A multi-agent system uses several specialized agents that work together instead of forcing one agent to do everything. One may plan, another may research, and another may review. This approach matters when tasks are too large, too varied, or too complex for one agent design.

A multi-agent system is a setup where multiple agents work together on a shared goal. Instead of building one giant agent that must plan, execute, review, remember, and communicate perfectly, you split responsibilities across specialists. For example, one agent may gather information, another may evaluate quality, and another may prepare the final response. This can improve modularity and make the system easier to extend. It can also mirror how human teams work: divide work, coordinate, review, and combine results. But multi-agent systems are not automatically better. They add communication overhead, coordination complexity, and more chances for failure. The best use cases are tasks where specialization actually helps. For product builders, the lesson is to use multiple agents when clear role separation improves reliability or quality, not just because it sounds advanced.

One Agent Is Helpful, Many Can Collaborate