Browny

Browny, Cloud & AI Architect 🦥
✍️ Writer of《非正式寫作》newsletter

[Steph Zhang @steph_zhang]

https://t.co/soMlXS55jU

[Viking @vikingmute]

/handoff 确实是非常好的 skill，其实就是一句话：
https://t.co/IgglSHLuL0

翻译过来就是：

将当前对话压缩成一份 handoff 文件，让新代理或另一个 session 能无缝接手。

文件保存到临时路径（使用 mktemp -t handoff-XXXXXX.md），必须先读取再写入，避免覆盖冲突。

根据用户提供的 argument来定制摘要内容。

不重复已存在于其他 artifacts的内容，只需引用路径或链接。

他说的两大用途是：Fire and forget 和 DIY Subagent，我用来也是这个，还有就是当一个工具实现效果不好的时候，我可以生成 handoff 文件交给其他的工具去继续处理。

[signüll @signulll]

the world is undergoing a fundamental transition where apps are becoming agents & it’s well underway.

this matters cuz the unit of distribution is changing. i.e. apps were how capabilities reached users.. neatly bundled with ui, brand, billing, & a discovery surface. if agents become the new distribution layer, everything downstream has to be rewired from discovery, trust, monetization, brand, to even what it means to “ship” a product.

shifts to the atomic unit of distribution are rare in modern history which is exactly why this opens opportunity scopes at every layer of the stack, from silicon up through the interface.

[Cormac @cormachayden_]

software engineers before vs after agents

[Jason Ng 阿禅 @jason5ng32]

3 年前我做的，目前日活还有 1k 多的 Chrome 扩展 Macify 发布 v2 了，主打功能依然是将苹果华丽的航拍视频，变成 Chrome 的新标签启动页。我觉得没有比这更漂亮的启动页了。

相比之前版本的变化：

1. 增加「禅意模式」，配合惬意的航拍视频和呼吸引导图案，工作累了，可以立马进行一次正念练习。
2. 增加「出去走走」，告诉你下一次日出和日落的时间，不要老坐在电脑前，要运动运动了。
3. 即使你用的不是 macOS ，依然可以使用。

https://t.co/JI0SlLlRiA

[S Li @YanyuRensheng]

