“Because 8 ≈ e², Anthropic’s researcher uplift is plausibly >2x” by Thomas Kwa
“Because 8 ≈ e², Anthropic’s researcher uplift is plausibly >2x” by Thomas Kwa  
Podcast: LessWrong (30+ Karma)
Published On: Thu Jul 09 2026
Description: 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. Introduction 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 uplift [2] ? 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 and code output increases by a factor , then researcher uplift is . CES (constant elasticity of substitution) production functions, due to a fun mathematical coincidence, infer a narrow range of about if code is [...] ---Outline:(00:25) Introduction(03:09) Economic models(03:57) Cobb-Douglas model(04:57) CES model(05:26) Setup(06:31) Because 8 ≈ e², the estimate is robust to σ!(09:15) M = 8 also implies a lower bound on σ(10:47) Code heterogeneity model: What if AI speeds up high-stakes code less?(12:22) Caveats: How could Anthropic's uplift be less than 2x?(12:36) Plausible reasons(12:39) Verbosity(14:42) Barely useful code(16:14) Irrational time allocation, intrinsic desire to use AI, etc.(17:17) Unlikely reasons(17:21) Extreme heterogeneity(18:04) Changing denominator(18:34) Discussion(18:37) Prefer code output over code uplift, for estimating overall uplift(19:40) Why is Anthropic's own estimate much lower?(21:55) There are reasons to expect even higher uplift(22:46) Conclusion(24:03) Appendix: Heterogeneous code model The original text contained 8 footnotes which were omitted from this narration. --- First published: July 9th, 2026 Source: https://www.lesswrong.com/posts/ix5qEyW9BjGEb4d8k/because-8-e-anthropic-s-researcher-uplift-is-plausibly --- Narrated by TYPE III AUDIO. ---Images from the article:Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.