Sequoia AI Ascent 2026: The Future of AI

"Sequoia recently hosted their annual AI Summit: AI Ascent, probably one of the most important AI events in the year. They brought together more than 150 leading founders and researchers in AI, including Demis Hassabis, Andrej Karpathy, Greg Brockman, Boris Cherny of Anthropic, Dmitri Dolgov of Waymo, Jim Fan of Nvidia, and many more."

"红杉(Sequoia)最近办了他们一年一度的 AI 峰会 AI Ascent,大概是一年里最重要的 AI 活动之一。他们聚齐了 150 多位 AI 领域的顶尖创始人与研究者,包括 Demis Hassabis(哈萨比斯)、Andrej Karpathy(卡帕西)、Greg Brockman(布罗克曼)、Anthropic 的 Boris Cherny、Waymo 的 Dmitri Dolgov、英伟达的 Jim Fan(范麟熙),等等。"

"Today, I want to share my breakdown of Sequoia's analysis for the future of AI."

"今天,我想分享一下我对红杉这场"AI 未来分析"的拆解。"

"Modern technology has come in layered waves, each building on the one before. Silicon-based transistors gave Silicon Valley its name. Transistors were assembled into systems. Systems were connected by networks. Networks went public as the internet. The internet supported applications like social media in the cloud. The cloud reached our pockets through mobile devices."

"现代科技是一层层浪潮叠上来的,每一波都建立在前一波之上。硅基晶体管给了硅谷它的名字;晶体管被组装成系统;系统被网络连起来;网络以互联网的形态走向大众;互联网在云上撑起了社交媒体这样的应用;云又通过移动设备进了我们的口袋。"

"Today all of those layers power something indistinguishable from magic: artificial intelligence. All of these waves are additive."

"今天,所有这些层一起驱动着一件几乎与魔法无异的东西:人工智能。而这一波波浪潮,是叠加(additive)的。"

"This AI wave is different in 3 ways."

"这一波 AI 浪潮,有三处不一样。"

"1. It's the biggest one yet. During the first 15 years of cloud, software total addressable market grew from roughly $350B to $650B, with cloud capturing about $400B of that."

"一、它是迄今最大的一波。在云的头 15 年里,软件的总可触达市场(TAM)从约 3500 亿美元涨到 6500 亿美元,其中云占了约 4000 亿。"

"AI adds an entirely new layer beneath: Sequoia estimates a roughly $10 trillion services market is now potentially addressable by machines."

"而 AI 在底下又加了一整层全新的东西:红杉估算,如今大约有一个 $10 万亿的服务市场,有可能被机器触达。"

"The exact figure is uncertain — it could be $5 trillion or $50 trillion — but the magnitude is clear. Legal services in the United States alone is a $400B market: one vertical, one country, equal in size to the entire global software industry."

"确切数字并不确定——可能是 5 万亿,也可能是 50 万亿——但量级是清楚的。光是美国的法律服务,就是一个 4000 亿美元的市场:一个垂直行业、一个国家,体量却抵得上整个全球软件业。"

"2. It's the fastest yet. The companies that crossed $1B+ in revenue from the cloud, mobile, and AI tectonic shifts are arriving faster with each successive wave. More billion-dollar AI businesses are likely to emerge in a fraction of the time it took during previous platform transitions."

"二、它是迄今最快的一波。借着云、移动、如今又是 AI 这几次地壳级变动而跨过十亿美元收入门槛的公司,一波比一波来得更快。能做到十亿美元体量的 AI 公司,很可能会以远短于以往平台迁移所需的时间冒出来。"

"3. Why this wave is different. There are 2 types of revolution: Communication — information distribution. Computation — how information is processed."

"三、这一波为什么不一样。革命分两种:通信(communication)——关乎信息怎么被分发;计算(computation)——关乎信息怎么被处理。"

"The internet, the cloud, and mobile were all revolutions in communication. AI is a revolution in computation — and that is a fundamentally different shape of wave."

