Plain answers
Jev FAQ
Jev is a typed decision model from TypeSafe AI; JevSkills is an independent place to discover practical projects, skills, videos and guides around it.
What is Jev?
Jev is TypeSafe AI's typed decision model. An application supplies structured state and receives a constrained decision instead of an open-ended paragraph.
Is Jev an LLM?
TypeSafe AI presents Jev as a System One model, not a general-purpose large language model. It is designed for narrow, typed decisions rather than conversational prose.
Why does Jev not generate paragraphs?
Its interface is intended to return a bounded decision that software can inspect and validate. A host application can explain that decision to a person when it needs to.
What are Choice, Score, and Noul?
Choice selects one allowed option. Score returns a bounded numeric assessment. Noul is a yes-or-no decision with a probability. The exact schema is defined by the application using Jev.
How is Jev different from GPT or Claude?
GPT and Claude are general-purpose language models that commonly generate text. Jev is positioned for a smaller decision boundary with typed output; the host still owns validation, policy and actions.
What can I build with Jev?
Useful starting points include routing, triage, scoring, eligibility checks and human-review decisions—where an application needs a clear, bounded result.
How do I use Jev with Claude Code?
Use Claude Code to help implement an application boundary around Jev: keep credentials server-side, send structured inputs and validate the returned type before acting. Check TypeSafe AI's current documentation for supported SDKs and setup.
How do I use Jev with Codex?
Codex can help build the same integration pattern: model the input and allowed output, call Jev from a secure server boundary, then validate before a downstream action. Follow the current provider documentation for the supported client.
How do I use Jev with Cursor?
Cursor can assist with implementing a typed Jev boundary in your codebase. Treat it as a coding environment, not a replacement for provider documentation, application validation or secure secret handling.
What is Jev useful for?
Jev is useful when a product needs one understandable, structured decision instead of a long generated answer—for example, where to route work or whether a case needs review.
Is Jev deterministic?
A typed response is not by itself a guarantee of mathematical determinism. Validate the behavior you need against the current provider documentation, model version and your own test cases.
Does Jev hallucinate?
Bounded output does not make a model infallible. Treat Jev results as inputs to application logic, validate important decisions and keep human review for consequential cases.
How fast is Jev?
A TypeSafe-recorded demo reported Jev at 0.114 seconds versus GPT-5.6 Terra at 8.566 seconds for one 27-question vendor-run example. That is context for a specific demo, not a universal benchmark.
What does Jev cost?
Pricing can change. Check TypeSafe AI's current pricing and documentation before planning a production integration.
Where can I find Jev projects and skills?
Explore JevSkills for source-screened builds, skills, GitHub projects, videos and learning guides. A sign-in is required only for protected details and high-intent actions.
What is JevSkills?
JevSkills is an independent community resource for discovering practical Jev projects, skills, videos and guides. It labels evidence so visitors can distinguish source pointers from tested work.
Is JevSkills affiliated with TypeSafe AI?
No. JevSkills is an independent community resource and is not affiliated with TypeSafe AI.
Sources and updates
Updated September 22, 2026. Product descriptions and the benchmark qualification above are based on TypeSafe AI's published Jev introduction; availability, pricing and SDK support should always be checked in current provider documentation.
TypeSafe AI: Introducing System One Models and Jev