Why companies are becoming a series of loops | Anish Acharya (a16z)

There's a lot of fear and worry about the future with AI. I want to talk about this idea that if you fall behind, you're going to become part of this permanent underclass. [music] It's a funny dark fantasy that we seem to have as Silicon Valley collectively.

人们对AI带来的未来充满恐惧和担忧。我想讨论这样一种观点：如果你落后了，就会成为永久底层阶级的一员。这似乎是整个硅谷共同抱有的一种荒诞而黑暗的幻想。

Like things have never been better by almost every measure.

几乎无论以哪个指标衡量，情况都从未如此之好。

This is a technology that really amplifies our agency. It kind of unbundles skill from desire. Not only can we dramatically [music] drive productivity, we can dramatically drive ambition.

这项技术确实能够增强我们的能动性，可以说是将技能与意愿分离开来。我们不仅能够大幅提高生产力，也能够极大地激发雄心。

Can you get too ambitious? Is there like a limit?

雄心也会过大吗？它是否存在上限？

In the old days, 3 years ago, we would see a company and if what they were trying to do was too ambitious, we would, [music] you know, not engage.

以前，也就是3年前，当我们看到一家公司时，如果他们想做的事情野心太大，我们就不会与其接触。

Today, we're almost seeing the opposite problem. An idea that's too small is not something that we want to engage with.

如今，我们看到的几乎是相反的问题：如果一个想法太小，就不值得我们接触。

You have this interesting take that company building more and more is going to become this kind of series of creating loops.

你提出过一个很有意思的观点：构建公司将越来越像打造一系列循环。

We're going to see this sort of cascading set of everything from a loop per person [music] to loops that can run large parts of the company. With that said, I think humans are a critical ingredient. The loop will help you climb to the local maxima, but then it plateaus. You need human intuition. You need somebody to actually help you land at the base of the next hill.

我们将看到这种层层递进的循环体系，从每人拥有一个循环，发展到由循环负责公司大部分业务。尽管如此，我认为人类仍是其中至关重要的要素。循环会帮助你到达局部最大值，但随后就会进入平台期。此时，你需要人类的直觉，需要有人真正帮助你抵达下一座山的山脚。

You have this take that the big opportunity is this idea of loop make me happier.

你还提出过一个观点：真正巨大的机会在于这样一个想法——循环，让我更快乐。

We believe that people want to be more productive, but they don't. I think more people want to spend time than save time. So, I think that the opportunity for this technology is the basics of consumer need. How do we feel more [music] connected, more loved? How do we make progress? How do we have fun? I don't think it's a model or a capability challenge. It's just a product design challenge.

我们以为人们想要提高生产力，但事实并非如此。我认为，更多人想要消磨时间，而不是节省时间。因此，这项技术的机会在于满足消费者最基本的需求。我们怎样才能感到与他人的联系更加紧密，感受到更多关爱？我们怎样才能取得进步？怎样才能获得乐趣？我认为，这并不是模型或能力方面的挑战，而只是产品设计方面的挑战。

Today, my guest is Anish Acharya. Anish is general partner at A16Z where he focuses on consumer investing. He is one of the most insightful, thought-provoking, mind-expanding, in-the-weeds product [music] investors I've met. He's been at A16Z for over 7 years now and unlike a lot of VCs and why I loved having Anish on the podcast is that he is a long-time product builder and founder. He founded a

今天，我的嘉宾是Anish Acharya。Anish是A16Z的普通合伙人，专注于消费领域投资。他是我见过的最有洞见、最发人深省、最能拓展思维，同时也最深入产品细节的投资人之一。他加入A16Z已经超过7年。与许多风险投资人不同，Anish长期以来一直是产品构建者和创始人，这也是我很喜欢邀请他做客播客的原因。他创办了

company called Social Deck which he sold to Google [music] and then ended up leading a number of efforts within Google, then he started a new company called Snowball, [music] which he then again sold, this time to Credit Karma, where he moved to VP [music] of product and then GM of the broader consumer product and the entire credit card business. This conversation [music] will get your mind buzzing.

一家名为Social Deck的公司，后来将其出售给了Google。随后，他在Google负责了多项业务，之后又创办了一家名为Snowball的新公司。后来，他再次出售公司，这次卖给了Credit Karma。他在那里担任产品副总裁，之后又成为更广泛的消费产品业务以及整个信用卡业务的总经理。这场对话会让你的思绪活跃起来。

Before we get into it, don't forget to check out Lenny's product pass.com for a free year of the hottest and most beautifully crafted AI products in the world, [music] available exclusively to Lenny's newsletter subscribers. With that, I bring you Anish Acharya.

在开始之前，请访问Lenny's product pass.com，免费畅享一整年全球最热门、设计最精美的AI产品。这项福利仅面向Lenny新闻通讯的订阅者。接下来，有请Anish Acharya。

[music] Anish, thank you so much for being here and welcome to the podcast.

Anish，非常感谢你来到这里，欢迎做客本播客。

Thank you, Lenny. I'm so excited to be here, thrilled.

谢谢你，Lenny。能够来到这里，我非常兴奋，也特别激动。

I want to start with a very light topic.

我想先从一个非常轻松的话题开始。

I want to talk about this meme of the permanent underclass.

我想讨论一下“永久底层阶级”这个梗。

It's kind of this joke that people have joke about, this idea that if you kind of fall behind and aren't just like on top of all the latest AI tools, aren't becoming the most productive person ever, you're going to become part of this permanent underclass and fall behind and have a really hard time.

这有点像人们经常拿来开玩笑的一种说法：如果你开始掉队，没能及时掌握所有最新的AI工具，也没有成为有史以来最高效的人，就会沦为永久底层阶级，逐渐落后，日子也会变得非常难过。

And some people are joke about it. I think a lot of people take this really seriously and stresses a lot of people out.

有些人会拿这件事开玩笑，但我认为，很多人对此非常认真，也因此承受着很大的压力。

How real of a concern do you think this really is? How seriously do you think people should take this?

你认为这种担忧在多大程度上真实存在？大家应该多么认真地看待这件事？

Not very seriously and it's a funny dark fantasy that we seem to have as, you know, Silicon Valley collectively. Like things have never been better really by almost every measure by how sort of distributed all the opportunities are, by the kind of technology we have access to, to the types of ambition we're allowed to have, and to the number of companies that are sort of independently working on things that are winning. And

不必太认真。这似乎是我们这个整体，也就是整个硅谷，共同抱有的一种好笑而阴暗的幻想。事实上，现实情况从未像现在这么好。几乎从每一个衡量标准来看都是如此，包括机会分布之广、我们能够获得的技术、我们可以拥有的雄心，以及众多公司各自独立开展卓有成效工作的程度。然而，

yet, there's this sort of discussion of permanent underclass, being outside of the light cone, I've heard it. And it's not just something for deep insiders or outsiders. It feels like there's a real fear kind of from, you know, researchers at Foundation Model Labs all the way through to the Silicon Valley layman. I mean, here's like a couple of points that I think are really important. So, first, I think the last era of tech was

人们却在讨论永久底层阶级、被挡在光锥之外等说法。这种想法并非只存在于圈内资深人士或圈外人之中。真实的恐惧似乎确实存在，从基础模型实验室的研究人员一直蔓延到普通的硅谷人。我认为有几点非常重要。首先，上一个科技时代

a lot more centralized. If you look at network effects, that's sort of the gold standard. You worked on a network effects product. Um that's the gold standard of businesses from the mobile era. And those things led to dramatic centralization, right? Of course, all of them are definitionally sort of end of one networks. If you look at what's happening now, it's like every part of the stack, there's not even two relevant

要集中化得多。以网络效应为例，它堪称黄金标准。在移动时代，打造具有网络效应的产品就是商业模式的黄金标准，而这类产品导致了高度集中化。从定义上看，它们最终都会形成一家独大的网络。再看当前的情况，技术栈的每一层都不只是有两个重要

players, there's like 20. You know, you've got labs, you've got open weight, you've got different variations within both. If you look at coding agents, we were talking about it, like your mental model for 2 years ago should have been would have been, I think it should be winner take all. And yet, Claude Code, Codex, Lovable, Replit, Wobby, like they're all sort of working. So, it's really really encouraging to see that.

玩家，而是大约有20个。既有实验室，也有开放权重，两类之中又各有不同的变体。再看我们刚才讨论的编程智能体，按照你2年前的思维模型，原本可能会认为这是一个赢家通吃的领域。但实际上，Claude Code、Codex、Lovable、Replit、Wobby等产品似乎都发展得不错。看到这一点，确实非常令人鼓舞。

You know, the second thing, you've heard all the kind of economic data, everything from radiologists um who are supposed to be cooked uh every year for I think about 20 years now. And of course, job postings are higher than they've ever been, as well as programmers, you know.

第二，各种经济数据也说明了这一点。以放射科医生为例，过去大约20年来，每年都有人声称这一职业即将消失，但相关职位的招聘数量却比以往任何时候都高。程序员也是如此。

So, I don't know that the empirical data bears it out. I I think the final thing is that there's this sort of discussion about RSI, and I know RSI is like recursive self-improvement is a fun term to throw around. But, if you ask the most sophisticated individuals at the labs, it's not actually RSI that's occurring, which could lead to some sort of runaway winner cuz they were an epsilon ahead of the others. It's

因此，我不确定实证数据是否支持这种说法。最后一点是，人们一直在讨论RSI。RSI，也就是递归自我改进，是一个很有意思、听起来很唬人的术语。但如果询问那些实验室里资历最深的人，就会发现实际发生的并不是RSI。因此，并不会因为某一方只领先其他人一点点，赢家就会一路失控、遥遥领先。真正发生的是

autocatalytic effects, which just means you're using the new technology to improve your process, but it's not truly recursive. So, I think everything from the most empirical to the most technical viewpoints in the other direction, and yet we can't seem to let go of this fantasy.

自催化效应，也就是利用新技术改进自身流程，但这并不是真正的递归。因此，从最实证的观点到最具技术性的观点，全部证据都指向另一个方向，但我们似乎仍然无法放下这种幻想。

Something I've been thinking about recently is seeing all these like even seeing these crazy um stories about OpenAI's models hacking hugging face.

我最近一直在思考这件事，尤其是在看到这些疯狂的新闻时，比如OpenAI的模型入侵Hugging Face。

Yes.

是的。

All these stories, to me feels like there's always been this question of are we on the fast takeoff or the slow takeoff scenario? And it feels very much so that we are on the slow takeoff scenario, because every one of these milestones is like, "Holy it hacked at We had no idea it was doing this, But, but like we're catching it, we're watching it, we're observing it, we're iterating, evolving. There's

所有这些新闻都让我想到一个长期存在的问题：我们身处快速起飞还是慢速起飞的情景？现在看来，我们显然正处于慢速起飞的情景。每一个这样的里程碑都会让人惊叹：“天啊，它居然入侵了……我们完全不知道它在做这件事。”但我们最终发现了它的行为，也在持续监控、观察它，并不断迭代和演进。大家总会

always this fear, okay, but tomorrow it's going to take off.

担心：“虽然现在如此，但它明天就会突然起飞。”

What I'm hearing from you is that's probably not the case, which I think is the source of a lot of people's fears, this idea that all of a sudden it's going to become super super intelligent and then we're in big trouble.

但从你的观点来看，这种情况很可能不会发生。我认为，这正是许多人恐惧的根源：他们担心它会突然变得极其智能，让我们陷入巨大的麻烦。

That's right. Like the line of reasoning for that case is always everything up until now, then something happens that no one can quite articulate and then fast take off.

没错。支持这种情况的推理逻辑总是：此前的一切照常发展，随后某件没人能够说清楚的事情突然发生，接着便出现了快速起飞。

So, I don't believe that that's going to happen. I do think that model progress is happening faster than ever before.

因此，我不认为这种情况会发生。不过，我确实认为模型的进步速度比以往任何时候都快。

But if you look at something like economic diffusion, you know, I grew up in a small town. I went back home last summer, like people's lives haven't changed that much. So, if nothing else, the sort of slow rate of economic diffusion will catch it. I think the other thing that's under discussed, Lenny, is, you know, how many problems are truly intelligence bound? Like if you had a, you know, a data center of

但如果观察经济层面的扩散，情况就有所不同。我在一个小镇长大，去年夏天回家时发现，那里人们的生活其实没有发生太大变化。因此，至少可以说，经济层面的缓慢扩散最终会赶上来。Lenny，另一件没有得到充分讨论的事是，究竟有多少问题真正受到智能水平的限制？例如，如果让一整个数据中心的

PhDs working at FedEx or Domino's Pizza, are they going to be like exponentially dominating supply chain and pizzas? Like I don't think so. So, I think we might be overestimating how many problems are intelligence bound versus bound by other things.

博士为FedEx或Domino's Pizza工作，他们就能凭借指数级优势主导供应链和披萨行业吗？我认为不能。因此，我们可能高估了受智能水平限制的问题数量，而低估了其他因素的限制。

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What are you seeing inside of companies in terms of um is there a more of a divide happening? And do you think there will be more of a divide between the people that are becoming really good and embracing versus like I don't have time for this. I hate all this stuff. My job's already so stressful. What are you seeing happening and where do you think things will go inside of companies in terms of maybe a divide?

你在公司内部观察到的情况如何？这种分化是否正变得更加明显？你是否认为，未来两类人之间会出现更明显的分化：一类人越来越擅长使用这项技术，并积极拥抱它；另一类人则认为：“我没有时间研究这些。我讨厌这一切。我的工作压力本来就已经很大了。”你观察到了哪些变化？你认为公司内部未来会不会出现某种分化？

I mean, I have so many thoughts on this.

对此，我有太多想法了。

I don't think we give the average employee enough credit. I think we have this abstraction of a white-collar employee. You know, the white-collar manager, the abstraction is like some Dilbert-esque manager who's just shuffling paper all day long. You know, it is abstraction of consumers that they're sort of these low-agency NBCs.

我认为我们低估了普通员工。我们心中似乎对白领员工有一种抽象印象。对于白领管理者，我们往往将其想象成某个《呆伯特》式的经理，整天只会处理文件。我们对消费者也有一种抽象印象，认为他们多少缺乏能动性，如同NPC。

Of course, that would never apply to us or our friends.

当然，我们绝不会用这种看法评价自己或朋友。

You know, we have this abstraction that everybody else's job is super automatable by AI, but of course ours is not. So, I think when you actually get into the details, a lot of people are actually excited to you know, better themselves, get more leverage, and you see this with of course sophisticated companies like Google, but even a company like Kavak where they sell, you know, used cars in Mexico, they've got

我们总有一种抽象印象，认为其他所有人的工作都特别容易被AI自动化，自己的工作当然不会。但真正深入了解具体情况后，就会发现很多人其实非常期待提升自己，获得更大的杠杆效应。这种情况当然会出现在Google这样的成熟公司里，但即使是在Kavak这样销售二手车的墨西哥公司，他们也开设了

this concept of a Jedi Academy where they're teaching everybody at the company including the mechanics how to use the new tools and technologies and kind of at the end of the 6-week course, they ship a cutting-edge in-production agent. So, I actually think that more people are embracing the technology than we sort of like to discuss. I think a big change is going to be using AI um versus reorganizing your entire company

所谓的“绝地学院”，教公司里的每一个人，包括技师，如何使用新工具和新技术。在这门6-week课程结束时，学员会发布一个投入生产环境的前沿智能体。因此，我认为，接受这项技术的人比我们平时讨论中所设想的更多。一个巨大的转变将是从使用AI，转向围绕AI重组整个公司。

around AI. And a great example of this is if you look at the diffusion of electricity as a technology, you know, it took 40 years for us to get from the inception of electricity to reorganizing factories. And that means like re- like burning the buildings down and starting from scratch versus taking what was previously coal and simply swapping it with electricity. So, I do think that like the most ambitious companies are

电力技术的普及过程就是一个很好的例子。从电力诞生，到围绕电力重组工厂，我们花了40年。所谓重组，是指将原有建筑拆除并从零开始，而不是直接用电力替代此前使用的煤炭。因此，我确实认为，最有雄心的公司正在

rethinking everything around the models.

围绕这些模型重新思考一切。

And those that are a little less ambitious or perhaps a little earlier are thinking more about how do we give people and existing orgs existing job functions access to the technology.

而那些雄心稍逊或仍处于较早发展阶段的公司，更多考虑的是如何让个人以及现有组织中承担既有岗位职能的员工使用这项技术。

So, a kind of a theme I'm hearing so far is we can be a little less stressed about where things are going and and the future of your job, your careers.

到目前为止，我听到的一个主题似乎是：我们可以少一些焦虑，不必过度担心事情将走向何方，以及自己的工作和职业生涯会有怎样的未来。

I think so, man. I mean I I think if you even just think of the kind of incentives for the CEO and executives, you know, Sundar running Google, he doesn't want to run a more efficient $4 trillion company. He wants to build a $40 trillion company. So, anytime you have an economically productive unit, it's rational to kind of especially if it gets more productive to maintain that sort of presence in your organization.

我也这样认为。只要想想CEO和高管所受到的激励，就会明白这一点。经营Google的Sundar并不想经营一家效率更高的$4 trillion公司，而是想打造一家$40 trillion公司。因此，只要一个单位能够创造经济价值，就有理由让它继续存在于组织中，尤其是在其生产力仍在不断提高的情况下。

And then I don't know what you hear, but anecdotally I talked to a good friend who's an executive at Google and I said, "Hey, have you laid anyone off?" And he said, "No, we didn't. What we instead do is now rip through our road map. So, 2 years of road map happens in 3 months.

此外，我不知道你了解到的情况如何，但根据我听到的个别案例，我曾与一位在Google担任高管的好朋友交谈。我问他：“你裁过人吗？”他说：“没有，我们没有裁员。相反，我们现在正在飞速推进路线图。原本需要2年完成的路线图，现在3个月就能完成。

And where actually our hardest problem is knowing what to add to the road map, which by the way is like every PM's fantasy. You know, how much emotion has been drained on prioritization conversations between you and I?"

