The rise of taste, human authenticity and judgment in an AI world | Adam Mosseri (Head of IG)

频道: Lenny's Podcast
视频: https://www.youtube.com/watch?v=yQ_EWmtfWvQ
原文语言: en
统计: 共 146 轮 · Adam 76 · Lenny 69

[0:00]

No, I think taste matters a ton. In a world where it's easier to build things, it's more important to make sure that your time is spent figuring out what you should be building in the first place. The people who I think are going to make the most of it are the ones who are cleareyed about what AI is good at and what it's not good at and also have an instinct or a nose for what it will be good at and not good at. What's something that the Instagram algorithm knows about human behavior that people may not realize?

不，我觉得品味（taste）太重要了。当造东西变得越来越容易时，把时间花在「先想清楚到底该造什么」上就变得更加重要。我觉得能真正吃到这波红利的人，是那些对「AI 擅长什么、不擅长什么」看得很清楚的人，同时对「它将来会擅长什么、不会擅长什么」还有直觉、有嗅觉。Instagram 的算法里，有什么是它了解人类行为、但大家可能没意识到的？

[0:30] Adam

I think people assume that there's a much more detailed semantic understanding of everybody's interests and preferences in the algorithm than there is.

我觉得大家会以为，算法里对每个人的兴趣和偏好有一套非常细致的语义理解，但其实并没有那么细。

[0:38] Lenny

Is the rise of AI content a headwind or a tailwind for Instagram versus other platforms?

AI 生成内容的兴起，对 Instagram 来说，相对于其他平台，是逆风还是顺风？

[0:45] Adam

I think it's going to be a tailwind, but I think it's going to be a challenge [music] in a world where there's an abundance of synthetic content. I actually think people are going to seek out creativity and authenticity and people. I don't think we should filter out AI content. I think we should [music] let you know if content is AI content or not. That's hard. By the way,

我觉得是顺风，但也会是个挑战。在一个合成内容（synthetic content）泛滥的世界里，我反而认为人们会主动去寻找创造力、真实感，还有「真人」。我不觉得我们该把 AI 内容过滤掉，而是应该让你知道这条内容到底是不是 AI 生成的。顺带说一句，这件事很难。

[1:04] Lenny

where do you think human brains will continue to be most valuable as AI continues to eat more and more of that product development life cycle?

随着 AI 越来越多地吞掉产品开发的整个生命周期，你觉得人脑会在哪些环节继续最有价值？

[1:12] Lenny

That's a great question. So today my guest is Adam Masseri, head of Instagram. Over three billion people use Instagram monthly. That's one in every three people alive. It boggles the mind. Prior to Instagram, Adam designed and led the early Facebook news feed. He also ran the team that built the Facebook ranking algorithm. And 8 years ago, he took over Instagram from its founders, Kevin Cyester [music] and Mike Kger. He's a designer turned product manager turned leader of Instagram. Adam is also famous for being the face of all of the controversy and changes that come with evolving Instagram as a product, which we talk about. Before we get into it, don't forget to check out lennisproduct.com [music] for a free year of the most interesting and well-crafted AI products in the world, available exclusively to Lenny's newsletter subscribers. With that, I bring you Adam Masseri. Adam, thank you so much for being here. Welcome to the podcast.

这是个好问题。今天我的嘉宾是 Adam Mosseri，Instagram 负责人。每个月有超过 30 亿人使用 Instagram——相当于每三个活着的人里就有一个，想想都觉得不可思议。在 Instagram 之前，Adam 设计并主导了 Facebook 早期的信息流（news feed），还带过打造 Facebook 排序算法的团队。八年前，他从两位创始人 Kevin Systrom 和 Mike Krieger 手中接过了 Instagram。他是设计师出身，转做产品经理，再成为 Instagram 的掌门人。Adam 还有个「名声」——他是 Instagram 作为一款产品不断演进过程中，所有争议和改动的「门面」，这一点我们后面也会聊到。在正式开始之前，别忘了去 lennysproduct.com 看看——Lenny's newsletter 的订阅者可以独家免费领取一年、全世界最有意思、做得最精良的一批 AI 产品。好，下面有请 Adam Mosseri。Adam，非常感谢你来，欢迎做客本期播客。

[2:13] Adam

Thank you for having me. Excited to be here.

谢谢你邀请我，很高兴来。

[2:15] Lenny

You've been doing product for a long time. You get to see how a lot of teams operate across Meta within Instagram. What does just kind of like the canonical product team look like in 2026? What's kind of most different today in how teams operate slash should operate versus say a couple years ago?

