Jev's speed is really a bit ridiculous.
Ran 8,724 Jev judgments over 724 live ads in 40 seconds to score hooks, offers, and landing-page match.
The original post, translated
Jev's speed is really a bit ridiculous. In 40 seconds, it directly broke down: 37 brands 724 currently running ads 8,724 judgments Each ad is analyzed for: Hook Ad format Offer CTA User awareness stage Whether the ad matches the landing page The total token cost is only $0.09. The most critical thing is, Jev is not "writing ad analysis reports." It is rapidly making thousands of structured judgments. This is exactly
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Jev 这速度真的有点离谱了。 40 秒，直接拆完： 37 个品牌 724 条正在投放的广告 8,724 次判断 每条广告都分析： Hook 广告形式 Offer CTA 用户认知阶段 广告与落地页是否匹配 全部 token 成本只有 $0.09。 最关键的是，Jev 不是在“写广告分析报告”。 它是在高速做成千上万个结构化判断。 这正是
The post above is a machine translation from zh; the untranslated text is in the fold-out.
Engagement when collected
Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.
Where this case fits
Filed under general Jev builds. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Browse the full case library for the work it sits next to.
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Last updated: 2026-09-22 · sources & corrections · every card links to its author's original post