我们真正最棘手的问题，是弄清楚应该在路线图中增加什么。顺便说一句，这简直是每个PM梦寐以求的状态。想想你我为了讨论优先级排序，耗费了多少情绪和心力？”

So, yeah, I actually think that people shouldn't be as stressed and I think they should feel really empowered. And and by the way, the best way to do it is just to ship stuff. I mean, Claire is my muse. Uh she is so awesome cuz she's always shipping. Yes, Claire Bow. She's shipping. She's trying things. She's not afraid to be a little embarrassed by it.

因此，我确实认为大家不必如此焦虑，而应该意识到自己大有可为。最好的做法就是直接把产品做出来并发布。Claire是我的缪斯。她非常出色，因为她始终在不断发布作品。没错，就是Claire Bow。她不断发布、持续尝试，也不怕因此感到些许难为情。

And if you just see her whole kind of affect, she feels like the best version of herself that she's ever been. And I think we all have an opportunity to be that.

如果观察她整体呈现出的状态，就会觉得她已经成为有史以来最好的自己。我认为，我们所有人都有机会成为这样的人。

Mhm.

是的。

I love that. I want to be Claire Bow when I grow up.

我很喜欢这句话。我长大后也想成为Claire Bow那样的人。

Totally.

完全同意。

Uh kind of along those lines, you have this interesting take that company building more and more is going to become this kind of series of creating loops and creating series of loops. Talk about that.

顺着这个思路，你提出过一个很有意思的观点：公司的构建将越来越像创建一个个循环，最终形成一系列循环。请具体谈谈这件事。

Yeah, yeah. Well, I think the broad concept and you know, it's I the loops concept kind of gets teased a little on X cuz at sometimes it feels like maybe we're big braining it. I know there was a a big meme around graphs, like the next stage of loops is graphs.

大体上的概念是这样的。“循环”这个概念在 X 上受到过一些调侃，因为有时我们似乎把它想得过于复杂了。之前有一个关于图的热门梗，说循环的下一阶段就是图。

Um but let me make the kind of steel man for it, which is you know, we had prompts and then we invented agents. Agents, of course, are just models in a loop with tools and memory and skill files. And then we had sort of loops, which are, you know, sets of agents that are doing tasks. If you look at a lot of work in coding, coding such a great domain because you have the best models and you have the most sort

不过，我会尽量为这个概念提供最有力的论证。我们最初有了提示词，后来又发明了智能体。当然，智能体无非是处于循环中的模型，再配上工具、记忆和技能文件。接着又出现了所谓的循环，也就是由一组执行任务的智能体构成的系统。观察编程领域的许多工作，就会发现编程尤其适合这种方式，因为这里拥有最好的模型，也拥有最

of technically apt customer. Plus you have these established loops. Like bug fix or sort of bug report comes in, uh repro gets generated, bug fix gets created, bug fix gets reviewed. If high risk, then human should confirm that it's okay to ship to prod. And if low risk, it just gets shipped. And maybe you even email the customer and say, "Hey, we fixed the bug you reported."

懂技术的客户。此外，这个领域已经形成了许多循环，例如修复 bug：收到 bug 报告后，先生成复现步骤，再创建 bug 修复方案，随后审核该方案。如果风险较高，就由人工确认是否可以发布到生产环境；如果风险较低，就直接发布。甚至还可以给客户发送邮件，告诉对方：“你报告的 bug 已经修复了。”

That happens in 5 minutes. There are many loops like that in engineering, everything from, you know, bug fixes to customer feedback to sales demos um to new feature development. Um So, coding sets this up well itself up well. So, you have a coding loop and the kind of change it makes is to the code base. My question is, what are the business loops? Right? So, if you're the GM of a business, you're looking across

整个过程可以在 5 分钟内完成。工程领域存在许多这样的循环，涵盖 bug 修复、客户反馈、销售演示和新功能开发等各种工作。因此，编程本身非常适合这种方式。由此便形成了编程循环，而它改变的是代码库。我的问题是：业务循环是什么？如果你是一家公司的总经理，就需要统筹

many job functions and you've got loops running in coding and marketing and sales and support and legal. The output of all of those loops is something that is itself a loop that you should be able to optimize for. And I think the strong form of this is that it sends a message to the CEO saying, "Hey, we need to actually make a change to one of the physical aspects of the business or to our business model or to our strategy."

许多职能部门，而编程、营销、销售、客服和法务都各自运行着循环。所有这些循环的输出又共同构成一个更大的循环，而你应该能够对其进行优化。我认为，它更强大的形态是向 CEO 发送一条消息：“我们确实需要改变业务中的某个实体环节，或者改变商业模式或战略。”

So, I think we're going to see this sort of cascading set of everything from a loop per person, loop per job function, loop across entire business units to, you know, loops that can run large parts of the company.

因此，我认为我们将看到一种层层递进的体系，其中包括每个人的循环、各个岗位职能的循环、横跨整个业务单元的循环，以及能够负责公司大部分运营的循环。

With that said, I think humans are a critical ingredient. I just don't think that most work in the organization can be done fully autonomously. When you think of what a human will do in this like AI native company, sales, support, strategy, and exceptions. Right? And all those things are super critical. If we've seen one thing, Lenny, it's that the ability for models to do new thinking out of distribution thinking is

话虽如此，我认为人类仍是至关重要的要素。我不认为组织中的大部分工作都能完全自主完成。思考人在这种所谓的 AI 原生公司中将承担什么工作时，答案无非是销售、支持、战略和处理例外情况，而这些工作都极其关键。如果说我们已经看清了一件事，Lenny，那就是模型进行全新思考和分布外思考的能力

still really limited. And I don't actually take the point that some of the new thinking in math is actually representative of new thinking in domains like business. So, you're still going to need a person to say, "Hey, here's the thing I think we should make." and have them be right about it.

仍然非常有限。我也不认同这样一种观点，即数学领域中的一些新思路真正代表了商业等领域中的新思路。因此，仍然需要有人站出来说：“我认为我们应该做的是这个。”而且这个人的判断必须正确。

Let me just kind of make sure this point is really clear cuz it's so interesting.

我来确认一下，确保这一点表达得足够清楚，因为它非常有意思。

What you're saying here is engineering and building more and more is becoming this loop of input, feedback, or support ticket, whatever, input of just like what to build, and then AI more and more is taking that, deciding here's a PR, here is this ready, and then shipping And you're saying that you expect that to spread to like say go to market, legal, uh growth, support. So, maybe describe what

你的意思是，工程开发和产品构建正日益变成一种循环：首先接收反馈、支持工单等关于应该构建什么的输入，随后越来越多地由 AI 接手处理，判断某项内容是否应成为一个 PR、是否已经准备就绪，然后将其发布上线。你认为这种循环还会扩展到市场推广、法务、增长和支持等领域。因此，或许可以描述一下

that loop looks like or may look like for within a company.

这种循环目前在公司内部是什么样子，或者未来可能会是什么样子。

I mean, a great example is a growth team. You worked on the growth team at Airbnb, right?

增长团队就是一个很好的例子。你曾在 Airbnb 的增长团队工作过，对吧？

Yeah. Yeah, supply growth. Yeah, that's right.

是的，我负责供给侧增长。

Yeah. Awesome. Right. So, you remember those like war I don't know how you ran your team, but I'm guessing it was something like you got everyone together, you built a list of possible experiments, you prioritized them, you built, then you shipped them, you measured them.

很好。你应该还记得那些类似作战会议的工作方式。我不知道你当时具体如何带领团队，但我猜大致是这样：先召集所有人，列出一份可能开展的实验清单，确定优先级，然后进行构建并发布上线，最后衡量效果。

Brainstormings. Yeah. A lot of brainstormings. A lot of spreadsheets.

大量开展头脑风暴，并使用大量电子表格。

So, the the the loop version of that should be that every variant gets generated, every variant gets measured.

因此，这件事的循环版本应该是生成每一个变体，再衡量每一个变体。

Once you get to stat sig with a high enough P value, you can merge and ship that variant. You then have a long-term holdout, and you start working on the next experiment. You know, and then you're going to hit some local maxima.

一旦达到统计显著性，而且P值足够高，就可以合并并发布这个变体。随后设置一个长期留出组，再开始下一个实验。最终，你会触及一些局部最大值。

And I think this is really important, you know, the loop will help you climb to the local maxima, but then it plateaus. And you need some sort of out of distribution thinking, you need human intuition, you need somebody to actually help you land at the base of the next hill.

这一点非常重要。这个循环会帮助你攀上局部最大值，但之后就会进入平台期。接下来，你需要某种分布之外的思维和人类直觉，需要有人真正帮助你抵达下一座山的山脚。

Yeah, you have this chart. I don't know, maybe we'll show it over later as we talk about this, which is such an interesting way of thinking about it.

你有一张图。或许稍后谈到这里时，我们会把它展示出来。这是一种非常有意思的思考方式。

This idea that agents will help you hill climb and reach some new plateau and then you need a human there to un- think about a bigger idea, kind of unlock it and then it keeps going and going and there's kind of this like agent to human kind of back and forth.

智能体会帮助你爬坡并到达一个新的平台，随后就需要有人跳出当前思路，构想一个更大的点子，打开新的局面，再继续向前推进。这有些像智能体与人类之间的来回接力。

Yes. Yeah, and you know what really illustrates that? If you've ever tried to have an agent come up with a business idea for you?

没错。最能说明这一点的，是尝试让智能体替你构想一个商业点子。

Like, you know, "Hey Claude, make me a million dollars, make no mistakes."

比如：“Claude，帮我赚一百万美元，而且不要犯任何错误。”

Like, why doesn't that work, you know?

这为什么行不通？

And it's because you sort of need to set it in the right direction and and nothing in the technology has shown us that that is not needed.

因为你必须先为它设定正确的方向。到目前为止，没有任何技术迹象表明这一步已经不再必要。

Yeah, it's interesting what like I've been hearing more and more. I just saw a tweet that I think at OpenAI, the go-to-market team now is using Codex more more of the go-to-market team is using Codex more often than even the engineering team.

这很有意思。最近，我越来越常听到这类事情。我刚看到一条推文，其中似乎提到，在OpenAI，市场拓展团队中越来越多的人使用Codex的频率甚至高于工程团队。

Yes.

对。

And and think of how happy that makes them. Like, what does the go-to-market team want to do? I mean, this is a caricature, but I'm going to stand behind it, which is they want to hit the gym, they want to go to steak dinners, and they want to like, you know, like raise the trophy up for being salesperson of the quarter of the year.

想想这会让他们多么开心。市场拓展团队想做什么？虽然这只是一种夸张的刻板印象，但我仍然认为：他们想去健身房，想享用牛排大餐，还想因为成为年度或季度销售冠军而举起奖杯。

Um so, I actually think that this is a distillation of their job into the thing that they're the best in the world at, that they're the most interested in, um and all the administration that goes around doing that core work is now handled for them. So, like that's where go-to-market is going and it's going to be awesome.

因此，我认为这实际上是把他们的工作提炼成一件事：专注于他们最擅长、堪称世界顶尖，同时也最感兴趣的核心工作，而围绕这项核心工作的一切行政事务，现在都有人替他们处理。市场推广的未来就是如此，而且一定会非常出色。

This reminds me of a PM friend who has this had this really funny take that as a PM, you're constantly having to say no to all these ideas that are coming at you and you have like, "I'll put it on the road map. We'll prioritize it." He's like, "Okay, I'm going to flip this. I'm going to say yes to everything. I'm going to build everything and then simulate every of every idea with like Simily or all these products that are

这让我想起一位做PM的朋友。他有一个非常有意思的观点：作为PM，你总要不断拒绝涌来的各种想法，并表示“我会把它放进路线图里，我们会安排优先级”。但他说：“我要反过来做，对一切都说‘好’。我要把所有东西都做出来，再使用Simily这样的产品，或者现在推出的其他产品，模拟每一个想法。”

launching where you can simulate how a user will react. And then that'll tell you should this be should we build this?

你可以用这些产品模拟用户的反应，结果则会告诉你：“这个想法是否值得实施？我们是否应该这样做？”

What a hilarious way to rethink PM.

这种重新思考PM工作的方式非常有趣。

And you know what's so beautiful about that? Actually, there's two things. I'll tell you maybe the one that's less obvious to me, which is I feel like every PM at every company feels like they're a true zero-to-one thinker, but they're held back by the kind of, you know, the heavy hand of management and executives and founders and engineering capacity.

这件事最妙的地方其实有两点。先谈一个对我而言可能没那么显而易见的点：我认为，每家公司的每个PM都觉得自己真正具备从零到一的思考能力，只是受制于管理层、高管和创始人的强力干预，以及工程能力的限制。

And in a world where every story gets told, every product story gets told, every feature gets tried, I think a lot of PMs are going to realize they're actually not that good at zero-to-one and it's much more fulfilling to work on someone else's good idea than your own bad idea.

而在一个每个故事都能被讲述、每个产品故事都能被讲述、每项功能都能被尝试的世界里，许多PM会发现，自己其实并不那么擅长从零到一。与其实施自己的糟糕想法，不如围绕别人的好想法开展工作，后者反而更有成就感。

So, I think even things like that are going to lead to a lot more organizational health than we've had in the past. You know, not to mention the fact that the idea that ends up winning doesn't have to be the one that's came up with by the person who can sell it best to an executive. It just gets tried and the best idea wins.

因此，我认为即使只是这样的变化，也会大幅改善组织的健康度，使其远胜以往。更重要的是，最终胜出的想法不一定非要来自最擅长向高管推销它的人。只要把想法拿来尝试，让最好的想法胜出即可。

So, coming back to this loops idea, the the way I'm thinking about it is how can every function start to think of their function as setting up an agent to be able to just go from input to Yeah.

回到循环这个概念，我的思路是：怎样才能让每个职能部门都开始把自己的职能视为搭建一个智能体，使其能够直接从输入走向某种影响？对。

some kind of impact. And what this makes me think about is something actually Clear tweeted recently. This point that people always used to joke that like soft skills are the least valuable and engineering skills the most important and valuable because they're so concrete and it turns out that's what AI is the best at. The things that are verifiable and and, you know, you know what success looks like. And

这让我想到Clear最近在推文中提到的一件事。她的观点是，以前人们总爱开玩笑说，软技能最没有价值，而工程技能最重要、最有价值，因为它们非常具体。但事实证明，AI恰恰最擅长这些可以验证且成功标准明确的事情。

so that the question I think about now is just like which skills can you not just turn into a loop because the output is so hard to verify.

因此，我现在思考的问题是：哪些技能无法被直接转化为循环，因为它们的输出实在太难验证？

Yeah, I think that's right and I think that those are going to be the rate-limiting factors cuz you can only do one steak dinner a night. I guess you could do a steak lunch, but, you know, to some extent there's going to be these rate-limiting factors in every system.

确实如此。我认为，这些技能将成为限制速率的因素，因为一个晚上一顿牛排大餐已经是极限。或许中午也可以吃牛排，但在某种程度上，这些系统中都会存在限制速率的因素。

Um I think a useful way to think about it is anytime the model's making a mistake or doing something you wouldn't do, what do you know that it doesn't know?

一种有用的思考方式是：每当模型犯错，或者做出你不会做的事情时，思考你知道哪些它不知道的事情。

Um and there's a really interesting example I heard from Ale at Kavak. He's probably the most sophisticated thinker on this stuff that I get to hang out with, where he said anytime they were agent they have an agent per customer, they sell used cars online, and when the agent gets stuck it actually calls a human.

我从 Kavak 的 Ale 那里听到过一个非常有意思的例子。他可能是我接触过的人中，对这类事情思考得最深入的人。他说，他们为每位客户配备一个智能体，用于在网上销售二手车。当智能体遇到无法解决的问题时，就会呼叫真人。

And the human will coach the agent through. Now, the magic of that is not only does it unblock the agent, but of course the agent then captures all the traces and learns from it. Like that's a really interesting mental model. It's either a knowledge gap or a data gap that you have to give the agent, and the next time it shouldn't have to call you.

真人会指导智能体解决问题。其巧妙之处在于，这不仅能帮助智能体摆脱困境，智能体还会记录完整的处理轨迹并从中学习。这是一种非常有意思的思维模型：问题要么源于知识缺口，要么源于数据缺口。你必须向智能体提供缺失的内容，使它下次不必再呼叫你。

I love that example. Basically, the takeaway here is you need to start thinking about every function as an agent loop, and the job is to figure out where it gets blocked, where it goes wrong, and give it more context, more insight, more direction, basically.

我很喜欢这个例子。这里的要点是，你需要开始将每一项职能都视为一个智能体循环。你的工作是找出它会在哪里受阻、在哪里出错，然后为它提供更多上下文、洞见和指引。

That's right. That's right. And then hopefully a lot of your day-to-day work, you know, when you come up with a new idea that works, the kind of implications of that idea, if it's a product, you know, there's marketing work, there's sales work, there's product marketing, there's communication, there's legal, all of that should be largely handled for you.

没错。理想情况下，当你想出一个可行的新点子后，由此产生的许多日常后续工作都能由智能体处理。如果这个点子涉及一款产品，那么营销、销售、产品营销、沟通和法务等工作，都应该在很大程度上由智能体替你完成。

And your idea, you know, your job is to go take a hike and dream the dreams and come up with the next hill to climb.

你的工作则是去徒步，尽情畅想，并找出下一座要攀登的山峰。

And this begs the question a bit of just what will separate the companies that win in this world where AI is kind of doing a lot of this?

这也引出了一个问题：在这个AI几乎包办许多事情的世界里，胜出的公司将靠什么脱颖而出？

I imagine part of the answer is the human in this local maxima coming in with the better idea. Is there anything else that you think becomes like a differentiator in this world where AI is doing so much of the work that humans are currently doing?

我认为，部分答案在于人类会在这个局部最大值处介入，提出更好的想法。你认为还有哪些因素会成为差异化优势？毕竟在这个世界里，AI正在承担大量目前由人类完成的工作。

I mean, I One thing that's under discussed is that um it's unclear that the sort of competitive equilibria that exists in a lot of industries will really change.

