马克·安德森谈为何此刻是科技史上最重要的时刻

其结果是，所有受影响的行业都会出现商品和服务的过剩。

The result of that is you get gluts of goods and services in all those affected sectors.

这些过剩导致价格暴跌。

The result of those gluts is you get collapsing prices.

对吧？

Right?

价格暴跌意味着，今天价值100美元的东西现在只值10美元，甚至1美元——这相当于给每个人发了一笔巨额加薪，对吧？

The collapsing prices mean that the thing today that cost you $100 now cost you $10 and now cost you $1 That's the equivalent of giving everybody a giant raise, right?

因为现在他们拥有了更多的可支配收入。

Because now they have all this additional spending power.

这种额外的购买力会进一步推动经济增长，对吧？

That additional spending power then translates to economic growth, right?

新兴领域的兴起。

The development of new fields.

每个人都会迅速变得物质上富裕得多。

Everybody's like materially like much better off very quickly.

而且顺便说一下，如果在这一过程之后确实出现了失业，那么提供社会安全网以防止人们陷入贫困的成本也大大降低了。

And then by the way, if you to the extent that you do have unemployment coming out the other side of that, it's it's now much cheaper to provide the kind of social safety net to prevent people from being immiserated.

对吧？

Right?

因为福利项目所需支付的所有商品和服务的价格都在大幅下降。

Because the prices of all the goods and services that like a welfare program has to pay from, they're all collapsing.

对吧？

Right?

因此，医疗保健的价格下降了，住房的价格下降了，教育的价格下降了，其他一切的价格都在下降，这是因为人工智能带来的巨大影响。

And so the price of health care collapses, the price of housing collapses, the price of education collapses, the price of everything else collapses because this incredible impact that AI is having.

所以在人们所设想的这种乌托邦式反乌托邦情景中，根本不存在所有人都变穷的可能性。

And so in this kind of utopian dystopian scenario that people have, there's no scenario in which everybody's just poor.

事实上，情况恰恰相反：所有人都变得更富裕了，因为价格暴跌了。

In fact, it's quite the opposite, which is everybody gets a lot richer because prices collapse.

而且，为那些由于某种原因找不到工作的人提供社会安全网，也变得容易多了。

And then it's actually much easier to pay for the social safety net for the people who, for some reason, can't find a job.

所以，我们可能会进入那种情境。

And so maybe we end up in that scenario.

我的意思是，我乐观的一面认为，是的，也许AI真的有那么强大，也许经济的其他部分真的能调整以适应它，也许这种情况就会发生。

I mean, the kind of optimistic part of me says, yeah, maybe AI is that powerful and maybe the rest of the economy can actually change to accommodate that and maybe that'll happen.

但结果将是，一个比人们想象中好得多的新故事。

But the result of that is gonna be a much better new story than people think it's going to be.

而且，顺便说一下，我刚才描述的一切，都只是基于基本经济学的直接推演。

And and again, everything I've just described, by the way, is like just a very straightforward extrapolation on very basic economics.

我并没有对我刚才所说的内容做出任何大胆的预测。

I'm not making any like bold predictions of what I just said.

这只是一个非常直接的机械过程，只要你有更高的生产率增长——而这必然源于更高的技术进步率。

This is just like a straightforward mechanical process that that plays itself out if you have higher rates of productivity growth, which are necessarily the results of higher rates of technological growth.

所以我认为，我们正在面对的，而且明确地说，是一个既不像乌托邦主义者设想的那样彻底变革，也不像反乌托邦者担心的那样极端的世界。

And so I think we're I think we're looking at and and and to be clear, I think we're looking at a world that's not like radically transform the way that maybe the utopians think that it will be or the dystopias think it will be.

我认为这会是一个渐进的过程，我们可以进一步讨论，但我相信，这种渐进变化总体上是利好消息，即使它发生得更快，也依然是一个利好过程。

I think it'll be more incremental for races we can discuss, but I think that incremental overwhelmingly, I think that process is going to be a good news process, and then even if it's much faster, it's also gonna be a good news process.

它将以我之前描述的另一种方式成为好消息的过程。

It'll just be a good news process in the other way that I was described.

我喜欢听到乐观和好消息。

I love hearing optimism and good news.

我还要补充一点，我在与你聊天前研究过你，你对世界走向的判断多次都是正确的。

I will also add that you've been I was researching you ahead of this chat, and you've been right so many times about where the world is heading.

这就是为什么我特别期待与你交谈。

That's why I'm especially excited to talk to you.

我给你列一个简短的清单。

I'll give you a short list.

我猜还有很多其他事情。

I imagine there are many more things.

好的。

Okay.

首先，你正确预测了网络和网页浏览器的重要性。

So one, you were right about the web and web browsers becoming important.

你正确地预测了软件正在吞噬世界。

You were right about software eating the world.

没错。

Check.

你在2011年说过，十年后将有50亿人使用智能手机，而实际数字最终达到了60亿。

You in 2011, you said that in ten years, we're gonna have 5,000,000,000 people using smartphones, and I believe the actual number ended up being 6,000,000,000.

你还和彼得·蒂尔有过一场辩论，我后来看到了，你们在讨论技术是否已经停滞，还是新技术会持续涌现，你坚持认为技术仍在进步。

You also you had this debate with Peter Thiel that I came across where you were debating whether technology has stopped progressing or if new technology will continue to emerge, and you were arguing there's progress.

进步会继续下去。

Progress will continue.

而他却说，不。

And he he was like, no.

我觉得我们已经不再有酷炫的技术了。

I think we're done with cool technology.

你是对的。

You were right.

想象一下，你还对了很多其他事情。

Imagine there are many more things you were right about.

所以，再次说一遍，我真的很喜欢听你的预测，因为我觉得它们最终都会成真。

So so again, I'm just I I love hearing your predictions because I feel like they're actually gonna turn out to be correct.

我本来想说，我错了很多事情，但你知道的，我把那些错误都埋在棚子后面了。

So I was gonna start by saying I've been wrong about tons of things, but, you know, I bury those out back behind the shed.

把它们从互联网上删掉。

Delete them from the Internet.

没有浏览器能丢弃‘是的’。

No browser can discard Yes.

我已经让它们从互联网档案中彻底消失了，这样就没人再能看到它们了。

I have them nuked out of the Internet archives so that they know they're never seen again.

所以我也经常犯错。

So I'm wrong plenty of times also.

但是啊，我的意思是，想想看，是的。

But yeah, I mean, look, think yeah.

其中一些并不正确。

Some of those are not right.

顺便说一下，关于彼得的观点，我越来越认同他的看法了。

By way, will say on Peter one, I have come I have come much more around to Peter's point of view.

如果今天再讨论这一点，我可能会有完全不同的看法，而且我会给予他的观点更多的认可。

I would probably argue that one, like, quite a bit differently today than I did, and I would give his view, I think I think, a lot more credit.

这实际上引出了我们刚才讨论的那种话题，也就是彼得所主张的核心：我们在比特层面有很多进展。

And and it actually goes to the kind of the discussion that would be the kind of conversation we just had, which is real form of what Peter was arguing was we have lots of process in bit.

我们在比特层面确实有很多进步，但在原子层面却几乎没有进展。

We have lots of progress in bits, right, but we have very little progress in atoms.

对吧？

Right?

这正是他主张的核心所在。

And that's the real core of what he was arguing.

我认为我当时有点忽略了这一点，或者只是轻描淡写地带过了，因为我太专注于确保人们明白，不是这样的。

And I think I I I think I I was a little bit, don't I know, missing that or kind of, you know, kind of glossing that over a little bit because I was so focused on making sure people understood, no.

实际上，比特领域仍然在取得进展。

There actually is still progress happening in in bits.

但我认为，他对原子领域缺乏进展的许多批评是切实存在的。

But I think, know, a lot of his critiques around the lack of progress in Adams is real.

