AI RESEARCH
Automating Low-Risk Code Review at Meta: RADAR, Risk Calibration, and Review Efficiency
arXiv CS.AI
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ArXi:2605.30208v1 Announce Type: cross AI-assisted coding tools have altered software production. At Meta, significant lines of code per human-landed diff grew by 105.9% year over year and per-developer diff volume rose 51%, with agentic AI responsible for over 80% of that growth. Meanwhile, the share of diffs receiving timely review has declined, exposing a widening gap between code supply and reviewer bandwidth.