"互联网、云、移动,都是通信的革命。AI 是计算的革命——这是一种形状根本不同的浪潮。"

"Grady identifies three discontinuous moments that define the current trajectory of AI. The first was November 2022, when ChatGPT revealed the power of pre-training to a mainstream audience."

"Grady(格雷迪)点出了三个定义当前 AI 走向的"不连续时刻"。第一个是 2022 年 11 月,ChatGPT 向大众揭示了预训练(pre-training)的威力。"

"The second came roughly two years later with o1, which surfaced a second scaling law around inference-time compute — reasoning models."

"第二个大约在两年后,随 o1 而来——它带出了围绕推理时算力(inference-time compute)的第二条 scaling law,也就是推理模型(reasoning models)。"

"The third is happening now, with Claude Code and the Opus 4.5 / 4.7 generation, which have demonstrated the power of long-horizon agents."

"第三个正在发生:Claude Code,以及 Opus 4.5 / 4.7 这一代,展示了长程 agent(long-horizon agents)的威力。"

"The first two inflections feel like points on a continuum. Between the second and third there is a hard break, a discontinuous shift in what software can do."

"前两个拐点像是同一条连续曲线上的点。但第二个和第三个之间,有一道硬裂口——软件"能做什么"这件事,发生了不连续的跃迁。"

"Grady offers a deliberately commercial, rather than technical, definition of AGI: if a system can be dispatched to perform a job, recover from failure along the way, and persist until the job is complete, it functionally qualifies."

"Grady 给 AGI 下了一个故意只讲商业、不讲技术的定义:如果一个系统能被派去干一件活、途中能从失败中恢复、并坚持到把活干完,那它在功能上就算数。"

"From Sequoia's perspective as investors, what matters is the practical capability, not the label."

"站在红杉作为投资人的立场上,真正重要的是实际能力,而不是那个标签。"

"For the past several years, AI produced faster horses — applications that made knowledge workers 10–40% more productive without changing the shape of their work."

"过去这几年,AI 造出的是更快的马——那些应用让知识工作者效率提升 10–40%,却没有改变他们工作的形态。"

"The current generation produces cars — applications that deliver 10–40x improvements and fundamentally restructure the work, the workflow, and the organization. AI changes the way that we work, the nature of the work, and the nature of the organization."

"这一代造出的是汽车——那些应用带来 10–40 倍的提升,并从根本上重构工作、工作流和组织。AI 改变的是我们工作的方式、工作的性质,以及组织的性质。"

"Echoing the famous question of Sequoia founder Don Valentine — so what? — Grady argues that what matters is that the race for the $10 trillion services opportunity is now underway."

"借用红杉创始人 Don Valentine(唐·瓦伦丁)那句著名的发问——"那又怎样?"——Grady 认为,真正要紧的是:争夺 $10 万亿服务机会的竞赛,如今已经鸣枪开跑。"

"Two strategies are visible. Foundation model labs are advancing tech-out, expanding capability and pushing into applications from the model layer down."

"眼下能看到两种打法。基础模型实验室走的是"技术往外推"(tech-out):扩张能力,并从模型这一层往下、往应用里挤。"

"Startups (largely Sequoia's portfolio shape) are advancing customer-back, building specialized applications on top of the labs and wrapping themselves around real customer workflows."

"创业公司(大体上也是红杉投资组合的形态)走的是"从客户往回想"(customer-back):在实验室之上做专门化的应用,把自己紧紧缠绕在真实的客户工作流上。"

"Driving a car is nothing like riding a horse, and building one is nothing like caring for one — the strategic playbook for this race looks fundamentally different from prior platform shifts."

"开车和骑马完全是两回事,造车和养马也完全是两回事——这场比赛的战略打法,和以往的平台迁移有着根本的不同。"

"1. Moats. Grady's most counterintuitive piece of advice: in a computation revolution, capabilities change faster than customers do."