而且，再次强调，这又回到了他长期以来一直在谈论的这个问题。

And and, again, this goes back to this thing of, like, in the and he you know, he's talking about this for a long time.

在过去五十年里，整个经济中几乎没有什么技术革新。

In the last fifty years, there has just been very little technological innovation in most of the economy.

尤其是在涉及原子领域的任何方面，技术革新都极少。

There's been very little technological innovation in particular in anything involving Adams.

你知道，现实世界中的技术变革非常有限。

You know, there's been very little real world technological change.

确实没有多少变化。

There hasn't been.

今天建成的世界与五十年前相比并没有太大不同。

The built world is just not that different today than it was fifty years ago.

再者，如果你对比1870年和1930年，那是一个截然不同的世界。

And again, if you contrast that, you compare and contrast 1870 to 1930, it was a dramatically different world.

如果你对比1930年和1970年，那也是一个截然不同的世界。

If you contrast 1930 to 1970, it was a dramatically different world.

如果你对比1970年到现在，变化并不大。

If you contrast 1970 to date, it's not that different.

对吧？

Right?

而且你看，你只要随便走走，就会发现，哦，确实如此。

And and, look, you just see that you could just, like, walk around, and it's just like, oh, yeah.

有很多建筑都是在1960年左右建的。

There's a bunch of buildings that were built in, like, 1960.

对吧？

Right?

有一座桥是1930年左右建的，有一座水坝是1910年左右建的，还有一座城市是1880年左右建立的。

And there's a bridge that was built in, like, 1930, and there's a dam that was built in, like, 1910, and there's a city that was founded in, you know, 1880.

那我们到底做了些什么？

And, like, what have we done?

我们的新城市在哪里？

And, like, where are our new cities?

我们的新水坝在哪里？

Where are our new dams?

你知道，加州高速铁路到底在哪？

Where you know, where's where's the California high speed rail?

你知道，到底发生什么事了？

Like, you know you know, like, what's going on here?

所以，我觉得他对很多事的看法是对的。

And so, like, I think he is I I think he is right about a lot of that.

同样，这也是为什么我认为人工智能不会产生如此迅速的影响。

Again, this is also why I think that AI is not going to have as rapid an impact.

它不会像人们想象的那样，一夜之间带来全然乌托邦或反乌托邦的改变。

It's not going to be again, this kind of utopian or dystopian view of, like, everything changes overnight.

我认为这根本不可能发生，因为彼得所阐述的原因——世界上有太多事情都被繁文缛节牢牢束缚住了。

I think it just kind of can't happen because of the reasons that Peter articulates, which is there's just there's so much about how the world works that's basically just, like, wrapped up in red tape.

比如官僚流程、规章制度、限制，还有政治因素。

Like, bureaucratic process, rules, restrictions, you know, the the the politics.

顺便说一句，工会、卡特尔、寡头垄断，世界上存在这么多经济、政治或监管结构，它们本质上都阻止了变革的发生。

By the way, you know, unions, cartels, oligopolies, there there's all these structures in the world that are kind of economic or political or regulatory structures that basically prevent things from changing.

我们拿人工智能对医疗系统的影响做个例子。

Let's take a great example, AI's impact on the healthcare system.

按理说，人工智能将对医疗系统产生巨大而积极的影响。

By rights, AI is gonna have a dramatic impact on the health care system and in very positive ways.

但如今医疗体系的很大一部分其实就是卡特尔。

But large parts of the medical system today are they are cartels.

对吧？

Right?

所以医生是卡特尔，护士是卡特尔，医院也是卡特尔。

And so there's like the doctors are cartel and, like, nurses are cartel, like, hospitals are cartel.

然后还有一种推动，想要将所有医疗体系国有化，这样一来，你就有了政府垄断。

And then there's this push to, like, nationalize all the health care systems, and then you've got, you know, then you've got a government monopoly.

对吧？

Right?

而事实是，卡特尔和垄断都不喜欢快速变革。

And it's like and and and guess what cartels and monopolies don't like is they don't like, like, rapid change.

对吧？

Right?

所以，当你作为一个年轻人出现时，你会说，哇。

And so, you know, you show up as a kid, and you're like, wow.

我有了这种新的AI医疗技术。

I've got, like, this new technology to do AI medicine.

但他们却说，哦，这会威胁到医生的利益吗？

And they're like, oh, well, does it threaten doctor's valves?

如果是这样，我们就阻止它。

In that case, we're gonna block it.

我认为很多消费者——顺便说一下，我在生活中就看到这种情况，你可能在你的生活中也会看到——实际上比你现在的医生要好得多。

And I think a lot of consumers, by the way I see this in my life, and you'll probably see this in your life also, is, like, is almost certainly a better doctor than your doctor today.

但ChatGPT无法获得行医执照。

But ChechiPT can't get a license to practice medicine.

所以它不能替代医生。

So it can't substitute for a doctor.

它不能开药。

It can't prescribe medications.

它不能进行手术。

It can't perform procedures.

因此，无论如何，我认为这一点说得非常清楚，而且长期以来一直如此：经济和政治体系中确实存在一些真正的结构性障碍，阻碍了变革速度，使其远不及过去人们所经历的变革速度。

And so there are these Anyway, so I think, was very articulate and has been for a long time on like, no, there are actually real structural impediments in the economy and in the political system that we have that actually prevent the rates of change that are anywhere near the rates of change that people have in the past.

而且你或许可以乐观地认为，AI这种新奇技术的存在，或许会让我们首次在几十年来重新审视许多这些假设，认真思考一下：

And and you can maybe say optimistically, you know, maybe the presence of it of the new of the new magic technology of AI, maybe it causes us to revisit a lot of these assumption assumptions for the first time in decades to really say, okay.

这真的是我们想要生活的世界吗？

Is this really the world we wanna live in?

我们难道不希望更快地抵达未来吗？

Don't we actually wanna get to the future faster?

所以这可能是乐观的看法。

So maybe that would be the optimistic view.

有人曾著名地说过：是时候去建设了。

It's time to build, somebody famously said.

在我的日程里，我确实把这句话设为我开始工作时的提醒。

I in my calendar, I actually have that as my when I start to work.

是时候去建设了。

It's time to build.

这是我今天上午的座右铭。

That's my block in the morning today.

谢谢你的分享。

Thank you for that.

好的。

Okay.

我喜欢你从宏观视角直接跳到个体终点，然后我想转向‘N个一’的思路。

I love I love the way you go from just, like, macro to just, like, end of one, and I wanna go to N of one.

这个播客的很多听众都是产品经理。

A lot of the listeners of this podcast are product managers.

他们是工程师。

They're engineers.

他们是设计师。

They're designers.

有很多创始人，但也有不少非创始人。

There's a lot of founders, but there's also a lot of non founders.

有很多不是创始人的产品构建者，显然，很多人对自己的职业发展方向感到担忧。

There's a lot of people building product that aren't founders, and obviously, a lot of people are worried about where their career is going.

这些角色中会有一个消失吗？

Is one of these roles gonna disappear?

这些角色中会有一个表现得特别出色吗？

Is one of these roles gonna do really well?

我该如何保持更新？

How do I stay up to date?

你和很多团队、很多产品团队关系都很密切。

You're close with a lot of teams, a lot of product teams.

你对这三种特定角色——产品经理、工程师、设计师——的未来有什么看法？

What's your sense of just the future of these three very specific roles, product manager, engineer, designer?

我觉得这个问题是

This, I think, is a

一个非常有趣的问题。

really funny question.

这三种角色，尤其是这三种，显然是科技公司构建产品时的核心角色。

So the the the these three roles in particular, obviously, are kind of the central roles for for building you know, for tech companies.

我一直以来的描述是，你知道墨西哥式对峙这个概念吧，就是电影里两个人用枪指着对方头部的场景。

So the way I've been describing it is, you know you know the concept of the Mexican standoff, right, which is the the movie scene where the, you know, the two guys have guns pointing at each other's heads.

嗯。

Mhmm.

