What is a multi agent system?
A multi agent system is a setup where several AI agents work together, each with its own role, coordinating to solve a problem too big or too complex for a single agent. Picture a small team instead of one generalist.
Key takeaways
Several AI agents work together, each with its own role, on a problem too big or too complex for a single agent.
They pass information back and forth and reach an outcome none could reach alone.
It mirrors how human teams actually work.
How the agents work together
One agent might research, another might write, a third might check the work. They pass information back and forth and reach an outcome none could reach alone.
Figure 1. How a multi agent system works together
Restates this article: one agent might research, another might write, a third might check the work; they pass information back and forth, and coordination decides who does what and how they hand off. The figure shows structure only; nothing in it is measured.
A small team instead of one generalist
A single agent
One generalist- One agent on the whole problem
- Some problems are too big or too complex for it
A multi agent system
A small team- Several agents, each with its own role
- One might research, another write, a third check the work
- They pass information back and forth
It mirrors how human teams actually work, and it is where a lot of the most ambitious AI projects are heading.
Related terms
Why use multiple agents instead of one?
Splitting work across specialized agents improves accuracy and handles complexity better than overloading a single agent.
