AI Agents
What is Multi-agent system?
An architecture where several specialized agents coordinate — often a director delegating to workers — instead of one agent doing everything.
How it works
You split a hard problem into roles: a planner, researchers, a coder, a reviewer. The win is focus and parallelism; the cost is coordination overhead and more places to fail. Most tasks don't need it until a single agent's prompt gets unwieldy.
Example
In practiceA director agent breaks a goal into subtasks, dispatches them to worker agents, then integrates their outputs into a final result.
When do I need multiple agents?
When one agent's instructions and tools get too large to manage, or when subtasks can run in parallel. Before that, a single well-built agent is simpler and cheaper.
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