Kai

中文参考

我和Jev一起重建了我的工作爬虫。 任务：从一家公司的官方主页开始，找到职业，并找到与我的个人资料相匹配的工作。 之前，攻读LLM：~5分钟。 之后，与Jev：在我的测试中刚刚超过20秒。 每家公司对其网站的组织方式都不同。Jev识别职业切入点、选择要关注的链接、识别职位页面并根据我的个人资料对每个职位进行评分。 这就是Jev对我来说有意义的地方：自动化需要大量小决策，比在每一步呼叫LLM具有更快的响应和更低的成本。 将其包装为一项技能：jev-jobs-hunter。 下面是演示。

原帖全文 / EN

I rebuilt my job crawler with Jev. The task: start at a company's official homepage, find Careers, and identify jobs that match my profile. Before, with an LLM: ~5 minutes. After, with Jev: just over 20 seconds in my test. Every company organizes its website differently. Jev identifies the Careers entry point, chooses which links to follow, recognizes job pages, and scores each role against my profile. This is where Jev makes sense to me: automation that needs lots of small decisions, with faster responses and lower costs than calling an LLM at each step. Packaged it as a skill: jev-job-hunter. Demo below.