你做产品已经很久了，也能看到 Meta 内部、Instagram 里很多团队是怎么运作的。到了 2026 年，一个典型的产品团队大概长什么样？跟几年前相比，今天团队的运作方式——以及应该怎么运作——最大的不同是什么？

[2:33] Adam

It's changed a lot this year. So for the longest time at a big company like ours, the canonical team was something like two or three Android engineers, two or three iOS engineers, two or three server engineers, maybe a generalist, a PM, a designer, a data scientist, a researcher if you were lucky, and maybe that's about it. So you know on the order of a baker's dozen and that is a function of you know you want to have for anybody who's writing code someone who can review their code and that's who's familiar with that codebase and having these different functions that are more specialized you know I think it's very different at a startup but this year it's changing we've adopted what we call pods which are just mini teams where it's call it four to six engineers who are a bit more generalists. Uh one we call product staff which is sort of an evolution of the PM. So a PM who can do some of what a designer does and some of what a data scientist does and some of what a research does leveraging um the latest tools that we have for them. And then whatever specialist they need if they if they're doing something that requires a pricing strategy you need a senior data scientist. If you're doing something that is really novel from an experience standpoint, you need a very senior product designer. So we try to build the team based on the needs of the work a bit, but then end up with a much smaller core which is more on the order of six or seven usually. And that is a very big shift that's just happening to us this year. But they just by virtue of having less people to coordinate they can often move faster and make um better decisions a little bit less design by committee. So we talk a lot about you know AI adjusting and improving productivity and that's part of it but I think another part of it is just the small teams I think often are just more effective. This episode is brought to you by our season's presenting sponsor, WorkOS. What do OpenAI, Anthropic, Cursor, Versell, Replet, Sierra, Clay, and hundreds of other winning companies all have in common? They are all powered by work OS.

今年变化很大。在我们这种大公司里，很长一段时间，典型团队大概是这样：两三个 Android 工程师、两三个 iOS 工程师、两三个后端工程师，也许一个通才工程师，一个 PM、一个设计师、一个数据科学家，运气好的话再加一个用户研究员，差不多就这样。也就是十来号人（一打半的量）。这背后的逻辑是：任何人写代码，你都得配一个熟悉这块代码库、能 review 他代码的人，所以要有这些更专精的职能。在创业公司当然很不一样。但今年这一切都在变。我们引入了所谓的 pod——就是迷你团队，大概四到六个工程师，他们更偏通才。其中一个角色我们叫 product staff，可以理解成 PM 的进化版：一个 PM，借助我们给他们配的最新工具，能干一部分设计师的活、一部分数据科学家的活、一部分用户研究的活。然后再按需要配专才——如果你做的事需要定价策略，就得配一位资深数据科学家；如果你做的事在体验上非常新颖，就得配一位非常资深的产品设计师。所以我们会根据工作本身的需要来搭团队，但最后的核心盘会小很多，通常也就六七个人。这对我们来说是今年正在发生的一个非常大的转变。而仅仅因为需要协调的人变少了，他们往往就能跑得更快、决策也更好，少了一点「委员会式设计」（design by committee）的味道。我们常说 AI 在调优、在提升生产力，这确实是一部分原因，但我觉得另一部分原因就是小团队本身往往更高效。本期节目由我们本季的冠名赞助商 WorkOS 带来。OpenAI、Anthropic、Cursor、Vercel、Replit、Sierra、Clay，还有其他好几百家赢家公司，有什么共同点？它们背后都用了 WorkOS。

[4:56] Lenny

If you're building a product for the enterprise, you've felt the pain of integrating single signon, skim, arbback, audit logs, and other features required by large companies. work OS turns those deal blockers into drop-in APIs with a modern developer platform built specifically for B2B SAS. [music] Literally every startup that I'm an investor in that starts to expand up market ends up working with Work OS. And that's because they are the best. Whether you are seedstage startup trying to land your first enterprise customer or a unicorn [music] expanding globally, work OS is the fastest path to becoming enterprise ready and unblocking growth. It's essentially Stripe for enterprise features. Visit works.com to get started or just hit up their Slack where they have actual engineers waiting to answer your questions. Workos allows you to build faster with delightful APIs, [music] comprehensive docs, and a smooth developer experience. Go to work os.com to make your app enterprise ready today. I I love this. So on this team of six to seven, what's what's the makeup again? And which role are you finding you have less of? If you're going from the kind of the if you're going 50% size,

