# Multi Agent Systems

Multi agent systems use multiple AI agents with distinct roles that coordinate toward a shared outcome.

## Why it matters

Multiple agents can divide specialized or parallel work, but they introduce communication, consistency, security, and evaluation problems. Teams should add agents only when measured task performance justifies the extra coordination.

## Example

A due-diligence workflow assigns financial, legal, and market research to separate agents, then requires a synthesis step that preserves disagreements and citations.

## FAQ

### What is Multi Agent Systems in simple terms?

Multi agent systems use multiple AI agents with distinct roles that coordinate toward a shared outcome.

### Why does Multi Agent Systems matter for teams using AI?

Multiple agents can divide specialized or parallel work, but they introduce communication, consistency, security, and evaluation problems. Teams should add agents only when measured task performance justifies the extra coordination.

### What is a practical example of Multi Agent Systems?

A due-diligence workflow assigns financial, legal, and market research to separate agents, then requires a synthesis step that preserves disagreements and citations.


Source: https://www.luffy.so/ai-glossary/multi-agent-systems

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