如果你看约翰·伍伊的电影，他会特别喜欢拍三方对峙的场景，就是形成一个三角形，每个人手里都拿着枪。

And then there's if you watch, like, John Woo movies, he loves to have he does the three way Mexican standoff where you've got, like, a triangle, you know, people and and, the, you know, and of course, it's John Woo movie is they've got, you know, guns in both hands.

所以他们每个人都瞄准另外两个人。

So they're all each each is aiming at the other two.

是的。

Yeah.

于是就形成了这种对峙的局面。

And you got this kind of standoff situation.

我一直以来是这样描述的：产品经理、设计师和程序员这三者之间正发生着一场类似墨西哥式对峙的局面，具体来说就是，现在的每个程序员都觉得自己也能当产品经理和设计师，对吧？

So the the the way I've been describing this is there's like a Mexican standoff happening between those three roles, between product manager, designer, and and coder, specifically of the following, which is every coder now believes they can also be a product manager and a designer, right?

因为他们有AI。

Because they have AI.

每个产品经理都觉得他们能当程序员和设计师，而每个设计师也确信自己能胜任产品经理和程序员的工作。

Every product manager thinks they can be a coder and a designer, and then every designer knows they can be a product manager and a coder.

因此，这三个角色中的每个人都认为，有了AI之后，他们不再需要另外两个角色了。

And so people in each of those roles now know or believe that with AI, they don't need the other two roles anymore.

对吧？

Right?

他们之所以能做到，是因为可以借助AI来完成。

They they they can do that because they can have AI do that.

当然，真正的讽刺在于，这三者最终都会意识到，AI也能成为更好的管理者。

And then, of course and then, of course, there's the real irony, which is, you know, all the the three all three of them are gonna realize that AI can also be a better manager.

对吧？

Right?

所以他们会把枪口对准组织架构的上方，但这可能是下一阶段的事。

So they're gonna they're gonna aim the guns up the org chart, but that that's probably the that's the next phase.

我觉得这个所谓的“墨西哥式对峙”最有趣的地方在于，他们其实都有一定道理。

And what I think is so fascinating about this Mexican Mexican tab is they're actually all kind of correct, I think.

对吧？

Right?

也就是说，AI现在确实是个相当不错的程序员。

Which is AI is actually a pretty good know, it's now it's actually now a really good coder.

它现在也是一个非常出色的设计师，同时还是一个非常出色的产品经理。

It's actually now a really good designer, and it's also a really good product manager.

对吧？

Right?

它实际上擅长做这三件事，或者至少能完成这三份工作中大量的任务。

It's actually good at doing all three of those things or at least doing a lot of the tasks involved in in in those three jobs.

所以，再次强调，这回到了超级赋能个体这个概念——如果我是个程序员，我的第一步是必须真正理解AI编程，以及这意味什么，还有编程在未来将如何变化。

And so, again, this this goes back to the the the super this kind of idea of the super empowered individual where if if I'm a coder, like, you know I mean, step one is, like, I need to make sure that I really understand AI coding and, like, what that means and what how coding is gonna change in the future.

也就是说，我需要明确知道，如何从一个完全手动编写代码的程序员，转变为一个能够协调十几个编码机器人的人。

You know, that that I need to under you know, specifically how to go from being a coder who writes code entirely by hand to being a coder who orchestrates a dozen instances of coding bots.

编程工作的本质正在发生改变，而这种变化正在当下发生。

There's a change in the actual job of coding itself, which is happening right now.

但另一部分是，我该如何成为这样的个体？

But the other part of it is, okay, how do I become that part individual?

我该如何成为一个程序员，同时还能利用AI，让自己也成为出色的产品经理和设计师？

How do I become a coder that also then harnesses AI so that I can also be a great product manager and I can also be a great designer?

对于产品经理来说也是同样的道理，我该如何确保自己能够使用编码工具？

And then the same thing for the product manager, which is how do I make sure that I can now use coding tools?

我该如何确保自己也能进行基于AI的设计？

How do I make sure I can also do AI based design?

对于设计师来说也是如此，我该如何利用AI来成为一名程序员和产品经理？

And the same thing for the designer, which is how do I use AI to also become a coder and also become a product manager?

于是，你可能会发现这些个体角色发生了变化，比如这些角色可能不再像过去三十年那样是彼此孤立的了。

And then what you get is maybe those individual roles change, like maybe those are not any more sort of stovepipe roles the way that they have been for the last thirty years or whatever.

但真正发生的是，这些领域中的优秀人才变得能力超群，能够同时精通这三件事。

But what happens is that the talented people in any of those roles become super powered and they become good at doing all three of those things.

而这些人才会变得极其宝贵，因为他们真的能够从零开始构建和设计新产品，而这才是最有价值的。

And then and then those people become incredibly valuable because then those are people who can actually, like, you know, build and design, right, new products, from scratch, which is the most valuable thing.

所以我认为，这就是其中的机会。

And so I think that's the opportunity.

我很喜欢这个回答。

So I love this answer.

所以我的理解是，如果你在这三个角色中的任何一个方面非常出色，就会表现得很好。

So what I'm hearing is essentially, if you're amazing at any of these three roles, will do well.

第一，如果你在这些角色中非常出色，那很好。

Number one, if you're amazing at these roles, that's great.

但成为这些角色中的佼佼者，还包括能够充分运用新技术。

But also part of being amazing in these roles is also being able to fully harness the new technology.

所以，如果你今天是一个顶尖的程序员，却始终无法学会如何利用AI来增强你的编程能力并提升效率，迟早你会遇到瓶颈。

So if you're a master coder today and you don't ever get to the point where you figure out how to use AI to leverage your coding skills and do more, at some point you are gonna hit an issue.

对吧？

Right?

经济学家们还有另一种说法，那就是所谓的‘职位’其实并不是职场中最小的工作单元。

Here's another way economists talk about this, which is there's a concept of the job, but the job is not actually the atomic unit of what happens in the workplace.

职场中最基本的单元是‘任务’。

The atomic unit of what happens in workplace is the task.

经济学家认为，职位实际上是一组任务的集合。

And so and and then what what the way the economists think about it is a job is a bundle of tasks.

每个人都想谈论失业，但你真正应该关注的是任务的消失。

And everybody wants to talk about job loss, but really what you wanna look at is is task task loss.

对吧？

Right?

任务在变化。

Tasks changing.

我的意思是，任务变化的经典例子。

I mean, the the classic the classic example of task changing.

经典的任务变化例子是，过去高管们自己从不使用打字机或个人电脑。

Classic example of task changing was once upon a time, executives never used typewriters or personal computers themselves.

对吧？

Right?

你知道，如果你是1970年或那时候一家公司的副总裁，你的桌上不会有打字机或电脑自己打字。

You know, if you were a vice president of a company in 1970 or whatever, you did not have like a typewriter or computer on your desk typing things.

你有一个秘书，你向她口述备忘录。

You had a secretary who you dictated memos to.

后来出现了电子邮件，秘书的工作也随之改变，从以前负责贴邮票寄信，变成了与其他行政人员收发电子邮件。

And there was this change where emails started to show up, and what would happen was the job of the secretary then went from job of the secretary changed for sending out letters with stamps on them to, like, sending or receiving emails with the other admins.

然后，秘书会把电子邮件打印出来，送到高管的办公室。

And then and then the the secretary would print out the email and bring it into the executive's office.

高管阅读纸质邮件后，手写回复，再把回复交给秘书，秘书回到自己的办公桌前，把内容打字输入电脑并发送出去。

The executive office would read the email and paper, scroll scroll the reply, and and and and give and give that message back to the secretary who would go back and type into the computer on on on on his or her desk and and send it as an email.

而如今，这一切都不再发生了。

Fast forward to today, none of that happens.

现在，高管们自己处理所有电子邮件。

Now executives just do all their own email.

他们仍然有秘书或行政人员，但这些人的工作内容已经不同了。

They still have secretaries or admins, but they're now doing different tasks.