有一点尚未得到充分讨论：许多行业现有的竞争均衡是否真的会发生变化，目前仍不明确。

You know, so let's say Pizza Hut and Domino's and Papa John's and Round Table all get a data center of PhDs, and you know, they're all going to either adopt it or have a CEO change and adopt it. So, it'll be a rocky period and there'll be some, you know, relative shuffling, but I think that they're all going to embrace new technology cuz most companies do. I don't know that one of them is going to have 99% of the market.

假设Pizza Hut、Domino's、Papa John's和Round Table都拥有整整一个数据中心的博士，它们最终要么都会采用这项技术，要么会在更换CEO后采用。因此，这期间会经历一段动荡期，也会出现相对位次的变化，但我认为它们最终都会拥抱新技术，因为大多数公司都会这样做。我不认为其中某一家公司会占据99%的市场。

So, I think kind of what's under discussed is that yes, in the near term, I think there'll be winners and losers based on adoption of the technology and kind of how ambitiously you adopt it, but I do think there's a lot of industries that will sort of maintain their current competitive dynamics because they're not intelligence bound.

因此，一个尚未得到充分讨论的问题是：短期内确实会出现赢家和输家，结果取决于企业是否采用这项技术，以及采用时抱有多大的雄心。但我也确实认为，许多行业会在某种程度上维持当前的竞争格局，因为它们并不受智能水平的限制。

Um I think the most useful question to ask yourself as a founder CEO is just, "Hey, if we assume these things are infinitely um intelligent and astonishingly cheap, how would we reorganize the company?" Cuz that's where we're going.

作为创始人兼CEO，你最应该问自己的问题是：“假设这些东西拥有无限智能，而且便宜得惊人，我们应该如何重组公司？”因为我们正在朝这个方向发展。

Kind of along those lines, you have this interesting take about this kind of split that might be coming within companies like between these uh generalists and specialists and how AI plays into that. Talk about that.

顺着这个思路，你提出过一个很有意思的观点，涉及公司内部未来可能出现的分化，例如通才与专才之间的分化，以及AI将如何影响这种分化。能具体谈谈吗？

Yeah, well, I think that there's so many interesting things that this touches on.

可以。我认为这涉及许多有意思的问题。

You know, one is the question of open weight versus frontier. So, I I'm sure Are you familiar with kind of Pareto efficiency? I'm sure you are.

其中一个问题是开放权重模型与前沿模型之间的关系。你应该了解帕累托效率。

Uh please explain.

请解释一下。

Yeah, so Pareto efficiency is just, you know, um for price performance, for example, what is the kind of the efficient frontier is what's considered the optimal trade-off of, you know, a unit of performance for a unit of price.

所谓帕累托效率，以性价比为例，有效前沿就是人们认为最优的权衡，也就是每单位价格能够换来多少单位性能。

And, you know, are you sort of if you're along that curve, you're always paying the rational amount for the performance.

如果你处在那条曲线上，那么为相应性能支付的价格始终是合理的。

And what's interesting is that frontier models are actually irrationally priced in that, you know, first of all, Mythos is infinite dollars a token, you can't use it.

有意思的是，前沿模型的定价其实并不合理。首先，Mythos每个token的价格是无限美元，你根本无法使用它。

Um but if you look at even something like Fable 5, you know, for one IQ, conceptually one IQ of extra intelligence, you're paying 100X more than Opus 48. So, it's not rational, but I think there's a lot of jobs in which you have unbounded upside like drug discovery, you know? And if that one IQ point lets you discover the next, you know, statin, it's a trillion-dollar outcome. So, it's sort of rational to

但即使考察Fable 5这样的模型，每增加一个IQ，也就是从概念上说，每提升一个IQ的智能水平，你支付的价格都比Opus 48高100X。因此，这种定价并不合理。不过，我认为许多工作拥有无限的上行空间，例如药物研发。如果多出的那一个IQ点能让你发现下一种他汀类药物，那将是价值一万亿美元的成果。所以，对于

pay for the highest intelligence in these types of jobs and industries. Now, on the other hand, um I'm going to pick on, you know, maybe legal.

这类工作和行业而言，为最高水平的智能付费在某种程度上是合理的。另一方面，可以用法律行业作为例子。

There's perhaps only so much upside to be had in legal or finance. And for those jobs, you actually do want to be very Pareto efficient and probably pay for, you know, good performance at a good price, not infinitely priced infinite potential upside performance.

在法律或财务等领域，能够获得的上行空间或许较为有限。对于这些工作，你确实希望实现极高的帕累托效率，并以合理的价格为出色表现付费，而不是为具有无限潜在上行空间的表现支付无限高的价格。

So, I think what we're going to see is a split between job functions that de- demand kind of mid-IQ um intelligence.

因此，我认为我们将看到一种分化：一类工作职能需要中等智商水平的智能。

And those will often be open-weight, sort of biased with reinforcement learning, you know, things that make the models even cheaper and more performant for a narrow job. Along with, you know, incredibly um quote-unquote expensive, but performant frontier tokens for sales, support, research, engineering.

这类工作往往会采用开放权重模型，再通过强化学习进行有针对性的调整，从而使模型在特定工作上成本更低、性能更强。与此同时，人们也会使用极其“昂贵”但性能强大的前沿模型 token，处理销售、支持、研究和工程工作。

So, I think you're going to end up having both architectures. And, you know, we can touch on this in a little bit, but I do think there are these sort of comparative advantages amongst model families. Um and then also amongst, of course, individual models that we're seeing more and more of. It's not going to be one or the other.

因此，我认为这两种架构最终都会存在。我们稍后可以继续讨论这一点，但我确实认为，不同模型家族之间存在某种比较优势。当然，我们也越来越多地看到，各个具体模型之间同样存在这种比较优势。这并不是非此即彼的选择。

Such an interesting insight. So, just to make sure I understand what you're describing here, you're thinking there's going to be this split between kind of within an org of function and model, where specific functions that have a lot more upside and in- potential leverage go for the frontier models. And you you describe these kind of product, sales, engineering, research roles. And then there's like And then for other

这个洞见很有意思。我想确认自己是否准确理解了你描述的情况：你认为组织内部将出现一种分化，即不同职能会采用不同的模型。上行空间更大、潜在杠杆效应更高的职能会选择前沿模型，包括你提到的产品、销售、工程和研究等岗位。除此之外，对于其他

functions, you don't need you don't need Mythos. You don't need Astra, I think.

对于这些职能，你不需要Mythos，也不需要Astra——我想它是叫这个名字。

Is that Is that the least one coming out?

这是即将推出的最弱的那个吗？

Yeah.

对。

And so, it's both you're saying that AI doesn't need to be the frontier model and the people don't have to be the smartest people in the world to do really well in that world.

你的意思包括两个方面：AI不需要是前沿模型，人也不必是全世界最聪明的人，就能在那个世界里做得非常好。

Yeah, and I don't I don't want to be diminutive. Like, there's extraordinary people in those job functions. I just think that they're bounded upside problems that they work on. You know, you can only kind of uh close the books correctly. You know, you can't close the books 100x better.

对。我并不想贬低这些人，那些职能中有非常优秀的人才。我只是认为，他们处理的问题上行空间有限。你最多只能把账结清，并且保证准确，不可能把账结得好上100倍。

So, yeah, that that's exactly what I'm saying.

对，这正是我想表达的。

I wonder if it's connected back to that discussion we had earlier about it's verifiable. If it's a lot more verifiable, you don't need the frontier model versus I don't know, the potential upside.

我在想，这是否又与我们之前的讨论有关，也就是问题是否可验证。如果可验证性高得多，相比可能存在的上行空间，或许就不需要前沿模型了。

I'm not sure. I mean, I think for a verifiability is a good question is I think for a like a drug development company, you have infinite upside. It is verifiable, but closing the books is also a verifiable problem, which has limited upside. I think the question is really how how much upside is there and how hard is it to calculate it? Like here's a nuance. Customer support, a customer may call in and report a bug.

我不确定。我认为可验证性是一个好问题。以一家药物研发公司为例，它有无限的上行空间，所处理的问题也是可验证的；结账同样是一个可验证的问题，但它的上行空间有限。我认为真正的问题在于，上行空间究竟有多大，以及计算它有多难。这里存在一个细微差别。例如，一位客户可能会致电客户支持，报告一个 bug。

That bug may actually be the first breadcrumb to a thing that changes our entire organization. And if the CEO is on that call or the smartest person, they could follow the trail.

那个 bug 实际上可能是第一条线索，最终引出足以改变整个组织的事物。如果由 CEO或最聪明的人接听这通电话，他们就能顺着这条线索追查下去。

Um but if we actually have this quote-unquote mid IQ generalist then not, that actually makes the case for as a basket of problems always use frontier intelligence. Um and I can of course make the case for the mid IQ basket as well, which is simply that we've crossed an intelligence threshold for almost every economically useful problem. And anything beyond that threshold is is simply waste.

但如果我们使用的确实是这种所谓的“中等智商通才”，它就做不到这一点。这实际上说明，从一揽子问题的整体角度来看，应该始终使用前沿智能。当然，我也可以为中等智商这一派提出论据：我们已经跨过了某个智能门槛，几乎所有具备经济价值的问题都已包含在内，超过这一门槛的任何智能都纯属浪费。

Yeah, and like I think I think people point people forget is that the models that are not the frontier models, they were like that was what the frontier was I don't know six months ago and we were so impressed and we loved it. It was like, "Holy it can do all this."

对。我认为大家忘记了一点：那些并非前沿模型的模型，大概只是处于六个月前的前沿水平，而当时我们还对它们惊叹不已，喜爱有加，觉得：“天啊，它居然能做这么多事。”

And now just because there's something better, we don't give those models as much credit.

如今，只因为有了更好的东西，我们就不再像以前那样认可那些模型的价值。

You're right cuz it's sort of like this thing is so crazy, you know, this is um this is AGI and then a day later it's like the old thing that you throw in the dustbin.

你说得对。当时的感觉是：“这东西太疯狂了，这就是 AGI。”结果仅仅一天后，它就成了被扔进垃圾桶的旧东西。

So kind of along those lines, uh I hear people jokingly call you a model sommelier.

顺着这个话题，我听说大家开玩笑地称你为“模型侍酒师”。

Tell us with your sommelier credentials, what's kind of like the current state of the model arts? What what are each What are What is each model great at? What's each What are models terrible at?

凭借你的侍酒师资历，请谈谈目前模型领域大致处于什么状态。每个模型分别擅长什么，又不擅长什么？

Yes, well, the you know, as you know, the secret of every sommelier is 10,000 hours or maybe 10,000 bottles. So I think that the secret of being a model sommelier is just using them all.

正如你所知，每位侍酒师的秘诀都是投入10,000小时，或许也可以说是喝过10,000瓶酒。因此，我认为成为模型侍酒师的秘诀，就是把所有模型都使用一遍。

Drinking them all.

把它们全都喝一遍。

Um I push myself really hard to ship something with every new model that comes out. And I think you learn so much. You know, I think for people who believe the models are commodities or totally fungible, you just haven't actually used the models. And you know, for example, in the last few weeks, I've been obsessed with Qwen 38B.

每当有新模型发布，我都会要求自己用它做出一些东西。我认为这样可以学到很多。那些认为模型都是商品，或者完全可以互相替代的人，只是还没有真正使用过这些模型。例如，过去几周，我一直痴迷于Qwen 38B。

Um Qwen is an awesome model. It's very good at long horizon tasks, and it's actually really creative. It's a great storyteller. So, I've been using it to create these uh impossible documentaries, um mostly of, you know, planets in the Star Wars universe.

Qwen是一个非常出色的模型，尤其擅长长周期任务，而且确实很有创造力，也很会讲故事。因此，我一直用它制作一些不可能存在的纪录片，内容主要围绕Star Wars宇宙中的星球。

I did uh Tatooine, which turned out great. I did Bespin last night. And it can just work for 4 or 5 hours. It tells a great story. It generates all the video using the MiniMax model via file.

我制作了Tatooine，效果非常好。昨晚我又制作了Bespin。它可以连续工作4或5小时，讲出一个精彩的故事。它会通过file调用MiniMax模型，生成所有视频。

Generates audio via 11. It actually like directs the movie, the 5-minute movie, in that it like cuts all of the clips in. It overlays it. It watches it. It's just extraordinary, you know? And that's just It's got a totally different shape than GLM 52. GLM 53 just came out, which I used for a bunch of product work. It doesn't have a vision component, and it's sort of like this neurotic PhD you put in the corner. And they both have

它还会通过11生成音频，并实际执导这部5分钟的电影：将所有片段剪辑进去、叠加起来，再观看成片。这简直不可思议。它的特性与GLM 52截然不同。GLM 53刚刚发布，我已经用它完成了许多产品工作。它没有视觉组件，有些像一个被安置在角落里的神经质博士。它们各自都有

their role, right? This is a little bit of the kind of these tension of models.

自己的用武之地。这在一定程度上体现了不同模型之间的张力。

It's not that one is ahead of another, one is more intelligent. It's rather one is sort of has a mind that's shaped in one direction, perhaps creativity and openness for Qwen, and others that are shaped in other directions, like, you know, neuroticism and precision, like GLM 53. Um So, that I just make something with every model, and that's how I build my intuition.

这并不是说一个模型领先于另一个，或者一个模型更加聪明，而是它们的思维方式各有侧重。例如，Qwen偏向创造力与开放性，其他模型则被塑造成不同的方向，比如GLM 53所体现的神经质和精准度。因此，我会用每个模型做一些东西，以此培养自己的直觉。

How important is this habit, do you think, for people? Because I hear a lot that it's really important to be using these models.

你认为这一习惯对人们有多重要？我经常听人说，实际使用这些模型非常重要。

And kind of a secondary question is, how do you come up with what to do with these models? Cuz a lot of people want to try these things. They're like, "Okay, what do I do?"

另一个相关的问题是：你如何想到该用这些模型做什么？很多人都想尝试这些东西，却会困惑：“好吧，我该做什么？”

I know.

我明白。

Any suggestions?

有什么建议吗？

Well, I think you Almost all of us have got, you know, the most insufferable thing for for a long time was your app idea friend. You know, every time you went to have a beer, they're like, "Let me tell you my app idea." You're like, "Ugh, here we go again." Like, we have got to be the the app idea guys uh now.

我想，我们几乎所有人长期以来都遇到过一种最让人受不了的朋友：他们满脑子都是应用创意。每次一起出去喝啤酒，他们都会说：“让我给你讲讲我的应用创意。”你心里则会想：“唉，又来了。”但现在，我们都得变成那种满脑子应用创意的人。

And all the silly ideas, actually, especially the silly ideas, cuz those are the ones that often have the most alpha, are the ones that we should all be building. So, I probably got, you know, two dozen apps that I build. I've got one or two large apps that I iterate on. And I think that if you don't have a chassis on which to like with which to use the models, it's just really hard to come up with an idea from scratch every

我们都应该把那些看似傻乎乎的点子付诸实践，尤其是这类点子，因为它们往往最有可能创造超额价值。我大概做了二十多个应用，还有一两个规模较大的应用一直在迭代。我认为，如果没有一个载体供你使用这些模型，那么每次都从零开始构思点子会非常

time.

困难。

So, I I'd say like work on something.

所以，我的建议是先动手做点什么。

It's actually better if it's not important with a capital I. And then keep finding new ways to invest in it and add to it with a model as a kind of tool rather than as a goal. Does that make sense?

而且，最好不要一开始就做某种大写的“重要”之事。你可以不断寻找新方法，继续投入其中，借助模型逐步完善它，并把模型当作工具，而不是目标。这样说你能理解吗？

Yeah. Like maybe even zooming out. I've been thinking more and more one of the most important habits to build right now is to whenever you're about to do something, ask yourself, "How can AI do this for me?"

能。或许还可以再退一步思考。我越来越觉得，现在最重要的习惯之一，就是每当准备做某件事时，都问问自己：“AI 怎么能替我做这件事？”

Totally.

完全同意。

And and visualizing this like input to response, you know, like the whole idea of there's a space between input and response. And meditation helps you uh think more deeply before you respond.

还可以把这件事理解为从输入到响应的过程，也就是在思路的输入与响应之间留出间隔。冥想能帮助你在作出回应前进行更深入的思考。

And I feel like the trick now is insert in that moment, "How can AI help me with this?"

我认为现在的诀窍，就是在那个瞬间加入这样一个问题：“AI 能怎么帮我处理这件事？”

Yeah, no, I think that's that's I mean I'm also a long-time meditator. We should talk about a lot of you like, but yeah, I think that's right. I think in our day-to-day knowledge work, sometimes it's less obvious to me. I guess my mind is I've always been a consumer product person. I love products. So, for me it's easier to think of a new feature to add to my DJ streaming app or um you know, my sort of Google Reader for X that I

对，确实如此。我也冥想很多年了，关于这方面，我们还有很多内容可以讨论。不过，我认为你说得对。在日常的知识工作中，这一点有时对我而言并不那么明显。我一直从事消费产品相关工作，也非常热爱产品。因此，对我来说，想出一个可以添加到我的 DJ 流媒体应用中的新功能，或者添加到我自己使用的那个 X 版 Google Reader 中的新功能，

use than it is to kind of find a part of my life to automate. But you're right, there's some fun examples. You know, I posted about one a few weeks ago where I had my laptop um transcribe everything that was happening in the kitchen.

要比找出生活中的某个部分并将其自动化更容易。不过，你说得对，这方面确实有一些很有趣的例子。几周前，我分享过一个例子：我让笔记本电脑把厨房里发生的一切都转录下来。

And then it would um award or detract screen time from my son's iPad depending on whether he was being good or bad. Um So, it was like a fun little social experiment. It also had a fun outcome, which is that he recorded a video of himself saying, "I love you, Dad." over and over and put it next to the mic to to hack the metrics.

