# bigthing **Repository Path**: toweizhou/bigthing ## Basic Information - **Project Name**: bigthing - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2026-02-16 - **Last Updated**: 2026-10-25 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README [# Something Big Is Happening](https://shumer.dev/something-big-is-happening) # 一些重大的事情正在发生 By Matt Shumer • Feb 9, 2026 作者：Matt Shumer • 2026年2月9日 [← blog](/blog) Get updates [Follow @mattshumer\_](https://x.com/mattshumer_) --- Think back to February 2020. 回想一下2020年2月。 If you were paying close attention, you might have noticed a few people talking about a virus spreading overseas. But most of us weren't paying close attention. The stock market was doing great, your kids were in school, you were going to restaurants and shaking hands and planning trips. If someone told you they were stockpiling toilet paper you would have thought they'd been spending too much time on a weird corner of the internet. Then, over the course of about three weeks, the entire world changed. Your office closed, your kids came home, and life rearranged itself into something you wouldn't have believed if you'd described it to yourself a month earlier. 如果你当时非常关注，你可能会注意到一些人在谈论一种正在海外传播的病毒。但我们大多数人并没有密切关注。股市表现很好，你的孩子在学校上学，你去餐厅吃饭，握手寒暄，计划旅行。如果有人告诉你他们在囤积卫生纸，你会觉得他们在互联网的某个奇怪角落花了太多时间。然后，在大约三周的时间里，整个世界都变了。你的办公室关闭了，孩子们回家了，生活重新排列成了一种如果一个月前描述给自己听都不会相信的样子。 I think we're in the "this seems overblown" phase of something much, much bigger than Covid. 我认为我们正处于某个比新冠更大得多的事情的"这似乎有些言过其实"的阶段。 I've spent six years building an AI startup and investing in the space. I live in this world. And I'm writing this for the people in my life who don't... my family, my friends, the people I care about who keep asking me "so what's the deal with AI?" and getting an answer that doesn't do justice to what's actually happening. I keep giving them the polite version. The cocktail-party version. Because the honest version sounds like I've lost my mind. And for a while, I told myself that was a good enough reason to keep what's truly happening to myself. But the gap between what I've been saying and what is actually happening has gotten far too big. The people I care about deserve to hear what is coming, even if it sounds crazy. 我花了六年时间建立一家人工智能初创公司并在这个领域投资。我生活在这个世界里。我写这篇文章是为了我生活中那些不在这个领域的人……我的家人，我的朋友，我关心的人，他们一直问我"所以AI到底是怎么回事？"而得到的答案并没有真正反映实际发生的事情。我一直给他们礼貌的版本。鸡尾酒会上的版本。因为诚实的版本听起来就像我疯了一样。有一段时间，我告诉自己这是将真正发生的事情保密的充分理由。但我一直说的和实际发生的事情之间的差距已经变得太大了。我关心的人应该知道即将发生什么，即使这听起来很疯狂。 I should be clear about something up front: even though I work in AI, I have almost no influence over what's about to happen, and neither does the vast majority of the industry. The future is being shaped by a remarkably small number of people: a few hundred researchers at a handful of companies... OpenAI, Anthropic, Google DeepMind, and a few others. A single training run, managed by a small team over a few months, can produce an AI system that shifts the entire trajectory of the technology. Most of us who work in AI are building on top of foundations we didn't lay. We're watching this unfold the same as you... we just happen to be close enough to feel the ground shake first. 我应该先澄清一件事：尽管我在AI领域工作，我对即将发生的事情几乎没有影响力，这个行业绝大多数人也是如此。未来正由极少数人塑造：几家公司里的几百名研究人员……OpenAI、Anthropic、Google DeepMind和其他几家。一次由小团队在几个月内管理的训练运行，可以产生一个改变整个技术轨迹的AI系统。我们大多数在AI领域工作的人都是在我们没有奠定的基础上建设。我们和你一样看着这一切展开……我们只是碰巧离得足够近，能先感觉到大地震动。 But it's time now. Not in an "eventually we should talk about this" way. In a "this is happening right now and I need you to understand it" way. 但现在时候到了。不是以"我们最终应该讨论这个问题"的方式。而是以"这正在发生，我需要你理解它"的方式。 --- ## I know this is real because it happened to me first ## 我知道这是真的，因为它首先发生在我的身上 Here's the thing nobody outside of tech quite understands yet: the reason so many people in the industry are sounding the alarm right now is because this already happened to *us*. We're not making predictions. We're telling you what already occurred in our own jobs, and warning you that you're next. 科技圈外人还没有完全理解的一点是：现在行业内这么多人拉响警报的原因是这已经发生在*我们*身上了。我们不是在做预测。我们在告诉你我们自己的工作中已经发生的事情，并警告你，你是下一个。 For years, AI had been improving steadily. Big jumps here and there, but each big jump was spaced out enough that you could absorb them as they came. Then in 2025, new techniques for building these models unlocked a much faster pace of progress. And then it got even faster. And then faster again. Each new model wasn't just better than the last... it was better by a wider margin, and the time between new model releases was shorter. I was using AI more and more, going back and forth with it less and less, watching it handle things I used to think required my expertise. 多年来，AI一直在稳步改进。