报告的核心观点：

Agentic AI 对科技服务商的冲击，会比上一轮生成式 AI 更直接。

生成式 AI 主要改变“知识生产效率”，Agentic AI 开始改变“服务交付方式”。对传统科技服务商来说，这动到的是收入底座。

过去很多 IT 服务、系统集成、外包、运维、软件工程项目，本质上依赖大量人力交付。客户买的是工程师、顾问、项目经理和交付流程。

但如果 Agent 可以完成一部分测试、迁移、工单处理、运维监控、根因分析、客服响应、财务分析，传统按人天、人月收费的模式就会受到挤压。

这篇文章里有几个数据值得注意：

1. 超过 80% 的受访企业高管已经在做 Agentic AI 试点

2. 约 12% 的企业已经在多个职能中规模化部署

3. 半数企业计划在未来 6 个月加大规模化部署投资

4. 约四分之三企业预计整体 IT 支出会继续增长

5. 但传统科技服务核心市场可能被压缩 20%–30%

6. 到 2030 年，Agentic AI 也可能带来 1000 亿到 4000 亿美元新增支出机会

这里的关键矛盾是：

科技服务市场整体可能还会增长，但原来的服务形态会被重构。

也就是说，市场不会简单消失。消失的是一部分低附加值、执行型、按人力堆出来的服务收入。

新增的是另一类需求：

1. Agent 架构设计

2. 多 Agent 编排

3. Agent 安全与治理

3. 企业系统集成

4. 工作流重构

5. 人机协同运营模式

6. 行业场景 Agent 定制

7. 结果导向的业务转型服务

目前看，企业自己做 Agentic AI 的意愿很强。很多大型企业会把能力内建到自己的全球能力中心里，不再长期依赖外部服务商。

这会削弱传统外包收入。

但企业真正把 Agentic AI 做到规模化，又会遇到三个现实问题：

1. 和现有系统集成很复杂

2. 内部缺少足够的 AI 与工程人才

3. Agent 的安全、权限、行为边界和治理风险更高

所以服务商仍然有位置。只是这个位置不再是“帮客户多派一些人做项目”，而是“帮客户重新设计人和 Agent 如何一起工作”。

这会带来两个新价值池。

1. 第一类是 Agentic AI 工作流服务。

包括基础设施、模型接入、Agent 工程、多 Agent 系统、编排平台、可观测性、安全治理、快速原型和规模化部署。

这类服务更偏技术底座。

2. 类是业务职能转型。

这类机会更大。因为 Agentic AI 不只进入 IT 部门，还会进入客服、销售、财务、法务、研发、供应链、医疗、金融风控和制造流程。

未来科技服务商大概率会分化成四类角色：

1. Agentic AI 使能者

提供云、数据、模型、架构和 Agent 基础能力。

2. 标准化 Agent 实施者

帮助客户快速部署第三方 Agent 方案，适合通用业务问题。

3. 定制 Agent 开发者

围绕企业独特流程和行业场景，开发专属 Agent。

4. 端到端工作流重构者

不只做 Agent，而是重设计整条业务流程和组织协作方式。

其中最有价值的，可能是第四类。因为 Agentic AI 的长期价值，不在于多部署几个智能体，而在于把原来的流程重新设计一遍。

这也是传统服务商必须转型的地方。

1. 它们需要从“卖人力”转向“卖结果”。

2. 从“项目交付”转向“持续能力”。

3. 从“系统集成”转向“业务流程重构”。

4. 从“按人天收费”转向“订阅、固定价格、按效果分成或生产力承诺”。

文章里提到，超过 70% 的企业更偏好替代性定价模式。

这个信号很强。

当 Agent 提高交付效率后，客户不会愿意继续按传统人力投入付费。服务商如果还用人天、人月模型，很容易出现收入和利润双重压力。

未来更合理的模式可能是：

1. 按 Agent pod 收费

2. 按平台订阅收费

3. 按业务结果收费

4. 按节省成本或新增收益分成

5. 按可验证生产力提升收费

这也会倒逼服务商建设自己的平台、工具链和可复用 IP。

仅靠项目制交付，很难在 Agentic AI 时代形成规模优势。

[🌞Sunny哥 @BTC__Sunny]

当年有人敢质问乔布斯：
你凭什么确定自己的决策就是对的？

乔布斯只沉默了一瞬，一句话直接怼到别人哑口无言

直到今天，这套逻辑依然能受用终身。

[howie.serious @howie_serious]

agency is a muscle。

很喜欢notion 创始人 evan zhao 的这个比喻。干净利落，抓住了 agency 的本质。

过去几十年，衡量工具好坏的标准几乎只有一个：效率。更快、更准、更省力。ai 更是把这条逻辑推到了极致——一切皆可自动化，一切皆可外包。但这里藏着一个危险的盲区：当工具接管的不是洗碗这样的纯机械劳动，而是需要判断力、创造力和好奇心参与的认知过程时，效率的提升可能正在悄悄侵蚀一种比效率更稀缺的东西：agency。

“agency is a muscle. tools can strengthen it — or let it atrophy.” 肌肉遵循一条铁律：用进废退。它需要阻力才能增长，需要持续锻炼才能维持。agency 也是如此——它不是天赋，不是人格特质，而是一种需要不断施加认知阻力才能保持的能力。

ai 对人类 agency 的影响，要么是加强（strength），要么是弱化萎缩（atrophy）。 strengthen 的路径是让人在使用过程中做更多决策、承担更多判断；atrophy 的路径是让人外包判断、放弃思考。医生使用 ai 辅助检测息肉三个月后，独立检测能力下降；年轻人越依赖 ai 做决策，批判性思维得分越低。这就是 the age of de-skilling 正在发生的事。

karpathy 发过一条推：agency is significantly more powerful and significantly more scarce. 如果 agency 比 intelligence 更稀缺、更强大，那么任何让 agency 萎缩的工具，都在摧毁人类最稀缺的资源。ai 的 agency 是工具理性，人的 agency 是目的理性。前者是手段，后者才是目的。

使用 ai，最重要的一条原则：它对使用者 agency 的净效应。每一个产品、每一个 ai agent、每一个工作流，都值得用这把标尺重新丈量一遍。

[宝玉 @dotey]

这个可视化看claude code原理、功能的网站不错，尤其是 Agent Loop 动画，很直观
https://t.co/z7P2DB8TCm

[kaize @0x_kaize]

https://t.co/ScYWvkqPa4

[James Clear @JamesClear]

Unexpected forms of generosity:

-Being early can be a form of generosity. You wait, so they don't have to.

