An Oct 15 Anthropic engineering post details layered review on the Claude Code repos: pre-PR self-verification plus fresh-context subagent review, parallel bug-hunting agents with voting verifiers, blocking security review, risk-tiered human approval (0/1/2 people), merge queue, flags and fast rollback. All metrics are the team's internal figures.

Key Takeaways

  • ✓Merged PRs to Claude Code more than doubled June–Sept while the revert share fell over 40% (internal figures)
  • ✓Anthropic monorepo changes per day grew from ~2,500 in May to 30,000+ in September
  • ✓Convergence fixes: one-round pass 65%→78%, 5+ rounds 8.9%→1.5%, mean reviews to pass 2.08→1.32
  • ✓After the Code Review research preview, internal PRs with substantive comments rose from 16% to 54%
  • ✓Risk tiers set human approvals at 0/1/2; an agent's approval never counts as a person's
How the Claude Code team reviews code: ~90% Claude-written, merged PRs more than doubled June–Sept while revert share fell over 40%
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In-Depth Technical Analysis

Anthropic's Claude Code team (Oct 15 post by Addy Osmani, Morgan Westlee Lunt and Qing Wang) says Claude writes about 90% of Claude Code's own code, and explains how they review it at that volume. Review moved from a final gate to continuous layers: pre-PR verification (tests, build, lint) plus a fresh-context subagent review; a Claude review on every PR where parallel bug-hunting agents are filtered by voting verifiers and tagged Important/Nit/Pre-existing; a separate security review whose open findings block merge; required CI; a risk classifier that sets 0, 1 or 2 human approvals based on the change, with sensitive paths and CI workflows always needing a person and agent approvals never counting as human ones; then a merge queue, flags, internal dogfooding, latest-before-stable releases and fast rollback. Internal metrics (no raw data published): merged PRs more than doubled June–September while the revert share fell 40%+; after a three-round cap, diff-only re-review and no repeated findings, one-round pass rose 65%→78% and mean reviews to pass fell 2.08→1.32. Past incidents and reverts form a daily eval for the reviewer. The team admits it lacks circuit breakers that tighten approval when revert or incident rates rise.

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