Multi-Agent System

What Is a Multi-Agent System

A multi-agent system is an architecture in which multiple AI agents, each with a defined role or area of responsibility, work on parts of a larger task and coordinate with each other, rather than a single agent handling the entire task alone. Coordination can take many forms, from agents passing messages directly to one another, to agents sharing a common task queue, to a coordinating agent that delegates subtasks to specialized ones.

Why Use Multiple Agents

Splitting work across multiple agents can make a system easier to reason about and maintain. A single agent handling research, writing, and code review at once must hold all of that context simultaneously, which can dilute its focus and make failures harder to diagnose. Separate agents, each scoped to one responsibility, such as one that gathers information and another that writes code based on it, can be tested, monitored, and improved independently. Multi-agent systems also allow parallel execution, letting independent subtasks run at the same time instead of sequentially.

Common Patterns

• Coordinator and workers: one agent breaks a task into subtasks and assigns them to other agents, then combines the results.
• Pipeline: agents pass output to one another in sequence, each performing a distinct transformation or review step.
• Peer agents: agents with overlapping capabilities communicate directly to negotiate, divide, or check each other's work.

Challenges

Coordinating multiple agents introduces problems that a single-agent system does not have: agents can duplicate work, disagree, or wait on one another indefinitely if communication is not well defined. Debugging a multi-agent system also requires tracing decisions across several independent processes rather than one, which typically calls for shared logging or an event stream that records what each agent did and when.

Multi-Agent System vs Agent Fleet

The two terms overlap but emphasize different things. A multi-agent system usually implies the agents are working together on a shared goal, with some form of coordination or communication between them. An agent fleet more often refers to a set of agents managed under one infrastructure, each potentially working on unrelated tasks for different users or projects, without necessarily coordinating with one another. A platform such as Agenhood, which runs many independent, containerized agents for different tasks, is closer to an agent fleet, while a set of those agents deliberately divided to solve one problem together would form a multi-agent system.