Openai published usage data from its own research org on september 6 showing 3.1 agent workdays per…
openai published usage data from its own research org on september 6 showing 3.1 agent workdays per human workday and a median researcher spending over 600 dollars a day at api prices. the company selling agent infrastructure is its own heaviest customer.
scale your agents to the point where the api bill hurts, that is the real adoption metric.
Context
OpenAI's post of 6 September 2026 says that by mid-August the median researcher was integrating agents daily, using more than 600 dollars per day of inference at API prices, and that the research organization used 3.1 agent-workdays of effort for every workday of human labor, measured against a standard 8-hour workday. It also says that before June 2026 total agent runtime across the research organization was still below total human labor.
The figures are OpenAI's own measurements of its research organization, not independent, and the method beyond the page was not read. The 600 dollars is inference at API list prices, not necessarily money paid. The page says figures include subagents created by users' agents. Its own heaviest customer was not found as a statement in the text read, so that superlative is unverified. Scaling agents until the API bill hurts as the real adoption metric is the author's opinion.
Watch next
- Independent measures of agent labor.
Sources
Provenance
The note above is reproduced unedited from the original post, first published on Threads on 19 September 2026 at 00:47 IST. Sources are the papers and datasets the note draws on.
View the original post ↗Embed this note
More notes
The air is now being asked to keep its own ledger
the air is now being asked to keep its own ledger: ecmwf’s aifs compo becomes the first ai model to forecast atmospheric composition globally every three hours, cleanair simulates 365 days of pm2.5 over china in ten seconds, and a unified framework maps six pollutants at one kilometer across the whole country. the air now files its own composition report.
read the note →The current is now being asked to draw its own map
the current is now being asked to draw its own map: china’s langya 2.0 predicts six ocean phenomena including internal waves and mesoscale eddies, a deep net called wenhai resolves eddies globally with air sea flux formulas built in, and scripps infers surface currents from the way temperature patterns deform in satellite images. the ocean now files its own circulation report.
read the note →The soil is now being asked to report its own carbon
the soil is now being asked to report its own carbon: a nix color sensor paired with generative data augmentation predicts soil organic carbon without a lab, random forest drives 74 percent of soil health mapping studies, and sentinel 2 tracks five year carbon change across france and italy from 922 samples. the dirt now files its own carbon account.
read the note →