Jev Fundamentals
A free course on Jev (TypeSafe AI): the model that gives up text generation and returns typed, calibrated decisions your code can use directly.
Free to read · unofficial educational resource; Jev and TypeSafe are trademarks of TypeSafe AI · vocabulary in the Glossary01Jev: The Model That Answers Instead of Writes
Read a Jev request and answer as fluently as a function signature: the three question primitives (Noul, Choice, Score), request and answer anatomy, fan-out economics, and a worked rubric-to-questions example.
02Jev State and Typed Questions
Author the two things you write by hand in every Jev request — the state and the questions. The three question types up close, criteria that define your answer space, independence by design, and a complete worked request.
03Confidence, Calibration & Composite Scoring
What Jev's confidence numbers promise, threshold routing, uncertainty gates for torn answers (margin, low confidence, torn distributions), composite scoring with weights in code, and measuring calibration instead of trusting it.