然后，它会根据我儿子表现得好还是不好，增加或扣减他的 iPad 屏幕使用时间。这就像一个有趣的小型社会实验，还产生了一个很有意思的结果：他录了一段自己说“我爱你，爸爸”的视频，在麦克风旁边反复播放，以此钻指标的空子。

To hack the metrics. So, yes. Uh so, yes, the kind of you know, we anything becomes a measure, it's no longer useful. Um but, it was just a cool little social experiment. I think those things are super fun.

他是在钻指标的空子。任何东西一旦成为衡量指标，就不再有用了。不过，这是一个很酷的小型社会实验。我觉得这类事情特别有意思。

That is hilarious. And one of So, one of the measures was how often he said I love you.

太好笑了。所以，其中一个衡量指标就是他说“我爱你”的频率。

And I was going to give him more screen time.

而我原本打算给他更多屏幕困难。

he saying things that are positive and prosocial or or or negative and antisocial? And it you know, saying I love you is very prosocial.

指标要判断的是：他说的是积极、亲社会的话，还是消极、反社会的话？而“我爱你”显然是非常亲社会的表达。

That's so funny. I had a friend who built this little device device that measured how often he and his kids laugh throughout the day.

太好笑了。我有个朋友制作了一个小设备，用来测量他和孩子们每天笑了多少次。

Oh, that's nice.

这真不错。

Yeah. He hacked like one of his Limitless pendants to do that. And then they just look at that metric every day.

对。他改装了一个 Limitless 吊坠来做这件事，然后他们每天都会关注这个指标。

Isn't that so And this is what I mean, you know, man? Like, I think we spent a lot of the time on the show so far really like intriguing talking about productivity, job loss, kind of all these like heady important topics with a capital I. But, what you just described, how often you laugh, like that's not a startup. That's probably not an economically consequential idea, but it is for like the quality of our life. And

正是如此，这就是我的意思。我认为，到目前为止，我们在节目中花了很多时间讨论一些非常引人入胜的话题，例如生产力、失业等。这些都是高深而重要的话题，而且是大写的“重要”。但你刚才描述的事情，例如衡量自己笑得有多频繁，并不是一家创业公司，可能也不是一个会产生重大经济影响的想法，但它确实关系到我们的生活质量。而且

I think we tend to think that happiness is fixed, but what if it's not? You know, if you and I were doing jobs 100 years ago, like what would our jobs be?

我认为，我们往往把幸福感视为固定不变的事物，但如果事实并非如此呢？试想一下，如果你我生活在 100 年前，我们会从事什么工作？

I promise they'd be less cool than they are right now. And And maybe 100 years from now, they'll be that much cooler.

我敢肯定，那些工作不会像我们现在的工作这样酷。也许再过 100 年，那时的工作又会酷上许多。

So, I think that the thing that gets often missed, and this is why I'm a fan of Claire and others, is just like how can this thing add texture to our human lives even if they don't have economic consequences?

因此，我认为有一点经常被忽略，而这也是我欣赏Claire 等人的原因：这些东西即使不会带来经济影响，又能如何使我们的人类生活更加丰富？

Yeah. Along these lines, I I saw somewhere you have this really interesting take that like the big opportunity, maybe just in consumer but broadly, is this idea of loop make me happier.

对。顺着这个思路，我曾看到你提出一个非常有意思的观点：最大的机会，也许仅限于消费领域，也许范围更广，就是“循环：让我更快乐”。

Yeah.

对。

Talk about that.

请展开讲讲。

Oh, yeah. I mean, I think that we believe that people want to be more productive, but they don't. I think more people want to spend time than save time. There's a reason the biggest products in the world are kind of entertainment and social. So, we get at the heart of how do we sort of deliver the value to the consumer? I think for most consumers, you know, I sometimes I I tease and I say it's like the

对。我认为，我们以为人们希望提高生产力，但事实并非如此。比起节省更多时间，更多人其实想要消磨时间。世界上最大的产品大多属于娱乐和社交领域，这是有原因的。因此，我们需要触及问题的核心：究竟应该如何向消费者交付价值？对大多数消费者来说，我有时会开玩笑说，这就像

Instagram AI user versus the X AI user.

Instagram AI 用户与 X AI 用户之间的区别。

The X AI user is like, you know, fearful of being outside of the permanent underclass, is really opinionated on GLM 53 versus Kimmy K3, like they're just so pilled. And then the Instagram person is like, "Oh, this is like a better Google search, kind of. It's cool, you know, I don't get what all the hype is about."

X AI 用户会担心自己被永远排除在底层阶级之外，还会对 GLM 53 和 Kimmy K3 孰优孰劣抱有强烈看法。他们实在太痴迷了。Instagram 用户则会说：“这有点像更好用的 Google搜索。挺酷的，但我不明白大家到底在炒作什么。”

So, I think that a lot of the And it's really a product design failure. We have the capabilities to radically transform people's lives. I mean, Lenny, in many ways we spent 40 years building a technology that enables better spreadsheets, right? We built this like technology that extends our intellect, but nothing to extend our soul. And I think that we have a little bit of a spiritual hunger, especially as a lot of

因此，我认为这其实是产品设计的失败。我们拥有彻底改变人们生活的能力。Lenny，从很多方面来看，我们花了40年时间打造一种能让电子表格变得更好用的技术。我们打造了这样一种能够拓展智力的技术，却没有任何东西能够滋养我们的灵魂。我认为，我们多少存在一些精神上的渴求，尤其是随着许多

these cultural institutions have gone away that fulfilled that, especially in the rest of America, you know, where you don't have as many hot yoga classes and Pilates and fasting and Friendsgiving.

曾经满足这种需求的文化制度逐渐消失，这一点在美国其他地区尤其明显，因为那些地方没有那么多热瑜伽课、普拉提、禁食活动和朋友感恩节聚会。

So, I think that the opportunity for this technology is like, "Hey, that the basics of consumer need. How do we feel more connected, more loved? How do we make progress? How do we have fun?" Like the things that we all aspire to, the basics. How do we apply these tech this technology to those areas? That's what I want to see more of. And And again, I don't think it's a model or a capability challenge, it's just a product design

因此，我认为这项技术的机会在于回归消费者最基本的需求：怎样才能让我们感受到更多联结与关爱？怎样才能让我们取得进步？怎样才能让我们获得快乐？这些都是所有人向往的最基本事物。我们应该思考如何将这项技术应用于这些领域，这才是我希望看到更多探索的方向。再次强调，我认为这并不是模型或能力方面的挑战，挑战只在于产品设计。

challenge.

挑战。

I love this so much. We talked about this idea of loop, like grow my business, loop find me more sales, loop close support tickets. But the way you're describing here, I think you the way I had it had my notes here, just like loop improve my health or loop make me a better friend. And there's no reason AI can't just think deeply and hard about all those things and figure out a way to actually do this.

我非常喜欢这个想法。我们刚才谈到了循环这个概念，例如“循环，帮我发展业务”“循环，帮我寻找更多销售机会”“循环，帮我关闭客服工单”。但按照你的描述，我在笔记中写下的则是“循环，改善我的健康”，或者“循环，让我成为一个更好的朋友”。AI完全可以深入而认真地思考所有这些事情，并找到真正实现它们的方法。

Yeah, and also, you know, look, there there's a we have to dial this in, but I think there's a way that AI can sort of challenge you, can push you, can be disagreeable. This is also why I think startups are advantaged over incumbents.

对。当然，其中有些地方仍然需要调整，但我认为AI可以通过某种方式挑战并推动你，而不是一味顺从。这也是我认为初创公司比现有企业更具优势的原因。

You know, the idea there's a thousand Google committees who would, you know, roll in their graves at the idea that they're going to release a model that's disagreeable or or God forbid it should be like sexually suggestive. Or but guess what? Those are all parts of human existence. So, I think exploring the kind of uncomfortable parts of our social existence are things that startups are uniquely set up to do.

试想一下，Google有上千个委员会。当他们听说公司要发布一个不那么顺从的模型时，恐怕都会气得从坟墓里翻身；更不用说这个模型竟然还会带有性暗示。但这些都是人类生存的一部分。因此，我认为，探索社会生活中那些令人不适的部分，正是初创公司得天独厚且特别适合从事的工作。

And I know you spent a lot of time investing in consumer companies. What I'm hearing here is this is a big opportunity for consumer businesses to basically build a app product that is exactly this loop around improve my connections with my friends and family.

我知道你投入了很多时间投资消费领域的公司。根据你的分析，对消费企业而言，这是一个巨大的机会：它们可以打造一款应用产品，以改善我与亲朋好友的关系这一循环为核心。

I think that's right. And you know, I think the thing that's held back consumer so far a little bit and it maybe held back is just strong cuz if you if we kind of put this into iPhone terms, we're in iPhone 2010, right? What is iPhone 2010? I think it's pre-Airbnb, pre-WhatsApp, pre-Uber, pre-all the important kind of consumer companies. Um so, it is early days, but what's held us back is I think three things. One is

我认为确实如此。此前在一定程度上阻碍消费领域发展的因素——甚至用“阻碍”来形容可能都太轻了——在于，如果参照 iPhone 的发展阶段，我们现在相当于处在 iPhone 的 2010 年。那么，iPhone 的 2010 年处于什么阶段？我认为，那是在 Airbnb、WhatsApp 和 Uber 出现之前，是所有这些重要消费公司诞生的前夜。因此，现在仍处于早期阶段，但我认为有3 个因素阻碍了我们。第一，

that the models have been expensive. So, if you want to do a kind of free to use product, it's that hasn't been easy.

模型一直非常昂贵。因此，如果想开发一款可以某种形式免费使用的产品，并不容易。

The second is that we've kind of had an interface problem. Like chat makes sense if you're the highest agency person in the world, which is Elon and Sam. But for the average consumer, like their ideal interface is TikTok.

第二，我们一直面临某种界面问题。对于世界上最具能动性的人，例如 Elon 和 Sam，聊天界面很合理。但对普通消费者来说，他们理想中的界面更接近 TikTok。

So, we need to find something between chat and uh TikTok. And then the fact that the technology has been so much more focused on productivity than things like, you know, human connection and entertainment. I think all those things are kind of up for grabs. Like the open weight models mean things are way cheaper. I think that we're starting to have conversations about things like loop make me happier. And I think that

因此，我们需要在聊天界面与 TikTok 之间找到一种合适的形态。此外，这项技术一直以来更关注生产力，而非人际联结和娱乐等领域。我认为，这些领域现在仍然充满机会。例如，开放权重模型已经使成本大幅下降。我们也已经开始讨论“来，让我更快乐”之类的事情。而且我认为，

founders like Eugenia uh who should have been on the show, she's tremendous, are thinking really ambitiously about user interfaces. Brian Chesky from Airbnb had he started a foundation lab focused on next gen user interfaces. So, I think all those problems will get solved or they're at least in a better position to be solved than they were 2 years ago.

像 Eugenia 这样的创始人——她确实应该来参加这个节目，她非常出色——正在以极具雄心的方式思考用户界面。Airbnb 的 Brian Chesky 已经创办了一家基础模型实验室，专注于下一代用户界面。因此，我认为所有这些问题都会得到解决；至少与2 年前相比，现在解决这些问题的条件已经更加成熟。

I want to come back to this the whole space of consumer and AI and things like that. But I I want to follow this thread a little bit more about just the optimism around where things might go. There's a lot of fear and worry about the future as with AI and just generally. Marc Andreessen when he came on the pod had this really interesting take that AI came just in time to save us because population is declining,

我还想回头进一步讨论整个消费与 AI 领域及相关话题，但我想先沿着这条思路继续谈下去，多探讨一些关于未来可能走向何方的乐观观点。人们对未来怀有许多恐惧和担忧，无论是针对AI，还是针对更广泛意义上的未来。Marc Andreessen之前做客播客时提出了一个非常有意思的观点：AI来得正是时候，能够拯救我们，因为人口正在减少，

productivity is going down, there's all this war, climate change and all these things and we would be in big trouble if AI wasn't here to fill that gap.

生产力正在下降，同时还存在各种战争、气候变化等问题。如果没有AI填补这一缺口，我们就会陷入巨大的麻烦。

Talk about just kind of your bigger picture perspective on why you think maybe people are underestimating the the positive and optimism around AI.

能否从更宏观的角度谈谈，为什么你认为人们可能低估了AI带来的积极影响，也低估了我们应当对AI抱有的乐观态度？

One, I think it it's a potential for it to be a sort of emotional spiritual interface on which we can kind of get leverage and explore aspects of ourselves that have been really buried.

第一，我认为它有潜力成为一种情感与精神层面的界面，使我们能够借助它探索自身那些一直被深埋的部分。

If you look at the kind of effect of the Industrial Revolution, it's that there are these scale advantages which are insurmountable. And as much as obviously I'm very pro-capitalism and I love the economy that we live in, I think that centralization it sort of discourages the individual in some ways and it maybe detracts from their identity. So, I think one of the really magical things is this a technology that really

审视工业革命带来的影响，就会发现它创造了一些无法撼动的规模优势。当然，尽管我非常支持资本主义，也很喜欢我们所处的经济体系，但我认为这种中心化在某种程度上会压抑个体，甚至可能削弱他们的身份认同。因此，我认为，真正神奇的一点在于，这是一项能够切实

amplifies our identity, our agency. It kind of unbundles skill from desire. For example, if you want to make music, you can make music now. You don't have to know how to play the piano. If you want to be a programmer and make software, you can make software now. So, it really amplifies our individuality. It allows us to explore aspects of our lives that we were never able to explore before.

增强我们的身份认同与能动性的技术。它在某种程度上将技能与意愿解耦。例如，如果你想创作音乐，现在就可以创作，而不必会弹钢琴。如果你想成为程序员、开发软件，现在也可以做到。因此，它确实放大了我们的个体性，使我们能够探索生命中那些过去无力探索的部分。

And you know, just in terms of the nuts and bolts, like we have been in this sort of morass of 2% GDP growth. Like who said that we have to be there? Why can't we be 10 or 15 or 20%? And this is a technology with which not only can we dramatically drive productivity, we can dramatically drive ambition. Like think of the maybe this is a caricature, but the 1950s and 1960s, we believed that we could do anything, right? We were coming

而且，从实际层面看，我们一直陷在 GDP 增长率只有 2% 的泥潭里。谁规定我们必须停留在这个水平？为什么不能达到 10%、15% 或 20%？这项技术不仅能大幅提高生产力，也能极大激发人们的雄心壮志。或许这样的描述有些夸张，但在 20 世纪 50 年代和 60 年代，我们相信自己无所不能。当时，我们刚刚经历了

out of World War where the entire economy, the entire world mobilized in a way that we didn't think was possible.

世界大战，整个经济乃至整个世界都以前所未有的方式动员起来，完成了此前被认为不可能做到的事情。

And one of my theories Lenny is that like when the stakes are high, we are awesome. When the stakes are low, we are at our absolute worst. And in a lot of ways, I think the world we lived in 5 years ago felt like a low stakes world, which is why we kind of collectively had a lot of these like side projects as a society which weren't necessarily productive or making any of us happier.

Lenny，我有一个看法：当事情事关重大时，我们会表现得非常出色；当事情无关紧要时，我们的表现则会糟糕到极点。从很多方面看，我认为 5 年前的世界似乎没有什么重大风险，因此整个社会共同开展了许多这样的副项目。这些项目未必有什么成效，也没有让任何人变得更快乐。

And now you've got, you know, it's not just Elon doing everything he's doing, but I think everybody feels like they're climbing the ambition ladder. You ship your bad ideas so you can discover your good ideas. And if you want to, you know, build software, great. If you want to build a bridge, you don't have to be a civil architect to know how to do that anymore. So, I really think that we have the makings of a sort of dramatically

如今，不只是 Elon 在做这一切，我认为每个人都感觉自己正在攀登抱负的阶梯。人们必须先实现那些糟糕的想法，才能发现自己的好想法。如果你想开发软件，完全可以去做；如果你想造一座桥，也不必先成为土木建筑师，才能知道该怎么做。因此，我确实认为，我们已经具备了打造一个幸福感大幅提升、

happier, more fulfilled, more productive society. And, you know, and yet we're here talking about permanent underclass.

更加充实、更加高效的社会所需的一切。然而，我们现在讨论的却是永久底层阶级。

I love all of that. That all feels so right. It's so hard to really believe that.

我非常认同你所说的一切，感觉这些观点都非常正确，只是很难真正相信这一切会实现。

But if you actually look at how things have gone so far with the rise of AI, uh unemployment's down, people are making a lot of money. You know, obviously a lot of people are struggling. There's a lot of downsides.

但如果认真观察自 AI 崛起以来的事态发展，就会发现失业率下降了，人们也赚了很多钱。显然，仍有许多人生活艰难，也存在许多负面影响。

Data centers causing problems for people, things like that. A lot of a lot of issues. But it feels like as a economy and as a country, feels like things are going well so far. Like they just almost like cured some kind of cancer the other day. So, yeah.

数据中心给人们带来了问题，类似的问题还有很多。但从经济和国家层面看，目前的一切似乎都进展顺利。例如就在前几天，他们似乎已经基本治愈了某种癌症。

Yeah, you're right. Moderna just did I mean, the fact that Dario can write a blog post and say, "What happens when we cure every disease?" And then we debate it as a serious topic. Like what world are we living in here, you know? Um I also think that we're collectively worried always. Like you know, the the kind of these abstractions, the world, the average worker, the middle manager, the person who lives in the vicinity of

你说得没错，Moderna 刚刚就做到了。Dario 甚至可以写一篇博客文章，提出“如果我们治愈所有疾病，会发生什么？”而我们还会把它当作一个严肃的话题来讨论。我们究竟生活在一个怎样的世界里？我还认为，我们所有人总是在担忧一些抽象概念，例如世界、普通员工、中层管理者，以及住在数据中心附近的

a data center. These are abstractions.

人。这些都是抽象概念。

But our actual lives feel like they're getting more fulfilled, we're more capable, we're more empowered. So, I think that's also something then the revealed preferences tend to show how people are experiencing individually.

