Virlo 用 Jev 做内容选题筛选
Virlo 的研究 agent 从 1280 万条短视频里用 Jev 逐条判断是否真对口，25 条视频约 7k token、成本约 0.03 美分，高置信度直接放行、不稳的升级给大模型或人工。
Jev is the first AI model that actually fits content research... numerous individuals are sharing poor-quality demos of it; thus, here is the marketing use case that truly resonates. Jev does not engage in writing; instead, it makes decisions You present it with a question and options, and it provides a selection, a score, or a yes/no likelihood, accompanied by a confidence metric that's literally what content research is: thousands of tiny calls a human makes while doomscrolling here's how Virlo wired it in: - a research agent pulls videos from 12.8M+ TikToks, Reels and Shorts in your niche - Jev checks every video first: is it actually on-niche, or just hashtag-stuffing - judged on caption + hashtags + transcript, not tags alone - 25 videos = ~7k input tokens, around 0.03 cents at Jev's pricing - only what passes gets tagged by hook, format and angle - the top outlier becomes a beat-by-beat script the rule: high confidence -> act, shaky -> escalate to a bigger model or a human you don't need a reasoning model to check if a video is on-topic... that's hiring a lawyer to sort your mail
这条是引用着另一条写的：x.com/rewind02/status/2102712931766915139