What is Multi-Agent Systems?
Architectures where multiple specialized AI agents collaborate, debate, or coordinate to solve complex tasks.
Definition
Multi-agent systems in AI involve multiple language model instances (agents) working together, each potentially with different roles, specializations, or perspectives. Architectures include: debate (agents argue different positions to reach better conclusions), delegation (a manager agent assigns subtasks to specialist agents), pipeline (agents process information sequentially), and swarm (agents self-organize around tasks). Multi-agent approaches can outperform single-model solutions on complex tasks by breaking problems into specialized subtasks, enabling self-critique, and simulating diverse perspectives. Council's approach of querying multiple AI models simultaneously is a form of multi-agent comparison.
Examples
Why It Matters
Multi-agent systems represent the frontier of AI capability. Council itself embodies this principle — comparing multiple AI perspectives produces better decisions than relying on any single model.
Related Terms
AI Orchestration
Managing and coordinating multiple AI models, tools, and workflows to complete complex end-to-end tasks.
Tool Use
An AI model's ability to select and invoke external tools like search engines, calculators, or code interpreters.
Prompt Chaining
Breaking complex AI tasks into sequential prompts where each step's output feeds into the next step's input.
Function Calling
An AI model's ability to output structured requests to invoke external functions, APIs, or tools during a conversation.
Common Questions
What does Multi-Agent Systems mean in simple terms?
Architectures where multiple specialized AI agents collaborate, debate, or coordinate to solve complex tasks.
Why is Multi-Agent Systems important for AI users?
Multi-agent systems represent the frontier of AI capability. Council itself embodies this principle — comparing multiple AI perspectives produces better decisions than relying on any single model.
How does Multi-Agent Systems relate to AI chatbots like ChatGPT?
Multi-Agent Systems is a fundamental concept in how AI assistants like ChatGPT, Claude, and Gemini work. For example: A coding agent and a review agent collaborating — one writes code, the other reviews it Understanding this helps you use AI tools more effectively.
Related Use Cases
AI Models Using This Concept
See Multi-Agent Systems in Action
Council lets you compare responses from multiple AI models side-by-side. Experience different approaches to the same prompt instantly.