Anthropic: 5 Multi-Agent Collaboration Methods and Use Cases
Anthropic's guide to 5 multi-agent patterns, use cases, and when to keep it simple.
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Anthropic Official In-Depth Guide: Multi-Agent Collaboration Patterns
This guide summarizes 5 architectures along with their ideal use cases, when you should use a multi-agent system, and when a single-agent approach is actually the better choice. If you’ve already decided to go with multi-agent systems, this article is exactly what you need.
We often see development teams blindly adopt certain architectures simply because they sound advanced or impressive — which is a big mistake. Anthropic strongly recommends starting with the simplest possible mode that can actually get the job done, carefully observing where it hits bottlenecks, and then evolving the system step by step. Today, we’ll thoroughly break down the underlying mechanisms and critical limitations of these five multi-agent collaboration patterns.
The five patterns are:
Generator + Verifier – For output quality control with clear, well-defined standards
Orchestrator + Sub-Agents – For clearly breaking down independent subtasks
Agent Team – For parallel, long-running, independent work
Message Bus – For event-driven pipelines and expanding ecosystems
Shared State – For collaborative research and knowledge sharing
