---
title: "what is an example of a multi-agent system?"
description: "concrete examples, from traffic lights and warehouse robots to a software team of planner, engineers, and reviewer working one codebase together."
url: "https://aldena.ai/learn/what-is-an-example-of-a-multi-agent-system"
---

# what is an example of a multi-agent system?

a software delivery team is the clearest example: a planner breaks a feature into tasks, two engineer agents implement in parallel, and a reviewer checks the result before anything merges. older non-ai examples include coordinated traffic lights, warehouse robot fleets, and the bidding agents in an ad auction.

## the examples that predate language models

Multi-agent systems are decades older than llms, and the classic examples are still the clearest way to see the shape:

- **Traffic signal control.** Each intersection is an agent optimising its own throughput while negotiating with neighbours. No central controller has the full picture in real time.
- **Warehouse robot fleets.** Hundreds of units route themselves around a shared floor, avoiding each other and reserving lanes. Amazon's fulfilment centres run this at scale.
- **Ad auction bidding.** Every advertiser runs a bidding agent with its own budget and goals, competing in a market that resolves in milliseconds.
- **Power grid balancing.** Distributed generators and storage negotiate supply against demand locally rather than through one dispatcher.

The common structure: several autonomous units, local information, shared environment, and a global outcome nobody explicitly programmed.

## the modern software example, step by step

Take one feature request landing in a backlog.

1. **The planner** reads the request, looks at the codebase, and splits it into four tasks with an order and dependencies.
2. **Engineer A** takes the database migration. **Engineer B** takes the api endpoint that depends on it and waits for A's work to land.
3. **The reviewer** reads both diffs against the standard, and rejects B's error handling with a specific reason.
4. **Engineer B** revises. The reviewer passes it.
5. **The planner** reports the feature as ready, with the changes attached.

Five agents, one goal, no human typing between steps. What makes it multi-agent rather than one long prompt is that each agent holds its own context and tools, and the reviewer genuinely can say no.

## why the reviewer is the point

The strongest argument for multi-agent over one big agent is not speed. It is that a separate reviewer with a separate context catches things the author cannot. An agent asked to check its own work is checking against the same assumptions that produced the error.

The cost is real: more tokens, more latency, more places to go wrong. Multi-agent earns that cost on long work with a quality bar. It does not earn it on a single well-specified task, where one agent is cheaper and faster.

## how this works in aldena

The software example above is what aldena is. You hire from eleven prebuilt [roles](https://aldena.ai/features/agents) into a [room](https://aldena.ai/features/isolated-rooms) with its own server, arrange them in an [org chart](https://aldena.ai/features/org-chart), and delegation happens down the reporting lines rather than through a script you wrote.

The coordination problem that sinks most multi-agent builds, agents overwriting each other and losing context between handoffs, is handled by shared room [memory](https://aldena.ai/features/agent-memory): up to 100 shared entries per room that every agent reads, plus 50 private per agent. And you watch it play out live rather than reading a log afterwards.

For the definition rather than the examples, see [what is a multi-agent system](https://aldena.ai/learn/what-is-a-multi-agent-system).

## related questions

- [what is a multi-agent system?](https://aldena.ai/learn/what-is-a-multi-agent-system): several autonomous agents sharing an environment and coordinating toward a goal. the term is 40 years old and predates language models by decades.
- [what is the best multi-agent system?](https://aldena.ai/learn/what-is-the-best-multi-agent-system): depends on whether you want a framework to build with or a platform to run. langgraph and crewai lead on frameworks. platforms differ on memory and gates.
- [is chatgpt a multi-agent system?](https://aldena.ai/learn/is-chatgpt-a-multi-agent-system): no. chatgpt is one model with routing and tools. it borrows some multi-agent machinery internally, but you get a single agent, not a team you can arrange.
- [what is an agent swarm?](https://aldena.ai/learn/what-is-an-agent-swarm): many simple agents producing useful behaviour through local rules and no central controller. in llm practice it usually means several agents with handoffs.