Jev cannot write. We gave it a job.

Our LLM Selector now uses a model that cannot write a reply. We gave it nineteen questions instead. TypeSafe released Jev on September 15. It reads text and returns choices, scores or yes-or-no probabilities, within the answer space you define. That makes it useful for the small decisions inside an AI workflow, such as routing a ticket or checking a stated criterion. It does not replace a model that has to write the reply.

Read the Jev breakdown →

Why the model is getting attention

One state, many typed decisionsJev evaluates the questions in a request in parallel. Each answer is a choice, score or yes-or-no probability that code can use directly, rather than prose that has to be recovered from a chat response.The price makes the design worth testingOpenRouter listed Jev 1.13 at $0.042 per million input tokens and $0 output on September 22. Questions and their criteria still add input tokens, so fan-out saves repeated state, not the cost of every question.The selector keeps the ranking outside the modelA description fills the same form a visitor can complete by hand. The deterministic selector code then ranks candidates from public evidence. Jev never sees a score or decides the shortlist.

The limit

A typed answer can still be wrong. We have not measured Jev’s calibration or speed on our selector traffic. A confidence value does not establish the accuracy of a job classification, and consequential actions still need permissions, confirmation and limits in code.

The boundary that matters

The option list is part of the contract.

Jev cannot select an option outside the list you provide. That bounds the output, but a badly defined list can still produce a bad decision.

Writing remains a separate job.

Jev cannot compose a summary, reply, patch or explanation. Pair it with a language model when a workflow needs both a bounded decision and generated text.

Analysis worth opening

Jev cannot write. That is the feature and the limit.What TypeSafe documents, what the selector sends, how external tests should be read, and what still has to be measured before treating Jev as a reliable decision layer.A valid JSON response can still be wrongOur structured-output evidence run shows why a constrained response shape does not settle semantic accuracy.

This issue in numbers

19
Fixed questions in the selector’s standard request: 14 + 5
Choice and yes-or-no readings in that request: 31 + unknown
Catalog jobs available to the primary job choice: $0.042 / M
Jev 1.13 input list price on September 22; output listed at $0