Judgment needs boundaries.
A useful decision model has a small job. It reads a situation, weighs the offered options, and gives software something precise to work with.
Make the decision explicit
A paragraph of generated text leaves the application to guess what to do. We want the decision itself to be an interface: named choices, ordered levels, or a true-or-false question. The developer defines the options and owns the consequences.
Uncertainty belongs in the result
A choice without uncertainty hides an important part of the answer. Probabilities make uncertainty visible. Calibration asks whether those probabilities match outcomes on data that resembles the task. A high number alone proves neither reliability nor safety.
Let software do the work around it
Code should validate inputs, check permissions, enforce policy and execute actions. The model supplies a judgment inside that system. The gate says whether the application's threshold was met; people handle the cases that need more context.
Learn from the cases that fail
We care about contradictions, missing options and decisions that look easy until the wording changes. Measure those failures on your own tasks. Prefer an honest limit to an impressive demonstration that fails in a real workflow.