Because 8 ≈ e², Anthropic's researcher uplift is plausibly >2x

Notes are unpolished research updates directly from METR researchers, and have gone through less review than our research posts. They do not necessarily reflect the views of METR as a whole. Note: the modeling assumptions and conclusion are Thomas Kwa’s opinion, and others at METR disagree.1 Also, the math was checked by Claude but not a second human. Anthropic’s RSI blog post reported that in Q2 2026, Anthropic contributors merged 8× as much code per day as in the 2021-2024 period. What does this imply about the factor by which a researcher’s total effective output increased — the (serial) researcher uplift2? Of course, 8× more code doesn’t mean 8× more research, as coding is only part of the job. However, if we assume each line of code (LoC) has equivalent quality and verbosity to pre-2025 code and make standard economic modeling assumptions, we can conclude a surprising amount: all models predict researcher uplift at Anthropic from coding agents alone is >2×. (Researcher uplift could be even higher, because these numbers assume no uplift on non-code tasks.) Cobb-Douglas predicts that if pre-AI time spent coding is \(\beta=50\%\) and code output increases by a factor \(M=8\), then researcher uplift is \(M^\beta =…