Jev versus text-generating models
Jev does not generate free-form text. A side-by-side video compares parallel decision-making with token-by-token text generation.
Jev loads skills on demand to keep context clean
The post suggests letting Jev classify which skills to load per request, keeping the skill inventory outside the context window so irrelevant content doesn't occupy the session.
Context hygiene as a product feature. Keep skills user-invocable only. Let Jev classify which ones to load per request — inventory stays outside the window until needed. Same lesson as tool output: what sits in context owns the session. Skills are no exception.
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Pricing, evaluations, and the name Jev
The launch thread explains code-and-AI workflow evaluations, the input price announced at launch, and free output tokens.
Jev Model: Decision-Making Probability Generation, 200× Faster and 400× Cheaper Than LLMs
This model is built for decision-making rather than text generation, outputting probabilities for each option in parallel instead of token-by-token responses. The author shares a simplified comparison of normal LLMs versus this Jev model.