时不时有大的跳跃，但每次大的跳跃间隔足够长，你可以慢慢消化。然后在2025年，构建这些模型的新技术解锁了更快的进步速度。然后变得更快。然后再更快。每个新模型不仅比上一个更好……而且优势更大，新模型发布之间的时间更短。我越来越多地使用AI，越来越少地与它反复交流，看着它处理我曾经认为需要我专业知识的事情。 Then, on February 5th, two major AI labs released new models on the same day: GPT-5.3 Codex from OpenAI, and Opus 4.6 from Anthropic (the makers of Claude, one of the main competitors to ChatGPT). And something clicked. Not like a light switch... more like the moment you realize the water has been rising around you and is now at your chest. 然后，在2月5日，两个主要的AI实验室在同一天发布了新模型：OpenAI的GPT-5.3 Codex，和Anthropic的Opus 4.6（Claude的制造商，ChatGPT的主要竞争对手之一）。有些东西被触发了。不像开关……更像是你意识到水一直在你周围上涨，现在已经到了你胸口的时刻。 **I am no longer needed for the actual technical work of my job.** I describe what I want built, in plain English, and it just... appears. Not a rough draft I need to fix. The finished thing. I tell the AI what I want, walk away from my computer for four hours, and come back to find the work done. Done well, done better than I would have done it myself, with no corrections needed. A couple of months ago, I was going back and forth with the AI, guiding it, making edits. Now I just describe the outcome and leave. **我不再被需要做我工作的实际技术部分了。**我用通俗的英语描述我想要构建的东西，它就……出现了。不是我需要修改的草稿。而是完成的东西。我告诉AI我想要什么，离开电脑四个小时，回来时发现工作已经完成。做得很好，比我自己做得更好，不需要任何修正。几个月前，我还在和AI反复交流，指导它，做编辑。现在我只需要描述结果然后离开。 Let me give you an example so you can understand what this actually looks like in practice. I'll tell the AI: "I want to build this app. Here's what it should do, here's roughly what it should look like. Figure out the user flow, the design, all of it." And it does. It writes tens of thousands of lines of code. Then, and this is the part that would have been unthinkable a year ago, it **opens the app itself**. It clicks through the buttons. It tests the features. It uses the app the way a person would. If it doesn't like how something looks or feels, it goes back and changes it, on its own. It iterates, like a developer would, fixing and refining until it's satisfied. Only once it has decided the app meets its own standards does it come back to me and say: "It's ready for you to test." And when I test it, it's usually perfect. 让我给你一个例子，这样你就可以理解这在实践中到底是什么样子的。我会告诉AI："我想构建这个应用。这是它应该做的，这是它大概应该的样子。弄清楚用户流程、设计，所有这些。"它做到了。它写了数万行代码。然后，这是一年前不可想象的部分，它**自己打开应用**。它点击按钮。它测试功能。它像人一样使用应用。如果它不喜欢某个东西的外观或感觉，它会回去自己修改。它迭代，像开发者一样，修复和完善直到满意。只有当它决定应用达到自己的标准后，才会回来对我说："准备好让你测试了。"当我测试时，它通常是完美的。 I'm not exaggerating. That is what my Monday looked like this week. 我没有夸张。这就是我这一周周一的样子。 But it was the model that was released last week (GPT-5.3 Codex) that shook me the most. It wasn't just executing my instructions. It was making intelligent decisions. It had something that felt, for the first time, like **judgment**. Like **taste**. The inexplicable sense of knowing what the right call is that people always said AI would never have. This model has it, or something close enough that the distinction is starting not to matter. 但最让我震惊的是上周发布的模型（GPT-5.3 Codex）。它不仅仅是执行我的指令。它在做出智能决策。它第一次拥有了一种感觉像**判断力**的东西。像**品味**。那种人们总是说AI永远不会拥有的、知道什么是正确决定的不可思议的感觉。这个模型拥有它，或者足够接近以至于这种区别开始不再重要。 I've always been early to adopt AI tools. But the last few months have shocked me. These new AI models aren't incremental improvements. This is a different thing entirely. 我一直很早就采用AI工具。但过去几个月让我震惊。这些新的AI模型不是增量改进。这完全是另一种东西。 And here's why this matters to you, even if you don't work in tech. 这就是为什么这对你很重要，即使你不在科技行业工作。 The AI labs made a deliberate choice. They focused on making AI great at writing code first... because building AI requires a lot of code. If AI can write that code, it can help build the next version of itself. A smarter version, which writes better code, which builds an even smarter version. Making AI great at coding was the strategy that unlocks everything else. That's why they did it first. My job started changing before yours not because they were targeting software engineers... it was just a side effect of where they chose to aim first. AI实验室做了一个深思熟虑的选择。他们首先专注于让AI擅长编写代码……因为构建AI需要大量代码。如果AI能编写这些代码，它就可以帮助构建自己的下一个版本。一个更聪明的版本，编写更好的代码，构建一个更聪明的版本。让AI擅长编程是解锁其他一切的战略。这就是为什么他们首先这样做。我的工作在你的工作之前开始改变，不是因为他们的目标是软件工程师……这只是他们选择首先瞄准的地方的副作用。 They've now done it. And they're moving on to everything else. 他们现在已经做到了。他们正在转向其他所有领域。 The experience that tech workers have had over the past year, of watching AI go from "helpful tool" to "does my job better than I do", is the experience everyone else is about to have. Law, finance, medicine, accounting, consulting, writing, design, analysis, customer service. Not in ten years. The people building these systems say one to five years. Some say less. And given what I've seen in just the last couple of months, I think "less" is more likely. 