How Cloudflare enforces engineering standards using AI (opens in new tab)
Cloudflare built the Codex to turn scattered engineering knowledge into governed, machine-readable standards that both engineers and AI agents can apply consistently. It now supports code reviews, technical design reviews, and incident reviews, with AI systems flagging nearly 230,000 violations and blocking about 16,000 merges. The central approach is to combine human-owned RFCs with structured extraction, staged enforcement, and context-aware agents. ## Why Cloudflare Built the Codex - Engineering guidance previously existed across formal documentation, repositories, chat, and individual experience. - Engineers struggled to determine whether guidance was current, authoritative, or relevant. - Growth made it difficult for anyone to know every standard or for reviewers to check every requirement. - The Codex provides a shared source of truth that can be retrieved and applied at the point of work. ## Governance and RFC Workflow - The Codex is divided into domains such as: - Architecture and control plane systems - Security and reliability - Programming languages including TypeScript and Rust - Each domain has an owner responsible for content quality and consistency. - Standards follow an RFC format using RFC 2119 terminology: - **SHOULD** for recommendations - **MUST** for mandatory requirements - Employees can propose RFCs through structured merge requests. - Proposals undergo increasingly broad review before domain-owner approval. - Approved RFCs are published to an internal Astro-powered site. - Enforcement is deliberately separated from approval: - Approved standards can generate findings. - Only enforced standards can block merges. - This gives teams time to adopt requirements and implement enforcement mechanisms. ## Structured Standards for Agents - Feeding all 60-plus RFCs directly into an LLM would consume too much context and reduce accuracy. - A dedicated agent extracts SHOULD and MUST statements into structured JSON. - Each statement includes: - A stable slug - RFC and domain metadata - Requirement level - Section and source link - Stable identifiers allow Cloudflare to track requirements across RFC revisions, systems, monitoring, and exception handling. - Cloudflare moved from concise Markdown extraction to JSON to enable filtering and progressive disclosure. - Future metadata may identify which SDLC stage applies, such as design, implementation, or runtime. ## AI Code Review - The AI code reviewer retrieves relevant statements first and loads complete RFCs only when more context is needed. - Approved-RFC findings are non-blocking recommendations. - Violations of MUST requirements in enforced RFCs can withhold approval or block a merge. - Since launch, the reviewer has: - Flagged nearly 230,000 violations - Withheld approval for almost 16,000 violations ## Faster Code Review Alternatives - Full AI reviews generally take several minutes because they use coordinators and multiple agents. - To reduce remediation delays, Cloudflare is also developing mechanically verifiable checks. - Language-specific Codex requirements can be distributed through custom linter configuration packages. - TypeScript was the first language to receive Codex linter support, alongside standardization on oxlint. The Codex’s practical value comes from connecting governed human standards to automated enforcement. Cloudflare’s staged RFC lifecycle, stable statement identifiers, and combination of AI review with fast linters provide a scalable way to preserve engineering knowledge while reducing review inconsistency.