Descending Depth

The ascending friction thesis holds that AI does not eliminate difficulty but relocates it upward, exposing higher-level creative and analytical challenges that lower-level struggle had always obscured. Descending depth names the failure mode in which relocation does not occur—in which the practitioner experiences the removal of lower-level friction not as an invitation to engage with harder problems but as permission to produce more fluent output at the same cognitive altitude. The developer who uses Claude Code to write three times as many applications in the same time, without ascending to the architectural and purpose questions that implementation friction had previously obscured, is experiencing descending depth. The writer who uses a language model to draft more text per hour without deepening her critical engagement with whether the argument being constructed deserves to exist is experiencing descending depth. The concept, introduced in Arthur Koestler's framework for the bisociative use of AI tools, names the failure