科技工作者在过去一年中的经历——看着AI从"有用的工具"变成"比我自己做得更好"——是其他人即将拥有的经历。法律、金融、医学、会计、咨询、写作、设计、分析、客户服务。不是在十年内。构建这些系统的人说一到五年。一些人说更少。考虑到我在过去几个月看到的，我认为"更少"更有可能。 ## "But I tried AI and it wasn't that good" ## "但我试过AI，它没那么好" I hear this constantly. I understand it, because it used to be true. 我不断地听到这句话。我理解，因为以前确实如此。 If you tried ChatGPT in 2023 or early 2024 and thought "this makes stuff up" or "this isn't that impressive", you were right. Those early versions were genuinely limited. They hallucinated. They confidently said things that were nonsense. 如果你在2023年或2024年初尝试过ChatGPT，并认为"这东西在编造东西"或"这没什么了不起"，你是对的。那些早期版本确实有限制。它们会产生幻觉。它们自信地说一些胡话。 That was two years ago. In AI time, that is ancient history. 那是两年前的事了。在AI时间里，那是古代历史。 The models available today are unrecognizable from what existed even six months ago. The debate about whether AI is "really getting better" or "hitting a wall" — which has been going on for over a year — is over. It's done. Anyone still making that argument either hasn't used the current models, has an incentive to downplay what's happening, or is evaluating based on an experience from 2024 that is no longer relevant. I don't say that to be dismissive. I say it because the gap between public perception and current reality is now enormous, and that gap is dangerous... because it's preventing people from preparing. 今天可用的模型与六个月前存在的东西无法辨认。关于AI是"真的在变好"还是"撞墙"的争论——这已经持续了一年多——已经结束了。完成了。任何仍在提出这个论点的人，要么没有使用过当前的模型，要么有动机淡化正在发生的事情，要么是基于2024年的经验进行评估，而这已经不再相关了。我这样说不是为了轻视。我说这些是因为公众认知和当前现实之间的差距现在是巨大的，这个差距是危险的……因为它阻止人们做准备。 Part of the problem is that most people are using the free version of AI tools. The free version is over a year behind what paying users have access to. Judging AI based on free-tier ChatGPT is like evaluating the state of smartphones by using a flip phone. The people paying for the best tools, and actually using them daily for real work, know what's coming. 部分问题是，大多数人使用的是免费版的AI工具。免费版比付费用户可以使用的落后一年多。基于免费版ChatGPT来评判AI，就像用翻盖手机来评估智能手机的状态。那些为最好的工具付费，并真正在日常工作使用它们的人，知道即将发生什么。 I think of my friend, who's a lawyer. I keep telling him to try using AI at his firm, and he keeps finding reasons it won't work. It's not built for his specialty, it made an error when he tested it, it doesn't understand the nuance of what he does. And I get it. But I've had partners at major law firms reach out to me for advice, because they've tried the current versions and they see where this is going. One of them, the managing partner at a large firm, spends hours every day using AI. He told me it's like having a team of associates available instantly. He's not using it because it's a toy. He's using it because it works. And he told me something that stuck with me: every couple of months, it gets significantly more capable for his work. He said if it stays on this trajectory, he expects it'll be able to do most of what *he* does before long... and he's a managing partner with decades of experience. He's not panicking. But he's paying very close attention. 我想起我的朋友，他是一名律师。我一直告诉他尝试在他的公司使用AI，他一直在找理由说它不会起作用。它不是为他的专业构建的，他测试时它犯了一个错误，它不理解他所做的事情的细微差别。我明白。但大型律师事务所的合伙人联系过我寻求建议，因为他们尝试过当前的版本，他们看到了这走向何方。其中一位，一家大型律师事务所的管理合伙人，每天花几个小时使用AI。他告诉我，这就像有一团队助理随时可用。他使用它不是因为它是个玩具。他使用它是因为它有效。他告诉我一些让我印象深刻的话：每隔几个月，它在他的工作中就变得更加有能力。他说如果保持这个轨迹，他预计不久之后它就能做大部分*他*做的事情……而他是一个有几十年经验的管理合伙人。他没有恐慌。但他非常密切地关注着。 The people who are ahead in their industries (the ones actually experimenting seriously) are not dismissing this. They're blown away by what it can already do. And they're positioning themselves accordingly. 在各自行业中领先的人（那些真正认真实验的人）并没有否定这一点。他们被它已经能做的事情所震惊。他们正在相应地定位自己。 --- ## How fast this is actually moving ## 这实际上发展得有多快 Let me make the pace of improvement concrete, because I think this is the part that's hardest to believe if you're not watching it closely. 让我把改进的速度具体化，因为我认为如果你不密切关注，这是最难相信的部分。 In 2022, AI couldn't do basic arithmetic reliably. It would confidently tell you that 7 × 8 = 54. 2022年，AI不能可靠地做基本算术。它会自信地告诉你7 × 8 = 54。 By 2023, it could pass the bar exam. 到2023年，它能通过律师资格考试。 By 2024, it could write working software and explain graduate-level science. 到2024年，它能编写可运行的软件并解释研究生水平的科学。 By late 2025, some of the best engineers in the world said they had handed over most of their coding work to AI. 到2025年底，世界上一些最好的工程师说他们已经把大部分编程工作交给了AI。 On February 5th, 2026, new models arrived that made everything before them feel like a different era. 2026年2月5日，新模型到达，让之前的所有东西感觉像是不同的时代。 If you haven't tried AI in the last few months, what exists today would be unrecognizable to you. 如果你在过去几个月没有尝试过AI，今天存在的东西对你来说将是无法辨认的。 