但在现实生活中，我们感觉自己变得更加充实，也更有能力和能动性。因此，我认为，这也表明显示性偏好往往反映了人们在个体层面的实际体验。

And the stated preferences tend to show how people are sort of observing it or believe it's playing out societally.

而声明偏好往往反映了人们如何看待这件事，或者认为它会如何影响整个社会。

You know, if you ask people if they want a data center in their neighborhood, most will say no, but if you ask them if they use ChatGPT today, most people will say yes. So, that's kind of the dissonance.

如果询问人们是否希望自家附近建一座数据中心，大多数人都会说不；但如果询问他们现在是否使用 ChatGPT，大多数人都会给出肯定的回答。这正体现了其中的不协调。

And the the obvious issue is that just the PR around AI has not been great.

显而易见的问题是，AI 的公众形象一直不太好。

There's a lot of fear-mongering.

围绕 AI 存在许多危言耸听的言论。

Thoughts on on that? What's going on there? Do you think that all change?

你如何看待这个问题？这种情况是如何形成的？你认为这一切会发生改变吗？

The The most important thing that we can do with AI to change the kind of conversation around it is make important things cheap.

要改变围绕 AI 的讨论氛围，我们能做的最重要的事情，就是让重要的东西变得便宜。

There's two things that are extraordinarily important in America that have only gotten more expensive, right? Health care and education.

美国有两样东西极其重要，却只变得越来越昂贵：医疗和教育。

Um if you look at health care, 45% is administrative.

以医疗领域为例，其中 45% 属于行政成本。

So, if you take a lot of that administrative burden out, you can actually see deflationary health care costs. Also, things like curing every disease, that sounds awesome. You know, GLP-1s, also obviously not an AI thing, but I think is a reason to be optimistic about um deflationary health costs. And then education as well. I think education now has the strongest form of competition, sort of traditional education, that it's

因此，如果能够消除其中很大一部分行政负担，医疗成本实际上就可能下降。此外，治愈所有疾病这样的事情听起来也非常美好。GLP-1s 显然并不是 AI 技术，但我认为，它让我们有理由对医疗成本下降感到乐观。教育领域也是如此。我认为，如今传统教育正面临 200 年来最强有力的

had in 200 years.

竞争。

Um and I think it's going to be very, very good to kind of unbundle learning from institutions. And and and also, by the way, like status from credentials.

我认为，将学习与机构拆分开来会非常有益。此外，也应当将社会地位与学历资质拆分开来。

You know, like you don't need a Harvard degree, you just need to get And that's pretty cool.

你不需要 Harvard 的学位，只需要获得相应的教育。这很酷。

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[音乐] 或团队设置支出限额，并让费用收据自动从 Gmail 或 [音乐] 短信中提取。你甚至可以为 AI 智能体单独发卡，并为其设置专属限额和政策。大多数创始人起初都采用同样的方式。

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I saw OpenAI recently slow down their AI development. They paused Yeah.

我看到 OpenAI 最近放慢了 AI开发速度。他们暂停了对。

their RL kind of phase on their latest model because of what they're seeing.

最新模型的 RL 之类的阶段，因为他们观察到的情况。

So, that's obviously a big concern for people, just how fast and smart these models get. Any thoughts on just that?

所以，这显然让人非常担忧，也就是这些模型变快、变聪明的速度。你对此有什么看法吗？

That's like a big shift now. Instead of race ahead to the fastest, best model ever, okay, we actually have to slow these things down. That feels crazy.

这算是现在的一大转变。以前是争相打造史上最快、最好的模型，现在则是：好吧，我们其实得放慢把这些东西压下来。感觉太疯狂了。

I mean, without commenting on OpenAI specifically, I think that um maybe I'm a little skeptical on some of these things where I think the kind of the aura that Anthropic got from having a model that was too dangerous to release was extraordinary. And maybe they had a GPU shortage. Now, maybe it was you know, the capabilities were more advanced than they actually wanted. You know, maybe they actually wanted to keep

我的意思是，先不具体评论OpenAI，我觉得，嗯，也许我对其中一些事情有点怀疑，因为我觉得，某种程度上，Anthropic因为有一个危险到无法发布的模型而获得的光环非同寻常。也许他们当时缺GPU。当然，也可能是，你知道，模型的能力比他们实际想要的更先进。你知道，也许他们其实想把

that proprietary model internal to extend their own lead. So, I think there's a lot of sort of confounding factors that would cause you to pull back a little bit. Look, I do take the points about offensive cyber seriously, which is we should harden all of our systems before we make them trivial to penetrate. Um but I think the sort of concept of the model that's too dangerous to release, it it kind of

那个专有模型留在内部，以进一步扩大自己的领先优势。所以，我觉得这里面有很多相互混杂的因素，会让你稍微收一收。听着，我确实认真看待关于进攻性网络攻击的观点，也就是说，我们应该加固所有系统，然后再让攻破它们变得轻而易举。嗯，但我觉得，这种“模型危险到无法发布”的概念，其实有点

conflates marketing, um inference capacity, and then also economic considerations like do you want to externalize your competitive advantage or use it to make yourself better?

把营销、嗯，推理算力，以及经济层面的考量混为一谈，比如你是想把自己的竞争优势对外开放，还是用它来让自己变得更强？

Yeah, I always think about that when I have folks from Anthropic and and open AI on the podcast just like how an advantage they have when they have the best model. It's crazy, right? Just like that's a loop right there is just have the best model for longer and they can move so much faster.

对，每次请Anthropic和OpenAI的人来播客时，我都会想到这一点，就是他们拥有的优势有多大，尤其是当他们拥有最好的模型时。太夸张了，对吧？就像这本身就是一个循环：只要把最佳模型的地位保持得更久，他们就能快上太多。

It's crazy though, you know, to take the other side for a moment, like it felt like Anthropic was unassailable and now open AI has had an amazing 6 months and open weights are also ripping. So, despite the like the sort of scary concept of this like you know supremely intelligent model that's totally proprietary to one company, the so far the kind of industry trends haven't played that way at all.

不过这也挺疯狂的，你知道，暂且站在另一边想想，之前感觉Anthropic简直不可撼动，可现在OpenAI在过去6个月里表现惊人，开放权重模型的势头也非常猛。所以，尽管这种想法有点吓人，也就是，你知道，有这么一个极其智能、完全由一家公司专有的模型，但到目前为止，行业趋势完全没有朝那个方向发展。

Yeah, like Grok bot just came out of nowhere and is now like the most amazing AI kind of assistant tool. I'm just hooked on it.

对，就像Grok bot突然横空出世，如今成了最惊艳的AI助手类工具。我简直用上瘾了。

Oh man, I mean we should talk about the personal agent thing. Like actually the three big products that I love here, Grok bot totally nailed it. And also the model underneath it is awesome, right?

哦天哪，我是说，我们应该聊聊个人智能体这类东西。其实我最喜欢的三款产品，Grok bot 完全做对了。而且它底层的模型也很棒，对吧？

They came out of you right out of left field. Um and that's I know a lot of the good work that Chris or team did. I think ChatGPT work it's kind of buried in the UI, but it's really really good.

他们的出现完全出乎你的意料。嗯，我知道这背后有很多是 Chris 或其团队的出色工作。我觉得 ChatGPT Work 有点藏在UI 深处了，但它真的非常非常好用。

It's one of the best products they've released. And then there's a a startup that's really getting some buzz called Instinct, which has made some more aggressive and interesting trade-offs, but all in the same domain.

这是他们发布过的最佳产品之一。另外还有一家初创公司最近很受关注，叫Instinct，它做出了一些更激进也更有意思的取舍，不过都属于同一个领域。

That's amazing. I I don't know if it was a strategy for some ran someone tweeting this vague tweet about how awesome it is and everyone's like, "What the hell are you talking about?"

太厉害了。我不知道这是不是某种策略，让某个人发了一条语焉不详的推文，说它有多么惊艳，然后所有人都在问：“你到底在说什么？”

That was really effective. Cuz it was like, "Where did you get that?" Uh chat GPT work the episode that will come out right before this is the PM in charge of that Atara.

这招真的很有效。因为大家都会问：“你从哪儿弄到的？”呃，关于 ChatGPT Work 的那期节目会在本期之前播出，嘉宾就是负责它的产品经理 Atara。

Oh, really?

哦，真的吗？

Yeah.

对。

Oh man, they they did such a good job on it. It's really I don't know how much you use it, but it's really well done.

哦天哪，他们真的做得太好了。它真的……我不知道你用得多不多，但确实做得非常好。

What is the what is it better than co-work there? Is it that that it runs in the cloud? Is that the big differentiator?

它比 Cowork 好的地方是什么？是因为它运行在云端吗？这是它最大的差异化优势吗？

It runs in the cloud. It does a good job of kind of caching browser credentials.

它确实运行在云端。而且在缓存浏览器凭据方面做得很好。

Though it's not as aggressive as Grok or Instinct. And it also the remote feature, it's got the full deep duplex voice mode. So you can actually just call it. It it can see all your threads and you can just talk to it and say, "Hey, what's happening across all my coding agents, across this? Can you change that?" So, it's just because the full duplex voice is so good, you really feel like you're calling your assistant

不过，它不像 Grok 或Instinct 那样激进。它的远程功能还配备了完整的全双工语音模式，因此你可以直接打电话给它。它能看到你的所有对话线程，你可以直接问它：“我所有的编程智能体目前分别进展到哪里了？这个地方能改一下吗？”全双工语音的效果非常好，确实会让人觉得自己是在给助理打电话。

who knows everything that's happening in your world, whereas with Grok, it's a sort of one-way transcription.

它了解你工作中正在发生的一切；相比之下，Grok 更像是某种单向转录工具。

Right? Or with some of the other assistants, it's a text. So, the voice plus the kind of model of it can see all threads is really well done.

至于其他一些助手，采用的则是文本交互。语音功能与能够查看所有内容的模型结合起来，效果非常出色。Threads 在这方面确实做得很好。

Awesome. Okay, I'm going to come back to this AI assistant consumer stuff, but something I wanted to kind of close the thread on. I feel like there's in terms of jobs and the economy as a result of AI, I see it almost as the spectrum of there's like the Dario end of the spectrum of 50% of knowledge work will be disrupted and we're all going to have massive unemployment to like the Sachs, David Sachs spectrum of like it's going

太棒了。之后我会再谈AI 助手这类消费产品，不过我想先结束刚才的话题。关于AI 对就业和经济的影响，各种观点几乎构成了一条光谱：一端是 Dario，他认为50% 的知识工作会受到冲击，而且我们都会面临大规模失业；另一端则是 Sacks，David Sacks 认为未来会

to be incredible.

非常美好。

Jobs are going to be fine. So far, everything is pointing in the good direction. Clearly, you're closer to the Sachs direction. Is there anything else just along the lines that you think might make people feel better about jobs in the future?

就业不会出现问题。到目前为止，一切都在朝着好的方向发展。显然，你的观点更接近Sacks 那一端。关于这个问题，你是否还有其他理由，可以让人们对未来的就业更加安心？

I mean, I think that the entire trend of human existence has been that our desires grow faster than our ability to fulfill them.

我认为，人类发展的整体趋势一直是：我们的欲望增长得比满足欲望的能力更快。

Um if you look at the things that are expectations today, they were unimaginable luxuries 500 years ago, even 50 years ago for things like therapy, right? Or things like antibiotics 100 years ago, right? I mean, didn't matter how rich you were, you simply didn't have access to it. So, I think we're underestimating um human ambition, human desire. You know, people are going to be mad that they don't have

看看今天那些已经被视为理所当然的事物，它们在500 年前是难以想象的奢侈品，甚至在 50 年前也是如此，例如心理治疗。再比如100 年前的抗生素，无论多么富有，都无法获得。因此，我认为我们低估了人类的抱负和欲望。20 年后，人们会因为自己没有

a vacation home in Mars in 20 years.

火星度假屋而生气。

Like really mad, like this really mad.

他们真的会非常生气。

They'll be seeing it on Insta and be like, "Come on, babe. We got to like work harder and make this happen." Every CEO is going to want to build a much bigger company. So, don't they already, it feels like we're living a much larger form of sort of human existence than we could have imagined 100 years ago?

他们会在 Insta 上看到别人展示自己的火星度假屋，然后说：“拜托，亲爱的，我们得更努力，想办法实现这个目标。”每个CEO 都会想打造一家规模大得多的公司。不过，他们现在不就已经如此了吗？如今人类生活的丰富程度，远远超出100 年前的人所能想象的范围。

And there's no reason that trend won't continue or accelerate.

没有理由认为这一趋势不会延续，甚至不会加速。

This idea of ambition, I was I'm glad you even brought that word up again.

说到抱负，我很高兴你再次提到这个词。

It's something that's coming up a lot on this podcast. That not only is AI making it easy to be a lot more ambitious, it's almost making us have to be more ambitious because everybody else can just do all the easy stuff now.

这个话题最近经常出现在这档播客中。AI 不仅让人们更容易胸怀远大抱负，几乎还迫使我们变得更有雄心，因为现在其他人都能轻松完成那些简单的事情。

And now what separates us is just how big can you go? Okay, I'm going to make a personal website. Okay, it's cool.

现在真正拉开差距的，只在于你能做到多大的规模。例如：“我要做一个个人网站。”这很不错。

It'll be this white simple background.

这个网站会采用简洁的白色背景。

No, okay, I'm going to make it this 3D game where you have to like walk through a world and discover all the things that you like everything is just getting more epic. Uh thoughts on just this idea of ambition becoming a bigger, I don't know, scale and habit.

不，我要把它做成一款 3D游戏，让人们在一个世界里四处走动，发现自己喜欢的一切。所有事情的规模都变得越来越宏大。你如何看待雄心不断变得远大这件事？无论规模还是习惯，都在升级。

A lot of things get conflated because when you and I say ambition on this pod, I think people have a very specific idea of what that ambition is, you know?

很多事情都被混为一谈。当你我在这期播客中谈到雄心时，人们对这种雄心往往有一个非常具体的概念。

Ambition to be a founder, ambitious to build a beautiful software product. Like those are types of ambition, but there other types of ambition. Let's talk about creative ambition. You know, when you're five, nobody says, "Lenny, you're good at painting, but you're bad at drawing." You know, you just have an ambition or a desire to make something and you make it. Like that's something that's very unique and can now actually

例如，成为创始人的雄心，或者打造一款精美软件产品的雄心。这些都是雄心的类型，但雄心还有其他形式。我们可以谈谈创作上的雄心。当你五岁时，没有人会说：“Lenny，你很会画油画，但不擅长画素描。”那时，你只是怀有创造某种事物的愿望，然后便付诸行动。这是一件非常独特的事，而且现在确实可以

be encouraged.

得到鼓励。

You know, think of a very local ambition. So, you know, they have the NHS in the United Kingdom. I think it's a sort of treasured institution that's not working well. Maybe the way AI shows up in their society is making like the NHS as good as the iPhone. Right? That's very specific and local to them. Or simply the ambition to be more connected to our family, to be more present parents. So, the ambition doesn't have

还可以设想一种高度本地化的雄心。例如，英国有NHS。我认为，它是一个备受珍视但运作不佳的机构。也许 AI 在英国社会中的具体体现，就是把NHS 做得像 iPhone 一样好。这对英国人而言非常具体，也非常本地化。雄心也可以只是更亲近家人，或者成为一名更全心陪伴孩子的父母。因此，雄心不一定

to be sort of ambition in the narrow economic sense. It can be really anything that we want to do more of and who doesn't have that in their bones?

非得是狭义经济层面的雄心。它可以是任何我们想要投入更多精力去做的事情。每个人的内心深处都有这种渴望。

Yeah, that's such like my example is so dumb now that I think about it. Like the It feels like the thing we have to uh unblock in our brain is like, "Okay, AI, solve cancer."

现在回想起来，我举的例子确实很愚蠢。我们需要打破的思维障碍，是敢于这样设想：“让 AI 解决癌症。”

We're not We're not like Like that's where we can start to think now and it's so unnatural to us, especially as product people that always have to think about the MVP and the constraints. Now we have to think big.

这并不是说 AI 已经能够解决癌症，而是说我们可以开始朝这个方向思考。目前，这种思维方式对我们而言还很不自然，尤其是对那些总要考虑 MVP 和各种限制的产品人来说。现在，我们必须大胆设想。

Okay, what can What's the big What's the 10x the 1000x version of this?

那么，这个宏大构想放大 10 倍、1000 倍后，会是什么样？

Yes. I know, right? In a way we have to think small because this thing that we've all Our whole lives have been built around how precious software and intelligence is, and now it's totally not precious. Like that probably will be a harder change for you and I.

是的。某种意义上，我们必须从小处着眼。我们这一代人所处的世界，建立在软件和智能无比珍贵这一前提之上，而现在，它们已经完全不再珍贵。对你我而言，这种转变可能更难适应。

Yeah. So, like all these new little habits uh I think a lot about on the Claude code team, they have a principle.

是的。谈到这些新的小习惯，我经常会想到 Claude Code 团队的一条原则。

Uh you know what's better than me doing it? It's Claude doing it.

有什么比我亲自做更好的方式？让 Claude 来做。

And that just created this habit in everyone on the team. How do I help Claude do this thing for me? And I feel like that's a thing we all have to start to build in our head. And And Grok Bot's really good at that. Like and not an investor not no affiliation, but it's just like so simple and good at this stuff.

这让团队中的每个人都养成了一个习惯：我该如何让 Claude 替我完成这件事？我认为，我们所有人都需要开始建立这种思维。Grok Bot 在这方面确实非常出色。我不是它的投资人，与它也没有任何关系，但它使用起来非常简单，而且特别擅长处理这类事情。

I also think that there is so much learning that happens through doing. You know, it's funny, if you look at the number of people that are talking about vibe coding versus the number of people that are talking about their projects, people are a little embarrassed. I'm a little embarrassed to talk about a lot of my projects cuz they don't seem important or substantial enough. But so much of it is learning through execution

我还认为，很多东西只有在亲手实践的过程中才能学会。比较一下讨论氛围编程的人数和讨论自己项目的人数，会发现大家多少都有些不好意思。我也不太好意思谈论自己的许多项目，因为它们似乎不够重要，也不够有分量。但事实上，很多东西都需要通过实际执行来学习。

or shipping or or being fulfilled through execution and shipping. Like I don't think we can underestimate that either, you know.

