Collation of Claude Code Best Practices – v2 (rosmur.github.io)

Anthropic’s “Collation of Claude Code Best Practices – v2” synthesizes 12 community and official sources into a practical playbook for using Claude Code reliably in production. The guide’s headline findings are clear: context management is paramount, upfront planning is non‑negotiable, and simplicity beats complexity. For the AI/ML community this matters because LLM-driven development fails mostly from context drift and brittle workflows—so adopting structured practices can turn fragile prototypes into maintainable systems without piling on opaque multi‑agent complexity. Technically, the guide prescribes concrete patterns: maintain concise CLAUDE.md files (root: 100–200 lines, subdirs 50–100 lines, target token budget ≪ monorepo baselines), aggressively clear context (clear at ~60k tokens or 30% of capacity; prefer “Document & Clear” over compaction), and use a three‑file dev docs pattern (plan/context/tasks) as a living record. Enforce Test‑Driven Development and continuous quality gates (pre‑commit/typecheck/hooks, test runs, build validation), commit incrementally with conventional messages, and run multi‑layer reviews (Claude self‑review in fresh context + human review). Favor simple control loops and low‑level tools over heavy RAG or complex frameworks; enable skills to auto‑activate, and use monorepos where possible to reduce context overhead. These recommendations give a pragmatic roadmap for scaling LLM‑assisted engineering while reducing silent technical debt and debugging cost.