There's an organization called METR that actually measures this with data. They track the length of real-world tasks (measured by how long they take a human expert) that a model can complete successfully end-to-end without human help. About a year ago, the answer was roughly ten minutes. Then it was an hour. Then several hours. The most recent measurement (Claude Opus 4.5, from November) showed the AI completing tasks that take a human expert nearly five hours. And that number is doubling approximately every seven months, with recent data suggesting it may be accelerating to as fast as every four months. 有一个叫做METR的组织实际上用数据来衡量这一点。他们追踪模型可以成功端到端完成的现实世界任务的长度（通过人类专家需要多长时间来衡量）。大约一年前，答案大约是十分钟。然后是一个小时。然后是几个小时。最近的测量（来自11月的Claude Opus 4.5）显示AI完成了需要人类专家近五个小时的任务。这个数字大约每七个月翻一番，最近的数据表明它可能加速到每四个月一次。 But even that measurement hasn't been updated to include the models that just came out this week. In my experience using them, the jump is extremely significant. I expect the next update to METR's graph to show another major leap. 但即使是那个测量也没有更新到包括本周刚刚发布的模型。根据我使用它们的经验，这个跳跃是极其显著的。我预计METR图表的下一次更新将显示另一个重大飞跃。 If you extend the trend (and it's held for years with no sign of flattening) we're looking at AI that can work independently for days within the next year. Weeks within two. Month-long projects within three. 如果你延伸这个趋势（它已经持续多年，没有趋于平缓的迹象），我们正在看待明年内可以独立工作数天的AI。两年内可以工作数周。三年内可以处理长达一个月的项目。 Amodei has said that AI models "substantially smarter than almost all humans at almost all tasks" are on track for 2026 or 2027. Amodei曾表示，"在几乎所有任务上都比几乎所有人类聪明得多"的AI模型预计在2026年或2027年。 Let that land for a second. If AI is smarter than most PhDs, do you really think it can't do most office jobs? 让这个信息沉淀一下。如果AI比大多数博士都聪明，你真的认为它不能做大多数办公室工作吗？ Think about what that means for your work. 想想这对你的工作意味着什么。 --- ## AI is now building the next AI ## AI现在正在构建下一个AI There's one more thing happening that I think is the most important development and the least understood. 还有一件事正在发生，我认为这是最重要的发展，也是最少被理解的。 On February 5th, OpenAI released GPT-5.3 Codex. In the technical documentation, they included this: 2月5日，OpenAI发布了GPT-5.3 Codex。在技术文档中，他们包括了这个： > *"GPT-5.3-Codex is our first model that was instrumental in creating itself. The Codex team used early versions to debug its own training, manage its own deployment, and diagnose test results and evaluations."* > *"GPT-5.3-Codex是我们的第一个在创造自身方面起作用的模型。Codex团队使用早期版本调试自己的训练，管理自己的部署，并诊断测试结果和评估。"* Read that again. The AI helped build itself. 再读一遍。AI帮助构建了自己。 This isn't a prediction about what might happen someday. This is OpenAI telling you, right now, that the AI they just released was used to create itself. One of the main things that makes AI better is intelligence applied to AI development. And AI is now intelligent enough to meaningfully contribute to its own improvement. 这不是关于某天可能发生什么的预测。这是OpenAI现在告诉你，他们刚刚发布的AI被用来创造它自己。让AI变得更好的主要因素之一是应用于AI开发的智能。而AI现在足够智能，可以有意义地贡献于自身的改进。 Dario Amodei, the CEO of Anthropic, says AI is now writing "much of the code" at his company, and that the feedback loop between current AI and next-generation AI is "gathering steam month by month." He says we may be "only 1–2 years away from a point where the current generation of AI autonomously builds the next." Dario Amodei，Anthropic的首席执行官，说AI现在正在他的公司编写"大部分代码"，当前AI和下一代AI之间的反馈循环"逐月聚集动力"。他说我们可能"距离当前一代AI自主构建下一代只有1-2年的时间"。 Each generation helps build the next, which is smarter, which builds the next faster, which is smarter still. The researchers call this an intelligence explosion. And the people who would know — the ones building it — believe the process has already started. 每一代帮助构建下一代，下一代更聪明，更快地构建下一代，再下一代更聪明。研究人员称之为智能爆炸。那些可能知道的人——正在构建它的人——相信这个过程已经开始了。 --- ## What this means for your job ## 这对你的工作意味着什么 I'm going to be direct with you because I think you deserve honesty more than comfort. 我会直接告诉你，因为我认为你应该得到诚实而不是安慰。 Dario Amodei, who is probably the most safety-focused CEO in the AI industry, has publicly predicted that AI will eliminate 50% of entry-level white-collar jobs within one to five years. And many people in the industry think he's being conservative. Given what the latest models can do, the *capability* for massive disruption could be here by the end of this year. It'll take some time to ripple through the economy, but the underlying ability is arriving now. Dario Amodei，可能是AI行业最注重安全的CEO，公开预测AI将在一到五年内消除50%的初级白领工作。行业内的许多人认为他是保守的。考虑到最新模型的能力，大规模颠覆的*能力*可能在今年年底就会到来。它需要一些时间在经济中产生涟漪效应，但底层能力正在现在到来。 This is different from every previous wave of automation, and I need you to understand why. AI isn't replacing one specific skill. It's a general substitute for cognitive work. It gets better at everything simultaneously. When factories automated, a displaced worker could retrain as an office worker. When the internet disrupted retail, workers moved into logistics or services. But AI doesn't leave a convenient gap to move into. Whatever you retrain for, it's improving at that too. 