这些经验也可以通过发布来获得。换言之，执行和发布本身就能带来满足感。我认为这一点同样不容低估。

I have a guest post coming together from uh someone at Google that works on a lot of their lab stuff. And I don't want to give away the the goods, but just broadly her concept is that building is now the new reading where you build to learn and infuse and experience, and it's totally okay for most of it to go throwing away because that's still it it building your your muscle, you know.

我正在筹备一篇客座文章，作者是 Google 的一位员工，参与过他们的许多实验室项目。我不想提前透露文章的精华，但概括而言，她的观点是：构建已经成为新的阅读方式。人们通过构建来学习、吸收和体验。即使其中大部分成果最终被丢弃，也完全没有关系，因为这个过程仍然能够锻炼人的能力。

So well said. Yeah, it's uh building as an activity rather than an outcome.

说得很好。应当把构建视为一种活动，而不是一种结果。

Right.

没错。

Yeah.

是的。

Which I think a lot of people feel bad.

我认为，很多人会因此感到沮丧。

I shipped all these things, but no one's using it or ever use it. And I think that the key here is like that's actually okay, and that's totally fine.

他们发布了许多东西，却没有人使用，甚至可能永远都不会有人使用。但关键在于，这其实没有关系，完全不是问题。

Oh man, I mean and it happens in every other domain, you know? Like I make a DJ set and like three people listen to it, and I listen to it a hundred times.

这种情况在其他每个领域都会发生。例如，我制作了一套打碟混音，可能只有三个人听，而我自己会听上一百遍。

And it's like very fulfilling. It doesn't matter.

这件事本身就非常有满足感，是否有人收听并不重要。

Mhm. Uh we're going to talk about your DJ stuff later.

我们稍后会谈谈你的打碟经历。

Okay. Okay.

好。好。

[laughter] Okay, let's come back to consumer stuff.

[笑声] 好，我们回到消费领域的话题。

So, you focus on consumer at A16Z.

你在 A16Z 专注于消费领域。

What's kind of like what's happening in consumer these days? What's kind of like the landscape? What are you excited about?

如今，消费领域出现了哪些新动向？整体格局如何？你对哪些方向感到兴奋？

So, I think there's three big areas.

我认为主要有三大领域。

We're very early as we kind of discussed. You know, the labs have done a good job, but there aren't as many sort of independent mass market consumer products. Um coding agents are awesome, and I think a total lightning bolt. You know, I think it's easy to say most people don't want to make code, but the the big change in my thinking is that coding agents are a way to interact with the world generally. And you've seen a

正如我们刚才讨论的，目前仍处于非常早期的阶段。基础模型实验室发展得不错，但市面上还没有太多独立的、大众市场消费产品。编程智能体非常出色，我认为它们犹如一道惊雷。人们常说，大多数人并不想写代码，但我的观念发生了重大转变：编程智能体其实是一种与整个世界互动的方式。这种变化已经有所显现。

lot of this on X. You know, people use Claude code to edit videos, you know, or Codex to you create a game that they play with their kid on an airplane ride.

在 X 上已经可以看到许多这样的例子。人们会用 Claude Code 剪辑视频，或者用 Codex 创建一款游戏，以便在乘飞机时和孩子一起玩。

Like there it's sort of this general problem-solving tool that consumers can use in very unique ways. Um you know, and and probably the best example company that we've invested in is Wabi, where it's sort of a platform for mini apps. People can create them, consume them, share them. So, coding agents is one big area I think that's important.

它在某种程度上是一种通用的问题解决工具，消费者可以用非常独特的方式使用它。在我们投资过的公司中，最好的例子可能是 Wabi。它类似于一个迷你应用平台，人们可以创建、使用和分享这些应用。因此，我认为编程智能体是一个非常重要的发展方向。

Personal agents, we had this credible moment around Open Claude, but guess what? Open Claude is a dev thing, you know? And Hermes, of course, and Multibook. Like all of that is now getting distilled into mass market consumer and enterprise agents that people understand, which is what we discussed previously. And then the last is I'm going to call it entertainment, but that doesn't fully do it justice. Um

第二个领域是个人智能体。Open Claude 前段时间确实引发了轰动，但 Open Claude 是面向开发者的产品。此外还有 Hermes 和 Multibook。如今，所有这些产品都在被提炼成面向大众市场的消费级和企业级智能体，使人们能够理解我们之前讨论过的内容。最后一个领域，我姑且称之为娱乐，但这个词并不能完全概括它。

I think that it's a lot of sort of creative tools. You know, Suno has done such an amazing job. It's companionship products. Um all of that that entire area is, you know, uh uncomfortable to talk about, so I think it's under discussed, but there's some huge fast-growing products there. So, I think those are the three big areas that we're watching right now.

这个领域包含许多创意工具，Suno 就做得非常出色。此外还有陪伴类产品。谈论整个领域可能会让人不太自在，因此我认为它并未得到充分讨论，但其中已经出现了一些规模庞大、增长迅速的产品。这就是我们目前关注的三大领域。

That's really interesting. Just thinking of it these three buckets. Coding agents, AI assistants, kind of Open Claude, but much simpler and easier and more reliable.

这确实很有意思。可以将其归纳为三类：编程智能体、AI 助手，以及类似 Open Claude 但简单得多、更易于使用也更可靠的产品。

Uh sounds like basically the three described there that you're excited about are um Instinct, uh Grok Bot, and and ChatGPT work.

听起来，你提到的三个令你兴奋的方向基本上就是 Instinct、Grok Bot 和 ChatGPT work。

That's right.

没错。

And then Wabi, I guess, would fit in that first one. It's like a personal coding agent that can build whatever you want for you.

我猜 Wabi 应该属于第一类。它就像一个个人编程智能体，可以替你构建任何想要的东西。

Yes. Yeah, that's exactly right. Yeah.

对。是的，完全正确。对。

And then entertainment is the third bucket. Like like AI girlfriends and that kind of stuff, right? Yeah, there's companies it's like crazy. You look you guys put out these market maps and like five of them are these different like companions.

娱乐则属于第三类，比如 AI 女友之类的产品。这方面的公司多得惊人。你们发布的市场版图中，大概有五家提供各种不同类型的陪伴产品。

Though though actually to be accurate is more boyfriends and girlfriends actually, you know.

不过，准确地说，其中更多是男友和女友类产品。

Um the majority of people using companion products are women that are in their 40s and 50s actually.

使用陪伴类产品的大多数人其实是四五十岁的女性。

Interesting. Mhm. Okay, cool. So So those are the three kind of areas you think the biggest opportunities will come from?

很有意思。所以，你认为最大的机会将来自这三个主要领域？

And it's interesting that they connect to this idea of loop. I don't know, make me happier. Like Like they Yeah, these are kind of These are kind of like the jobs to be done for humans. Make me happy. Uh make me healthier. Make me live longer. That kind of stuff.

有意思的是，它们都与循环这个概念有关。我也无法准确描述，或许可以说是让我更快乐。某种意义上，这些就像人类有待完成的任务：让我快乐，让我更健康，让我活得更久，诸如此类。

Yes. Yes, give me a channel for my ambition, a channel for my sort of fulfillment, and then a thing to do when I'm not doing everything else.

对，既要为我的抱负和成就感提供一个出口，也要让我在不做其他事情时有事可做。

Mhm. That makes sense.

嗯。说得通。

Okay.

好。

The other question I have for you along these lines is there's so many companies and so many startups, so many products everyone's launching. The speed at which companies and products are shipped is like thousand x-ing. How do you think about durability and moats when you look at a startup? Because a lot of founders get that question. Everyone's getting that question. How am I not a rapper?

顺着这个思路，我还有一个问题想问你。现在有太多公司、初创企业和产品不断涌现，公司创立和产品上线的速度简直提升了千倍。在评估一家初创企业时，你会如何看待其持久性和护城河？很多创始人都会被问到这个问题，几乎所有人都要回答：我怎样才能不只是一个套壳产品？

What are What are signs that tell you this might be a durable thing?

哪些迹象会让你认为它可能成为一项持久的业务？

Well, I think there's two important ideas. One is something that um Jesse from Decagon said, which I love, and that is that moats are most often discovered, not designed.

我认为这里有两个重要观点。其一是 Decagon 的 Jesse 说过的一句话，我非常喜欢：护城河往往是发现的，而不是设计出来的。

I think it's really easy, I've done this as a founder, to get in your own head about like hey, I need a business plan that survives scrutiny from MBAs and VCs. I've got to have some really sophisticated, you know, idea of what my moat will be. And for that team, they just started shipping and it developed over time. Another great example of this is Cursor. You know, they were criticized a lot for not having a moat,

人们很容易陷入这种状态，我担任创始人时也是如此：在脑海中反复纠结，认为自己需要一份经得起 MBA 和风险投资人审视的商业计划，也必须对未来的护城河形成一套非常复杂精妙的构想。而那个团队只是开始不断推出产品，护城河便随着时间逐渐形成。另一个很好的例子是 Cursor。他们曾因缺乏护城河而饱受批评。

but it turned out that initially being a high-end PSD AU product was really good.

但事实证明，最初做成一款高端 PSD AU 产品其实非常不错。

And over time they captured all the reasoning traces, they trained their own models, the composer one two models, and you know, so on and so forth. We know how that story plays out. So, moats can be discovered. They don't have to be designed is one. And then, I think the other is that we seem to have forgotten that the classic moats, none of the classic moats are based on how hard it is to make the software.

随着时间推移，他们收集了所有推理轨迹，训练了自己的模型，也就是 Composer one two 模型，随后还有许多类似进展。我们都知道这个故事后来如何发展。因此，护城河可以在发展过程中被发现，并不一定要预先设计出来。这是第一点。另一点是，我们似乎已经忘记，经典护城河没有一种取决于软件的开发难度。

You know, like we're not building self-driving cars. Most of us aren't.

我们并不是在制造自动驾驶汽车，至少大多数人都不是。

So, it's network effects, it's scale advantages, it's brand effects, proprietary sort of data or what was historically called a cornered resource.

这些经典护城河包括网络效应、规模优势、品牌效应、某种专有数据，或过去所谓的独占资源。

Every moat from 5 years ago generally is still a good moat. We just need founders that have ambition in those directions.

5年前的各种护城河，总体而言现在依然是很好的护城河。我们只是需要有志于朝这些方向发展的创始人。

We need more multiplayer products. We need consumer social. We need products that get dramatically better the more you use them like town. Um so on and so forth.

我们需要更多由多人参与的产品，需要面向消费者的社交产品，也需要那些使用得越多就会变得越好的产品，比如 town 等。

So, still read Hamilton Hamilton Helmer and uh all that stuff still applies.

所以，还是要读 Hamilton Helmer，而且其中的内容依然适用。

Yes. Love this book.

对，我很喜欢这本书。

Yeah, he's been on the podcast.

是的，他来过这档播客。

He has?

真的吗？

Yeah.

是的。

Maybe I missed that. Yeah. I feel like there's only five real business books in the world. Every other one is uh in the business of selling business books. And they're fake. And his uh his is on my list of five.

可能是我错过了。我认为，全世界真正的商业书其实只有五本，其他每一本都是为了销售商业书而写的，而且内容都是假的。他的书就在我的五本书名单里。

Are there any other in this list that come to mind real quick or anything?

这份名单里还有其他你立刻能想到的书吗？

The two that are so obvious are High Output Management. Which is like that is as good as it ever was. And then, Ben's book, you know, Hard Things is it was the first emotionally honest book about business that was ever written.

最显而易见的有两本。一本是《High Output Management》，时至今日依然十分出色。另一本是 Ben 的《Hard Things》，它是有史以来第一本在情感上如此坦诚地讲述商业的书。

And that's why founders love it. That's why I love it. Cuz you read it and you're like, "Wow, I'm not the only one that's, you know, anxious and feels like a failure and can't tell anyone what I'm going through." Ben went through it, too.

因此，创始人会喜欢它，我也会喜欢它。阅读时，你会意识到：“原来不只我一个人会焦虑，会觉得自己很失败，也无法告诉任何人自己正在经历什么。”Ben 也经历过这一切。

Mhm. Two of the most mentioned books on this podcast, turns out.

这两本书恰好也是这档播客中最常被提到的书。

That's a surprise.

真没想到。

So, so on this moat idea. So, say you're a founder and you're just like, you know, you're putting a pitch together trying to pitch you uh or other VCs. What's the best way to talk about a moat? Is it like Can you just say, "We're going to discover it.

继续谈护城河这个概念。假设你是一位创始人，正在准备一份融资推介材料，打算向你或其他风险投资人进行推介。谈论护城河的最佳方式是什么？是否可以直接说：“我们之后会找到它。

We're not sure. Nobody really knows yet."?

目前还不确定，其实还没有人知道。”

Yeah, I think that we would happily take a bet on a product that doesn't have a quote-unquote moat or durability story if it has, you know, a lot of momentum, a lot of craft, a lot of, you know, sort of growing engagement. So, actually the thing I've learned over the years, I used to be very worried about people stealing my idea, but I've learned in that the big ideas are always supported by a dozen small

是的。即使产品还没有护城河，只要它势头强劲、经过精心打磨，而且用户参与度不断提升，我们也很乐意押注，而不必已经具备所谓的“护城河”或持久性叙事。这些年来，我认识到了一点：过去我特别担心别人窃取我的创意，但后来我明白，一个大创意背后总有十几个

ideas that are invisible. And even if somebody replicates your big idea, they they never see the small ideas that make the big idea work. So, I actually think that there's some there's some just something special in the water with certain products that make them incredibly successful despite extraordinary competition. I mean, look at Granola. You know, 2 years ago, it was really criticized and I don't know

看不见的小创意作为支撑。即使有人复制了你的大创意，也永远看不到那些让它真正奏效的小创意。因此，有些产品仿佛拥有某种特殊的魔力，即使面对异常激烈的竞争，依然能够取得巨大成功。以 Granola 为例：2 年前，它饱受批评，而我也不确定

that they have a super strong durability story today and yet it is like beloved and dominant.

如今它是否拥有特别有说服力的持久性叙事，但人们就是非常喜欢它，而且它占据着主导地位。

So, they you know, you sort of I listen to like what the customers are saying more than, you know, what the what the business books say.

因此，比起商业书籍的观点，我更愿意听取客户的看法。

You get a free year of Granolas become a subscriber to Lenny's newsletter. I'm going to I should do this more often when it's part of this product pass.

只要成为 Lenny newsletter 的订阅者，就能免费使用 Granola 一年。我以后应该多提及这件事，因为它是这个 Product Pass 的一部分。

Lenny's product pass.com. You get a free year of all these amazing products including Granola.

Lenny's product pass.com。你可以免费使用所有这些优秀的产品一年，其中就包括 Granola。

I just saw Ramp put out a report of the fastest growing companies according to their data and Granola is like number two or three.

我刚看到 Ramp 发布了一份报告，根据其数据列出了增长最快的公司，Granola 好像排在第二或第三位。

It's a tremendous product. It's the craft is is really high.

这是一款非常出色的产品，打磨水准确实很高。

Yeah, and then that I think about that a lot these days because there's so much like there's co-work, there's ChatGPT work, there's cursor, there's grokbot and it's crazy how quickly one can switch from one to the other. And the underlying model is not that different. All it really is most of it is the harness and slash UX of the product. And so to me that tells you there's so much opportunity in the

是的，这也是我最近经常思考的问题。现在有太多这类产品，例如 co-work、ChatGPT work、Cursor、grokbot，而用户能以如此快的速度从一个产品切换到另一个产品，实在令人惊讶。它们的底层模型其实并没有太大差别，真正的差异大多在于产品的外层框架和／或 UX。在我看来，这说明实际的用户体验很有可能

actual user experience being a moat or at least giving a lot of time to find something that is durable.

成为护城河，或者至少能为寻找持久性优势提供基础。

100% and I think for the people that are at the edge, they pay for all of them because they all have their respective areas of specialization.

完全同意。对于那些走在前沿的人来说，他们会为所有这些产品付费，因为每款产品都有各自擅长的领域。

Yeah, I have many $200 a month plans right now.

是的，我现在订阅了多个每月 $200 的套餐。

I know. I know, right?

我知道，确实如此。

So, it's a little painful, but yes, me too.

所以，这确实有些肉疼。不过没错，我也是如此。

And I think Cursor has a $300 a month plan now.

我认为 Cursor 现在有一个每月 $300 的套餐。

So does Grok. Oh yeah, you're right.

Grok 也有。你说得没错。

Yeah, that was the Grok one. It's pretty with Grok heavy.

对，那是 Grok 的，很像 Grok Heavy。

RIP. Yeah, RIP Cursor. I think they've transitioned away from that brand.

安息吧，Cursor。我觉得他们已经不再使用那个品牌了。

Um, something I've been talking a lot about is the is the distribution.

我经常谈到的一件事是分发。

I call it distribution's new moat, but it's like it's always been a moat, but it feels like more and more that is actually a massive advantage because everybody is There's like a thousand launch videos a day.

我称之为“分发是新护城河”。其实，分发一直都是护城河，只是它如今越来越像一项巨大的优势，因为每天大概有一千个产品发布视频。

Everyone's launching launch launch launch. And really the ability to get your stuff into people's atten- into people's feed, get them continue to be reminded your product exists feels like increasingly is powerful and important. Thoughts on the rising value of distribution existing distribution being a big lever for growth and success.

