Jev doesn't write emails, it does one thing more ruthless

@NFT_Chen SuSu_酥酥👅 · Sep 18, 2026 · case #658605 · listed via Jev Hub

Still from the clip posted with this case; watch it in the original post on X.

Ran 700 high-intent leads through Jev in 40 seconds to decide which personalized emails to send, auto-sending high-confidence ones and routing low-confidence ones to humans.

The original post, translated

Jev doesn't write emails, it does one thing more ruthless: judging whether this email should be sent to this person! 700 high-intent leads × personalized copy done in 40 seconds: predicting replies, giving confidence scores, catching people-product mismatches. The cost is only $0.09. What an SDR spends two hours thinking about, it treats as a single function call. The large model handles writing, Jev handles judging. High confidence sends automatically, low confidence goes to a human. GTM

Show the original post in its source language ▾

Jev 不写邮件，它只做一件更狠的事：判断这封邮件该不该发给这个人！ 700 个高意向线索 × 个性化文案 40 秒打完：预测回复、给置信度、抓人货错配成本只有 $0.09 SDR 花两小时想的事，它当一次函数调用。大模型负责写，Jev 负责判。高置信自动发，低置信丢给真人。 GTM

The post above is a machine translation from zh; the untranslated text is in the fold-out.

Engagement when collected

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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 sales, ads & marketing. 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. Other posts in the same family are on the sales, ads & marketing page.

📈 Sales, ads & marketing