CONCEPT
AI Practice Framework
The Berkeley researchers' prescription for the AI-augmented workplace — structured pauses, sequenced workflows, protected human-only time, behavioral training alongside technical training — the operational counterpart to Maslach's fix-the-mine principle.
The AI Practice framework was proposed by Xingqi Maggie Ye and Aruna Ranganathan in their 2026 Harvard Business Review article documenting the Berkeley embedded study of AI adoption. The framework translates the study's findings into organizational design: structured pauses built into the workday, sequenced rather than parallel workflows, protected time for human connection that cannot be optimized away, and behavioral training alongside the technical training that AI adoption typically emphasizes. The framework addresses the mechanisms through which AI intensifies work — task seepage, attentional fragmentation, scope creep — at the level of daily work design rather than at the level of individual coping.
In The You On AI Field Guide
Structured pauses are deliberately designed intervals during which the worker disengages from AI-mediated work and engages in activities that use different cognitive resources — conversation, physical movement, unstructured reflection. They are not breaks in the conventional sense. They serve a specific neurological function: allowing the default mode network, the brain system