每个人都在不断发布产品。真正重要的是，你能否让自己的产品进入人们的视野和信息流，不断提醒他们这个产品依然存在。分发似乎正变得越来越强大和重要。你如何看待分发价值的上升，以及现有分发渠道成为推动增长与成功的一大杠杆？

This is so important and you know, I asked Chris Dixon about this um, because he sort of author- authored the famous come for the tool stay for the network.

这太重要了。我曾就此询问 Chris Dixon，因为正是他提出了那句著名的“因工具而来，为网络而留”。

I think the issue is that our entire generation of founders and CEOs were trained on the theory of networks and network building.

我认为，问题在于我们这一整代创始人和 CEO 接受的都是网络理论与网络构建方面的训练。

And as a result, every network that exists today is hyper trained to ensure no one else builds a network on their network.

结果是，如今存在的每一个网络都对此高度警觉，确保没有其他人能在自己的网络之上构建另一个网络。

So I actually think that the sort of network effect has gone back to this grassroots like true word of mouth. When somebody is getting a ton of mentions on X and on YouTube and on Instagram and all these places organically, that is probably the best form of the sort of third-party network effect that you can hope for today. And actually just like the Web 2.0 era, unlike the mobile era where you had the App Store and you had

因此，我认为这种网络效应已经回归草根式的真正口碑传播。当某个产品在 X、YouTube、Instagram 以及其他平台上自然获得大量提及时，这可能就是如今所能期待的最佳第三方网络效应。事实上，这种情况更像 Web 2.0 时代，而不同于移动互联网时代；在移动互联网时代，有 App Store。

growth hacking and you had all of these sort of, you know, little cottage industries, we have to kind of build our own channels off of that word-of-mouth growth. So in a sense, it's a it's a purer growth problem but a harder one than we've had in a couple of product cycles.

当时还有增长黑客以及各种小型配套产业，而现在我们必须依靠口碑增长，自行建立渠道。从某种意义上说，这是一个更纯粹的增长问题，但也比过去几个产品周期中的增长问题更难解决。

And to get word of mouth, you need to build something. I always think about Seth Godin's line, build something remarkable.

要获得口碑，就必须做出一些东西。我总会想到 Seth Godin 的那句话：做出一些值得谈论的东西。

Something that people that is worth remarking about. Which is basically, you know, build an amazing product that people want to talk about. Which is a and you know, a very hard to do. And it makes sense that because there's so much happening, people are just going to pay attention to what are my friends using saying is worth paying attention to.

也就是做出值得人们谈论的产品。你必须打造一款出色的产品，让人们愿意谈论它。这非常难做到，但也很合理，因为正在发生的事情实在太多了，人们只会关注自己的朋友正在使用什么，以及他们认为什么值得关注。

Well, I you know, here's the one thing I would say that the here's the hopeful point, which is I always say that nobody has a growth problem these days, they have a product problem.

这里仍有一点值得抱有希望。我总是说，如今没有人面对的是增长问题，他们面对的是产品问题。

I mean, the reason for that is like you can build such a wildly ambitious product in any direction, you know, functional or emotional.

原因在于，无论选择哪个方向，你都可以打造极具雄心的产品，无论是在功能上还是情感上。

You can charge a lot of money for it.

你可以为这样的产品收取高昂的费用。

So, my challenge is like, "Hey, is it that you have a growth problem or is it a failure of our collective imagination?

因此，我会追问：“你面对的究竟是增长问题，还是我们集体想象力的匮乏？

You know, if we imagined our product cost a thousand dollars a month, ten thousand dollars a month, like what if our product was a software Birkin bag?

设想一下，如果我们的产品每月收费一千美元或一万美元，会怎么样？如果我们的产品是软件界的 Birkin 包，又会怎么样？

What would it have to do to justify that? Okay, let's figure out how we build that."

它必须做到什么，才能配得上这个价格？那么，我们就设法把它做出来。”

And it comes back to the ambition question.

这又回到了雄心的问题。

Yes. And still though, you still need some advantage to get in front of people, to get it out there, at least initially, because there's like a thousand things launching every day. Imagine that's still a big opportunity and and I don't know, advantage, which to me make me feel like incumbents have a huge advantage. They have a their products, they can tell you, "Hey, go use Gemini."

对。不过，你仍然需要某种优势，才能出现在人们面前并推广产品，至少在初期如此，因为每天都有上千种产品发布。这仍然是一个很大的机会。就分发而言，在我看来，现有企业拥有巨大的优势。他们有自己的产品，可以直接告诉你：“去用 Gemini。”

And every time you go search Google. I guess Do you think Do you feel like that? Do you feel like it's harder for startups now because of this distribution challenge?

每次你使用 Google 搜索时，都会接触到这类推广。你也这样认为吗？你是否觉得，仅仅因为这个分发难题，如今初创公司的处境变得更困难了？

I don't know. I I think it's easier because like Gemini, despite all the kind of heavy cross-selling Google has done, nobody would say they're winning.

我不确定。我认为如今其实更容易了。以 Gemini 为例，尽管 Google 进行了各种大力的交叉推销，但没有人会说 Google 正在胜出。

Um you know, startups can build in directions that incumbents are uncomfortable building in, like everything we talked around companion, but there's many others.

初创公司可以进入现有企业不愿涉足的方向，例如我们刚才围绕陪伴讨论的那些产品，除此之外还有许多其他方向。

It's true.

确实如此。

You know, prices can be pretty high.

价格可以定得相当高。

Like people are open to paying 200 a month for their enterprise, they're open to signing million-dollar ACV contracts without really knowing what they're getting. So, I think like the kind of the floodgates are open. It feels like Christmas 2009, where everybody got their iPhone and wanted to download new apps. You know, that'll change at some point. People will feel like they you know, they're done and they're tired and

例如，人们愿意每月为企业版支付 200，也愿意签下 ACV 达百万美元的合同，即使根本不知道自己会得到什么。因此，我认为闸门在某种程度上已经打开了。这就像2009年圣诞节，每个人都拿到了自己的 iPhone，都想下载新的应用。这种情况总有一天会改变，人们会觉得已经够了，也感到疲倦，

they don't want to try any more apps, but the windows are open for now. I think it's easier for startups.

不愿再尝试更多应用。但眼下这个窗口仍然敞开着，我认为这对初创公司更有利。

That's a really interesting insight and your line about how it's not a distribution or growth problem, it's a the problem, is such an important one.

这个洞见很有意思。你提到这不是分发或增长问题，而是一个……的问题，这一点非常重要。

Because if your product was that good, people would talk about it and share it and use it.

因为如果产品确实足够好，人们自然会谈论、分享并使用它。

And it can be. I mean, what are the wild social experiments that we're going to see with this technology kind of intermediating them?

事实也确实可能如此。我们将会看到哪些疯狂的社会实验出现？这种技术又会以何种方式介入其中？

Um You know, I think a lot about actually, here's a fun example from a few years ago. Have you heard of MSCHF? You know MSCHF?

我经常想到几年前的一个有趣例子。你听说过 MSCHF 吗？

Yeah. Yeah. Yeah.

知道。

Right, they're awesome, right? They're sort of like this creative studio that uses technology as their medium. I'm very web 2.0 in that way, actually. Many of the kind of, you know, the Ev Williams, the Kevin Roses, that's who they were painters except technology was their canvas.

他们很出色。他们有点像一家以技术为创作媒介的创意工作室。我在这方面的看法其实很有 web 2.0 的风格。许多这类人，例如 Ev Williams、Kevin Rose，就像画家，只不过技术是他们的画布。

So, they created this very funny product called card versus card where they shipped, I think, 100,000 people a debit card and then every day they would text those people with um a location that they had to spend the money at and they would put $100 on the card and everyone would rush out spend the money and one or two would be able to spend it and everybody else would get declined. And it was just this hilarious

他们做过一款很有意思的产品，叫 Card Versus Card。我记得他们向 100,000 个人寄出了借记卡，随后每天给这些人发短信，告知一个必须前往消费的地点。接着，他们会向卡里存入 $100，所有人都会赶去花这笔钱，但最终只有一两个人能成功消费，其他人的交易都会被拒绝。这是一项非常有趣的社会实验，火爆到了

social experiment that went hyper viral and for me it was always inspiring in the world of fintech cuz it was like, "Wow, why don't we build more products like that?" You know, money is inherently social and yet all the financial products we have are so dry and personal and embarrassing.

病毒式传播的程度。它一直给我在金融科技领域带来启发，让我思考：“我们为什么不多做一些这样的产品？”金钱本质上具有社会性，但我们拥有的所有金融产品却都如此枯燥、私密，而且令人难为情。我认为 AI 领域现在也正在经历

I think there's a sort of similar moment happening in AI right now where we can build these wildly ambitious products that touch on many of our social nerves.

一个类似的时刻。我们可以打造出野心极大的产品，触动社会生活中的许多敏感神经。我们只需要付诸行动。

We just have to do it.

我就顺着这个话题继续提问。

So, let me follow that thread.

你能接触到大量公司，其中既包括

You get to see tons of companies both pitching you and also companies you're working with that you're investing in.

向你推介的公司，也包括你正在合作和投资的公司。你从那些

What are some counterintuitive lessons you've learned from watching the companies that operate well and have succeeded? Uh lessons that maybe go against typical wisdom, startup wisdom.

运营良好并取得成功的公司身上，学到了哪些反直觉的经验？呃，也就是一些可能有悖于常规智慧、创业智慧的经验。我来告诉你最重要的一条。你知道，以前，也就是 3 年

I'll tell you the biggest one and you know, in the old days, which is 3 years ago, um we would see a company and if what they were doing, trying to do was too ambitious, we would you know, not engage. Just too crazy, too complex.

前，我们看到一家公司时，如果他们正在做或试图做的事情野心太大，就不会与其接触，因为那实在太疯狂、太复杂了。这背后也意味着，你不会投资一笔 $100 million 的种子轮，因为

You know, and implied by that is you wouldn't do a $100 million seed because just it's too much money for almost any problem. It's too much money for any person to actually manage. It's too much money to build a the sort of talent to absorb. Like it doesn't make sense as an inception round. I think today we're almost seeing the opposite problem where, you know, an idea that's too small is not something that we want to

对几乎任何问题而言，这笔钱都太多了。任何人想要真正管理好这笔钱都非常困难。这笔钱实在太多，很难组建起能够消化它、并打造出这样一个……的人才团队。从初创轮的角度看，这并不合理。我认为如今我们面对的几乎是相反的问题：如果一个想法太小，我们就不会想

engage with. And you can talk about how you put $100 million to work in the seed productively. Now, I'm not recommending you raise $100 billion, but I think that there's this sort of no ceiling on ambition is also showing up in how we're picking companies. And and maybe how they're picking us as well. Because when we invest, we tell every founder like we're here to help you build the strongest form of your vision. You know, Mark told

参与。你也可以讨论如何在种子轮有效投入 $100 million。我并不是建议你融资 $100 billion，但这种野心不设上限的理念，也体现在我们挑选公司的方式上，也可能体现在它们挑选我们的方式上。我们投资时会告诉每一位创始人，我们是来帮助你打造出愿景最强大的形态。Mark 在

this to me when him and I were talking about coming here. And he said, "Aneesh, the way we um sort of told our story when we were raising our first fund was, you know, we were going to the moon or we were going to leave a moon-size crater in the ground.

与我讨论来这里时，也对我说过这句话。他说：“Aneesh，我们当初讲述自身故事的方式，也就是筹集第一只基金时的说法是：我们要么登上月球，要么就在地面留下一个月球般大小的陨石坑。

And there was no other option." That's sort of how um how we want to work with our founders as well.

没有第三种选择。”这也正是我们希望与创始人合作的方式。

I love that point. So, like is can you get too ambitious? Is there like a limit? Obviously, you look at the you know, the team and what they're But kind of the key lesson here is be more ambitious. Uh it's like the opposite of what used to be of like here's our here's our wedge. Here's where we're going to go. What you're looking for is just how big is the idea.

我很喜欢这一点。那么，野心会不会太大？是否存在上限？显然，你们会考察团队及其……但这里的关键经验其实是要更有野心。这与过去那种“这是我们的切入点，这是我们接下来要前往的方向”恰好相反。你们看重的是这个想法究竟有多大。

I mean, look at Atoms.

以 Atoms 为例。

Yeah.

对。

How crazy is Atoms, you know? I mean, what an incredible hero's journey for all of us collectively. But also what they're trying to do is something that, you know, 5 or 7 or 10 years ago would have felt insurmountable.

Atoms 多么疯狂。对我们所有人而言，这都是一段不可思议的英雄之旅。但与此同时，他们想做的事情，在 5 or 7 or 10 年前还会让人觉得根本无法实现。

And now it's like, "Okay, it's challenging. Let's see." You know?

而现在，人们会说：“好吧，这很有挑战性，那就试试看。”

Interesting. Is there anything else Anything else that has changed or I guess you've changed your mind about around what you think it takes to build a successful company these days?

很有意思。还有什么发生了变化，或者有哪些方面是你改变了看法的？在你看来，如今要打造一家成功的公司，需要具备什么？

I mean, I think that the the kind of old wisdom around consumer products have to be free. I'm almost taking the opposite take, which is let's think about consumer products that are extraordinarily expensive. I think every um every part of consumer discretionary spend is up for grabs right now.

过去有一种传统观念，认为消费产品必须免费，而我几乎持相反的看法：我们应该思考那些价格极其昂贵的消费产品。我认为，如今每一项消费者可自由支配的支出都有机会被重新争夺。

And I think a really useful because price is a measure product market fit, a really useful product exercise is what is the Birkin bag $10,000 a month, $1,000 a month version of our product.

由于价格是衡量产品市场契合度的指标，因此有一项非常有用的产品思考练习：在我们的产品中，什么是像 Birkin 包一样每月收费 $10,000 或 $1,000 的版本？

So, I think expensive consumer software is something like new and important that we wouldn't have thought about 5 years ago.

因此，我认为昂贵的消费软件是一个新颖而重要的方向，这是我们 5 年前不会考虑的。

I love that framing. Cuz it just pushes you again to be more ambitious.

我喜欢这个思考框架，因为它会推动人们再次树立更大的雄心。

Yeah.

是的。

You mentioned Mark and you work closely with Mark Andreessen and Ben Horowitz.

你提到了 Mark，而且你与 Mark Andreessen 和 Ben Horowitz 共事密切。

Yes.

是的。

What's What's one thing you've learned from each of those guys?

你分别从他们两人身上学到的一件事是什么？

They're such extraordinary leaders, founders. I mean, the thing that I actually feel so grateful to be a part of that they really embody to their core, I think is a feeling of stewardship for the technology industry and for really the country and the sort of maybe the western way of living and thinking.

他们都是极其杰出的领导者和创始人。我非常感激自己能够参与其中。我认为，他们真正体现出了一种守护的责任感，守护科技行业乃至整个国家，以及某种西方的生活与思维方式。

You know, and if you look at sort of a Ron Conway, you know, or Brook Byers, Tom Perkins, there was this feeling, I think, of obligation to sort of leave it better than you found it from an industry perspective.

如果观察 Ron Conway、Brook Byers 或 Tom Perkins 这样的人，就会发现他们都有一种责任感：希望从行业角度而言，自己离开时，这个行业能够比自己刚进入时更好。

And that sort of aspiration goes way beyond just being the best investor in the world, though we want to do that, too. I see them both show up that way over and over again, where they want to do hard important things that don't directly benefit the firm or at least not singularly because they're just sort of important. You know, Ben has done a lot of that in the direction of the industry and and Mark in sort of the

这种抱负远远超越了仅仅成为全世界最优秀的投资人，尽管我们也希望做到这一点。我一次又一次地看到他们两人以这种方式行事。他们愿意去做那些艰难而重要、不会直接让公司受益的事情，至少不会只考虑公司的利益，因为这些事情本身就很重要。Ben 在推动行业发展方面做了很多这样的事，而 Mark 的工作则更多体现在另一个方面。

direction of the country, though of course both work on both.

这个方面就是推动国家发展。当然，两人其实都会兼顾行业与国家这两个方面。

Another really cool thing is just to see how I think Mark and Ben, but maybe the firm a little bit, has shaped our collective ambition as a founder community. I think if you look at 5 or 7 or 10 years ago, deep tech was deeply unpopular. You know, it wasn't a high-status thing to be working on. It was very fringe.

另一件特别重要的事，是看到 Mark 和 Ben，或许还有这家公司，在一定程度上塑造了我们整个创始人群体的抱负。回看 5 年、7 年或 10 年前，深度科技非常不受欢迎，研究它也并不被视为有地位的事，而是处于非常边缘的位置。

And and now it's become very popular, high-status, and mainstream. And I think there's a lot of firms that have, of course, pulled in that direction, but I think that um like Mark has been very full-throated in his support of working on sort of capital I important work in the national interest.

如今，深度科技已经变得非常流行、有地位，而且成了主流。当然，有很多公司都在推动这一趋势，但 Mark 始终非常旗帜鲜明地支持大家投身那些事关国家利益、真正重要的工作。

And all of Silicon Valley has changed as a result.

整个硅谷也因此发生了改变。

And you guys have had some big wins uh in the past couple weeks investing wise, too.

而且，从投资角度看，过去几周里你们也取得了几次重大成功。

Yeah.

是的。

Thank you.

谢谢。

Congrats.

恭喜。

Uh final question before we get to our very exciting lightning round.

在进入令人期待的快问快答环节之前，还有最后一个问题。

What's your advice to product people who are trying to think about what they might want to shift in how they work, how they think, how they operate to be more successful in the future in their careers and with their companies?

对于那些正在思考如何调整自己的工作方式、思维方式和行事方式，从而在未来的职业生涯和所在公司中取得更大成功的产品人，你有什么建议？

Just make more things. And I know it sounds silly. I know everybody says it, but just please like come up with a project. You don't have to tell anyone about it. It can be totally unimportant.

