The source provides a detailed guide on implementing Claude Code subagents to transition from simple, one-off AI prompts to a robust, reliable, multi-agent workflow for software development, as demonstrated by PubNub's internal practices. It explains that subagents are specialized, autonomous assistants defined by Markdown and YAML that handle specific tasks like writing specifications, reviewing architecture, and implementing code, promoting reproducibility and separation of concerns. Key best practices include assigning single responsibilities to each agent, managing permission hygiene with scoped tools, and using hooks to reliably chain steps and keep humans in the loop for approval. The text also covers architecture concepts, such as a three-stage pipeline (pm-spec, architect-review, implementer-tester), and describes how to integrate external LLMs like GPT-5 for specialized reviews using MCP servers or local scripts, ultimately turning Claude Code into a complete engineering system.============== Code content percentage: 0% Total text length: 15001 characters 🔗 Original article: https://www.pubnub.com/blog/best-practices-for-claude-code-sub-agents/?utm_source=chatgpt.com📋 Monday item: https://omril321.monday.com/boards/3549832241/pulses/18021290562

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