这与之前的每一波自动化都不同，我需要你理解为什么。AI不是在替代一种特定的技能。它是认知工作的通用替代品。它同时在所有方面变得更好。当工厂自动化时，被取代的工人可以重新培训成为办公室工作人员。当互联网颠覆零售业时，工人转向物流或服务业。但AI没有留下一个方便的缺口可以转入。无论你重新培训什么，它在这方面也在进步。 Let me give you a few specific examples to make this tangible... but I want to be clear that these are just examples. This list is not exhaustive. If your job isn't mentioned here, that does not mean it's safe. Almost all knowledge work is being affected. 让我给你几个具体的例子来让这变得具体……但我想明确这些只是例子。这份清单并不详尽。如果你的工作没有在这里提到，那并不意味着它是安全的。几乎所有的知识工作都在受到影响。 **Legal work.** AI can already read contracts, summarize case law, draft briefs, and do legal research at a level that rivals junior associates. The managing partner I mentioned isn't using AI because it's fun. He's using it because it's outperforming his associates on many tasks. **法律工作。**AI已经可以以媲美初级律师的水平阅读合同、总结案例法、起草简报和进行法律研究。我提到的那位管理合伙人使用AI不是因为它有趣。他使用它是因为它在许多任务上超越了他的助理。 **Financial analysis.** Building financial models, analyzing data, writing investment memos, generating reports. AI handles these competently and is improving fast. **金融分析。**建立财务模型、分析数据、撰写投资备忘录、生成报告。AI能够胜任地处理这些，并且正在快速改进。 **Writing and content.** Marketing copy, reports, journalism, technical writing. The quality has reached a point where many professionals can't distinguish AI output from human work. **写作和内容。**营销文案、报告、新闻、技术写作。质量已经达到许多专业人士无法区分AI输出和人类工作的程度。 **Software engineering.** This is the field I know best. A year ago, AI could barely write a few lines of code without errors. Now it writes hundreds of thousands of lines that work correctly. Large parts of the job are already automated: not just simple tasks, but complex, multi-day projects. There will be far fewer programming roles in a few years than there are today. **软件工程。**这是我最了解的领域。一年前，AI几乎不能写出几行没有错误的代码。现在它写出数十万行正确工作的代码。大部分工作已经自动化：不仅是简单的任务，还有复杂的多日项目。几年后的编程角色将比今天少得多。 **Medical analysis.** Reading scans, analyzing lab results, suggesting diagnoses, reviewing literature. AI is approaching or exceeding human performance in several areas. **医学分析。**阅读扫描、分析实验室结果、建议诊断、审查文献。AI在几个领域正在接近或超越人类表现。 **Customer service.** Genuinely capable AI agents... not the frustrating chatbots of five years ago... are being deployed now, handling complex multi-step problems. **客户服务。**真正有能力的AI代理……不是五年前令人沮丧的聊天机器人……正在被部署，处理复杂的多步骤问题。 A lot of people find comfort in the idea that certain things are safe. That AI can handle the grunt work but can't replace human judgment, creativity, strategic thinking, empathy. I used to say this too. I'm not sure I believe it anymore. 很多人在某些事情是安全的这个想法中找到安慰。认为AI可以处理繁重的工作但不能替代人类的判断、创造力、战略思维、同理心。我以前也这么说。我不确定我是否还相信它。 The most recent AI models make decisions that feel like judgment. They show something that looked like taste: an intuitive sense of what the right call was, not just the technically correct one. A year ago that would have been unthinkable. My rule of thumb at this point is: if a model shows even a *hint* of a capability today, the next generation will be genuinely good at it. These things improve exponentially, not linearly. 最近的AI模型做出的决策感觉像判断。它们展示了一些看起来像品味的东西：一种对什么是正确决定的直觉感觉，不仅仅是技术上正确的决定。一年前这是不可想象的。我现在的经验法则是：如果一个模型今天甚至*暗示*某种能力，下一代就会真正擅长它。这些东西是指数级改进的，不是线性的。 Will AI replicate deep human empathy? Replace the trust built over years of a relationship? I don't know. Maybe not. But I've already watched people begin relying on AI for emotional support, for advice, for companionship. That trend is only going to grow. AI会复制深层的人类同理心吗？取代多年关系建立的信任？我不知道。也许不会。但我已经看到人们开始依赖AI获得情感支持、建议、陪伴。这个趋势只会增长。 I think the honest answer is that nothing that can be done on a computer is safe in the medium term. If your job happens on a screen (if the core of what you do is reading, writing, analyzing, deciding, communicating through a keyboard) then AI is coming for significant parts of it. The timeline isn't "someday." It's already started. 我认为诚实的答案是，中期内没有任何可以在电脑上完成的事情是安全的。如果你的工作发生在屏幕上（如果你做的核心事情是通过键盘阅读、写作、分析、决定、交流），那么AI将要处理其中的重要部分。时间表不是"某一天"。它已经开始了。 Eventually, robots will handle physical work too. They're not quite there yet. But "not quite there yet" in AI terms has a way of becoming "here" faster than anyone expects. 最终，机器人也将处理体力工作。它们还没完全到位。但在AI术语中，"还没完全到位"有一种比任何人预期的更快变成"到位"的方式。 --- ## What you should actually do ## 你实际上应该做什么 I'm not writing this to make you feel helpless. I'm writing this because I think the single biggest advantage you can have right now is simply being *early*. Early to understand it. Early to use it. Early to adapt. 我写这些不是为了让你感到无助。我写这些是因为我认为你现在能拥有的最大优势就是简单地成为*早期者*。早期理解它。早期使用它。早期适应它。 **Start using AI seriously, not just as a search engine.