他们现在负责规划和协调活动，做各种其他事情，那些优秀的行政人员擅长的那些事。

You know, they're planning and orchestrating events and, like, doing all these other things, you know, that that, you know, that that that that great admins do.

讽刺的是，高管的职责范围反而扩大了，他们自己要承担更多文书工作，比如坐在那里亲自打字写备忘录——而这在五十年前，他们是绝对不会做的。

And then the and then the test the test set ironically of the executive has expanded to do actually more of the clerical work themselves, actually, like, sit there and, like, type their memos, which again, fifty years ago, they never would have done that.

所以高管的工作仍然存在，秘书的工作也仍然存在，但任务已经改变了。

And so the executive job still exists, the secretary job still exists, but the tasks have changed.

我认为这是编程领域即将发生情况的一个绝佳例子。

I think that's a great example of what's gonna happen in coding.

任务将会发生变化。

The tasks are gonna change.

这也会发生在产品管理上，任务将会发生变化。

This was gonna product management, the tasks are gonna change.

设计师的任务将会改变。

Designer tasks are gonna change.

因此，工作比单个任务持续得更久。

And so the job persists longer than the individual tasks.

当任务变化到一定程度时，工作才会真正发生变化。

And then as the tasks change enough, then that's when the jobs change.

所以对于个人而言，你最好这样想：我有一份工作，这份工作是一系列任务的集合。

And so at the level of an individual, you kind of want to think of like, okay, I have this job, The job is a bundle of tasks.

我需要非常擅长确保自己能够随时替换任务。

I need to be really good at making sure that I can like swap the tasks out.

我能很好地适应，使用新技术，比如精通AI编程。

I can really adapt, use the new technology, get really good at AI coding, for example.

然后你希望逐步增加技能。

And then you wanna kind of add skills.

我也可以在设计方面变得非常出色。

I can also get really good at design.

我也可以在产品管理方面变得非常出色，因为我有了这个新工具。

I can also get really good at product management because I've this new tool.

所以随着你这样做，你希望不断拓展自己的职责范围。

So you wanna kinda pick up more and more scope as you do that.

十年后，你的职位头衔是程序员，还是程序员兼设计师兼产品经理，或者只是‘我构建产品’，又或者只是‘我指导AI如何构建产品’？

And then ten years from now, is your job title coder or coder designer product manager, or is it just I build products, or is it just I tell the AI how to build products?

不管这个职位叫什么，谁知道它将来会变成什么样呢？

It's like, whatever that job is called, who even knows what it's gonna be?

但这将变得极其重要，因为从事这份工作的人将负责协调AI。

But it's gonna be incredibly important because the people doing that job are gonna be orchestrating the AI.

因此，最优秀的人才会走上这条道路，我认为这是我们应该全力投入的方向。

And so that's the track that the best people are going to be on, and I think that's the thing to lean hard into.

我认为人们还没有完全意识到软件工程本身正在发生多大的变化。

I think people aren't fully grasping just specifically software engineering and how much that is changing.

很明显，我们很快就会进入一个工程师不再实际编写代码的世界，这一点在一年前我们还无法想象。

Like, it's pretty clear we're gonna be in a world soon where engineers are not actually writing code, which I think a year ago we would not have thought.

但现在，这显然是未来的发展趋势。

And now it's just clearly this is where it's heading.

将来会有一种‘工匠式’的体验——坐在那里亲手写代码，这多么疯狂啊，这份工作已经发生了如此巨大的变化。

It's like there's gonna be this artisanal experience of sitting there writing code, which is so crazy how much that job is gonna change.

是的。

Yeah.

所以，再次回到这一点，我还是要回顾一下历史，或许这算是一堂历史课，但我想问一下，你知道‘计算器’这个词最初的定义吗？

So again, here, I go back, and again, pardon maybe the history lesson, but like I go back like, Cody, so the first Do you know the original definition of term calculator?

你知道这个词指的是什么吗？

Do you know what that referred to?

不知道。

No.

它指的是人。

It referred to people.

在电子计算器、计算机或这些设备出现之前，进行计算的方式是：比如保险公司计算精算表，军队计算 troop logistics 公式等等，都是通过让一屋子人来完成的。

So back before there were electronic calculators or computers or any of these things, the way that you would actually do computing, the way that you would do calculating, like the way that an insurance company would calculate actuarial tables or the military would calculate, I don't know, whatever troop logistics formulas or whatever it was, the way that you would do it is you would actually have a room full of people.

顺便说一下，这些房间都很大。

And by the way, these are big rooms.

你可能会有数百、数千甚至数万人在做这件事，你会让房间前端的人负责整个数学方程，然后把各个计算步骤分发给坐在桌前的人，他们全部手工完成。

You could have hundreds or thousands or tens of thousands of people doing this, and you would actually figure out You have somebody at the head of the room who was responsible for whatever the mathematical equation was, and then they would parcel out the individual mathematical calculations to people sitting at desks who were doing them all by hand.

这些人的职位名称就是‘计算员’。

That job title was those people were calculators.

所以我们从一个 literally 由人手工进行数学运算的世界，进入了第一代计算机的时代。

And so we've gone from a world in which you literally have people doing mathematical equations by hands, Then we got the first computers.

最早的计算机当然没有编程语言。

The first computers, of course, didn't have programming languages.

它们只有机器码。

They only had machine code.

所以最早的计算机是用一和零来编程的。

So the first computers were programmed with ones and zeros.

因此，程序员的任务变成了处理一和零，后来这演变成了打孔卡片。

And so the task of the programmer became do the ones and zeros, and then that became punch cards.

直到今天，仍然有一些程序员的工作是处理打孔卡片。

And there's still people kicking today whose job as a programmer was to deal with the punch cards.

然后你迎来了一个重大突破，那就是汇编语言，它本质上是用某种类似英语的符号来表示机器码。

And then you got actually this big breakthrough, which was called assembly language, which was basically the way to do machine code, but with some level of English kind of added to it.

而最优秀的程序员都使用汇编语言。

And then the best programmers did assembly language.

当我刚入行时，程序员使用的是像C这样的高级语言，这些语言会编译成机器码，这就是程序员的工作。

And then when I was coming up, it was higher level languages like C that compiled into machine code, and that's what programmers did.

我记得当时我们在Netscape开发了JavaScript，随后Python和Perl等其他脚本语言迅速兴起。

And then I still remember when languages we developed JavaScript at Netscape, then Python took off and Perl, and these other scripting languages.

当脚本语言在二月份兴起时，技术界爆发了一场大争论：脚本编程算不算真正的编程？

When scripting languages took off in the February, there was this big fight in the technical community, which is, is scripting real programming or not?

因为这有点像作弊——真正的程序员会编写编译成机器码的代码，亲自管理内存，精通C语言编程的全套技艺，而JavaScript或Python程序员只是在做些轻量级的事情。

Because it's it's kind of cheating because real programmers write code that compiles to machine code, and real programmers do memory management themselves, they do all they get this whole craft of writing C code, and these JavaScript or Python programmers are just doing this lightweight thing.

这甚至都不算真正的编码，但当然，答案是肯定的，这绝对算数。

It doesn't even really count as coding, and of course, the answer is yes, it very much counted.

现在大多数编码都是用脚本语言完成的，对吧？你应该明白我的意思了。

And now most coding is done with the scripting languages, right, which have you see my point.

脚本语言已经抽象掉了过去人们手工完成的五层底层细节，现在没人再做这些了。

The scripting languages have abstracted away, like, five layers of detail underneath that that people used to do by hand that they don't anymore.

然后，正如你所说，AI编程是这一趋势的下一层次。

And then and then there's and then your to your point, like, AI coding is the next layer on that.

AI编程实际上抽象掉了编写脚本代码这一过程。

AI coding actually abstracts away the process of actually writing the scripting code.