"一、护城河(Moats)。Grady 最反直觉的一条建议是:在一场计算革命里,能力变化的速度,快过客户变化的速度。"

"The instinct of most technical founders is to chase the technology — to optimize endlessly against the latest model release. But that's where the ground is least stable. Sequoia's recommendation is to wrap tightly around specific customers and their specific problems."

"大多数技术型创始人的本能,是去追技术——围着每一次最新模型发布没完没了地优化。但那恰恰是地面最不稳的地方。红杉的建议是:紧紧缠绕住特定的客户,以及他们特定的问题。"

"Product still matters; best product generally still wins. But customer intimacy, workflow integration, and earned trust are the moats that compound over time even as the underlying tech keeps shifting."

"产品依然重要,最好的产品一般还是会赢。但客户亲密度、工作流的深度嵌入、以及一点点挣来的信任,才是那种即便底层技术不断变动、也能随时间复利的护城河。"

"In a revolution in computation, the things that you build today might be irrelevant tomorrow. The degree you wrap around your customers is going to be way more valuable."

"在一场计算革命里,你今天造的东西,明天可能就无关紧要了。而你把自己缠绕在客户身上的那个程度,会有价值得多。"

"2. Affordance, borrowed from the design world, is the quality of an object that signals how it should be used without explanation."

"二、Affordance(可供性),从设计圈借来的词,指的是一个物件无需解释、就能暗示出"该怎么用"的那种属性。"

"A hammer has high affordance — its shape suggests its function instantly. Grady notes that raw foundation model access has low affordance: a terminal interface with Claude Code is enormously powerful, but the average enterprise employee has no idea how to make use of it."

"锤子的 affordance 很高——它的形状一眼就暗示了它的功能。Grady 指出,直接访问基础模型则是低 affordance:一个跑着 Claude Code 的终端界面强大得惊人,但普通的企业员工根本不知道该怎么用它。"

"The opportunity at the application layer is to take immense underlying capability and package it into surfaces so intuitive that the customer reaches the desired outcome with minimal effort."

"应用层的机会,就在于把底层那股巨大的能力,封装进足够直觉的界面里——直觉到让客户几乎不费力就能拿到想要的结果。"

"3. Diffusion. Grady highlights a widening gap between the rate at which new AI capabilities are created in the labs and the rate at which those capabilities diffuse into real enterprises. Foundation models advance daily; the average Fortune 500 absorbs change in months or years."

"三、Diffusion(扩散)。Grady 强调了一道正在拉大的鸿沟:实验室里新 AI 能力被创造出来的速度,与这些能力真正扩散进企业的速度,差距越来越大。基础模型每天都在进步,而普通的财富 500 强企业,要以月或年为单位才能消化变化。"

"Every day that the gap widens, the application-layer opportunity grows. In Sequoia's view, closing that diffusion gap — turning frontier capability into deployed business value — is the core mission of the application layer."

"这道鸿沟每拉大一天,应用层的机会就更大一分。在红杉看来,弥合这道扩散鸿沟——把前沿能力变成真正落地的商业价值——正是应用层的核心使命。"

"Sonya Huang opens the second section with a clean thesis: if 2022–2024 was defined by chat interfaces and 2024–2025 by reasoning models, 2026 is defined by agents. The transition, in her framing, is from systems that respond to a prompt to systems that pursue a goal."

"Sonya Huang(黄之熹)用一个干净利落的论点开启第二部分:如果说 2022–2024 是被聊天界面定义的、2024–2025 是被推理模型定义的,那么 2026 是被 agent 定义的。在她的框架里,这场转变是从"响应一个提示词的系统",走向"追逐一个目标的系统"。"

"Huang reminds the audience that the idea of an autonomous AI agent is not new. In 2022, projects like AutoGPT and BabyAGI became overnight GitHub sensations by wrapping GPT-3 in a planning loop and pointing it at a goal."

