How do multi-agent systems work?
Multi-agent systems split a complex job among several specialized AI agents, such as a triage agent, a billing agent and a technical agent, coordinated by an orchestrator or a shared protocol. Agents pass tasks and results to each other, ideally share the same memory of the customer or case, and each operates within its own permissions and guardrails.
Common patterns
When to use multiple agents
When tasks need different tools, permissions or expertise, or when one agent’s instructions become too long to manage. Otherwise a single agent is simpler.
Risks
Lost context between agents, loops, and unclear accountability. Shared memory and end-to-end tracing reduce these.
