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jevVIDEO

用 Jev 给 agent 做廉价决策层:1 万次 42 美分

一张图讲清 Claude 思考、Jev 选择、代码执行的架构:路由/打分/审批交给 Jev,含 choice/score/Noul 题型、Browser Use 菜单刷新与真实成本拆解。

Superior
@andreysuperior2026.10.03收录原推发布于 2026.10.02
Superior @andreysuperior原推发布于 2026.10.02
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JEV + YOUR AI AGENT = 10,000 DECISIONS FOR 42 CENTS This one sheet maps the whole setup. From an empty folder to a working AI chief of staff with one API key. Right now your agent calls a frontier model every time it has to pick a worker or approve a draft. Jev answers those calls for a fraction of a cent. The split: Claude thinks, Jev picks, your code pulls the trigger. The setup: 1. Spot the cheap decisions > Routing, scoring, approvals. Anything with a fixed menu of answers goes to Jev. 2. Try it with zero code > One state, one choice question, three options in the playground. 3. Build the router > chief. py, about 40 lines. Below 0.85 confidence the job lands in review. 4. Pick the right question type > choice for "which one", score for "how good", Noul for "yes or no". 5. Refresh the options > Browser Use rebuilds its menu after every click. Its agent finds flights in 7 seconds. 6. Fire questions together > Same models, browser calls down from 1,092 to 101. 7. Read the real price > $0.042 per 1M input tokens, zero for output. 10,000 decisions come to $0.42. 8. Ship a use case > Flights for $0.0039, 1,018 papers for $0.08, 500 emails for 3.5 cents. Your agent stops paying frontier prices for a coin flip, and the big model only wakes up for work that needs it. Put this in one agent this week. Next month's AI invoice will show the difference. The full guide with working code is in the article below ↓

这条是引用着另一条写的:「长文:如何搭好 Jev 驱动的 agent 技术栈」

x.com/andreysuperior/status/2106051443669061790采集于 2026.10.03 10:03