所以从某种意义上说，这在所有显而易见的方面都是件大事，但另一方面，这不过是程序员工作职责下新一轮的任务重构。

And so in one sense, this is a really big deal for all the obvious reasons, but on the other hand, it's like, okay, this is the next layer of the task redefinition under the job of programmer.

那么，程序员的工作到底是什么？

Now what's the job of the programmer?

正如你所说，现在的工作未必是亲手写代码，而是这样：好吧。

It's to your point, it's not necessarily to write the code by hand, but what it is now is, alright.

如果你去问当今世界上最顶尖的程序员，他们会告诉你：我的工作就是坐在那里，协调十个并行运行的代码机器人。

Now you know, if you talk to the world's best programmers today, what they'll tell you is, oh, my job is I'm sitting there and I'm orchestrating 10 code bots, right, coding bots that are running in parallel.

对吧？

Right?

我的意思是，他们真的就是坐在那里，从一个浏览器切换到另一个浏览器，或从一个终端切换到另一个终端，他们现在的日常工作本质上就是跟AI机器人争论，试图让它们写出正确的代码。

And I mean, literally, they sit there and they shift from browser, you know, browser to browser or terminal to terminal, and their and their their their their day job now is kind of arguing with the AI bots trying to get them to, like, write the right code.

然后调试、修复问题、来回修改，做所有这些事情。

And debug it and fix the problems and change this back and do all these things.

所以现在，程序员的工作就是跟代码机器人争论。

And so now the job of the program is to argue with the coding bots.

但如果你自己不会写代码，你就无法评估编码机器人给你的结果。

But if you don't know how to write the code yourself, you don't know how to evaluate what the coding bots are giving you.

对吧？

Right?

所以你知道，你提到的那个10岁孩子，他特别喜欢电脑和编程。

And so you you know, you asked about the 10 you know, our our 10 year old is, you know, super into computers and super into programming.

我要告诉你的是，他正在使用Claude、ChatGPT和Copilot这些工具。

What I'm what I'm tell you know, he's he's using Claude and ChatGPT at Copilot and all these things.

我告诉他的意思是：你看。

And what I'm telling him is like, look.

顺便说一下，他特别喜欢氛围编程。

And by the way, he loves vibe coding.

他整天都在RemPLA上做氛围编程，写游戏什么的。

He's on RemPLA all the time doing vibe coding, you know, doing gay doing games.

你知道，他坐在那儿，这场景简直太搞笑了，因为他真的坐在那儿。

You know, he's sitting there you know, it's hysterical, right, because he's sitting there.

这是一个十岁的孩子，居然在晚餐时花两个小时跟AI争论，纯粹为了好玩。

It's a 10 year old basically who's know, spends two hours at dinner arguing with an AI for fun.

对吧？

Right?

没错。

Right.

但我告诉他的却是：不行。

But but what I'm telling him is, no.

听好了。

Look.

你仍然需要完全理解并学会如何编写和理解代码，因为编码机器人给你的都是代码。

You need to still fully understand and learn how to write and understand code because the coding bots are giving you code.

如果代码运行不了、没达到你的预期、速度不够快，或者出现其他问题，你都必须能理解AI给出的结果。

If it doesn't work or if it's not doing what you expect or it's not fast enough or whatever, you need to be able to understand the results of what the AI is giving you.

就像写脚本语言的人，最终也需要理解微处理器是如何工作的。

In the same way that somebody who's writing scripting language code does need to understand ultimately how the microprocessor works.

因此，这实际上是一种能力的提升，你仍然需要具备深入理解这些工具真正运作方式的能力，即使你每天并不亲自手动去做这些事。

And so again, it's kind of this up leveling of capability where you actually want the depths to be able to go down and be able to understand what this thing is actually doing, even if you're not spending your day actually doing that by hand.

再者，我看到这一点时就想，好吧，程序员的生产力现在可能会是过去的十倍、百倍甚至千倍。

And again, I look at that and I'm like, okay, now programmers are gonna be 10 times or a 100 times or a thousand times more productive than they used to be.

对吧？

Right?

而这毫无疑问是一件极好的事情。

And and and that is overwhelmingly a good thing.

任务确实正在发生变化。

The the the the the the tasks are definitely changing.

工作的性质正在改变。

The nature of the job is changing.

但人类还会参与编码过程，监督AI的编码工作吗？

But are human beings going to be involved in, like, in in the coding process and overseeing the the AI coding and all that?

答案当然是绝对的，100%。

The answer is, of course, absolutely, 100%.

毫无疑问。

No question.

所以你属于仍然认为学习编程是一项有价值技能的阵营吗？

So you're in the camp of still learning to code, still a valuable skill?

当然了。

Oh, totally.

再说一遍，如果你想要成为那种顶尖人才，看好了，如果你只是想把自己设为自动模式，懒得动手，完全让AI写代码，让它生成任何它能生成的东西，那也没问题。

Well, again, if you want to be one of these super Look, if you just want to put your self on autopilot and I can't be bothered and I'm just gonna have AI write the code and it's gonna generate whatever it does, and that's fine.

如果目标只是成为一个平庸的程序员，那就让AI去做吧。

And I'm gonna be if the goal is to be a mediocre coder, then just let the AI do it.

没问题。

It's fine.

AI完全能完美地生成海量的平庸代码。

The AI is gonna be perfectly good at generating infinite amounts of mediocre code.

没问题。

No problem.

一切都好。

It's all good.

如果目标是成为世界上顶尖的软件人才，想要打造真正重要的新软件产品和技术，那么是的，你100%需要彻底深入下去。

If if if the goal is I wanna be one of the best software people in the world and I wanna build new software products and technologies that, like, really matter, then, yeah, you 100% want you still you wanna go all the way down.

你的技能要一直深入到汇编语言和机器码层面。

You want your skill set to go all the way down to the assembly to assembly and machine code.

你希望理解栈的每一层。

You wanna understand every layer of the stack.

你想深入理解芯片、网络等层面究竟发生了什么，对吧。

Wanna deeply understand what's happening at the level of of the chips, right, and and and the network and so forth.

顺便说一下，你真的非常希望理解AI本身的工作原理。

By the way, you also really deeply wanna understand how the AI itself works.

对吧？

Right?

因为你想要，对吧？

Because you wanna right?

因为了解AI工作原理的人，显然能从中获得比不了解的人更多的价值。

Because if people who understand how the AI works are able to they're clearly able to get more value out of it than somebody who doesn't understand how it works.

但我的意思是，当你使用机器时，如果你知道它是如何工作的，你的效率会更高，对吧？

But, I mean, you're more productive if you know how the machine works, right, when you use the machine.

所以，是的，那些希望利用这项新技术做出卓越成就的超级赋能个体，你100%需要彻底理解这个技术的每一层，因为你希望真正理解它能为你提供什么。

And so, yeah, the the super empowered individual on the other end of this that wants to do great things with the new technology, yes, you a 100% wanna understand this thing all the way down the stack because you wanna be able to understand what it's giving you.

对吧？

Right?

而且当某些东西出问题或不对劲时，你希望能够迅速弄清楚原因。

And and and when something doesn't work or when something isn't right, you wanna be able to really quickly understand why that is.

顺便说一下，这又回到了教育问题。

By the way, again, this goes back to education.

AI是你学习所有这些知识的最好伙伴。

AI is your best friend at helping you learn all that.

因为你会想，哦，我需要理解这个。

Because it's like, oh, I need to understand.

我不知道，这速度还不够快。

I don't know, this isn't fast enough.

作为程序员，我得想办法换一种内存管理的方式之类的。

Need to figure out as a coder, I need to figure out how to do a different approach to memory management or something.

你可能会说：天啊，我真不知道该怎么弄。

And you can be like, well, shit, don't quite know how to do that.

好吧，AI，我们花十分钟，教我怎么做这个。

Okay, AI, let's spend ten minutes, Teach me how to do this.

教我这一切到底意味着什么。

Teach me what this all means.

对吧？

Right?

