Jev 是什么：只输出决策和置信度、不写字的模型
介绍 Jev 的定位——agent 每天大量调用 LLM 只为拿一个「是/否」，Jev 用类型化问题换回答案加置信度，演示面板显示 6 个 agent 跑了 17233 次决策、中位 3ms。
Jev AI is a $40M model built by an ex-OpenAI researcher that can't write a single word. It can't chat, can't code and can't read an image, and it launched just 2 weeks ago from Diogo Almeida, who worked on the RLHF research behind ChatGPT and then built the opposite. Your AI agent spends most of its day not working but deciding: is this urgent, which tool is next, which agent takes it, are we done, and every one of those is a full LLM call burning thousands of tokens of prose to get back 1 word: "yes." Jev skips the prose, so you send state and a typed question and get back an answer with a confidence score and nothing else, which means it can't hallucinate a format it was never allowed to write. The demo dashboard shows 6 agents running 17,233 decisions at 3 ms median and $0.00003 per call, while TypeSafe's own benchmark puts it at 193.6x faster and 444.6x cheaper, with input at $0.042 per 1M tokens and output free. Your LLM is the slow brain that thinks, and Jev is the reflex that routes it. But the real tell is the name, because Jev comes from William Stanley Jevons, who noticed in 1865 that better engines didn't cut England's coal use but made it burn more. Make a decision 444x cheaper and nobody makes fewer decisions, they build agents that make 444x more. Cheap reflexes don't shrink the swarm, they breed it.