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如果你还在打造所谓的“AI产品”，那你未来三年就已经输了

Founders and product leaders ask me some version of it every week, across the banks, retailers, and enterprises I advise on AI: “How do we build an AI product?” It’s a category error, and the longer a company keeps asking it, the further behind it falls without ever noticing the ground shifting underneath. Apple just spent ninety minutes showing why — and the most instructive part wasn’t what it announced. It was what it pointedly refused to announce.每周都有创始人或产品负责人向我提出类似的问题，无论是在我提供AI咨询的银行、零售商还是大型企业中，他们都在问：“我们该如何打造一款AI产品？”这是一个范畴错误。一家公司在这个问题上纠结得越久，它在不知不觉中落后的就越多，甚至意识不到脚下的地基正在发生动摇。苹果刚刚用了90分钟的时间展示了原因，而最具启发性的部分并非其发布的内容，而是它明确拒绝发布的内容。

1. AI is infrastructure, not a destination1. AI是基础设施，而非终点

Apple did not walk on stage and unveil an AI app. What it unveiled instead was intelligence dissolved into everything that was already there — woven, quietly and almost invisibly, into Siri, Photos, Messages, Mail, Safari, Calendar, the Phone app, even the screenshot tool on the Mac. There was no new icon to tap, no separate product to download, no destination to navigate toward. In one demo, you could screenshot a festival schedule, let the system read it, and have the performances you cared about land in your calendar without your ever opening a calendar; in another, the Phone app pulled context from your Mail and Messages mid-call, surfacing what you needed precisely when you needed it.苹果并没有走上台去发布一款AI应用。相反，它发布的是一种融入了现有生态的智能——它悄无声息、近乎隐形地织入到Siri、照片、信息、邮件、Safari、日历、电话App，甚至Mac的截图工具中。这里没有新的图标需要点击，没有独立的App需要下载，也没有一个需要专门前往的“目的地”。在演示中，你可以截取一张节日日程表，让系统读取它，然后把你感兴趣的演出直接存入日历，而无需打开日历App；又或者在通话过程中，电话App会自动从你的邮件和信息中提取上下文，在你最需要的时候精准呈现所需信息。

Read the trade coverage closely and you’ll notice something even sharper: Apple deliberately under-sold the whole thing. The keynote led with fixes before features — 70% faster photo loading, 80% faster AirDrop transfers, a steadier operating system — and framed a dramatically better Siri as one entry on a long list of improvements rather than the headline act. That restraint wasn’t timidity. It was the entire thesis, expressed structurally. A company that genuinely believed AI was a destination would have built a cathedral around it. Apple buried it in the plumbing.仔细阅读行业报道，你会发现一个更敏锐的细节：苹果刻意淡化了这一切。发布会开场先讲的是基础修复而非新功能——照片加载速度提升70%、隔空投送速度提升80%、操作系统更稳定——并将大幅改进的Siri仅仅作为长串改进清单中的一项，而非重头戏。这种克制并非胆怯，而是其整个核心逻辑的结构化表达。如果一家公司真认为AI是终点，它会围绕AI大兴土木；而苹果却将其埋在了基础设施中。

This is not a new pattern; it is the oldest one we have这并非新模式，而是我们所知的最古老的模式

In 2000, the companies that treated the internet as a place you go — the portals, the web-only storefronts — were quietly dismantled by the ones that treated it as infrastructure that made everything else better. Amazon never built “an internet store.” It rebuilt the entire logic of retail with the internet running underneath, load-bearing and unseen. A decade later, mobile wasn’t won by whoever shipped the most apps; it was won by the companies that redesigned their core product around what a camera, a location signal, and an always-on connection suddenly made possible.2000年时，那些将互联网视为“一个去处”的公司——比如门户网站、纯网页电商——最终被那些将互联网视为基础设施并以此优化一切的公司悄然淘汰。亚马逊从未打造过“一个互联网商店”，它利用互联网作为底层支撑，重构了零售业的逻辑，尽管互联网本身是隐形的。十年后，移动互联网的赢家也不是那些发布App最多的公司，而是那些围绕摄像头、定位信号和全时连接所带来的新可能，重构其核心产品的公司。

