Anthropic’s engineering team published one of the cleanest write-ups available on how a multi-agent system actually works in practice . The post is about Claude Research, an orchestrator-subagent pattern built for breadth-first research. The architecture is optimized for a particular task class, and the price of admission is a roughly fifteenfold token cost compared to a chat conversation. That cost is the tradeoff the system makes on purpose. Most production systems make different tradeoffs. They run under cost ceilings, accuracy SLAs, speed budgets, and error rates that the research context does not impose. The blueprint’s patterns travel — orchestrator delegation, parallel subagents, condensed-return artifacts, end-state evaluation — but the architecture that emerges from applying them under production pressure is rarely the architecture in the post. The choices look the same up close and different at the system level.…