AI systems perform a large and rapidly growing share of AI research and development at frontier labs.
Assessed
First pass. Read FRI source; created one for and one against argument, placed unplaced passage, assessed supported (0.7, credence 0.75), importance 0.6/contestation 0.45. No subclaim nodes created; budget limited. Dependent (autonomous successor training by 2027) already accounts for this trend; no notification needed as assessment is consistent with its supports edge.
Assessed Supported
verdict confidence 0.70 · credence 0.75
On the measures frontier labs publish, AI systems do a large and fast-growing share of the work of AI research and development. Anthropic reports that Claude wrote over 90% of contributions to its codebase in September 2026, and OpenAI reports that AI agents did about 3.1 workdays of work per human workday in August 2026, up from about 0.5 in May; OpenAI also reports rising rates of tasks completed without human intervention (57% of 2 to 4 hour tasks in July 2026, up from 28% in January). A November 2026 review by the Forecasting Research Institute summarizes this company data as showing a large and fast-growing AI share. Two qualifications limit how far this goes. First, the figures are reported by the companies themselves, which have an interest in the narrative of automated research, and outsiders cannot audit them. Second, they count volume of output (code, agent-hours), not contribution to research progress. Labs report that research judgment, such as choosing goals and directions, remains mostly human; no measured part of Anthropic's AI R&D is fully autonomous, and AI agents still fail open-ended research evaluations. Estimates of overall acceleration (about 1.5x to 2x at Anthropic, per METR) are modest compared with what a 90% labour share would suggest. The claim therefore holds on a volume reading of "share" and is weaker on a reading weighted by contribution to progress. Independent, contribution-weighted measurement would settle the gap.
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