于是，你突然间与AI形成了一种极其协同的关系，它在为你做大量工作的同时，也在帮助你不断提升。

So all of a sudden, you have this, like, incredibly synergistic relationship with the AI where it's also helping you get better at the same time that it's doing a lot of work for you.

顺便说一下，我

By the way, I

我本来想说，我曾经是个资深的Pearl程序员。

was gonna say, I was a big Pearl programmer.

我当了十年工程师，那时候Pearl是我最钟爱的语言。

I was an engineer for ten years, and that was my my language of choice.

你还记得吗？我不确定你那时候在做什么，但至少在早期，你有没有遇到过这种情况：C语言程序员们瞧不起你，心里想，天哪。

Do do you remember I don't know when you were doing it, but do do you remember that at the at least early on, do you remember did you ever did you ever hit this where, like, c coders were, like, looking down their nose at you being like, man.

当然有。

For sure.

这速度太慢了。

It's like, this is so slow.

根本没法扩展。

It's not gonna scale.

你们到底在忙些什么，花这么多时间在这上面？

What are you what are you spending all your time on this thing?

是的。

Yeah.

没错。

Exactly.

当然，而且again，当时的情况是，他们说得其实有一定道理，因为一开始，它确实不够快之类的。

And, of course, know and again, it was sort of this thing where, you know, they were they were sort of correct, which is at the beginning, it wasn't, know, fast enough or whatever.

但到了后期，他们显然是错的，因为它的速度变得快得多，而且席卷了全球。

By the end, they were definitely wrong, right, which is it got much better, much faster, and it swept the world.

如今大多数编程都是用脚本语言完成的。

Most coding today happens in scripting languages.

顺便说一句，那些真正理解脚本语言、同时又懂底层系统的人，才是能让脚本语言真正高效运行的人。

And then by the way, the people along the way, the people who really understood the scripting languages and the people who understood all the lower level systems, they were the ones who were able to actually make the scripting languages actually work really well.

对吧？

Right?

所以，这正是这种适应能力的一个绝佳例子。

And so that that was that was a great example of this kind of adaptation.

而且again，结果就是，使用脚本语言编程的人数远远超过了曾经使用底层语言编程的人数。

And and, again, the result of that was, you know, a far higher number of people writing code with scripting languages than were ever writing code with lower level languages.

我认为这将会是那种情况的一个更加戏剧化的版本。

And I I think this will just kinda be a more dramatic version of that.

我很喜欢Perl是由一位语言学家设计的。

I love that Perl was designed by a linguist.

我不知道你是否记得这一点，这正是它编程起来如此愉快的原因。

I don't know if you remember that part, and that's what made it so nice to to code with.

这很有趣，因为当然，它以难以理解而臭名昭著。

Well, that's funny because, of course, it was so notorious for being impossible to understand.

多么讽刺啊。

So how ironic.

是的。

Yeah.

回到这种三元结构，我越来越常听到的另一个要素是品味、设计和用户体验的能力。

Coming back to this kind of triad, the other element that I hear more and more of is the skill of taste and design and user experience.

这似乎是一种非常难以掌握的技能，在我看来，这表明设计在未来将变得更有价值。

It feels like that's a very hard skill to learn, and to me, it tells me design is gonna be much more valuable in the future.

是的。

Yeah.

没错。

That's right.

而且在这里，这是一个很好的例子。

And again, here, this this is a great example.

所以，再次强调，任务层面的设计——比如设计一个完美的图标——将会变得很简单。

So the the the again, the task level the the the the the task level of, design the perfect icon, right, is gonna be like, alright.

AI会整天做这些事。

AI's gonna do that all day long.

对吧？

Right?

这已经是游戏的终点了。

It's the end of the game.

它能为你生成一千个图标设计。

Gives you a thousand icon designs.

这会很棒。

It's gonna be great.

就像，这会非常棒。

Like, it's gonna be fantastic.

随便吧。

Like, whatever.

懂吗？

Know?

顺便说一下，还是会有一些人类设计图标之类的，但 hey。

And there will still by the way, there will still be some level of human icon design or whatever, but, like, hey.

它在这方面会变得非常出色。

It's gonna get really good at that.

但，我们到底想做什么呢？

But, like, are we trying to do?

就像，那个，你知道的，所谓的宏大设计，好吧。

Like, the the the, you know, kind of capital d design of, alright.

这个东西是做什么用的？

What is this thing for?

这个东西在人类世界中将如何运作？

And how does this how is this going to function in a world of human beings?

而且，你知道，这个东西能让人用起来感到开心吗？

And like, you know, what what's gonna is is this gonna make people happy when they use it?

它能让人对自己感觉良好吗？

Is this gonna make people feel good about themselves?

它能融入他们生活的其他部分吗？

Is it gonna fit into the rest of their life?

它会不会，你知道的，以正确的方式挑战他们？

Is it gonna, you know, I don't know, challenge them in the right way?

所有这些更高层次的问题，一直都是优秀设计师所思考的，比如设计师的工作将更多地涉及这些更高层次、更重要的部分，而AI则会承担更多底层任务。

All these kinds of higher level questions that the great designers have always thought about, like the job of designer will involve much more of those higher level, more important components, and then again, with AI doing a lot more of the underlying tasks.

一种思考方式是，我不知道，就想象一下那样。

And one way to think about it is, I don't know, think of like that.

不知道，世界上最好的设计师，比如乔尼·艾维之类的，可能会让人惊叹。

Don't know, the world's best designers, Johnny Ive or whatever, it could be like, wow.

比如说，如果我现在是个25岁的设计师，十年后想成为乔尼·艾维那样的人，突然间就有了一个新的路径可以帮我去实现，因为乔尼·艾维做的一切都是在没有AI的情况下完成的。

Like, if I'm a designer today, if I'm a 25 year old designer and I aspire to be Johnny Ive in a decade, it's it's all of a sudden, have a new path that I can use to kinda get to to to get there, which is I you know, because Jeff Johnny Ive did everything he did without AI.

现在，年轻的设计师可能会想，哇。

Now, you know, a young designer can just be like, wow.

如果我能在十年内充分运用AI，我可能会成为世界上有史以来最伟大的设计师，因为这不仅仅是靠我一个人，而是我加上这项技术赋予我的超强能力，让我能做更多事，从而让我有更多时间和精力专注于那些大多数设计师根本接触不到的高层次问题。

If I really harness AI in a decade, I'm gonna be like the best designer the world's ever seen, because it's not just gonna be me, it's gonna be me plus being so super empowered by this technology to be able to do so much more, and then so much more of my time and attention gonna be able to be focused on these higher level things that most designers never get to.

我认为这将是另一个很好的例证。

And I think that's gonna be another great example of that.

所以，我听到的可能是这种T型策略：如果你想在这三个角色中的任何一个取得成功，就要在那个特定角色上做到极致——产品管理、工程或设计，然后对另外两个角色也要达到足够好的水平。

So maybe what I'm hearing here is kind of this T shaped strategy of if you want to be successful in any three of these roles, be very, very, very good at that specific role, product management, engineering, design, and then get good enough at these other two roles.

我觉得这很棒。

Well, so I think that's great.

我觉得这真的非常相关。

I think that's really, really relevant.

然后，你知道，斯科特，斯科特·亚当斯刚刚去世了，这真是一个巨大的悲剧。

And then, you know, Scott, know, Scott Adams and firstly just passed away, you know, which which is a real tragedy.

但我多年来一直引用斯科特·亚当斯的观点。

But I was always I've always I referred for years to actually Scott's Scott Adams.

