A September 20 post argues that inputs and intermediate measures can be hard to interpret: activity can change without outputs changing, or vice versa. The author favors more focus on aggregate outputs, while noting that experiments are harder to run and changes can be difficult to attribute to AI. In an August 18 post, the same author shared tentative conclusions about discovery trends: sharp acceleration in cyber, some acceleration in math and no clear acceleration in algorithms.