Both interruptions and auto-approvals increase with experience. This apparent contradiction reflects a shift in users’ oversight strategy. New users are more likely to approve each action before it’s taken, and therefore rarely need to interrupt Claude mid-execution. Experienced users are more likely to let Claude work autonomously, stepping in when something goes wrong or needs redirection. The higher interrupt rate may also reflect active monitoring by users who have more honed instincts for when their intervention is needed. We expect the per-turn interrupt rate to eventually plateau as users settle into a stable oversight style, and indeed the curve may already be flattening among the most experienced users (though widening confidence intervals at higher session counts make this difficult to confirm).
Measuring AI agent autonomy in practice · Miles McCain et al. · 18 February 2026