他曾经给人们提供过一条著名的职业建议，我觉得非常有道理，和你所说的不谋而合。他说，我或许能成为一个不错的漫画家，也可能成为一个不错的商人，但因为我既是漫画家又懂商业，才让我创作《呆伯特》时表现得异常出色——因为即使世界上最好的漫画家，如果不了解商业，也根本写不出《呆伯特》；而世界上最好的商人，如果不懂绘画，也同样无法创作出《呆伯特》。

He had this famous he this famous career advice he would give people, which I think makes a lot of sense, which dovetails with what you're saying, which is he used to say, used to say, it's like, look, he said, I could have been a pretty good cartoonist, or I could have been pretty good at business, but the fact that I was a cartoonist who understood business made me spectacularly great at making Dilbert, because even the world's best cartoonists who didn't understand business could have never written Dilbert, and then the world's best business people who didn't know how to do cartoons couldn't have done Dilbert.

只有同时具备这两种技能的人，才能创造出《呆伯特》——这是历史上最成功的漫画之一。

It took somebody who actually had both of those skills to be able to make Dilbert, which is one of the most successful cartoons in history.

因此，斯科特一直这样描述：从职业发展的角度看，精通两项技能的叠加效应，远不止是翻倍。

And so the way Scott always described it was that from a career development standpoint, the additive effect of being good at two things is like more than double.

精通三项技能的叠加效应，甚至超过三倍，因为你成为了这些领域交叉结合的超级专家。

The additive effect of being good at three things is more than triple, because become a super relevant specialist in the combination of the domains.

你在整个经济中都能看到这种现象，我给你举个例子。

You see all the economy, over but I'll give you an example.

好莱坞就是一个例子。

Hollywood just Hollywood as an example.

有很多作家不会拍电影，但他们依然可以非常成功。

There are a lot of writers who can't direct a movie, and they can be very successful writers.

也有很多导演不会写剧本，但他们可以成为非常成功的导演，但娱乐业的超级明星往往是那些既能写又能导的人。

There are a lot of directors directors who can't can't write a movie, they can be very successful directors, but the superstars in the entertainment industry are the people who can write and direct.

他们并没有一个专门的术语来称呼这类人。

They don't have a term for those.

他们称这些人为作者型导演，而这些人正是推动整个行业发展的真正创意力量。

They call those auteurs, and those are the people who are the real creative forces that move the field.

顺便说一句，好莱坞真是挺有意思的。

And by the way, Hollywood It's just really funny.

我花了很多时间和好莱坞的人讨论人工智能。

Been spending a lot of time talking Hollywood people about AI.

好莱坞现在正经历着我们之前在《攻击》中描述的那种僵局，只不过在好莱坞，比如电影制作中，涉及的是导演、编剧和演员。

Hollywood has the same Mexican standoff going right now that we described in Attack, except in Hollywood, for example, for filmmaking, it's the director, it's the writer, the actor.

因为导演现在在想：天啊，我不再需要编剧了，因为AI能写剧本；我也不再需要演员了，因为我可以用AI演员。

Because the director is now thinking, wow, I don't need the writer anymore because AI can write the script, and I don't need the actor anymore because I can have AI actors.

编剧说：我不需要导演了，因为我可以自己执导，AI也能搞定演员。

The writer is saying, Well, I don't need the director because I can direct the movie and the AI can do the actors.

演员说：我谁都不需要。

And the actor is saying, I don't need either one of these guys.

我可以请AI来执导，让AI写剧本，而我只需要到场表演就行了。

I can have AI direct the thing, I can have the AI write the thing, and I'm just gonna show up and do my performance.

所以，这形成了同样的三角结构。

And so it's the same kind of triangular configuration.

而有趣的是，他们每个人都是对的。

And again, what's great about it is they're all correct.

在这三个领域中的每个人，将来都能横向拓展，掌握额外的技能。

Each person in each of those three fields is going to be able to expand laterally and pick up those additional skills.

结果就是，会有更多人能够写剧本并执导，或写剧本并表演，或执导并表演，甚至三者兼备。

And then as a consequence, you're gonna have more people who can write and direct or write and act or direct and act or do all three.

我认为，正如你提到的T型转变，这种趋势几乎会遍及整个经济领域。

And I think to your point, T shift thing, think that's gonna be true basically across the entire economy.

如果你想想T型结构，它就像是，是的，T的横杠代表你对多少个独立领域足够熟悉，能够利用AI工具做出出色的工作？

If you think about the T configuration, it's like, yeah, the the top of the T is like, how many individual domains are you familiar enough with to be able to use the AI tools to be able to do really good work?

而T的竖杠则代表你至少能在其中一个领域深入到什么程度，真正彻底地掌握你所做的事情。

And then this part of the T is how deep can you go in at least one of those domains so that you really, really deeply know what you're doing.

但如果你在编程方面非常精通，又能用AI做设计、用AI做产品管理，那这就是你的T型结构——你在T的横杠上是三栖人才，同时又具备扎实的技术基础，到那时，你就是一个超级个体。

But if you're super deep on coding and you can use AI to do design and you can use AI to do product management, that's your T right there, and you're a triple threat at the top of the T, but with this level of technical grounding underneath that, and at that point, again, you're the superpowered individual.

你将能够完成类似魔法般的壮举，比如设计和构建出我们这一代人根本无法想象的新产品。

You're gonna be able to just perform like feats of magic, for example, in terms of designing and building new products that people in my generation couldn't have even dreamed of.

所以我认为这是一种普遍性的

And so I think that this is a universal kind

适用于整个经济体系的理论。

of theory that I think can apply across the entire economy.

我现在要发明一个新的框架。

I'm gonna invent a new framework right now.

好的。

Okay.

忘记T框架吧。

Forget the T framework.

我想象的是一个横向的F或E，有两到三个向下的部分，我不确定。

I'm picturing an F sideways or an E, where there's three two or three, I don't know, downward parts.

所以我听到的是，至少要精通两项技能。

And so what I'm hearing is get good at least two.

我觉得这是对的。

I think that's right.

我觉得没错。

Think that's right.

然后就是那个。

And then the yeah.

这个组合。

The combination yeah.

我的朋友劳伦斯·萨默斯对斯科特·亚当斯的观点有不同版本，他过去常对人们说。

My my friend Larry Summers had a had a different version of the Scott Adams thing, which is he he used to tell people.

他说，职业规划的关键是，别让自己变得可替代。

He said, the key for career planning is he said, don't be fungible.

他是个经济学家，所以这是从经济学角度说的。

And he's an economist, so that was economic speaking.

这实际上意味着，别让自己可以被轻易取代。

And what that means essentially is don't be replaceable.

所以，别当一颗螺丝钉。

And so don't be a cog.

这意味着，别只做一件事。

What that meant was don't just be one thing.

所以，如果你仅仅是个设计师、仅仅是个产品经理、仅仅是个程序员，理论上你随时可以被替换。

So if you're quote unquote, again, just a designer, just a product manager, just a coder, then in theory you can be swapped in or out.

但如果你拥有这种横着的E或F那样的组合，而且具备这种相当罕见的综合能力，那你就不容易被替代了。

But if you have this E or F laying on its side kind of thing, and if you have this combination of things that's actually quite rare, then all of a sudden you're not fungible.

你不仅不可替代，而且极其重要，因为你是世界上少数几个能完成这种综合任务的人之一。

Not only you're not fungible, you're actually massively important because you're one of the only people in the world who can actually do that combination of things.

而且，你避免成为那种人的能力，相比以往任何时代，都因为人工智能而得到了巨大的提升。

And yeah, your ability to not become one of those people is like just titanically enhanced with AI as compared to anything we've ever seen before.

这太有趣了，因为我曾经和那些精通这两种技能的人共事过，他们总是被公司称为独角兽。

This is so interesting because I've worked with people that are good at these two skills, and they were always called unicorns at the company.

她既能做产品管理，又能做设计。

She can coat and design.

天啊。

Oh my god.

我在这里听到的是，你需要成为这样的人。

And what I'm hearing here is this is what you need to become.

你需要至少在两项技能上变得非常出色。

You need to become really good at at least two things.

我好像听到你提到过‘烟囱’之类的词，就是说产品经理在这里，工程师和设计师在那里，而我听到的是，你需要至少在这几项技能中精通两项。

I think you used the term smokestack or something, where it's like PM over here, engineer design, and what I'm hearing here is you need to get good at at least two of these skills.

