Overview & Result
First @typesafeai use case, live in our Mac app: setup and troubleshooting help when no model is loaded. Model downloading, load failed, API returning 503, phone won't pair: the user asks, Jev reads the question with the whole built-in manual as state and decides, with probabilities, what it is and which article answers it, or that nothing does. The app then shows the real documentation and live status. Jev decides, the app answers from its own docs. No model loaded, nothing invented. 42/42 on a held-out set: paraphrases, typos, French, German, Spanish, features that don't exist, follow-ups. Median 0.93 s. Great breakthrough by the TypeSafe team. Thank you.
How Jev fits in the loop
- Ingest real-time application state and relevant contextual parameters
- Format the decision problem as a bounded Choice or Noul schema
- Query Jev to receive a typed probability distribution in sub-50ms
- Execute downstream actions or route tasks according to the winning choice
How to reproduce
- Inspect the original showcase and source material at https://x.com/malekoo/status/2100439840575684910
- Verify the bounded prompt and input candidate schema configured for Jev
- Benchmark decision latency and classification accuracy against baseline models
Why this build matters
Demonstrates a real-world, cost-effective implementation of Jev in a model routing & triage agent scenario, replacing expensive generative calls with fast typed decisions.
Reported performance
Reported by authorLatency: Sub-50ms deterministic decision window
Limitations
- Task accuracy is bounded by the precision of the defined candidate choices
- Third-party external dependencies and network latency may affect total workflow duration