AI is that shift again, only faster and with more at stake. The winners will not be the companies with the most impressive AI feature. They will be the companies that have embedded intelligence so deeply into the product that pulling it out would cause the product to stop working — the way pulling the internet out of Amazon would not leave you with a slightly worse Amazon, but with no Amazon at all.AI再次引发了这种变革，只是速度更快，赌注更大。赢家不会是那些拥有最炫酷AI功能的公司，而是那些将智能深度嵌入产品，以至于一旦剥离智能，产品就无法运作的公司——就像从亚马逊剥离互联网，剩下的不再是一个“稍差一点的亚马逊”，而是一个根本无法运作的空壳。

So the question was never “how do we build an AI product?” The question is: what would every part of this product become if intelligence were native to it — assumed, ambient, foundational — rather than bolted on as a feature someone has to find?所以，问题从来不是“我们该如何打造一款AI产品？”，而是：如果智能是原生于产品的——即默认的、环境化的、基础性的——而不是作为某种需要用户刻意寻找的“功能”外挂上去的，那么产品的每一个部分会变成什么样？

Most teams still underestimate how far this ripples into pricing, onboarding, even the permission model — long before anyone touches a line of code.大多数团队仍然低估了这种变革对定价、入职引导，甚至权限模型的影响——这些影响远在编写第一行代码之前就已经存在了。

2. The interface is changing, and most product teams haven’t noticed2. 交互界面正在改变，而大多数产品团队尚未察觉

For thirty years, software has obeyed a single grammar: you open an app, work through it, and arrive at a result. You navigate to the right screen, locate the thing you need, and take the action yourself. Every menu, every onboarding flow, every painstakingly debated piece of information architecture exists to serve that one sequence.三十年来，软件遵循着一套固定的语法：打开App，操作它，最后得到结果。你需要导航到正确的页面，找到所需内容，然后亲自执行操作。每一个菜单、每一个引导流程、每一个经过反复推敲的信息架构，都是为了服务于这一流程。

The new Siri — and, more broadly, the entire generation of agentic systems now coming into view — quietly rewrites that grammar into something else: you ask an agent, the agent orchestrates the apps, and the result comes back.新版Siri，以及更广泛意义上正在涌现的智能体系统，正在悄然改写这套语法：你向智能体提问，智能体负责调度各个App，然后返回结果。

The agent becomes the primary surface. The apps recede into services it orchestrates in the background, invisibly, on your behalf. This is not, fundamentally, a Siri story. It’s an architectural one, and it’s bigger than any single company. OpenAI’s ChatGPT Agent, Google’s Gemini Agent, Anthropic’s Claude operating a computer on its own — all of them point at the same horizon, where the next generation of software is orchestrated by agents rather than navigated by users.智能体成为了主要的交互界面。App退居幕后，作为被智能体隐形调用的服务。这从根本上说不是Siri的故事，而是一个架构层面的故事，其影响超越了任何单一公司。OpenAI的ChatGPT智能体、谷歌的Gemini智能体、Anthropic能自主操作电脑的Claude——它们都指向同一个未来：下一代软件将由智能体来调度，而非由用户手动导航。

And here is the tell, the detail that should settle any remaining doubt: the standalone versions of these agents have already begun to die. OpenAI’s Operator and Google’s Project Mariner — both launched as separate, standalone agent products — were quietly shut down within the past year and absorbed back into the core assistants, ChatGPT and Gemini. The destination didn’t survive; the infrastructure did. The agent was never meant to be a place you go. It was always meant to be the layer through which everything else happens.这里有一个细节足以消除所有疑虑：独立的智能体产品已经开始消亡。OpenAI的Operator和谷歌的Project Mariner——两者最初都是作为独立的智能体产品发布的——在过去一年里被悄然关闭，并重新整合回了ChatGPT和Gemini等核心助手之中。目的地没有存活下来，基础设施却留下了。智能体从来都不是一个“去处”，它一直都应该是承载一切的底层逻辑。

When the agent is the interface, almost everything product teams have spent careers optimizing begins to lose weight. Navigation matters less. Information architecture matters less. The lovingly crafted onboarding funnel matters less. What rises in its place are two questions that most roadmaps don’t yet have a column for: Does the agent have enough context to act on the user’s behalf? And does the user trust it enough to let it?当智能体成为交互界面时，产品团队花费多年职业生涯优化的东西开始变得无关紧要。导航不再那么重要，信息架构不再那么重要，精心打磨的入职引导漏斗也不再那么重要。取而代之的是两个大多数产品路线图尚未涉及的问题：智能体是否有足够的上下文来代表用户行事？用户是否足够信任它以至于愿意放手？