这两个角色之间的壁垒正在消失。

The silos of these two roles are disappearing.

没错。

That's right.

没错。

That's right.

而且我要再次强调，这对所有正在听的人至关重要。

And again, I can't overstress the following for anybody listening to this.

我认为人们还没有充分受益于人工智能的一点是，它会教你。

The thing about AI that I think people are just not getting enough benefit out of yet is just it will teach you.

这太棒了。

This is amazing.

以前从未有过这样的技术，你可以问它：教我怎么做这件事。

There's never been a technology before where you can ask it, teach me how to do this thing.

所以我总是觉得，人们把太多注意力放在了如何使用大型语言模型上。

So it's I always feel like it's like it's like people spend too much it's it's one of these things where it's like so much focus on figuring out to use like a large language model.

好吧。

It's like, okay.

我打算让它为我做些什么？

What am I gonna try to get it to do for me?

对吧？

Right?

这当然非常重要。

Which is, of course, very important.

但另一方面，我能让它教我做什么？

But the other side of it is what can I get it to teach me how to do?

它在这方面同样出色。

And it's just as good at that.

所以，这又是一种潜在的超强能力。

So again, this is this level of latent superpower.

在我看来，那些真正想提升自己、发展事业的人，现在应该把每一刻空闲时间都用来和AI对话，说：‘好吧，训练我吧。’

People who really wanna improve themselves and develop their career should be spending every spare hour, in my view, at this point, talking to an AI being like, all right, train me up.

让我变得超级强大。

Super empower me.

告诉我该怎么训练我，教我如何成为一个产品经理，我是个程序员，教我怎么做产品经理。

Tell me how to, you know, train me, train me how to be, you know, I'm a coder, train me how to be a product manager.

它很乐意这么做。

It will happily do that.

它完全知道该怎么做到这一点。

Knows exactly how to do that.

你知道的，给我出难题，给我布置任务，评估我的结果，对吧？

Know, run me dread, you know, make me problems, you know, make me assignments that evaluate my results, right?

它会同样乐意做这些事，就像它为你‘干活’一样。

And it will do that just as happily as it will do work, quote unquote, for you.

我听说过两种类似的方法。

Two tricks I've heard along those lines.

一种是观察代理在工作时的输出、它在做什么以及怎么思考。

One is to watch the output, what the agent is doing and thinking as it's doing the work.

所以如果你不是工程师，就坐在那里看着它，思考并做决定。

So if you're not an engineer, just sit there and watch it, think, and make decisions.

而且，学习编程之上几乎又多了一层：学会观察代理在做什么、怎么想，因为这能让你理解架构。

And it's almost become this layer on top of learning to code is learning to see what the agent is doing and thinking because that teaches you about architecture.

另一个技巧是一些播客嘉宾提到过的。

And the other is a couple podcast guests have mentioned this.

当你遇到瓶颈，然后自己找到解决方法时，可以问它：我本可以怎么做不同？

When you get stuck and then you figure out how to unstuck yourself, you ask it, what could I have done differently?

我本可以怎么说，才能从一开始就避免这个错误？

What could I have said that would have avoided this error in the first place?

是的。

Yeah.

没错。

That's right.

没错。

That's right.

是的。

Yeah.

听我说，关于第一点，这正是我和我十岁的孩子在做的事情。

Look, on that first one, and this, again, this is what I'm doing with my 10 year old.

是的。

Yeah.

听好了，如果你问一个嗯。

Look, if if if you ask an yeah.

这是一个非常好的观点。

This is this is a really good point.

所以，如果你问人工智能，比如，帮我写这段代码，然后它写出来了，但根本跑不通。

So if you ask an AI, don't know, write me this code, and then and then it doesn't, it comes back, and it doesn't work right.

比如，如果你只知道单个函数，问了它之后它给你的结果不好，那你到底该怎么办？

Like, if if all you know is, like, single function, asked it and it gave me back something that's not good, like, what do you, like, what do you even do with that?

对吧？

Right?

你根本搞不懂它为什么会给出那样的结果。

Like, you you don't understand why it gave you that result.

你真的明白该怎么做吗？你甚至清楚该怎样指导它，让它尝试做点不同的事情吗？

Do you really understand it even what to do you even understand what to tell it to try to get it to do something different?

但说到你的观点，如果你观察它在做什么，并且具备那种基础——就像你的E或F的根基——如果你有这个基础，你就能明白：哦，我看出它在做什么了。

But to your point, if you watch what it's doing and then you have the grounding, kind of that leg of your E or your F, if you have that grounding, then you can be like, oh, I see what it's doing.

我看出它哪里出错了。

I see where it made the mistake.

我看出它哪里偏离了方向。

I see where it went sideways.

然后你就能立刻介入，说：不，不，我不是这个意思，伙计，应该是另一回事。

Then you're all of a sudden able to intervene and be able to say, No, no, that's not what I'm mad, dude, this other thing.

而且，再次强调，这种真正的协同关系的关键就在于你能够理解。

And again, this is a big part of having the actual synergistic relationship is that you understand.

顺便说一句，我们此刻所说的一切，也同样适用于你与人类合作的情况。

And by the way, look, everything that we're saying right now also is the same as if you're working with human beings.

如果你我和我是同事，我让你做件事，你却回给我完全不一样的东西。

If you and I are colleagues and I would ask you to do something, you'd come back with something completely different.

我需要理解你脑子里当时在想什么，才能给你有效的反馈。

I do need to understand what was happening in your head right, in order to be able to give you feedback.

如果我只是告诉你‘错了’，那什么都不会发生。

If I just tell you, oh, that's wrong, nothing happens.

我真的需要去理解。

I need to actually understand.

我需要具备心理理论。

I need to have theory of mind.

我需要明白你当时的思考，才能给出正确的反馈。

I need to understand what you were thinking in order to really give you the right feedback.

所以，而且你知道，AI了不起的地方在于，它会乐意一直坐在那里解释它为什么这么做。

And so and and, you know, and, again, the great thing with AI is AI will happily sit there and explain all day long why it's doing what it's doing.

它会乐意自我批评。

It'll, you know, it'll happily critique itself.

你知道，你也可以这么做。

You know, and you can do this.

顺便说一下，这其实也很有趣，你可以让一个AI去批评另一个AI，比如让一个AI写代码。

By the way, this is also a very fun thing where you can have have one AI critique the other AI, right, which is another thing, which is like, you have one AI write the code.

再让另一个AI来指出代码的问题。

You have another AI debunk the code.

所以你实际上可以让这些AI互相竞争，让它们彼此争论。

And so you can actually use you could play the AIs off against each other and get them to argue with each other.

是的，这些都是一些我认为将会变得极其重要的技能。

And, yeah, these are all these are all the kinds of skills that are gonna become, I think, incredibly valuable.

我认为人们称这些为大语言模型委员会，因为它们在互相交流。

I think people call those LLM councils because they're talking to each other.

是的。

Yeah.

没错。

That's right.

没错。

That's right.

我确实觉得，如果我没有任何设计背景的话。

I do feel like if I were like, I have no design background.

我一直都想做设计。

I've always wanted to design.

我一直都想成为一名优秀的设计者。

I've always wanted to be a great designer.

仅靠观看和交谈，我觉得这三者中，设计是最难学会的。

It feels like that's the hardest one to learn of all these three by just watching and talking.

对吧？

Right?

因为需要大量的实践时间，就像人们所说的，你究竟该如何学会成为一名优秀的设计者？

Because there's a lot of exposure hours as as folks have used this term, just like, how do you learn to be a great designer?

我觉得这会非常困难，但也非常有价值。

That feels like that's gonna be really hard and valuable.

所以我要坦白一下，我一直都挺想当一名漫画家的。

So my my true confession is I've always kinda wanted to be a cartoonist.