Designing Multi-Agent Systems (MAS): How to Make Agents Talk to Each Other

In 2024, we were impressed when an AI could write a function. In 2026, we are building Crews.

One agent is like a talented freelancer. A Multi-Agent System (MAS) is like a high-performance engineering team. When you have multiple agents talking to each other, you can solve problems that are too complex for a single prompt to handle.

But how do you get them to actually communicate without it turning into a chaotic group chat? Here is the 2026 guide to agent orchestration.

🧠 The Concept of "Shared State"

The most important thing to understand in MAS is State. If Agent A writes code and Agent B tests it, Agent B needs to know what Agent A did.

In 2026, we use a "Shared State"—a central brain or memory that all agents can read from and write to. Instead of passing giant walls of text back and forth, agents simply update a shared object. This keeps the context clean and the costs low.

🚀 The Big Three Frameworks

Depending on your project, you’ll likely choose one of these three dominant 2026 frameworks:

1. CrewAI (Role-Based Teams)

• The Vibe: A corporate office.
• How it works: You define specific roles (Researcher, Writer, Manager). Work flows from one to the next in a "Process."
• Best For: Content pipelines, market research, and linear workflows.

2. LangGraph (The Flowchart)

• The Vibe: A logic gate or state machine.
• How it works: You define nodes (agents) and edges (the paths between them). It allows for loops—if the "Reviewer Agent" finds a bug, it sends the work back to the "Coder Agent" automatically.
• Best For: Complex engineering, autonomous coding, and any task that requires iteration.

3. AutoGen (Conversational Group Chat)

• The Vibe: A Discord channel for agents.
• How it works: Agents "chat" with each other to reach a consensus. It is the most flexible but can also be the most unpredictable.
• Best For: Open-ended discovery and collaborative problem solving.

🏗️ Common Communication Patterns

The Sequential Chain

The simplest pattern. Agent A -> Agent B -> Agent C. It’s predictable and easy to debug.

The Hierarchical Team

A "Manager Agent" receives the task and delegates sub-tasks to "Worker Agents." The workers report back to the manager, who then gives you the final answer. This is how most enterprise agents are built in 2026.

The Joint Collaboration

Agents work in parallel on the same state. This is high-speed but requires advanced "conflict resolution" logic to make sure they don't overwrite each other's work.

🏁 Starting Your First MAS

Don't try to build a 10-agent team on day one. Start with two:
1. An Executor: The one who does the work.
2. A Critic: The one who checks the work.

This simple "Coder/Reviewer" loop is the foundation of almost every successful AI engineering project today.

Want to see this in action? Check out our guide on Windsurf vs. Cursor to see how these IDEs are integrating agentic teams directly into your editor.