A side-by-side guide to assigning closed, repeated decisions to Jev and leaving composition, multimodal interpretation, and open-ended reasoning to a general-purpose language model.
Original by Made with JevGetting startedMade with Jev guideSource reviewed
Before you dive in
What you’ll find in the original
Jev returns one of defined options, probabilities, and confidence; an LLM generates unrestricted text.
Use Jev where the answer set can be written in advance and the decision repeats at scale or under latency pressure.
Combine them in a pipeline: an LLM proposes or writes, Jev judges a bounded property, and code enforces the result.
Worth knowing
Comparisons mix TypeSafe evaluations and builder reports. Agreement with model-generated references is not human-verified accuracy.