A support message arrives. Your code has to decide where it should go.

Decision Models for Developers

Calibrated Routing, Moderation and Triage with Jev and Local Models

A support inbox gets a message, and your code has to send it to the right handler. That isn't a job for prose. It's a job for a decision model, which reads a text and a typed question and returns a decision with a probability: yes or no, one option from a set, or a level on a scale. It writes nothing else.

The book is for a working Python developer who wants to use that kind of model for routing, moderation and triage, and to know when its probabilities can be trusted. You call Jev from TypeSafe AI through its Python SDK and see what each question type returns and what the tokens cost. Then comes calibration from first principles. What should a probability of 0.8 mean? You check it on your own labelled data with reliability tables, Brier score and expected calibration error.