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trailAI tools sped up developers more in early 2026 than early-2025 estimates indicated.
Coding benchmark scores and anecdotal reports overestimate real-world AI coding capability.
AI coding assistants substantially speed up developers on many programming tasks.
Direction-of-bias reading of the follow-up data· for
Selection effects from AI-reliant developers opting out bias measured AI productivity speedup estimates downward.
Developers who rely on AI increasingly decline to participate in productivity experiments that require working without AI.
Developers who opt out of AI productivity experiments would experience larger AI speedups than those who participate.
Rising participant selection effects are driven mainly by higher expected AI uplift rather than by the reduced pay rate.
Developers' self-reported estimates of AI-driven productivity speedup are unreliable.
AI coding tools became substantially more capable during 2025 with the adoption of agentic tools.
atomic
Unreliability of the direct measurements· against
METR's August 2025 developer productivity experiment yields an unreliable signal of AI's current effect on productivity.
assumed
Using AI tools caused experienced open-source developers to complete tasks about 20% slower in early 2025.
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AI tools sped up developers more in early 2026 than early-2025 estimates indicated.
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