Summary
A post on X by @naufaldi shares details from an Anthropic post on how the Claude Code team handles review when Claude writes about 90% of the code, according to the headline. The snippet says merged pull requests to Claude Code more than doubled from June to September, while the share of reverted changes fell by more than 40%. Monorepo changes per day rose from about 2,500 in May to over 30,000 in September. The described process requires Claude to show tests or screenshots, runs an AI review on every pull request, and uses a classifier to set a risk tier that decides whether zero, one or two humans approve.
AI-assisted summary based on the listed source.
What happened
Anthropic's post says merged PRs to Claude Code more than doubled from June to September while the share reverted fell by more than 40%, and monorepo changes per day rose from about 2,500 in May to over 30,000 in September. Claude must show tests or screenshots, every PR gets an AI review, a classifier sets a risk...
Why it matters
The described workflow combines automated AI review with risk-based human approval, which teams using AI coding agents may want to compare with their own review rules. Engineering leads and code reviewers would be most affected by how approval requirements are set. The snippet cuts off before explaining whether an agent's approval counts, so the full rules and results should be checked in Anthropic's original post.
Signal Intelligence
Signal Strength 89%
Technical label WATCH
Public Interest 46
Category BIG MOVE
Reader Depth TECHNICAL
Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.
Public Interest components
Recognizable Entity Score 73
Practical Impact Score 8
Novelty Interest Score 70
Consequence Score 30
Curiosity Score 16
Shareability Score 58
Why this is here
VQV surfaced this signal because it is recent, relevant to AI Coding Tools, connected to Scobleizer News Pulse (X).
