RuntimeAgent systems topic

Multi-agent systems

Multi-agent systems divide work among specialized or isolated agents and synthesize their outputs. They are valuable when work partitions cleanly or trust boundaries differ, but they add coordination, context transfer, conflict resolution, and observability costs.

Apply the lifecycleReview sources

Questions to answer

Resolve these before adding tools, frameworks, or automation.

  • Can the work be partitioned without constant shared-state coordination?
  • What context, tools, and permissions does each agent receive?
  • Who resolves conflicts and verifies the combined result?

Implementation lifecycle

Build the evidence in this order

  1. 01

    Partition

    Split work around independent outputs, expertise, or trust boundaries.

  2. 02

    Delegate

    Provide scoped context, tools, budget, and an explicit return contract.

  3. 03

    Synthesize

    Resolve overlap and contradictions before verifying the whole outcome.

Artifacts to maintain

  • agent roster
  • delegation contract
  • handoff schema
  • synthesis checklist

Continue through AgentAtlas

Evidence ledger

Primary documentation behind this guide

OpenAI

Codex subagents

Subagent configuration, scoped roles, delegation behavior, and parallel work inside Codex.

Anthropic

Create custom subagents

Specialized subagent configuration, context isolation, tools, permissions, and delegation patterns.

Next topic

Agent interoperability