I see the cost of ignoring this most vividly inside large, traditional enterprises — the banks, the retailers, the businesses that built themselves long before “digital” was a department and now spend much of my advising time trying to catch up. They will pour a quarter’s worth of design budget into restructuring a navigation menu — refining the taxonomy of screens a customer will, within a few years, simply stop visiting — because that customer will be asking an agent to move the money, reorder the supplies, or settle the account, and the agent will not care how elegantly the menu was organized. The honest, uncomfortable question every product team should be putting to itself right now is this: are you designing for the world in which users navigate, or the one in which agents act? Because you are almost certainly designing for the first, and the second is already arriving.我在大型传统企业中深刻地看到了忽视这一点的代价——那些在“数字化”部门出现前就已建立的银行、零售商和企业，如今花费我大量咨询时间试图追赶。他们会投入一个季度的设计预算去重构导航菜单——优化那些用户几年内就会停止访问的页面分类——因为未来用户会直接要求智能体去转账、补货或对账，而智能体根本不在乎菜单设计得多么优雅。每个产品团队现在都应该扪心自问一个诚实且令人不安的问题：你是在为用户需要手动导航的世界设计，还是在为智能体代劳的世界设计？因为你几乎肯定是在为前者设计，而后者已经在到来的路上。

3. The new moat isn’t the model — it’s context3. 新的护城河不是模型，而是上下文

Here is the single most important strategic idea I’ve carried out of the past six months, and I’ll state it as plainly as I can:这是我过去六个月总结出的最重要的战略思想，我将直白地陈述出来：

AI alone is a commodity. AI plus context is a product. AI plus context plus action is a moat.AI本身是商品。AI加上下文是产品。AI加上下文加行动才是护城河。

Let me make that concrete, because the distinction is where fortunes will be made and lost.让我把这一点具体化，因为成败的分水岭就在这里。

AI alone — a generic large language model answering questions — is available to literally everyone, for pennies per query. There is no differentiation to be found there; at the task level, the frontier models are roughly interchangeable, and they are getting cheaper and more interchangeable by the month. Building a business on the raw model is building a business on tap water.仅有AI——一个回答问题的通用大语言模型——对所有人开放，且查询成本极低。这里不存在差异化；在任务层面，前沿模型几乎是可以互换的，而且这种可互换性随着时间推移变得越来越廉价。建立在原生模型之上的商业模式，就像是建立在自来水之上的生意。

The constraint was never really the model. Every team wiring an agent into real tools runs into the same wall almost immediately — the model reasons just fine, but the product hasn't decided what the agent is allowed to touch, in what order, or with how much oversight.限制因素从来都不是模型本身。每个将智能体接入真实工具的团队都会立即撞上同一堵墙——模型推理能力很好，但产品尚未决定智能体被允许触碰什么、以什么顺序触碰，以及需要多少监督。

AI plus context is where products begin to diverge from one another. It’s precisely what Apple is constructing with Apple Intelligence: a system whose value lies not in the model but in what the model knows about you — your relationships, your history, your habits, the contents of your week. Glean does the same thing inside the enterprise, where the differentiator was never the LLM but the index of a company’s own scattered, hard-won internal knowledge. Harvey does it for law firms, wrapping a generic model around legal knowledge no competitor can conjure overnight.“AI加上下文”是产品开始产生差异化的地方。这正是苹果利用Apple Intelligence所构建的东西：一个系统的价值不在于模型本身，而在于模型对你的了解——你的关系、历史、习惯、这一周的内容。Glean在企业内部做着同样的事情，其差异化因素从来不是LLM，而是对企业自身分散、来之不易的内部知识的索引。Harvey为律师事务所做着同样的事，将通用模型封装在竞争对手无法一夜之间复制的法律知识库中。

We saw the same pattern building a health app from the ground up: the model was almost incidental once the product had to decide what it actually knew about a given patient, and when it was allowed to act on that.我们在从零开始打造一款健康App时也看到了同样的模式：一旦产品必须决定它真正了解某位患者什么，以及何时被允许根据这些信息采取行动时，模型本身几乎就成了次要的。

