How a multi-agent system is organised
- A supervisor receives the goal, breaks it into steps and assigns each one.
- Specialist agents each handle one kind of work — research, data lookup, drafting, checking.
- Results flow back to the supervisor, which reviews them and decides what happens next.
- Shared state records progress so long tasks can pause and resume.
Why split the work
A single agent with dozens of tools and a long list of instructions becomes harder to steer. Specialists with small, focused toolsets make fewer mistakes, can use different models suited to their job, and are easier to test one at a time.
Good fits
- Research and reporting that gathers information from several sources
- Document-heavy workflows with separate extract, check and draft stages
- Operations tasks that span several systems and approval steps
When not to use one
If one agent with a handful of tools does the job reliably, adding more agents adds cost, latency and new ways to fail. Start with a single agent, measure where it struggles, and split only the part that needs it.
What makes them dependable
- Clear responsibilities and inputs for each agent
- Step-level tracing so you can see which agent did what
- Limits on loops and retries to control cost
- Human checkpoints before anything irreversible