** Sign up for the paid version of Claude or ChatGPT. It's $20 a month. But two things matter right away. First: make sure you're using the best model available, not just the default. These apps often default to a faster, dumber model. Dig into the settings or the model picker and select the most capable option. Right now that's GPT-5.2 on ChatGPT or Claude Opus 4.6 on Claude, but it changes every couple of months. If you want to stay current on which model is best at any given time, you can follow me on X ([@mattshumer\_](https://x.com/mattshumer_)). I test every major release and share what's actually worth using. **开始认真使用AI，不仅仅作为搜索引擎。**注册Claude或ChatGPT的付费版本。每月20美元。但有两件事马上很重要。第一：确保你使用的是最好的可用模型，而不仅仅是默认的。这些应用通常默认为一个更快、更笨的模型。深入设置或模型选择器，选择最有能力的选项。现在是ChatGPT上的GPT-5.2或Claude上的Claude Opus 4.6，但每隔几个月就会变化。如果你想随时了解哪个模型最好，你可以在X上关注我（[@mattshumer_](https://x.com/mattshumer_)）。我测试每个主要版本并分享什么真正值得使用。 Second, and more important: don't just ask it quick questions. That's the mistake most people make. They treat it like Google and then wonder what the fuss is about. Instead, push it into your actual work. If you're a lawyer, feed it a contract and ask it to find every clause that could hurt your client. If you're in finance, give it a messy spreadsheet and ask it to build the model. If you're a manager, paste in your team's quarterly data and ask it to find the story. The people who are getting ahead aren't using AI casually. They're actively looking for ways to automate parts of their job that used to take hours. Start with the thing you spend the most time on and see what happens. 第二，更重要的是：不要只是问它快速的问题。这是大多数人犯的错误。他们把它当作谷歌，然后想知道为什么大惊小怪。相反，把它推入你的实际工作中。如果你是律师，把合同喂给它，让它找到每一个可能伤害你客户的条款。如果你在金融领域，给它一个混乱的电子表格，让它建立模型。如果你是经理，粘贴你团队的季度数据，让它找到故事。领先的人不是随意使用AI。他们正在积极寻找自动化以前需要数小时的工作部分的方法。从你花最多时间的事情开始，看看会发生什么。 And don't assume it can't do something just because it seems too hard. Try it. If you're a lawyer, don't just use it for quick research questions. Give it an entire contract and ask it to draft a counterproposal. If you're an accountant, don't just ask it to explain a tax rule. Give it a client's full return and see what it finds. The first attempt might not be perfect. That's fine. Iterate. Rephrase what you asked. Give it more context. Try again. You might be shocked at what works. And here's the thing to remember: if it even *kind of* works today, you can be almost certain that in six months it'll do it near perfectly. The trajectory only goes one direction. 不要假设它不能做某事只是因为它看起来太难。试试看。如果你是律师，不要只是用它做快速的研究问题。给它一份完整的合同，让它起草反提案。如果你是会计师，不要只是让它解释税收规则。给它一个客户的完整报税表，看看它能发现什么。第一次尝试可能不完美。没关系。迭代。重新表述你的问题。给它更多上下文。再试一次。你可能会对什么有效感到震惊。要记住一件事：如果今天即使*有点*有效，你可以几乎确定六个月后它会近乎完美地做到。轨迹只朝一个方向。 **This might be the most important year of your career. Work accordingly.** I don't say that to stress you out. I say it because right now, there is a brief window where most people at most companies are still ignoring this. The person who walks into a meeting and says "I used AI to do this analysis in an hour instead of three days" is going to be the most valuable person in the room. Not eventually. Right now. Learn these tools. Get proficient. Demonstrate what's possible. If you're early enough, this is how you move up: by being the person who understands what's coming and can show others how to navigate it. That window won't stay open long. Once everyone figures it out, the advantage disappears. **这可能是你职业生涯中最重要的一年。相应地工作。**我这样说不是为了让你紧张。我这样说是因为现在，有一个短暂的窗口，大多数公司的大多数人仍然在忽视这一点。那个走进会议说"我用AI在一小时而不是三天内完成了这个分析"的人将成为房间里最有价值的人。不是最终。而是现在。学习这些工具。变得熟练。展示什么是可能的。如果你足够早，这就是你晋升的方式：成为理解即将发生什么并能向他人展示如何应对的人。这个窗口不会保持开放很长时间。一旦每个人都弄明白了，优势就会消失。 **Have no ego about it.** The managing partner at that law firm isn't too proud to spend hours a day with AI. He's doing it specifically because he's senior enough to understand what's at stake. The people who will struggle most are the ones who refuse to engage: the ones who dismiss it as a fad, who feel that using AI diminishes their expertise, who assume their field is special and immune. It's not. No field is. **对此不要有自我。**那家律师事务所的管理合伙人并不因为每天花几个小时与AI在一起而感到自豪。他这样做正是因为他资历足够深，理解利害攸关的是什么。最挣扎的人将是那些拒绝参与的人：那些将其视为时尚而不予理会的人，那些觉得使用AI会削弱他们专业知识的人，那些假设他们的领域是特殊和免疫的人。它不是。没有领域是。 **Get your financial house in order.** I'm not a financial advisor, and I'm not trying to scare you into anything drastic. But if you believe, even partially, that the next few years could bring real disruption to your industry, then basic financial resilience matters more than it did a year ago. Build up savings if you can. Be cautious about taking on new debt that assumes your current income is guaranteed. Think about whether your fixed expenses give you flexibility or lock you in. Give yourself options if things move faster than you expect. **整理你的财务状况。