OpenAI reports AI “research interns” and warns about its own pace at the same time
OpenAI is releasing internal data showing how much AI agents now drive its own model development, and it says it has hit a self-set milestone on the path toward self-improving AI. Chief scientist Jakub Pachocki pairs that with an unusually blunt warning: no lab has solved control of these systems well enough.
OpenAI published two matched texts. One is a blog post with internal metrics on increasingly automated AI research. The other is the essay “An Alien Mind” by chief scientist Jakub Pachocki. Both landed three days after the company unveiled GPT-6 Astra. The core message is that OpenAI is moving fast toward recursive self-improvement (RSI), and it considers that dangerous. All the data comes from inside the company, and OpenAI mentions no independent review. The company says it has reached the goal it announced last fall of an “automated research intern,” a system that handles clearly scoped research tasks under human guidance, including ones that would take an experienced researcher several days. OpenAI doesn’t share a detailed validation of that claim. The post only says the milestone was met “according to our measurements.” By March 2028, the company wants to build a full automated AI researcher. OpenAI says people still set research priorities, judge results, and decide on scaling, pauses, and deployment. The usage numbers show how deeply coding agents have worked their way into daily research. According to the report, the median researcher at OpenAI burns more than $600 a day in inference at API prices, and the 90th percentile runs above $7,000. The token output of the median researcher has jumped 124-fold since December 2025, far faster than in other parts of the company. Since June, agent runtime has topped human working hours. As of mid-August, the research organization runs 3.1 agent workdays for every human workday.
