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Conway's Law states that system design mirrors team communication structure. Using the hexagon as a metaphor from nature (beehives) to software (hexagonal/ports-and-adapters architecture), the post argues that intentional team organization is critical to product quality. Examples include Tesla vs. GM and AWS microservices. The post also introduces JigJoy, a platform for building modular AI agent teams structured similarly to hexagonal architecture principles.

Structure Shapes Success: Conway's Law, AI Teams & Hexagonal Architecture

We are building an operating system for AI agents. We want to enable every developer to create and, if possible, control autonomous AI workflows. Here we are sharing content on this topic.

JigJoy Community

<p>Conway’s Law applies to AI agent setups too honestly. every dev has a different <a href="http://CLAUDE.md" target="_blank" rel="noopener nofollow">CLAUDE.md</a>, different MCPs configured, different context. the agent output mirrors the team structure in the worst way. been using an open source tool called Caliber that generates a shared baseline config from the actual codebase, so at least the agents start from the same place. MIT licensed so you can see exactly what it does: <a href="http://github.com/caliber-ai-org/ai-setup" target="_blank" rel="noopener nofollow">github.com/caliber-ai-org/ai-setup</a></p>
