calibration — How well a model's confidence matches reality — a calibrated model saying "90% sure" is right about 90% of the time.
guardrails — The checks around a model that block bad inputs and outputs — filters, validators, and permission rules the model itself can't override.
Why it matters
It lays out concretely how logprob-based classifiers work and why a frontier lab folding that capability into its base models could undercut a standalone classifier product, a pattern worth watching for any tool built as a thin layer over model outputs.
