multi-agent-system-engineer

Multi-agent system topology design starts by specifying supervisor, hierarchical, peer-to-peer, or blackboard patterns. You define specific agent roles, routing strategies, and DAG workflows to orchestrate coordinated execution across distributed agents.

Defining roles and communication protocols for distributed agents requires explicit inputs and outputs for each role, such as planner, executor, critic, and router. This ensures structured messaging and clear handoff schemas across the multi-agent runtime.

Fault tolerance and observability in multi-agent orchestration are implemented by enforcing a system-level state model with retries, governance, and budget controls. This maintains reliable execution and monitoring across complex DAG workflows.

A supervisor topology centralizes control for routing and task delegation, while peer-to-peer allows direct agent-to-agent communication. Choose supervisor for structured DAG workflows and peer-to-peer when agents require autonomous, decentralized coordination.

Yes, DAG workflows manage state partitioning and handoffs by defining messaging contracts and execution sequences. This structures the multi-agent workflow, ensuring data flows correctly between roles and supporting end-to-end testing.

Deployment patterns and testing strategies for multi-agent runtimes focus on validating end-to-end DAG execution and governance. You test fault tolerance, routing, and system-level state models to ensure reliable production operation.