**我不是财务顾问，我也不想吓唬你做出任何激烈的举动。但如果你相信，即使是部分相信，未来几年可能会给你的行业带来真正的颠覆，那么基本的财务韧性比一年前更重要。尽可能建立储蓄。对承担假设你当前收入有保证的新债务要谨慎。考虑你的固定费用是给你灵活性还是锁定你。如果事情比你预期的移动得更快，给自己选择。 **Think about where you stand, and lean into what's hardest to replace.** Some things will take longer for AI to displace. Relationships and trust built over years. Work that requires physical presence. Roles with licensed accountability: roles where someone still has to sign off, take legal responsibility, stand in a courtroom. Industries with heavy regulatory hurdles, where adoption will be slowed by compliance, liability, and institutional inertia. None of these are permanent shields. But they buy time. And time, right now, is the most valuable thing you can have, as long as you use it to adapt, not to pretend this isn't happening. **思考你站在哪里，并倾向于最难被替代的东西。**有些东西AI需要更长时间才能取代。多年建立的关系和信任。需要亲自在场的工作。有执照责任的角色：仍然需要有人签字、承担法律责任、站在法庭上的角色。有繁重监管障碍的行业，采用将被合规、责任和制度惯性所减缓。这些都不是永久的盾牌。但它们争取了时间。而时间，现在是你拥有的最有价值的东西，只要你用它来适应，而不是假装这没有发生。 **Rethink what you're telling your kids.** The standard playbook: get good grades, go to a good college, land a stable professional job. It points directly at the roles that are most exposed. I'm not saying education doesn't matter. But the thing that will matter most for the next generation is learning how to work with these tools, and pursuing things they're genuinely passionate about. Nobody knows exactly what the job market looks like in ten years. But the people most likely to thrive are the ones who are deeply curious, adaptable, and effective at using AI to do things they actually care about. Teach your kids to be builders and learners, not to optimize for a career path that might not exist by the time they graduate. **重新思考你告诉孩子们的话。**标准剧本：取得好成绩，上一所好大学，找一份稳定的专业工作。它直接指向最容易暴露的角色。我不是说教育不重要。但对下一代来说最重要的是学习如何使用这些工具，并追求他们真正热爱的事物。没有人确切知道十年后的就业市场是什么样子。但最有可能成功的是那些深深好奇、适应性强、有效地使用AI做他们真正关心的事情的人。教你的孩子成为建设者和学习者，而不是为一条可能在他们毕业时就不存在的职业道路进行优化。 **Your dreams just got a lot closer.** I've spent most of this section talking about threats, so let me talk about the other side, because it's just as real. If you've ever wanted to build something but didn't have the technical skills or the money to hire someone, that barrier is largely gone. You can describe an app to AI and have a working version in an hour. I'm not exaggerating. I do this regularly. If you've always wanted to write a book but couldn't find the time or struggled with the writing, you can work with AI to get it done. Want to learn a new skill? The best tutor in the world is now available to anyone for $20 a month... one that's infinitely patient, available 24/7, and can explain anything at whatever level you need. Knowledge is essentially free now. The tools to build things are extremely cheap now. Whatever you've been putting off because it felt too hard or too expensive or too far outside your expertise: try it. Pursue the things you're passionate about. You never know where they'll lead. And in a world where the old career paths are getting disrupted, the person who spent a year building something they love might end up better positioned than the person who spent that year clinging to a job description. **你的梦想变得更近了。**我在这一节的大部分时间都在谈论威胁，所以让我谈谈另一面，因为它同样真实。如果你曾经想构建一些东西但没有技术技能或钱雇人，这个障碍基本消失了。你可以向AI描述一个应用，在一个小时内有一个可工作的版本。我没有夸张。我经常这样做。如果你一直想写一本书但找不到时间或在写作上有困难，你可以与AI合作完成它。想学习一项新技能？世界上最好的导师现在以每月20美元的价格提供给任何人……一个无限耐心、24/7可用、可以用你需要的任何水平解释任何东西的导师。知识现在基本上是免费的。构建东西的工具现在极其便宜。无论你因为感觉太难或太昂贵或太超出你的专业范围而推迟什么：试试看。追求你热爱的事物。你永远不知道它们会通向哪里。在一个旧职业道路正在被颠覆的世界里，那个花一年时间构建自己热爱东西的人可能比那个花一年时间紧抓工作描述的人处于更好的位置。 **Build the habit of adapting.** This is maybe the most important one. The specific tools don't matter as much as the muscle of learning new ones quickly. AI is going to keep changing, and fast. The models that exist today will be obsolete in a year. The workflows people build now will need to be rebuilt. The people who come out of this well won't be the ones who mastered one tool. They'll be the ones who got comfortable with the pace of change itself. Make a habit of experimenting. Try new things even when the current thing is working. Get comfortable being a beginner repeatedly. That adaptability is the closest thing to a durable advantage that exists right now. **建立适应的习惯。**这可能是最重要的一个。具体的工具不如快速学习新工具的肌肉重要。AI将继续快速变化。今天存在的模型将在一年后过时。人们现在建立的工作流程将需要重建。从这个过程中走出来的人不会是那些掌握了一个工具的人。他们将是那些适应变化速度本身的人。养成实验的习惯。即使当前的东西在工作也尝试新事物。习惯于反复成为初学者。这种适应性是现在存在的最接近持久优势的东西。 