaptive collaboration across diverse agent roles.

You coordinate multiple AI agents by defining a YAML-based schema that specifies parallel, pipeline, or DAG modes. This configuration maps varied tasks across agent roles, enabling scalable automation through declarative templates and dynamic role assignments.

Yes, you can use declarative templates to configure reusable multi-agent teams. These templates allow you to spin up cohesive teams quickly by defining dynamic role assignments and standardized workflows without starting from scratch each time.

Multi-agent orchestration supports real-time monitoring, cross-agent communication, and error handling. It includes human-intervention capabilities to manage failures and ensure robust coordination across diverse agent roles within your workflows.

The best way to set up a DAG coordination pattern is to define a YAML team configuration. This schema maps complex task dependencies across agents, enabling coordinated execution through declarative templates and dynamic role assignments.

YAML schemas for agent orchestration require defining robust configurations for modes, templates, monitoring, and error handling. Complex DAG workflows may need significant upfront schema design and human-intervention setup to ensure proper cross-agent communication.