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Agent少自己找代码：SWE-bench主模型成本降29%","动察 Beating AI 快讯，开发者 David 基于 Jev 开源了一个专门给 Coding Agent 找代码的研究工具 Jevgrep。\n用户只要问一句「登录校验写在哪里」，它就会用 TypeSafe 的决策模型 Jev 逐层搜索代码库，找出相关文件和源码片段，再交给 Claude Code、Codex 等 Agent 继续修改和测试。\n它主要解决 Coding Agent 很费 token 的「找代码」环节。Jevgrep 不会先把整个仓库塞给模型，也不是只做一次语义搜索。它会先判断哪些目录值得继续找，再检查相关文件和代码声明，最后返回源码片段、行号和后续阅读线索。仓库还提供了 Skill，让 Agent 知道什么时候调用 `jg` 收集上下文。\n最新 SWE-bench 实验用了 10 个 Python 任务。使用 Jevgrep 和不用 Jevgrep 都完成了 8 个，但 GPT-5.6 Sol 的总成本从 7.62 美元降到 5.44 美元，减少 28.63%。作者最初在 X 上写的是 40%，仓库随后更新实验结果，目前已经改成「约 30%」。\n不过，这个数字只统计 Sol 的费用，没有把 Jev 算进去。实验日志中能够确认的 Jev 调用费用已经至少有 1.57 美元，部分调用缺少完整计费记录，实际总额未知。此外，这组实验只有 10 个任务，而且每题只跑了一次。",1790592180000,null,"Mon Sep 28 2026 10:43:00 GMT+0000 (Coordinated Universal Time)",{"id":21,"title":22,"content":23,"publishTime":24,"important":9,"sourceName":10,"language":18,"dateString":25},195325,"「不会聊天」的AI可以怎么玩？开发者用Jev接管Agent快速决策","动察 Beating AI 快讯，前 OpenAI 研究员 Diogo Almeida 创办的 TypeSafe 昨天刚发布新模型 Jev。它不生成文本，只返回选项、分数和概率。社区很快出现一批开源项目，开始把 Jev 塞进 Agent 和软件流程里。\nBrowser Use 做的 jev-ultrafast 最直观。浏览器每走一步，Jev 都会从当前页面里判断「下一步做什么、操作哪个元素」，只有需要填写文字时才调用一个小型语言模型。团队用它在 Google Flights 搜索苏黎世到伦敦的航班，一次完整运行只用了 7.1 秒。\nJev Codex Router 让 Jev 先判断每轮编程任务的难度，再决定交给不同档位的模型；jev-mcp 则把它做成 Agent 的事实核验、Prompt Injection 检测和语义排序工具。\n这些项目有个很明显的共同点：没人拿 Jev 当聊天机器人，而是把它塞进软件和 Agent 的执行链里，专门负责那些高频、有限选项的判断。",1789627680000,"Thu Sep 17 2026 06:48:00 GMT+0000 (Coordinated Universal Time)",{"id":27,"title":28,"content":29,"publishTime":30,"important":31,"sourceName":32,"language":18,"dateString":33},210382,"Jev开发商TypeSafe AI以75亿美元估值融资8.7亿美元，a16z领投","PANews 10月9日消息，据彭博社报道，人工智能初创公司TypeSafe AI完成约8.7亿美元融资，本轮融资由风险投资机构Andreessen Horowitz（a16z）领投，公司估值达到75亿美元。据悉，TypeSafe AI旗下AI模型Jev在发布数周后迅速走红，其联合创始人Diogo Almeida表示，发布视频走红后，公司获得大量企业高管、开发者和投资者关注，目前已被约三分之一的《财富》500强企业使用，并在数天内突破100万用户。",1791551340000,true,"PANews","Fri Oct 09 2026 13:09:00 GMT+0000 (Coordinated Universal Time)",{"id":35,"title":36,"content":37,"publishTime":38,"important":9,"sourceName":32,"language":18,"dateString":39},198432,"TypeSafe AI与 OpenRouter 推出 Jev 智能路由器提升 LLM 调用效率","PANews 9月26日消息，TypeSafe AI在X上最新发帖称，OpenRouter 已集成 Jev 路由能力至全部 LLM 调用，通过 typesafe\u002Fjev-router 在每次请求时动态选择最优模型与推理强度，实现“cache-aware”的模型路由，以平衡质量、速度与成本。该路由器可根据上下文命中缓存，避免重复计算，减少无效 token 消耗，优化复杂 agent 工作流性能。部分开发者称，其在大规模真实样本评分任务中实现了近乎100%准确率，但也反映随着使用激增，响应时延有所上升。",1790383500000,"Sat Sep 26 2026 00:45:00 GMT+0000 (Coordinated Universal Time)",{"id":41,"title":42,"content":43,"publishTime":44,"important":9,"sourceName":10,"language":18,"dateString":45},198370,"Jev把TypeSafe估值炒高50倍？传正谈10亿美元融资","动察 Beating AI 快讯，《The Information》称，Jev 开发商 TypeSafe AI 已开始与投资者讨论新一轮融资，规模可能达到 10 亿美元甚至更高。部分投资者已经提出按 100 亿美元以上估值投资。谈判仍处早期，最终金额和估值都可能变化，TypeSafe 拒绝置评。\n一周多前，TypeSafe 刚宣布完成 4000 万美元种子轮，由 DCVC 领投。PitchBook 当时给出的估值约为 2 亿美元。如果按最新的 100 亿美元报价计算，短短几天内，投资者给 TypeSafe 的估值已经抬高约 50 倍。\nJev 上线后的采用速度确实很快。Vercel 称，它进入 AI Gateway 后 24 小时内就被近 13% 的付费团队使用，是该平台历史上采用速度最快的新模型。TechCrunch 此前还报道称，早期需求一度让 TypeSafe 的 API 无法正常服务。\nJev 不负责生成长文本，主要在预设选项里做分类、评分和是非判断，再给出概率，适合塞进 Agent 循环里做路由、安全审核和任务分流。TypeSafe 自己测得的最高提速达到 193.6 倍，但也明确表示，这一数字属于真实使用中表现较好的情况，并非所有任务都能达到。Vercel 在具体安全分类任务上的测试则测到约 5 至 18 倍提速。",1790347620000,"Fri Sep 25 2026 14:47:00 GMT+0000 (Coordinated Universal Time)",{"id":47,"title":48,"content":49,"publishTime":50,"important":9,"sourceName":10,"language":18,"dateString":51},194745,"前OpenAI研究员做了个「不会聊天」的AI：Jev只做判断，最高快200倍","动察 Beating AI 快讯，前 OpenAI 研究员 Diogo Almeida 创办的 TypeSafe AI 推出新模型 Jev。它有点像一个能读懂自然语言的超级分类器，不生成文本，只返回选项、分数和概率，专门给软件做判断。\n普通大模型需要一个 token 一个 token 往外生成，Jev 则可以并行给出多个结果。TypeSafe 还用新的 RLCD 方法训练它的置信度，让模型在给出判断的同时，告诉程序自己有多大把握。\nTypeSafe 用安全告警、Agent 审查、发票处理和客服做了 4 组自动化工作流测试。在这套自建评测里，Jev 最高比 Claude Sonnet 5 快约 193.6 倍，比 Claude Opus 5 便宜约 444.6 倍。\nTypeSafe 把 Jev 称为首款「System One Model」（快速决策模型），名字来自卡尼曼《思考，快与慢》里的 System 1。它专门处理分类、打分、路由和下一步决策这类快速判断任务。",1789529460000,"Wed Sep 16 2026 03:31:00 GMT+0000 (Coordinated Universal 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