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Turn unmanaged AI into a managed agent identity with lifecycle controls in minutes. Use the Agent 365 CLI and SDK to assign an Entra Agent ID to any agent. See how it works. Take control of every AI agent, managed or not, running in your environment using Agent 365 and Microsoft Entra. Surface agents across AWS Bedrock, Google Vertex, Databricks, and Salesforce in one registry, assign Entra Agent IDs via CLI or SDK, and enforce least-privilege access through Conditional Access policies and Agent Blueprints, all without rebuilding your existing identity infrastructure. #Agent365Entra# #agent365# #microsoftsecurity# #microsoft365# #aigovernance# #agenticai#

.@Mintlify grew 10x in a year. CEO @handotdev shared what's in their internal AI stack: Code: @claudeai @cursor_ai @tryreplicas Design: @replit @lovable Personal agents: @gumloop Code review: @cursor_ai @greptile Agent ops: @slackhq @temporalio Support triage: @parahelp_ai @plainsupport @linear Sales intel: @tryattention @salesforce @meetgranola Knowledge base: @notionhq @mintlify

Luke Pierce 表示，Starbucks 每年在软件上花费 4 亿美元。 昨天，Starbucks 宣布将脱离 IBM 和 Microsoft，转而在内部构建自己的定制系统。 消息传出后，IBM 股价下跌 3%，Salesforce 下跌 4%。

Q：ChatGPT Work 桌面端和 Claude Cowork 桌面端有什么区别？ 两者现在都是桌面端智能体，都能操作本地文件，都能用 Computer Use 控制你的电脑，都支持定时任务。但实际用起来，路径和体验差别不小。 1. 执行架构不同。 Cowork 在你的电脑上运行一个隔离的 Linux 虚拟机作为沙箱，所有文件操作都在这个本地沙箱里完成，生成的文件（.docx、.xlsx、.pptx、.pdf）直接保存到你指定的文件夹。 ChatGPT Work 的桌面端继承了 Codex 的沙箱和权限控制体系，用操作系统原生隔离机制（macOS 上是 Seatbelt，Windows 上是 Windows Sandbox），同时还有一个内置浏览器，不需要额外装扩展就能上网查资料、操作网页工具。 2. 操作电脑的方式不同。 ChatGPT Work 桌面端的 Computer Use 可以在后台操作你的其他应用，点击、打字、移动文件，你会看到屏幕上出现一个"不是你在动"的第二个光标。 Cowork 也有 Computer Use（目前仍是研究预览阶段），通过 Claude in Chrome 扩展操作浏览器，通过桌面端直接操作应用。 3. 应用连接方式不同。 ChatGPT Work 用统一的 plugins 目录，60 多个连接器对接 Slack、Teams、Google Drive、SharePoint、Salesforce 等。你在提示词里用 @ 指定应用名就能拉数据。 Cowork 用 MCP（Model Context Protocol，模型上下文协议）连接器，对接 Slack、Notion、HubSpot、Jira、Linear 等，还有 11 个官方行业插件（销售、法务、营销、财务等），也支持自建插件。 4. 产品结构相似但不同。 ChatGPT 桌面端现在是三合一：Chat、Work、Codex 在同一个 App 里通过模式切换器选择。 Claude 桌面端最近也改版了，从原来的三个标签（Chat、Cowork、Code）合并成了两个标签：Home 和 Code。 Home 里 Chat 和 Cowork 共享同一个首页，对话、Cowork 任务、项目和文件都在同一个侧边栏里，你在消息框左下角切换 Chat 和 Cowork 模式。 Code 标签是 Claude Code 的桌面界面，专门用于软件开发。 结构上，两家现在很像：都是把日常对话、知识工作、编程三种模式塞进了同一个桌面 App。 5. 跨设备能力不同。 Claude Cowork 从 7 月 7 日开始向网页和手机端扩展（Beta，Max 用户优先，其他付费计划陆续开放）。 Cowork 任务现在可以远程跑在 Anthropic 的服务器上，关掉电脑也能继续执行，你可以在手机上查看进度、回复 Claude 的问题、或在另一台设备上接着干。定时任务也能在后台跑了。但有一个限制：如果任务需要读写本地文件、用浏览器、或用 Computer Use，你的桌面端 App 必须保持打开状态，远程会话通过桌面端去够这些本地资源。 ChatGPT 这边，Chat 对话可以在网页和桌面端之间同步。但 Work 对话目前不互通：网页/手机端创建的 Work 对话留在云端，不会出现在桌面端的 Work 里；桌面端的 Work 线程和本地文件也留在那台电脑上。Codex 桌面端任务不会出现在网页端，但可以通过手机 App 的 Remote 标签远程查看。 Claude Cowork 的跨设备同步走得更前面一步，同一个会话可以在桌面、网页、手机端之间流转。ChatGPT Work 目前云端和桌面端是割裂的，这是 OpenAI 明确说了"at launch"的限制，后续大概率会补上。 【来源：

Starbucks spends $400 million a year on software. Yesterday they announced they're moving off IBM and Microsoft to build their own custom systems in-house. IBM dropped 3% and Salesforce dropped 4% on the news. And honestly this is, unequivocally, the biggest signal I've seen since OpenAI and Anthropic launched their consulting arms back in Q1. The largest companies in the world are done paying for software that half fits how they work. We saw this coming about a year ago. Moved everything we build off Airtable and low-code tools and went fully custom. Already paying off, and it's only going to compound from here. This is the opportunity right now. You get all of a company's data into one system. You build out a single operating system for the entire business. You cut out bad, redundant processes. Then you layer AI on top of it, under the correct processes. That's the core of AI consulting. Helping companies actually operate better. There are a lot of fly-by-night offerings circulating right now when it comes to Ai Services. For example, 'second brains'. Throwing scattered data into a second brain while the processes underneath stay broken does nothing. The companies who will absolutely destroy their competition over the next 5 years are rebuilding how they work from the ground up. Starbucks is showing you what other companies will be doing over the next several years. Your job is to position yourself to facilitate that process for as many companies as you can.