"Huang 提醒在场的人:自主 AI agent 这个想法并不新鲜。2022 年,AutoGPT、BabyAGI 这类项目就靠着把 GPT-3 套进一个规划循环、再给它指一个目标,在 GitHub 上一夜爆红。"

"The concept was right; the execution was not. The agents looped, hallucinated, and failed repeatedly. The lesson she draws in retrospect is that agents were a known destination years before they were viable — the models simply weren't yet capable of sustaining performance."

"概念是对的,执行不行。那些 agent 不停打转、产生幻觉、一次次失败。她事后总结的教训是:早在 agent 真正可行的好几年前,它就已经是一个看得见的终点了——只不过当时的模型,还撑不住表现。"

"Huang breaks agents into three functional capabilities. Reasoning and planning provide the baseline intuition required to think through a task."

"Huang 把 agent 拆成三种功能能力。推理与规划(reasoning and planning),提供想透一件任务所需的底层直觉。"

"Action-taking provides the means to do something in the world — call APIs, run code, search the web, write files."

"采取行动(action-taking),提供在真实世界里做事的手段——调用 API、运行代码、搜索网页、写文件。"

"Iteration provides persistence across long time horizons. The combination is what produces agency: the practical ability to get things done."

"迭代(iteration),提供跨越长时间跨度的持续性。这三者合在一起,才产生了"能动性"(agency):把事情搞定的实际能力。"

"Huang argues that agentness is a spectrum, not a binary, and uses coding as the canonical example."

"Huang 认为,"agent 化的程度"(agentness)是一道光谱,而不是非此即彼,并拿写代码当作典型例子。"

"First came tab autocomplete in 2023 — an AI suggestion in the editor, useful but not transformative. Then came agentic development, where a human directs an agent or coordinates a small team of them."

"最早是 2023 年的 tab 自动补全——编辑器里的一条 AI 建议,有用,但谈不上变革。接着是 agentic 开发:一个人指挥一个 agent,或者协调一支由 agent 组成的小队。"

"Now emerging are background and async agents — long-running workers that operate without continuous human supervision, often spawning sub-agents of their own."

"现在正在涌现的是后台 agent 和异步(async)agent——长时间运行、无需人持续盯着的"工人",还常常自己派生出子 agent。"

"At the frontier sit dark factories: pipelines in which human review has been removed entirely. Huang notes that dark factories sound implausible until they appear in production, which is already happening in narrow domains such as cybersecurity."

"顶在最前沿的,是"黑灯工厂"(dark factories):一种把人工审查彻底拿掉的流水线。Huang 指出,黑灯工厂听上去不靠谱,直到它真出现在生产环境里——在网络安全这类窄领域,这已经在发生了。"

"The same trajectory — assistant to managed intern to self-managing intern to trusted autonomous worker — is repeating across every domain in which agents are being applied."

"同一条轨迹——从助手,到需要被管的实习生,到自我管理的实习生,再到可被信任的自主工人——正在每一个用上 agent 的领域里重复上演。"

"Huang flags this as the most important takeaway of her section, attributing the framing to Pat Grady and to fellow Sequoia partner Julian, whose article on the topic is referenced: services, not software, becomes the addressable opportunity."

"Huang 把这一条标为她这一节最重要的结论,并把这个提法归功于 Pat Grady,以及红杉合伙人 Julian(她引用了他关于此题的文章):成为可触达机会的,是服务,而不是软件。"

"In medicine, an agent can analyze a genome, recommend interventions, prescribe medications, and identify clinical trials. In law, an agent can negotiate contracts, perform litigation work, and settle disputes."

"在医疗,一个 agent 能分析基因组、推荐干预方案、开药,并找到合适的临床试验。在法律,一个 agent 能谈合同、做诉讼工作、了结纠纷。"

"In the sciences, agents are solving Erdős-class math problems and proposing novel superconductors. In consumer life, personal agents are taking over inboxes, calendars, financial accounts, and tax filings."

