How the Claude Code Team Redesigned Code Review for AI

X postClaudeDevsOpinion

Around 90 percent of Claude Code is written by Claude itself. The Anthropic engineering team shares how shifting to automated, multi-layered reviews more than doubled merged pull requests while cutting reverts by over 40 percent.

Key points

  1. Claude writes roughly 90 percent of Claude Code; daily landing changes in Anthropic's monorepo grew from 2,500 in May to over 30,000 in September.
  2. Code review shifted from an end-of-process gate to a continuous, automated workflow running before and during PR creation.
  3. Engineers rely on subagents and dedicated skills to run tests, simplify diffs, and inspect behavior before any human reviews.
  4. Project rules, conventions, and area-specific guidelines are enforced through instructional files such as CLAUDE.md and REVIEW.md.
  5. Claude Code creator Boris Cherny highlights that giving the model a verification mechanism (builds, bash commands, simulators) improves output quality by 2x to 3x.
  6. The process aims for most PRs to merge with at most one human in the loop without increasing incidents or revert rates.

Why it matters

Manual line-by-line review becomes impossible at the speed and volume of agentic code generation. This workflow provides an operational blueprint for scaling software delivery through continuous automated review while protecting human attention.

Analysis

Anthropic's approach treats code review as a multi-layered filter rather than a single approval barrier. By shifting routine bug-hunting, formatting, and behavioral checks to automated subagents with direct verification tools, human intervention is reserved for complex or high-risk changes. Relying on explicit prompt files like CLAUDE.md for repo-specific rules helps address recurring errors at the root, making high-velocity, agent-assisted software development manageable.

Original post

ClaudeDevs

@ClaudeDevs · 16 October 2026

Claude writes about 90% of Claude Code's code. From June to September, merged PRs more than doubled while the share reverted fell by more than 40%. We wrote about how we changed code review to get there, and how to adopt it: t.co/9sZe64g3mb

12.6k likes400 replies10k bookmarks1.6m views

View on X
Selected replies (5)
  • @z4mbon @ClaudeDevs The guys that code the other 10% t.co/SFmzS2OlJ5
  • @hd3adp00l @ClaudeDevs 90% anthropic team hitting approve all day t.co/1GRigWaRcT
  • @den_spirin @ClaudeDevs Love the progress bar t.co/NAFdTrORvB
  • @ravartd @ClaudeDevs basically, to some extend we were doing the same good to get some verification on that t.co/77zHXFO5zt
  • @AdamJHumphreys @ClaudeDevs I really like to use Claude Engineer and security to audit code from time to time. With each model improvements come. I'd like to think that @ClaudeDevs has an active subscription to recursively update based on CVEs and should notify devs on changes or even proactively patch

Links and tools from this entry

Summary generated by AI (Gemini 3.8 Flash, 19 October 2026). It may contain errors – the original source is authoritative.

Similar in content, found by the AI search.

  • Article:Addy Osmani, Morgan Westlee Lunt, Qing Wang

    Code Review at Anthropic: How the Claude Code Team Reviews AI-Generated Code

    The Claude Code engineering team explains how they handle code reviews when agents write around 90 percent of the codebase. Instead of exhaustive manual line-by-line checks, they rely on pre-PR verification, automated multi-agent reviews, risk-tiered human approvals, and rapid rollbacks.

    AI & LLMs· Resource

  • Article:Anthropic

    Claude Code Power User Tips from Anthropic's Engineering Team

    Engineers from the Claude Code team at Anthropic share core workflow patterns for shipping code faster, highlighting parallel execution via Git worktrees, plan-first workflows, automated verification, and persistent project memory.

    AI & LLMs· Resource

  • X post:Casey Lee

    Anthropic's AI-Native SDLC Playbook: Scaling Pipelines for Fast Coding Agents

    Casey Lee highlights Anthropic's AI-native SDLC playbook. While agents like Claude Code can generate PRs within hours, traditional security reviews and product sign-offs still take days. Anthropic proposes structuring planning, reviews, and releases into agent-executable steps governed by human checkpoints.

    276bookmarks22kviews

    AI & LLMs· Opinion

  • Link:Anthropic

    Anthropic examines progress towards recursive self-improvement in AI

    The Anthropic Institute shares internal metrics and external benchmark trends demonstrating how AI agents are accelerating the development of subsequent AI models. As of May 2026, over 80% of merged code at Anthropic is written by Claude, with engineers merging 8x more code per day than in 2024. While full recursive self-improvement remains constrained by models' lack of strategic judgement in goal selection, progress is advancing rapidly.

    AI & LLMs· Research

  • Video

    Video:CURT

    How Anthropic Builds Software: Thariq Shihipar on Claude Code and the Future of Engineering

    In an interview with Ryan Peterman, Thariq Shihipar, an engineer on Anthropic's Claude Code team, discusses how engineering practices are evolving alongside advanced AI models. At Anthropic, developers treat Claude as a thought partner operating at higher levels of abstraction, with manual IDE coding largely diminishing. Shihipar discusses the critical role of harness engineering, loop engineering workflows, verification strategies to prevent incidents, and why foundational technical knowledge remains vital even as coding becomes increasingly automated.

    AI & LLMs· Talk

  • Link:Anthropic

    Anthropic Claude Code: Agentic Coding in the Terminal and IDEs

    Anthropic introduces Claude Code, an AI coding agent designed for the terminal, IDEs, web, and Slack. The tool maps codebases using agentic search, applies multi-file edits, runs tests, and creates pull requests directly within the developer's environment.

    AI & LLMs· Tool

Let's talk about your project

Locations

  • Mattersburg
    Johann Nepomuk Bergerstraße 7/2/14
    7210 Mattersburg, Austria
  • Vienna
    Ungargasse 64-66/3/404
    1030 Wien, Austria

Parts of this content were created with the assistance of AI.