SpaceXAI's Grok 4.5 takes the #1# spot on AutomationBench-AA with a score of 51%, ahead of Claude Fable 5 (49%) and Claude Opus 4.8 (48%) at roughly a quarter of their cost per task - the first model to complete more than half of workflow objectives without breaking any business rules AutomationBench-AA, our independent leaderboard for @zapier’s AutomationBench, tests whether AI agents can automate real SaaS workflows while adhering to business rules. The test set is private to prevent contamination. Models complete 657 tasks across 40 simulated app environments including Gmail, Google Sheets, Slack, Salesforce, and HubSpot, and the headline score is the share of objectives completed without violating any guardrails. Key takeaways: ➤ Grok 4.5 completes more objectives than any other model: It completes 79.9% of task objectives and strictly passes 21.9% of tasks. This is the highest we’ve measured on both outcomes, exceeding Claude Fable 5’s 73.3% objective completion and Claude Opus 4.8’s 19.3% of fully-completed tasks ➤ Grok 4.5 pushes out the Pareto frontier of score vs. cost per task: At $0.34 per task, it is both cheaper and higher-scoring than every other leading model - Claude Fable 5 ($1.35 per task), Claude Opus 4.8 ($1.46), GPT-5.5 (xhigh, $1.28), and Gemini 3.5 Flash (high, $0.49) ➤ It is extremely token-efficient: Grok 4.5 uses ~8k output tokens per task, the fewest of any leading model - less than a quarter of Claude Opus 4.8 (32k) and a third of Gemini 3.5 Flash (24k). Its total token usage of 0.44M per task is among the lowest on the leaderboard. Low cost is driven by this efficiency as well as low token pricing ➤ Grok 4.5 uses fewer turns with many parallel tool use: Grok 4.5 resolves tasks in ~16 turns, fewer than GPT-5.5 (xhigh, 25) and less than half of Gemini 3.5 Flash (high, 35), while making the most tool calls per task of any leading model (52.5). It batches 3.3 tool calls per turn, compared to ~2.5 for Claude Opus 4.8 and ~2.0 for GPT-5.5 (xhigh) ➤ Guardrails still get broken: Grok 4.5 triggers 0.63 violations per task, above Claude Opus 4.8 (0.55) and Gemini 3.5 Flash (0.46). At 13.0 objectives completed per violation, it trails Gemini 3.5 Flash (15.0) and Claude Opus 4.8 (13.5) ➤ Its strongest lead is in the hardest domain: Grok 4.5 completes 71% of Finance objectives, the domain with the lowest average score, ahead of Claude Fable 5 (64%) and Claude Opus 4.8 (62%) Congratulations to @SpaceXAI and @elonmusk on topping the leaderboard!

Bitget已上线10只热门股票永续合约，覆盖半导体产业链、消费出行等热门板块： $VOO 标普500ETF $SOXX 半导体产业链ETF $TXN 模拟芯片龙头 $AMKR 先进封测龙头 $ASX 全球最大封测厂 $WEN Wendy’s $AAL 美国航空 $PDD 拼多多 $BAC 美国银行 $CRM Salesforce #买美股首选Bitget#

Codex 公认最强的 6个 Skill，有没有你没装的 1、Superpowers（227k star） 给 Agent 装上一整套资深工程师的工作方法： 先拆需求，再写计划，按测试驱动开发，最后再派一个子 Agent 回头审查自己的代码。 这是目前最强的 Skill 之一，实至名归 2、OpenAI 官方插件 把 Codex 变成不同岗位的员工，让它不只会写代码，而是进入全岗位工作流。 数据分析可以接 Snowflake，销售可以接 Salesforce，另外还能做投研分析、内容创意、PPT 生成等任务。 开箱即接入 62 个商业应用、110 个预置 Skill。 现在非开发者已经占 Codex 用户的两成，而且比例还在持续上升 3、claude-mem（82k star） 给 Codex 装上长期记忆。 每次对话里的关键信息会自动压缩归档，新开会话时自动注入，不用每次都从项目背景讲起。 多个 Agent 通用，多个代理也能共享同一套记忆资源 4、Agent-Reach（27.7k star） 给 Codex 装上一双互联网的眼睛。 一条 CLI 就能让它去读、去搜 Twitter、Reddit、YouTube、小红书、B 站、公众号等 17 个平台。 否则 Agent 只能搜网页；有了它，就能翻帖子、看视频、抓热点和用户反馈 5、GitNexus（42k star） 把几十万行的老项目整理成一张代码图谱，让 Codex 看懂藏在深处的依赖关系、模块边界和抽象命名。 接手老代码、重构项目、排查历史包袱时，不再像两眼一抹黑 6、Humanizer-zh（10.1k star） 专门去掉 AI 写作痕迹，比如滥用的破折号、空话套话、机械句式。 写文档、README、博客时，最后过一遍非常好用

AI 公司正在疯狂收购： SpaceX → xAI（2500 亿美元） SpaceX → Cursor（600 亿美元） Google → Wiz（320 亿美元） Meta → Scale AI（290 亿美元） OpenAI → io（65 亿美元） Salesforce → Fin（36 亿美元） Winston Weinberg ：在并购中多数买下技术本身并不重要，真正重要的是人才