"在科学领域,agent 正在解 Erdős(埃尔德什)级别的数学难题,并提出新型超导体。在消费生活里,个人 agent 正在接管收件箱、日历、金融账户和报税。"

"The economic activity once captured by professional service firms is now being absorbed into the application layer."

"曾经被专业服务公司攫取的经济活动,如今正被吸进应用层。"

"Constantine Buhler picks up where Grady left off, offering a second bifurcation to complement the computation vs. communication framing from the opening. There are two fundamental kinds of work."

"Konstantine Buhler(布勒)接着 Grady 留下的话头,提出第二个"二分",来补足开场那套"计算 vs 通信"的框架。工作,从根本上分两类。"

"Physical work moves matter through space — the package on the Pony Express, the satellite on a Falcon 9. Cognitive work moves ideas through minds — Pythagoras formulating his theorem, DeepMind solving protein folding."

"体力工作是让物质在空间里移动——Pony Express(快马邮递)上的包裹、猎鹰 9 号(Falcon 9)上的卫星。认知工作是让观念在心智间流转——Pythagoras(毕达哥拉斯)推导他的定理、DeepMind 攻克蛋白质折叠。"

"The two are profoundly different in substance, but Buhler argues their revolutions follow a strikingly similar arc."

"这两类工作在本质上天差地别,但 Buhler 认为,它们的革命走的是一条惊人相似的弧线。"

"For millennia, virtually all physical work serving humans was performed by muscle — human or animal. The transition began around 1700 with water and wind, accelerated through steam and combustion, and reached its modern form with electric motors."

"几千年来,几乎所有为人服务的体力工作,都靠肌肉完成——人的,或牲畜的。这场转变大约从 1700 年的水力和风力开始,经由蒸汽与内燃机加速,到电动机才走到它现代的形态。"

"By 2026, more than 99% of physical work done on behalf of humans is performed by machines: the aircraft that move people, the manufacturing systems that produce goods, the logistics networks that deliver them. Muscle has been almost entirely displaced by machine."

"到 2026 年,为人完成的体力工作里,超过 99% 是由机器干的:运送人的飞机、生产商品的制造系统、把货送到的物流网络。肌肉,几乎已被机器彻底取代。"

"Buhler's central claim is that a parallel transition is now underway in cognition. For most of history, nearly all thinking on Earth was performed by biological brains, with a small assist from animals and mechanical aids like the astrolabe or the clock."

"Buhler 的核心论断是:一场平行的转变,正在认知领域上演。在历史的大部分时间里,地球上几乎所有的思考都由生物大脑完成,外加一点点来自动物、以及星盘(astrolabe)、时钟这类机械装置的辅助。"

"Electronic computation began to shift this balance in the twentieth century — at any moment today, trillions of calculations are running in service of human needs. The neural network, in his view, is the next wave."

"电子计算在 20 世纪开始改变这个平衡——今天的任何一瞬间,都有数以万亿计的运算在为人的需求服务。在他看来,神经网络就是下一个浪潮。"

"The trajectory suggests that within a generation, 99.9% of cognition on Earth will be performed by machines. The cognitive revolution will resemble the industrial revolution in shape, but will be substantially larger in scope and substantially faster in tempo."

"这条轨迹暗示:一代人之内,地球上 99.9% 的认知,将由机器完成。认知革命在形状上会很像工业革命,但在范围上要大得多、在节奏上也要快得多。"

"1. Aluminum and the Washington Monument. Buhler illustrates the coming devaluation of cognitive skills with the story of aluminum. In the mid-1800s, the Washington National Monument — then the tallest building in the world — was capped with 100 ounces of aluminum."

