Multi-Agent System

What is a multi-agent system?

One AI is capable, but on complex work, a single agent often drops the ball. A multi-agent system assembles several agents into a team: one digs up research, one drafts, one pokes holes, and someone ties it all together.
They collaborate like coworkers instead of one model grinding through everything alone.

How is it different from "one very strong AI"?

Division beats solo work
No matter how strong a single model is, it fumbles on long pipelines. Split the job across focused agents and each step gets attention — fewer mistakes.
They can review each other
One agent produces, another critiques. Separating the writer from the reviewer is an extra layer of quality control.
It mirrors real workflows
Real projects aren't done by one person. Multi-agent systems bring "teamwork" into the AI world.

Where it shows up

A deep report: one agent researches, one outlines, one writes, one proofreads. Or software: one writes code, one writes tests, one does the code review.

Bottom line: a multi-agent system is a group of AIs playing as a team. Complex work is more reliable in the hands of "a team" than "one person".