15 Patterns Summarizing Multi-Agent Design from GitHub, Google, and Siemens

Summary

A Japanese IT publication compiled 15 multi-agent design patterns from GitHub (2), Google (8), and Siemens (5). These patterns cover architectures such as contract-first communication, orchestrator-worker, debate, supervisor, and hierarchical topologies, and are used to configure large language model (LLM)-based agent systems.

Why it matters

As multi-agent orchestration becomes the dominant architecture for production AI, the field still lacks a common terminology. A provider-agnostic, unified pattern catalog offers engineers a shared reference point when selecting coordination topologies, thereby reducing the trial-and-error costs of developing agent systems. Siemens' inclusion in the list indicates that pattern design is now being driven not only by software engineering but also by industrial and manufacturing scenarios.

Highlights

• GitHub's two patterns (contract-first via JSON schemas, tool-first via MCP) focus on structured inter-agent interfaces rather than free-form prompting.
• Google's eight patterns cover the full spectrum of coordination: pipeline, orchestrator-worker, debate, supervisor, hierarchical, voting, and reflection.
• Siemens offers patterns based on industrial workflows, demonstrating that multi-agent design is expanding beyond pure software into operational contexts.

Critical take

The article is essentially a list that repackages public blog posts and documentation from three companies. It lacks original analysis, benchmarking, or discussion of failure scenarios. Calling 15 loosely related coordination ideas 'design patterns' risks over-formalizing concepts that are often just workflow preferences. The absence of quantitative comparisons or real-world deployment data prevents the article from offering practical value beyond a reading list.