"一、铝与华盛顿纪念碑。Buhler 用铝的故事,来说明认知技能即将到来的贬值。19 世纪中叶,当时世界最高的建筑——华盛顿纪念碑——顶端封的是 100 盎司的铝。"

"Aluminum was, at the time, the most precious metal known; it was displayed at Tiffany's in Manhattan before being installed. Within a few decades, the invention of electrolysis allowed aluminum to be separated cheaply from ore, and the metal became disposable — candy wrappers, sandwich foil, packaging discarded after a single use."

"铝在当时是已知最珍贵的金属;装上去之前,它还在曼哈顿的 Tiffany's(蒂芙尼)橱窗里展出过。短短几十年内,电解法(electrolysis)的发明,让铝能被廉价地从矿石里分离出来,这种金属随即变成了一次性用品——糖纸、三明治锡箔、用一次就扔的包装。"

"Buhler's analogy: aluminum is intelligence, electrolysis is artificial intelligence. Capabilities that once required decades to acquire — PhD-level expertise in narrow domains — are becoming instantly invocable and effectively disposable."

"Buhler 的类比是:铝就是智能,电解法就是人工智能。那些一度需要几十年才能习得的能力——某个窄领域里博士级别的专长——正变得可以即刻调用、且基本上一次性可弃。"

"2. The Age of Alien Design. The built environment today is overwhelmingly optimized for human cognition because humans have been doing the cognition. When machines take over the design process, the outputs begin to look strange."

"二、异形设计的时代。今天的人造环境之所以压倒性地为人类认知而优化,是因为一直以来都是人在做认知。一旦机器接管设计过程,产出就会开始变得奇怪。"

"In 2006, NASA used an evolutionary algorithm — a precursor to modern reinforcement learning — to optimize an antenna for a satellite mission. The conventionally designed antenna was a clean, symmetric, geometric form."

"2006 年,NASA 用一套进化算法(evolutionary algorithm)——现代强化学习的前身——为一项卫星任务优化天线。按传统方式设计的天线,是一个干净、对称的几何造型。"

"The machine-designed antenna was a contorted, asymmetric shape that no human engineer would have proposed — and it dramatically outperformed the conventional design."

"而机器设计出来的天线,是一个扭曲、不对称、任何人类工程师都不会提出的形状——可它的性能,远远胜过传统设计。"

"Buhler's forecast is that as AI takes over the design of chips, vehicles, buildings, and software, the outputs will increasingly look alien by human standards. The aesthetic and structural intuitions that have governed human design for centuries may not apply."

"Buhler 的预判是:随着 AI 接管芯片、车辆、建筑、软件的设计,产出会越来越"以人的标准看像异形"。那些主宰了人类设计数百年的审美与结构直觉,可能不再适用。"

"3. Emerging Sciences. The mature engineering disciplines often emerge long after the practical technology they describe. For nearly a century, steam engines were perfected through pure tinkering — engineers like Newcomen and Watt iterating empirically without a unifying theory."

"三、新兴的科学。成熟的工程学科,往往在它所描述的那项实用技术出现很久之后才诞生。差不多有一个世纪,蒸汽机都是靠纯粹的"瞎鼓捣"被打磨出来的——Newcomen(纽科门)、Watt(瓦特)这样的工程师,在没有统一理论的情况下凭经验反复试。"

"Then, in the early 1800s, Sadi Carnot formalized thermodynamics, giving the field a rigorous foundation that ultimately enabled the next several generations of progress. AI, Buhler argues, is currently in its tinkering phase. The systems work, but the science of why they work is incomplete."

"然后,在 19 世纪初,Sadi Carnot(萨迪·卡诺)把热力学形式化,给这个领域奠下严谨的基础,最终撑起了之后好几代人的进步。Buhler 认为,AI 眼下正处在它的"瞎鼓捣"阶段:系统能跑,但"它为什么能跑"的科学还不完整。"

"His forecast: within the next two decades, a new fundamental science of intelligence — at the level of thermodynamics in scope and rigor — will emerge. It will be taught in high schools. It may provide the conceptual tools needed to genuinely master AI, and possibly to understand consciousness itself."

