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9月3日周四
  1. Boris Cherny71

    Claude 现可在 Claude Cowork 和 Claude Code 中后台使用你的电脑,像人一样点击、输入和打开应用,同时你可以做其他事。Boris Cherny 评论称后台 computer use 被低估了。

    引用Claude@claudeai

    Claude can now use your computer in the background in Claude Cowork and Claude Code. Give it something to do on your desktop and Claude clicks, types, and opens apps just like you would, while you work on something else.

  2. 公众号:卡尔的AI沃茨67

    实测豆包当国产 Codex 用的 7 种玩法

    作者总结一周高强度使用豆包的经验,介绍如何把豆包当成国产 Codex 使用。核心差异在于豆包把本地电脑和云电脑(Windows 虚拟机)打通,切换即可,而 Codex 本地和云端是两套分开的环境;授权一次飞书后可直接用 PRD、表格、会议预约等内置工具。

  3. Rohan Paul61

    @thehypedotnews 用 Three.js 让 Fable 5.1、Fable 5 和 Opus 5 分别从单张参考图程序化重建 bag end、barad-dûr、rivendell 三个《魔戒》场景,全程经 OpenRouter 运行。

    引用thehype.@thehypedotnews

    fable 5.1 vs fable 5 vs opus 5 – three lord of the rings landmarks, built in 3d from one image the setup: one reference image per scene, one html file per build, everything procedural – no meshes, no textures, no image files, nothing past @threejs from a cdn. each model reads the picture, writes its own prompt from it, then builds to that prompt in the same turn. three named camera shots per scene on keys 1/2/3, so it can be screen-recorded. run through @openrouter tasks: 1. bag end – hobbiton from two frames, outside and in. the round green door has to open onto the room you are standing in 2. barad-dûr – the tower and orodruin from one film still. the eye has to move and track the camera, the volcano erupts on a cycle, the clouds never stop 3. rivendell – jerry vanderstelt's painting. sun shafts that shimmer, water that falls without a break, trees that sway on a gust models: @anthropicai fable 5.1, fable 5, opus 5 total cost, three builds #1 fable 5 – $14.97 #2 opus 5 – $18.53 #3 fable 5.1 – $22.38 wall clock, three builds #1 fable 5 – 38m #2 fable 5.1 – 92m #3 opus 5 – 122m output tokens #1 fable 5 – 298,592 #2 fable 5.1 – 439,435 #3 opus 5 – 724,418 lines of code shipped #1 fable 5 – 2,885 #2 fable 5.1 – 4,021 #3 opus 5 – 5,161 biggest single build, lines #1 opus 5, bag end – 2,410 #2 fable 5.1, barad-dûr – 1,375 #3 fable 5, bag end – 1,319 observations: • fable 5.1 is the only model that furnished the bag end interior – a live fire, panelling, books on the floor, leaded diamond windows, against fable 5's flat color and opus's dark tunnel. the round door outside opens onto that room, the hard part of the brief • what it costs is thinking room. the 128k output ceiling is a thinking budget in disguise: fable 5.1 burned 102,116 of it on reasoning and hit the wall mid-file. opus spent 109,241 and hit the same wall. fable 5 spent 61,240 and finished bag end in one call – the only one that did • fable 5.1's first pass is not the finished thing. its barad-dûr came back with three defects you only catch by looking at it – nothing a read of the code would have flagged • it is the best of the three at being corrected. handed a plain list of what was wrong, it returned 32 targeted patches over two rounds, every one applied first try, and it worked out one of the causes itself instead of guessing at constants conclusion: nine scenes, 12,067 lines and 1.46m output tokens for $55.88 all in – and the cheapest model was also the fastest, by 3.2x! follow @thehypedotnews for 24/7 ai news, analysis and breakdowns

  4. Rohan Paul66

    Meta 发布 Muse Spark 1.3,官方称比 1.2 减少 20% 工具调用和 25% token 用量。作者汇总基准数据:MRCR 256K–512K 得分 98.5,超过 GPT-5.6 Sol 的 91.5;JobBench 64.9、OSWorld 66.9、AutomationBench 49.4,接近 Opus 5 的 65.7、68.3、50.3。

    引用Mark Zuckerberg@finkd

    Muse Spark 1.3 is rolling out today with frontier performance almost too cheap to meter. This is the biggest jump we've made so far on coding and agentic work. Try it in Muse Code and our API. Next up 🍉 and Muse Spark open weights releases coming soon.

  5. GitHub Blog62

    GitHub Copilot 如何在不牺牲任务质量的前提下降低 AI 编码成本

    GitHub 工程师 Erik Kristensen 分享了 Copilot 降本的四项改动:选择性压缩工具输出、移除 view 工具行号前缀(线下推理成本降约 5%,线上用户日均推理成本降约 3%)、压缩 task-tool 提示词(每轮省约 1300 token,每活跃小时归一化成本降 2.9%)、后台任务完成后直接交付结果(AI Credits 用量降约 2.3%)。

    推荐理由:GitHub 用四项改动说明压缩 token 为何要看整个任务而非单次调用,并给出可复用的评估方法与踩坑教训。

  6. Cursor Blog68

    Cursor 推出 Self-Hosted Machines,云智能体可在企业自有机器上执行

    Cursor 发布 Self-Hosted Machines,让云智能体的工具执行迁移到企业自有网络内的机器,智能体循环、推理和规划仍留在 Cursor 云端,通过 worker 的出站 HTTPS 连接对接,Cursor 不会主动连入企业网络。

    推荐理由:官方介绍了让智能体工具执行迁入企业自有基础设施的方案与适用场景, teams 可据此判断何时值得自托管以及如何按需扩容。

  7. Claude:Blog64

    Anthropic 发布 Claude 商务智能体蓝图,含购物与商家智能体参考实现

    Anthropic 发布面向电商、旅游、电信和票务平台的商务智能体蓝图,提供可在数天内上线的 harness、模式和护栏,附购物智能体与商家智能体的完整参考实现及 Claude Code 插件。

    推荐理由:原文给出完整可部署的购物与商家智能体实现、接入方式和合作生态,工程团队可据此评估落地铁路线。

  8. Claude:Blog79

    Anthropic 发布 Claude 电商智能体构建指南及参考实现

    Anthropic 发布构建电商智能体的指南,总结架构、延迟与成本优化、生产运维三部分实践,涉及购物和商家两类智能体,企业客户部署后出现购物车变大和卖家运营效率提升。核心建议包括用单个智能体加技能而非子智能体、将 UI 组件做成工具、用提示词缓存实现 90-99% 命中率、在 harness 中强制安全规则,并开源参考实现 anthropics/commerce-agents。

    推荐理由:Anthropic 根据多个企业部署经验总结电商智能体架构、延迟成本优化和生产实践,并附参考实现,可迁移到类似 Agent 项目。

9月2日周三
  1. Google AI:DEV 作者专属69

    什么是 harness 工程?Google 用 ADK 2.0 与 Antigravity SDK 演示自动修复编码循环

    Google 员工 Shir Meir Lador 介绍 harness 工程,即用确定性组件包裹 LLM,包括编排层、执行沙箱、状态持久化和验证工具,让 Agent 不需逐行人工审查即可安全生成代码。

    推荐理由:原文解释了 harness 工程的构成要素,并给出可运行的沙箱与修复循环示例代码,方法可直接迁移到自己的 Agent 工作流。