-Leaving something unsaid can be a form of generosity. You don't always need the last word.

-Delivering your work on time can be a form of generosity. You make life easier for everyone downstream.

-Not taking things personally can be a form of generosity. You give people the space to say things imperfectly.

[Browny @brownylin]

太多東西需要被管理 XDDD

[a16z @a16z]

Why OpenClaw will create jobs:

" I can't see these as doing anything other than creating a lot more jobs. Like there's just so much more stuff that needs to get built and needs to get managed."

"The same thing happened with cloud, right? When cloud came around, I remember sitting in my big corporate job thinking 'half of these people will be gone in five years.'"

"And then, lo and behold, 10 years later, 20 years later, the IT organizations are bigger than they were then, and they're spending even more money."

" Trying to ignore this new technology and waiting for it to go away usually doesn't work."

@stuffyokodraws @appenz on the AI + a16z Podcast

[Luyu Zhang @goocarlos]

随着 AI 和语音输入的普及，我们需要重新思考办公室的设计逻辑。

过去十年，开放式办公室是主流。理由是促进协作、节省成本。但这个设计是建立在一个假设上的：工作是用键盘和眼睛完成的，噪音可以忍受。

这个假设正在失效。

当你开始用语音跟 AI 对话、用语音转文字写报告、用语音指令操控工具——开放空间就从"低效"变成了"不可用"。你没办法在一个十人大厅里对着空气说话。

所以我认为，下一代办公室的基本单元不是工位，而是小书房。

每个人应该有一个完全封闭的独立空间。大桌子、几台显示器、窗帘、可以调节的灯光。一个你可以完全掌控的物理环境——可以大声思考，可以跟 AI 对话，可以进入深度工作状态，不需要顾及任何人。

这是认知主权，不是特权。

而认知主权的价值，远比很多管理者意识到的要大。当一个人真正进入心流状态，不被打断、不需要压低声音、不需要管理自己对周围人的影响——我相信，如果这种状态能被合理制度化，团队每天的实际生产力可以提升 2 到 3 倍。这不是夸张，这是专注本身的复利。

我们在湾区已经付诸实践了。我们拒绝租任何超过 7 人容量的房间。需要更多空间？再租一个小的。空间不够切，就切得更多。我们彻底告别了大开间——作为 CEO，我甚至觉得 7 人还是太多，还可以切得更小。

当然，协作仍然重要。但协作空间需要被主动设计，而不是靠"大家挤在一起自然就会合作"。你需要刻意制造摩擦点——一个有吸引力的午餐区，一个大家都会路过的咖啡机——让偶遇和碰撞真实发生。

有人会说这太贵了。

但算一笔账：一个设计合理的封闭小间只需要 6-8 平方米。比起传统工位加会议室的低效组合，它的实际利用率要高得多。如果生产力真的能翻倍，多花的租金根本不值一提。

混合办公解决了"要不要来公司"的问题。

下一个要解决的问题是：来了之后，给你一个真正能工作的地方。

[Readwise @readwise]

Introducing the Readwise CLI.

Anything you've saved in Readwise (highlights, articles, PDFs, books, youtube, newsletters) is now instantly accessible from the terminal.

For you, and your AI agents.

npm install -g @readwise/cli

[Tantan Fu @luckytantanfu]

Vertical Tab 终于来到了 Chrome
升级到最新版本， chrome://flags/#vertical-tabs 设置打开即可

[GitHub Projects Community @GithubProjects]

Obsidian just got agent-ready.

obsidian-skills teaches AI how to actually work with your vault:
• write valid Obsidian Markdown
• generate Bases databases
• create JSON Canvas diagrams
• manage notes via CLI

Turn your AI into a real second brain.

[signüll @signulll]

you should treat everything in your life as a cherry on top as opposed to the actual sundae.

[George @odysseus0z]

https://t.co/GqhyL4KRJw

[Lenny Rachitsky @lennysan]

My biggest takeaways from @qasar:

1. The real AI revolution over the next 5 to 10 years will happen in the physical world, not in software. While everyone obsesses over ChatGPT, Claude and coding agents, the real impact will come from autonomous vehicles, mining robots, and farming equipment. They’ll save lives (over 30,000 die annually in U.S. car accidents), enable mobility for disabled people, solve labor shortages in dangerous industries where nobody wants to work, and much more.

