Stage 5: Multi-Agent Coordination

Many agents under shared governance—within one institution or across many.

Task

Execute hundreds or thousands of agents simultaneously with shared budgets, quotas, and policies. Enable agents owned by different institutions to cooperate under shared protocols.

Why This Matters

Large-scale discovery requires specialized agents working together. Coordination prevents conflicts, ensures fair resource allocation, and enables cross-institutional collaboration—a core DOE differentiator.

Details

Aspect	Value
CAF Components	Shared state, policy engine, budget ledger
Where it runs	Distributed (single institution or federated)
Scale	O(10²–10³) concurrent agents
Status	Emerging

Architecture

Multi-agent coordination: Shared State, Policy, and Budget controlling multiple agents

Code

Example	Description
AgentsCoordination	Shared budget, state, and policy across agents
AgentsLangGraph	5-agent pipeline with LangGraph orchestration
AgentsAcademy	5-agent pipeline with Academy messaging

Prerequisites

Before diving into multi-agent coordination:

AgentsLangGraph — Multi-agent pipelines with LangGraph
AgentsAcademy — Agent-to-agent messaging with Academy
Governed Tool Use — Policy enforcement patterns

Next Steps

After mastering coordination:

Long-Lived Agents — Agents that persist across sessions
Agent Workflows — Dynamic workflow construction

Federated Agents — Coordination across institutions
Scale Inference — Parallel agent execution at scale