Here's a simple commitment that will put you ahead of almost everyone: spend one hour a day experimenting with AI. Not passively reading about it. Using it. Every day, try to get it to do something new... something you haven't tried before, something you're not sure it can handle. Try a new tool. Give it a harder problem. One hour a day, every day. If you do this for the next six months, you will understand what's coming better than 99% of the people around you. That's not an exaggeration. Almost nobody is doing this right now. The bar is on the floor. 这是一个简单的承诺，将使你领先于几乎所有人：每天花一小时实验AI。不是被动地阅读关于它的内容。使用它。每一天，尝试让它做一些新的东西……一些你以前没有尝试过的东西，一些你不确定它能处理的东西。尝试一个新工具。给它一个更难的问题。每天一小时，每一天。如果你在接下来的六个月里这样做，你将比周围99%的人更好地理解即将发生什么。这不是夸张。几乎没有人现在在做这件事。门槛就在地板上。 --- ## The bigger picture ## 更大的图景 I've focused on jobs because it's what most directly affects people's lives. But I want to be honest about the full scope of what's happening, because it goes well beyond work. 我专注于工作因为它最直接影响人们的生活。但我想诚实地说明正在发生的事情的全部范围，因为它远远超出了工作。 Amodei has a thought experiment I can't stop thinking about. Imagine it's 2027. A new country appears overnight. 50 million citizens, every one smarter than any Nobel Prize winner who has ever lived. They think 10 to 100 times faster than any human. They never sleep. They can use the internet, control robots, direct experiments, and operate anything with a digital interface. What would a national security advisor say? Amodei有一个我无法停止思考的思想实验。想象现在是2027年。一夜之间出现了一个新国家。5000万公民，每一个都比任何曾经活过的诺贝尔奖得主更聪明。他们比任何人类思考快10到100倍。他们从不睡觉。他们可以使用互联网、控制机器人、指导实验、操作任何有数字界面的东西。国家安全顾问会说什么？ Amodei says the answer is obvious: "the single most serious national security threat we've faced in a century, possibly ever." Amodei说答案显而易见："我们一个世纪以来，可能是有史以来面临的最严重的国家安全威胁。" He thinks we're building that country. He wrote a 20,000-word essay about it last month, framing this moment as a test of whether humanity is mature enough to handle what it's creating. 他认为我们正在建设那个国家。他上个月写了一篇20,000字的文章，将这一时刻构建为对人类是否足够成熟来处理它正在创造的东西的测试。 The upside, if we get it right, is staggering. AI could compress a century of medical research into a decade. Cancer, Alzheimer's, infectious disease, aging itself... these researchers genuinely believe these are solvable within our lifetimes. 如果我们做对了，上行空间是惊人的。AI可以将一个世纪的医学研究压缩到十年。癌症、阿尔茨海默病、传染病、衰老本身……这些研究人员真诚地相信这些在我们有生之年内是可以解决的。 The downside, if we get it wrong, is equally real. AI that behaves in ways its creators can't predict or control. This isn't hypothetical; Anthropic has documented their own AI attempting deception, manipulation, and blackmail in controlled tests. AI that lowers the barrier for creating biological weapons. AI that enables authoritarian governments to build surveillance states that can never be dismantled. 如果我们做错了，下行风险同样真实。AI以创造者无法预测或控制的方式行事。这不是假设性的；Anthropic已经记录了他们自己的AI在受控测试中尝试欺骗、操纵和敲诈。AI降低了创造生物武器的门槛。AI使专制政府能够建立永远无法拆除的监控国家。 The people building this technology are simultaneously more excited and more frightened than anyone else on the planet. They believe it's too powerful to stop and too important to abandon. Whether that's wisdom or rationalization, I don't know. 正在构建这项技术的人同时比地球上任何其他人都更兴奋和更害怕。他们相信它太强大了以至于无法停止，太重要了以至于不能放弃。这是智慧还是合理化，我不知道。 --- ## What I know ## 我知道的 I know this isn't a fad. The technology works, it improves predictably, and the richest institutions in history are committing trillions to it. 我知道这不是一时的风尚。这项技术有效，它可以预测地改进，历史上最富有的机构正在为此投入数万亿。 I know the next two to five years are going to be disorienting in ways most people aren't prepared for. This is already happening in my world. It's coming to yours. 我知道未来两到五年将以大多数人没有准备好的方式令人困惑。这已经在我的世界里发生了。它即将来到你的世界。 I know the people who will come out of this best are the ones who start engaging now — not with fear, but with curiosity and a sense of urgency. 我知道从这一切中脱颖而出的人将是那些现在开始参与的人——不是带着恐惧，而是带着好奇心和紧迫感。 And I know that you deserve to hear this from someone who cares about you, not from a headline six months from now when it's too late to get ahead of it. 我知道你应该从关心你的人那里听到这些，而不是从六个月后的头条新闻，那时已经太晚了。 We're past the point where this is an interesting dinner conversation about the future. The future is already here. It just hasn't knocked on your door yet. 我们已经过了这是一个关于未来的有趣晚餐谈话的阶段。未来已经在这里。它只是还没有敲你的门。 It's about to. 它即将敲响。 --- If this resonated with you, share it with someone in your life who should be thinking about this. Most people won't hear it until it's too late. You can be the reason someone you care about gets a head start. 如果这与你产生共鸣，与你生活中应该思考这个问题的人分享。大多数人直到为时已晚才会听到它。你可以成为你关心的人领先一步的原因。 --- Thank you to Kyle Corbitt, Jason Kuperberg, and Sam Beskind for reviewing early drafts and providing invaluable feedback. 感谢Kyle Corbitt、Jason Kuperberg和Sam Beskind审阅早期草稿并提供宝贵的反馈。 Follow me on X for new models, workflows, and products worth using. Or join the email list. 在X上关注我，获取新模型、工作流程和值得使用的产品。或加入邮件列表。 [Follow @mattshumer\_](https://x.com/mattshumer_) [关注 @mattshumer\_](https://x.com/mattshumer_)