dr. jack morris

Simple text-only tweet, no images, dark mode, cropped to just the tweet body (no engagement counts visible).

A wry researcher joke about AI-coding-agent productivity gains being partly illusory due to unreliable results (10x throughput × 15% trustworthiness ≈ 1.5x, generously rounded up to "50% more productive"). Relevant to Nathan's tracking of AI R&D automation/productivity measurement debates already noted in project memory (Anthropic's 50% self-reported productivity claim vs. METR's controlled 20% slowdown finding) — this tweet is a satirical data point on the same self-report-inflation problem.

An anecdote (unverified, "friend of a friend") claiming a single bug fix in Gemini training code produced a large jump in benchmark performance, offered as commentary on how fragile/contingent frontier model quality can be. Industry rumor about ML training practices.