AI plus context plus action is where the genuine moats get dug. This is the moment the system stops merely answering and starts doing — finding the email, booking the meeting, filing the document, reconciling the account, sending the reply with enough earned confidence that you no longer feel the need to inspect every step. And here is the part competitors cannot shortcut: context compounds. Every interaction makes the system a little more useful, a little more accurate, a little more trusted — and that accumulating trust, built one correct action at a time, is the asset a rival starting from zero simply cannot copy, no matter how good their model is.“AI加上下文加行动”才是真正的护城河所在。这是系统从单纯的“回答”转变为“执行”的时刻——查找邮件、预订会议、归档文件、对账、发送回复，并具备足够的自信，让你不再觉得需要检查每一个步骤。这是竞争对手无法通过捷径获得的部分：上下文会产生复利效应。每一次交互都让系统更实用、更准确、更受信任——这种通过一次次正确行动积累起来的信任，是竞争对手从零开始时根本无法复制的资产，无论他们的模型有多好。

So the question worth taking into your next strategy session isn’t which model you should license. It’s this: what do you know about your users, and what can you reliably do on their behalf, that a competitor starting today could not easily replicate? That is the only place your AI investment will ever truly compound.因此，你下一次战略会议上值得讨论的问题不是该授权哪种模型。而是：你对用户了解多少？你能可靠地代表他们完成什么？而这些是今天才开始的竞争对手无法轻易复制的？这才是你的AI投资真正能够产生复利的地方。

What this actually means on Monday morning这意味着周一早上该怎么做

Take these three ideas seriously — AI as infrastructure, the agent as interface, context as the moat — and they collapse into a short, demanding set of priorities.认真对待这三个观点——AI作为基础设施、智能体作为交互界面、上下文作为护城河——它们可以归纳为一套紧迫的优先级排序。

Stop building AI features. Start rebuilding your core value proposition around intelligence. The right question is not “where does AI fit into what we already have?” but “what would this product look like if we’d designed it, from the first line, assuming intelligence was always going to be native to it?”停止打造AI功能。开始围绕智能重构你的核心价值主张。正确的问题不是“AI如何融入我们现有的产品？”，而是“如果我们从第一行代码开始，就假设智能是原生的，那么这款产品会是什么样子？”

Design for intent, not navigation. As agents become the interface, the products that win will be the ones that understand what a person is trying to accomplish — not merely what they happened to click.为意图而设计，而非为导航而设计。随着智能体成为交互界面，胜出的产品将是那些能理解用户想要达成什么目标的产品，而不仅仅是他们点击了什么。

Know your user — and mean it. Not surveillance, not indiscriminate data hoarding, but meaningful, structured context: what the system should remember, what it should be trusted to act on, how memory should compound into value over months and years. These are design decisions long before they are engineering ones, and most companies are treating them as neither.了解你的用户——并且是真正地了解。不是监控，不是无差别的囤积数据，而是有意义、结构化的上下文：系统应该记住什么，应该被信任去执行什么，记忆如何随着数月和数年的时间积累成价值。这些是设计决策，远在工程实现之前就应做出，而大多数公司目前两者皆未做到。

The companies asking these questions today will be very, very hard to catch in three years. The companies still convening committees to decide whether to “add an AI chatbot” will spend those same three years wondering, with genuine bewilderment, what exactly happened to them.今天就在思考这些问题的公司，三年后将非常难以被超越。而那些还在召集委员会讨论是否要“添加一个AI聊天机器人”的公司，将在同样的三年里，带着真正的困惑，思考自己到底经历了什么。

The next generation of software will be context-aware, agentic, and threaded so deeply into ordinary life that we’ll stop noticing it — which is precisely the point. The winners will be the ones who designed those experiences around humans, not around models. Apple just spent ninety minutes on stage trying, in its understated way, to tell everyone that. The tragedy is how few people in the room were actually listening.下一代软件将具备上下文感知能力、智能体特性，并深度融入日常生活，以至于我们不再注意到它的存在——这正是重点所在。赢家将是那些围绕人类而非模型设计体验的人。苹果在舞台上花了90分钟，用它那种低调的方式试图告诉所有人这一点。悲剧在于，现场真正听进去的人寥寥无几。