2. AI isn’t replacing jobs in industries like trucking and farming—it’s arriving just in time to fill a labor gap that already exists. The average age of a farmer in the U.S. is in the late 50s. Long-haul trucking jobs go unfilled not because people can’t do them but because the tradeoff isn’t worth it anymore; a family can choose DoorDash or Uber so the parent can pick up their kid. Qasar’s view is that physical AI will fill gaps created by demographic shifts and changing preferences, not displace workers who want those roles. He’s careful to say this doesn’t mean there are no downsides, but that the framing of “AI is coming for your job” misses the more immediate reality.

3. Comparing Chinese AI companies to American AI companies is a category error. Qasar uses Huawei as his example: the company’s name means “China’s ambition,” roughly a quarter of its employees are Communist Party members, and its goal is not to grow profits but to extend the state. So when people say Chinese EVs are outcompeting Detroit, they’re comparing a government-backed entity with no profit constraint to companies like Rivian that get hammered by public investors for losing money. Qasar says that if American companies were freed from profit expectations the same way, they’d field comparable products. The point isn’t that China is incompetent or not a serious competitor; it’s that the comparison framework most people use is wrong.

4. The Industrial Revolution is the best mental model for AI. Just like the late 1800s brought child labor and monopolies but also unprecedented access to healthcare, heating, cooling, and material goods, AI will have downsides we must address while delivering massive benefits. The key: don’t pump the brakes on technology to protect jobs—that hurts the people you’re trying to help most. Find solutions that account for workers while enabling progress.

5. Building under the radar can be your competitive advantage. Qasar built Applied Intuition for nearly a decade without a social media presence. One of the company’s early core values was “Our best work is done alone and quietly.” His reasoning: every minute spent on a podcast, a post, or content for public consumption is a minute not spent on customers and the product. Qasar adds an important caveat—he could afford to stay quiet because he was already known in the ecosystem. Founders without an existing network may need the visibility that public presence creates.

6. Qasar thinks most Silicon Valley CEOs lack taste—both in the artistic sense and in the sense of making good operational decisions—because their life experience is too narrow. A founder who grew up in Cupertino, went to Berkeley, and immediately started a company has never experienced what it’s like to be at the bottom of a 100,000-person organization. Qasar spent over a decade at GM and Bosch and says that experience—the bureaucracy, the bad tools, the disconnected leadership—directly informs how he leads Applied Intuition today. His broader point is that taste comes from exposure to a wide range of human experience: backpacking, reading old books, working in different cultures and industries.

7. Successful companies almost always show traction early. If you’re two years in and the market isn’t giving you increasingly specific signals about what to build, consider resetting. The foundation might be wrong—co-founders, market, or life phase. Your first startup is practice; treat it as building the muscle of being a founder, not as your magnum opus.

8. Emotions are a filter that distorts decision-making, and the goal should be to remove that filter so the “raw image” of the decision comes through. Qasar doesn’t mean leaders shouldn’t have empathy; he means that attachment to your own idea, the desire to be right, and the tribal instinct to follow the loudest voice are all emotional distortions. His practical heuristic: the same decision, presented to multiple people independently in the company, should produce the same result. If it doesn’t, some emotional filter is warping the signal. This connects to his broader philosophy of creating a culture where the best idea wins regardless of who proposed it or how senior they are.

9. Qasar’s advice on company values: don’t invent them philosophically. Instead, write down the 5 to 10 things that explain why your company is already successful, and those become your values. Applied Intuition’s values include “Move fast, move safe,” “Never disappoint the customer,” “Technical mastery,” “High output matters,” “Laugh a lot,” and “Half of the work is follow-up.”

10. Treat your first startup as a zero—a practice round, not destiny. Qasar tells founders leaving Applied Intuition to start companies that their first three years will likely produce nothing, and that’s fine. Founding is a craft, like woodworking. If your first table is wobbly, you don’t quit—you build another one. He thinks a lot of founders, especially first-timers, put so much pressure on themselves to succeed immediately that they miss the real value of the experience: learning and building the muscle. His own third company is the most successful by far, and he sees this pattern repeatedly. There are entire funds focused exclusively on multi-time founders for exactly this reason.

[Olivia Moore @omooretweets]

🚨 The @a16z consumer AI Top 100 is back!

For the sixth time, we ranked consumer AI websites and mobile apps by usage (monthly unique visits and MAUs).

This edition, we changed the rules. Here's why - and what the new list says about where consumer AI is heading 👇