"他的预判是:在接下来的二十年里,会诞生一门关于智能的、全新而根本的科学——在范围与严谨度上,堪比热力学。它会被写进高中课本。它或许能提供真正驾驭 AI 所需的概念工具,甚至可能让我们理解意识(consciousness)本身。"

"4. The Art of Unreason. For tens of thousands of years, visual art trended steadily toward realism. From cave paintings to Egyptian hieroglyphs, Greek pottery to Renaissance masterworks, the dominant pursuit was capturing the world as the eye perceived it."

"四、非理性之艺术。数万年来,视觉艺术一直稳步朝写实(realism)演进。从洞穴壁画到埃及象形文字,从希腊陶器到文艺复兴杰作,主流的追求,都是按眼睛所见去捕捉这个世界。"

"The arrival of the daguerreotype and early photography abruptly made that pursuit obsolete: a camera could capture a scene in seconds with more fidelity than a master could achieve in months. Many predicted the end of painting."

"银版照相法(daguerreotype)和早期摄影的到来,让这一追求骤然过时:一台相机几秒就能捕捉一个场景,其逼真程度超过一位大师数月之功。许多人预言绘画将就此终结。"

"Instead, painting reinvented itself by asking a different question — not how the eye sees the world, but how the heart and the soul see it. Impressionism, Expressionism, Cubism, and Neo-Expressionism followed."

"结果,绘画通过提出一个不同的问题完成了自我重塑——不是"眼睛如何看世界",而是"心与灵魂如何看世界"。印象派、表现主义、立体主义、新表现主义,相继而来。"

"Buhler's expectation is that a similar reorientation will occur as machines take over the literal execution of cognitive work. Human creative and interpretive activity will shift toward the dimensions machines cannot replicate."

"Buhler 预期,当机器接管认知工作的字面执行,一场相似的转向也会发生。人类的创造与诠释活动,将转向那些机器无法复制的维度。"

"Buhler closes with a line from the Greek philosopher Protagoras, written twenty-five centuries ago: 'man is the measure of all things.' His reading: nothing in a vacuum has value in itself. Not aluminum, not art, not intelligence."

"Buhler 以希腊哲学家 Protagoras(普罗泰戈拉)写于 2500 年前的一句话收尾:"人是万物的尺度。"他的解读是:任何东西在真空里,本身都没有价值。铝没有,艺术没有,智能也没有。"

"Value is conferred by human experience and human meaning. AI can perform the work. AI will perform the work. But only human relationships and human attention supply the reason any of it matters."

"价值,是由人的体验和人的意义赋予的。AI 能做这些活,AI 也将会做这些活。但唯有人与人的关系、人的注意力,才能提供"这一切为何重要"的理由。"

"A decade from now, in Buhler's view, the substance of daily work will look unrecognizable compared to today. What endures is the human side — the relationships formed during this transition, among builders, collaborators, and the communities that gather to make sense of moments like this one."

"在 Buhler 看来,十年之后,日常工作的实质会变得与今天判若两样。真正留下来的,是属于人的那一面——在这场转变中结下的关系:在建造者之间、协作者之间,以及那些聚到一起、试图读懂此刻这种时刻的社群之间。"

"Three forces now define this cycle: a technology floor that moves weekly, an addressable opportunity roughly 10x larger than prior platform shifts, and a playbook that breaks from cloud and mobile precedent."

"如今,有三股力量定义着这一轮周期:一块每周都在移动的技术地基、一个比以往平台迁移大约大 10 倍的可触达机会、以及一套与云和移动先例彻底决裂的打法。"

"Hope this was valuable. Cheers, Guillermo."

"希望这篇对你有价值。祝好,Guillermo。"