多做些东西。我知道这听起来很傻，也知道每个人都这么说，但还是请你想一个项目。你不必告诉任何人，这个项目完全可以无关紧要。

Um but use it as a chassis to use all the new models, ship things, talk about them, build your own intuition. I promise you're one sort of slightly frustrating and then very fulfilling week away from being as pilled as anyone. So, you just got to use the technology. Um and if not now, then when, right? This is all of us got in the game to build the products we saw in our mind's eye.

但可以把它当作一个载体，用来尝试所有新模型、发布成果、讨论模型，并培养自己的直觉。我向你保证，只要经历一个略显沮丧、随后又极具成就感的星期，你就会和其他人一样彻底着迷。因此，你必须使用这项技术。如果不是现在，还要等到什么时候？我们所有人入局，不正是为了打造那些曾在脑海中构想的产品吗？

Um and now you have a chance to do it.

现在，你已经有机会把它们做出来了。

So, just please please use the models.

所以，请务必使用这些模型。

You know, and and tell me what you built. Text me. You know, tag me. Like I will reply and respond and engage with you and so will everyone else because we that the magic of Silicon Valley is that it's a very positive sum mindset. You know, it's sort of everybody is building on each other and vulnerability is really rewarded. Um so, I definitely would encourage people to use the models.

然后告诉我你做出了什么。你可以给我发短信或者 @ 我。我一定会回复并与你交流，其他人也会如此。硅谷的魅力就在于这种高度正和的心态：大家都在彼此的基础上继续构建，而展现脆弱也会得到充分的正向反馈。因此，我非常鼓励大家多使用这些模型。

What's like a good heuristic if you were doing this enough? Is it like build something once a month? Is it sit uh like some number of hours per day sitting, talking, building? Anything that you think might help people be like, "Okay, you're doing a good job."

要判断自己做得是否足够，有什么好的经验法则吗？比如每个月做出一个东西，或者每天花几个小时进行交流和构建？是否有某种标准，能让大家觉得自己做得不错？

I mean, just just ship something once a week. And it doesn't have to be crazy.

我认为，每周做出一个东西即可，不必多么惊人。

You know, I mean, for example, um when I was playing around with Codex, I had it build a slide deck for um Mother's Day for my wife that pulled from my text messages. It looked at my photo gallery.

例如，我之前试用 Codex 时，让它根据我的短信为妻子制作了一份母亲节幻灯片。它还查看了我的照片库。

Um it set some music to it. Created like a 20, you know, slide deck of our relationship and pulled some cool old texts from when I first asked her out.

它为幻灯片配上音乐，制作了大约 20 页的内容，讲述我们一路走来的感情，还找出了一些很有意思的早期短信，比如我最初约她出去时发出的那些短信。

It was a really nice Mother's Day, you know? I mean, it wasn't important. It wasn't something that I It might come back to, but it was shipping something.

那个母亲节过得特别美好。这并不是什么重要的作品，也未必是我日后会再次回顾的东西，但我确实做出了一个东西。

So, it can be that small.

所以，它完全可以小到这种程度。

I know that you're a our mutual friend Nikil Singh Goel.

我知道你认识我们共同的朋友Nikil Singh Goel。

Uh you worked at Credit Karma with him.

你曾和他一起在 Credit Karma 工作。

He had a really good way of thinking about this. He finds that people sh- flip on AI and how they feel about it once they find some moment of joy that it had created for them. And this Mother's Day idea is such a good example.

他有一种很好的思考方式。他发现，只要人们经历某个由 AI 创造并能给自己带来快乐的时刻，就会彻底改变对 AI 的看法和感受。你的母亲节创意就是一个很好的例子。

And so, I think that's kind of a tip I always think about is just like what's something that just would will bring you joy if this works.

因此，我经常想到的一条建议是：找一件一旦成功就会给你带来快乐的事。

What's something you can do for someone else? You know, maybe that's a good starting point as well. I love that.

也可以思考自己能为别人做些什么。这或许是个不错的起点，我很喜欢这个想法。

Uh Anish, before we get to our very exciting lightning round, is there anything else that you want to share, anything else you want to double down on before we get into the lightning round?

Anish，在进入令人期待的快问快答环节之前，你还有什么想分享或再次强调的吗？之后我们就进入快问快答环节。

I don't think so. I've loved the conversation so far.

我想没有了。我很喜欢到目前为止的对话。

Me too. And with that, we reached our very exciting lightning round. I've got five questions for you. Are you ready?

我也是。接下来，我们进入令人期待的快问快答环节。我有五个问题要问你。准备好了吗？

I am.

准备好了。

Okay. Here we go. Uh what are two or three books that you find yourself recommending most to other people?

好，那就开始吧。你最常向别人推荐的两三本书是什么？

Yeah, so okay. Conquests and Cultures is my very favorite book. Um it's Thomas Sowell, and it just talks about how um conquests have led to culture change in different societies around the world.

Conquests and Cultures 是我最喜欢的一本书。作者是 Thomas Sowell，内容讲述征服如何导致世界各地不同社会的文化发生变化。

Sometimes positive, sometimes negative.

这些变化有时是积极的，有时是消极的。

I think to me, it's just the best historic view of sort of culture as the biggest driver of outcomes. Um and I've experienced a lot of that as, you know, somebody who was born in Canada and lived here to America, which has a very different culture of ambition. There's that word again. Um So, Conquests and Cultures is great.

对我而言，它是从历史角度审视文化如何成为结果最大驱动因素的最佳作品。我也亲身经历过许多这样的差异。我出生在加拿大，后来搬到美国生活，这里的进取文化截然不同。我又提到了“进取”这个词。总之，Conquests and Cultures 很出色。

Seven Powers, you mentioned, um is actually just an awesome book. It's I think it's a very intellectual distillation about kind of, you know, moats in business theory and compounding advantages. I really like it. You know, the maybe the third is the one that Mark I I actually thought that he was um maybe punking me when he sent this to me before I started. I said, "Mark, are there any books that I should read?" and

还有你提到的 Seven Powers，也是一本非常出色的书。我认为，它对商业理论中的护城河和复利优势进行了极具思想深度的提炼，我很喜欢。第三本或许就是 Mark 推荐的那本。在我入职前，他把这本书发给我时，我还以为他可能是在捉弄我。我问：“Mark，有没有什么书是我应该读的？”

he sent me a couple. And one was a book, a textbook, called um Increasing Returns to Scale.

他给我发了几本，其中一本是名为 Increasing Returns to Scale 的教科书。

Which I think is Brian Arthur is the author. It's It's an awesome book. It's It's a you know, it's a slightly dense study of why things like software have such outlier economic effects, but it really helps put things in perspective or it helped me in terms of like why does our industry work in the way that it does? Why does our culture work in the way that it does, right? Why are we so positive sum?

我记得作者应该是 Brian Arthur。这是一本很棒的书，深入研究了软件之类的事物为何会产生如此超常的经济效应。虽然读起来稍显晦涩，但它确实能帮助读者从更宏观的角度看待问题。至少，它帮助我理解了我们的行业和文化为何会以这种方式运作，以及我们为何如此强调正和。

I'd love to say that we're better people, but I think it may be a sort of better system and structure we work within.

我很想说，这是因为我们本身更好，但我认为更可能是因为我们所处的体系和结构更好。

Favorite recent movie or TV show you have really enjoyed?

最近有没有哪部电影或电视剧是你特别喜欢的？

Oh, man. I watch trashy movies and TV. I mean, we we watched House of Dragon.

我看的都是些没什么营养的电影和电视剧。我们看了 House of Dragon。

Um which is pretty cool. Yeah.

还挺酷的。

Yeah, I don't know. Yeah, maybe it's it's it's not highbrow. It's not important with the capital I, but it was awesome. We loved that. Um and then I uh I did see Odyssey. Um I saw it in London. I was there for a board meeting in in an IMAX theater packed with people drinking pints and having fun and amazing. It was cool cuz it's just a whole The movie was great, but it was just like a theater experience, like a weird social

我也说不准。也许它确实不是什么高雅作品，也谈不上是大写 I 开头的“Important”，但真的非常精彩，我们都很喜欢。后来我还去看了 Odyssey。当时我去 London 参加董事会会议，在一家 IMAX 影院里看了这部电影。影院里挤满了喝着啤酒、玩得很开心的人，体验特别棒。电影本身很精彩，但那更像是一种影院体验，也是一种奇妙的社交活动。

experience, kind of alone together.

这种体验有点像大家一起独处。

Um those are two recent ones.

这就是我最近看的两部作品。

Uh I have I have not been able to get tickets to the Odyssey at at an IMAX.

我一直没能买到 IMAX 版 Odyssey 的票。

So, I actually have a Grok bot just watching the site constantly and finding me good seats.

所以我做了一个 Grok 机器人，让它持续查看网站，帮我寻找好座位。

Perfect.

完美。

Perfect. The they've got them dumb capture though on the AMC website that hasn't been able to get through.

确实很完美。不过，AMC 网站上有一个很麻烦的验证码，它始终无法通过。

Really?

真的吗？

Uh it's like a tricky one. It's a really tricky one.

那种验证确实很难。

Is it the like select the fruit? Anyway.

是那种需要选择水果的验证吗？

Yeah, it's like you have to click three different matching shapes, which like come on, you can't do that.

对，需要点击三个相同的图形，根本无法完成。

Hopefully by the time this comes out I've seen it. I think there's few podcasts that are on like I haven't seen it yet.

希望等这期节目上线时，我已经看过了。我觉得有几档播客都在讨论这件事，但我还没看。

Oh, man. Okay.

好吧。

uh favorite new AI product. I don't know.

至于最喜欢的新 AI 产品，我还没有答案。

Favorite AI product recently that you've that give me joy.

最近有没有哪款你喜欢的 AI 产品，能够给你带来快乐？

Oh, man. I've I've spent a lot of time with the personal agents. I think Grok's okay. I'm going to give it to Grok bots only cuz it's just so unhinged for it to be so ambitious about sort of caching credentials and getting work done on your behalf. Like, I love it and I expect it from a startup. Um but they actually are doing things that I think no other sort of big company would do.

我在个人智能体上投入了很多时间。我觉得 Grok 很不错。我要把这一票投给 Grok 机器人，因为它实在太放飞自我，也非常有野心，竟然试图缓存登录凭据并替用户完成任务。我真的很喜欢这一点，而且我原本以为只有创业公司才会这么做。但他们确实在做一些我认为其他大公司都不会做的事情。

It's a really, really well done. It's a really thoughtful UI. It's got a really powerful foundation model. I think it also is like, okay, wait, maybe this is not a two-horse race on the sort of model side.

它的表现确实非常出色，UI 设计得很用心，基础模型也非常强大。它还让人意识到，模型领域或许并非两强争霸的局面。

So, I I just think the product is like fun and ambitious and uh and is sort of taking risks that other products like that wouldn't take.

我认为这个产品既有趣又有野心，而且敢于承担其他同类产品不敢承担的风险。

Two more questions. Do you have a favorite life motto that you often come back to in work or in life?

还有两个问题。你有没有一句最喜欢的人生格言，在工作或生活中经常会想起？

Oh, man. I've got one. It's I I learned this or I sort of, you know, this is from my founder days, but it also is something that's very true of parenting.

我确实有一句。这是我创业时学到的，但它也非常适用于养育孩子。

Which is um, you know, don't discover things through painful experience that some somebody can just tell you.

如果有些事别人直接告诉你就能明白，就不要非得通过痛苦的亲身经历来领悟。

Um so, and I unfortunately have had a bad habit of sort of discovery versus learning from somebody who's just a few steps ahead of me and I find my children have that habit, too.

遗憾的是，我一直有个坏习惯：总要自己摸索，而不愿向那些只比我多走几步的人学习。我发现我的孩子们也有这个习惯。

What's one example of something that you wish someone had told you?

能举个例子吗？有什么事是你希望当初有人告诉你的？

I mean, for my kids, it's don't touch the hot stove. Um for my startup, it was like Literally. For my startup, it was don't build a a product and a platform at the same time. You know, if you're going to be a platform company, build one. Our first company we tried to build a a sort of a social platform for mobile games and be a gaming studio.

以我的孩子为例，就是不要碰滚烫的炉灶，而且确实是字面意义上的。对我的创业公司来说，教训就是不要同时做产品和平台。如果你想做一家平台公司，就应当专心做平台。我们的第一家公司当时既想打造一个面向手机游戏的社交平台，又想经营游戏工作室。

And you know, somebody wise told me right away, like, look, you can't being a studio is so hard, much less being a studio and a platform. Pick one. And and we did and and it was it took us years to figure out we were wrong.

一位智者一开始就告诫我：“听着，光是经营工作室就已经很难了，更不用说同时经营工作室和平台。选一个。”但我们确实选择了两者，而且花了好几年才意识到自己错了。

Final question. I asked Ben Horowitz what to ask you about and he just said, uh ask him about his DJing. He's very good. And I went to your I found your DJ site uh I don't know if that's what you call it on SoundCloud/illscience.

最后一个问题。我问 Ben Horowitz应该问你些什么，他只说：“问问他打碟的事，他非常厉害。”后来，我找到了你的 DJ网站——我不知道你是否这样称呼它——网址是 SoundCloud/illscience。

Uh it's very good. I'm just like listening to it while I work. Um any tips for somebody that wants to get into DJing, any tools you found useful, any I don't know, insights that might help someone become better at this?

内容真的很不错，我工作时一直在听。对于想要入门打碟的人，你有什么建议吗？你是否发现过什么有用的工具，或者有什么心得能帮助别人更擅长打碟？

Totally. I mean, I think that this is why I love music models so much. So I DJing has always I I mean, I love DJing.

当然。我认为，这正是我如此喜欢音乐模型的原因。我一直很喜欢打碟。

I've been playing for 30 years now since '95, actually 31. Wow. Um and it's an awesome way to kind of express yourself musically if you're not a classically trained musician. You know, you select the music, you pick the records, you mix them together, so it requires some technical skill. But now I think you can go a step further and just make music with the models. And the best part is when you can come up with music

从'95年开始，我已经玩了30年，实际上是31年了。哇。如果你不是受过古典音乐训练的音乐家，打碟也是一种很棒的音乐表达方式。你可以选择音乐、挑选唱片，再把它们混合起来，因此需要具备一定的技术能力。但现在，我认为还可以更进一步，直接用模型创作音乐。最棒的是，你可以先构思一些音乐

ideas and have the models do the kind of strong form of them. So I think music is just such a visceral, satisfying way to kind of, you know, experience and and, you know, provide experiences in the world. So whether it's DJing or making music, I just suggest everyone do it.

创意，再让模型把它们转化为更成熟的形式。因此，我认为音乐是一种非常直观且令人满足的方式，让你既能亲身体验，也能为这个世界创造体验。无论是打碟还是创作音乐，我都建议每个人尝试一下。

I hadn't thought about how DJing has changed now that you have Suno and things like 11 Labs and all these things where you could just generate music, not have to just splice together existing music.

我以前确实没有想过，有了Suno、11 Labs之类的产品以及所有这些工具之后，打碟会发生怎样的变化。现在可以直接生成音乐，而不必只是把现有的音乐拼接起来。

I mean, think of the history of it. You know, you went from Okay, you know, first you could only hear music if you were there with the person playing it on an instrument. You know, recorded music on the phonograph. The big change in music actually, from a medium perspective, was um the cassette tape.

想想音乐的发展历史。最初，人们只有亲临现场，与演奏乐器的人待在一起，才能听到音乐。后来，留声机带来了录制音乐。其实，从媒介的角度来看，音乐领域的一大变革是盒式磁带。

Cuz the cassette tape was really the first time you could create, right? You could actually compose your own {quote} album. I think a lot of why music struggled in the 2000s is the sort of that went away and we went back to broadcast, and now that people are making music again, I think the music industry is going to be bigger than it's ever been.

盒式磁带第一次真正让人们能够进行创作。你可以编排属于自己的{quote}专辑。我认为，音乐产业在2000s陷入困境，很大程度上是因为这种创作方式消失了，我们又回到了广播模式。如今，人们又开始创作音乐了，我认为音乐产业的规模将达到前所未有的高度。

Wow. Man, so much disruption.

真令人惊叹，颠覆无处不在。

Anish, this was incredible. We covered so much ground. Uh final question, how can listeners be useful to you?

Anish，这次访谈太精彩了，我们讨论了非常多的内容。最后一个问题：听众可以怎样帮助你？

I mean, show me what you're building.

请让我看看你在做什么。

Um please don't be despondent. Build something and then tag me, um and I'd love to see it.

请不要灰心。动手做点东西，然后艾特我，我很想看看。

Um if you're interested in hearing more stuff like this, please follow me on X.

如果你想听到更多这样的内容，请在 X 上关注我。

I try to kind of engage and follow back.

我会尽量与大家互动，也会回关。

Um and otherwise, make sure you check out all the amazing folks in Lenny's network. Claire is a star. Elena is so, so good. And there's just so much compelling content here.

另外，一定要去看看Lenny 人脉圈里的所有优秀成员。Claire 是位明星，Elena 也非常出色，这里还有许多精彩的内容。

Nikkel, which we talked about.

还有我们聊到过的 Nikkel。

Nikkel is the best, man. That guy is is everything.

Nikkel 是最棒的。那家伙简直就是一切。

And amazing. And Nish, thank you so much for being here.

太棒了。Nish，非常感谢你来做客。

Thank you, Lenny.

谢谢你，Lenny。

Thank everyone.

谢谢大家。

Thank you so much for listening. If you found this valuable, you can subscribe [music] to the show on Apple Podcasts, Spotify, or your favorite podcast app.

非常感谢你的收听。如果你认为本节目内容有价值，可以在 [音乐] Apple Podcasts、Spotify 或你常用的播客应用上订阅。

Also, please consider giving us a rating or leaving a review, [music] as that really helps other listeners find the podcast. You can find all past episodes or learn [music] more about the show at Lennyspodcast.com.

此外，也请考虑为本节目评分或留下评论。[音乐] 这确实有助于其他听众发现这档播客。你可以查看往期所有节目，或前往 [音乐]Lennyspodcast.com 进一步了解本节目。

See you in the next episode.

下期节目再见。