如果你在为企业级客户做产品，你一定体会过接入 SSO（单点登录）、SCIM、RBAC、审计日志（audit logs）等大公司要求的功能有多痛苦。WorkOS 把这些「卡单」的障碍变成了即插即用的 API，还配了一个专为 B2B SaaS 打造的现代开发者平台。说真的，我投的每一家开始往上走、去做大客户的创业公司，最后都用上了 WorkOS。因为它们就是最好的。不管你是想拿下第一个企业客户的种子期创业公司，还是要全球扩张的独角兽，WorkOS 都是让你最快具备「企业级就绪」能力、打通增长的那条路。它本质上就是「企业级功能界的 Stripe」。去 workos.com 就能上手，或者直接去他们的 Slack，那儿有真人工程师随时回答你的问题。WorkOS 让你用顺手的 API、完整的文档和顺滑的开发者体验，做得更快。今天就去 workos.com，让你的应用具备企业级就绪能力。我特别喜欢这个话题。那在这个六七人的团队里，构成到底是怎样的？以及你发现哪个角色变得更少了？如果你把团队砍到原来的一半——

[5:59] Adam

you just have less specialists, right? So you might not [clears throat] have any. You might be four engineers and a product staff and there's no data scientist, there's no designer, there's no researcher, there's no content designer. The product staff is the generalist that sort of supports all of those things. I mean, what's clearly happening is all the functions are starting to bleed into each other and the and the whole industry is wrestling with what that means. You know, a lot of what a data scientist does at a big company, for instance, is relatively mechanical. And so, you know, there's stuff that they do that is really more like, you know, art and science. And the stuff that's really more like just pulling data, data management, you know, so some of the tools that we're building internally to understand, for instance, a traditional data science question would be a waterfall. So if you wanted to look at people creating reels, you would look at all the steps and then how people fall off on each step and try to figure out where there might be opportunities to improve things. That kind of basic waterfall analysis is like much easier now to use some of our internal tools to just pull automatically as opposed to having to have a data scientist do a bunch of bespoke work for that. So a product staff might be able to do that now and they couldn't do that a year ago. So you just end up with this generalist these people who have more generalist shapes and then and then when you need it when you really need it you have a more senior ideally or just more creative specialist um so you know a phenomenal uh product designer or just a just a genius uh data scientist or researcher.

就是专才更少了，对吧？所以可能一个都没有。可能就是四个工程师加一个 product staff，没有数据科学家、没有设计师、没有用户研究员、没有内容设计师。这个 product staff 就是那个通才，某种程度上把所有这些事都撑起来。现在很明显正在发生的是：所有职能开始互相渗透、彼此交融，整个行业都在琢磨这到底意味着什么。举个例子，在大公司里，数据科学家做的很多事其实相对机械。他们有些活儿更像是「艺术加科学」，但有些活儿就是纯粹拉数据、做数据管理。我们内部在做一些工具来处理这类事。比如一个传统的数据科学问题是 waterfall（漏斗式流失分析）：如果你想看有多少人在创建 Reels，你会把每一步都拆出来，看人们在每一步是怎么流失的，再找哪里有优化空间。这种基础的漏斗分析，现在用我们内部的一些工具就能自动拉出来，不用再让数据科学家专门定制一大堆工作。所以 product staff 现在可能就能自己搞定，这在一年前是做不到的。于是你最后得到的，就是这批「通才形态」更强的人，然后当你真正需要的时候，再配一位更资深、最好是更有创造力的专才——比如一位极其出色的产品设计师，或者一个天才级的数据科学家、研究员。

[7:32] Lenny

This is so interesting. It's exactly what I just heard. I had uh Fiona Fong the head of engineering for cloud code and co-work on the podcast. She's force attorney's manager and she described the people she hires now are one builders with great taste that can take an idea from end to end and people with deep expertise in a very specific domain.

这太有意思了，跟我刚听到的一模一样。我请过 Fiona Fong 上节目，她是 Claude Code 和 Cowork 的工程主管，也是 Boris Cherny 的经理。她说她现在招的人分两类：一类是有极佳品味、能把一个想法从头做到尾的 builder；另一类是在某个非常具体的领域有深厚专长的人。

[7:53] Adam

The tasting matters a lot. I really agree with that. Boris used to work at Instagram. Um I love

品味特别重要，这点我非常认同。Boris 以前在 Instagram 待过。我很喜欢——

[7:59] Adam

Yeah. He was a senior IC at Instagram for a while. I love seeing him. He's all over threads now. It's like he's sort of like the face of Clark K. He's he's a celebrity now. He really is. He's his own little Yeah, for sure. In a world that is like on fire right now. Um, no, I think taste matters a ton. Uh, so in a world where it's easier to build things, it's more important to make sure that your time is spent figuring out what you should be building in the first place. Um, actually, so a lot of designers right now are very anxious about their roles. you know, you've got these other generalists doing design, you've got engineers doing design, product staff doing design, but I'm actually pretty long on design or designers because they tend to have taste and I think that is something that is much more difficult to imagine being automated away. And so there's other challenges with design sometimes, but I I'm pretty long right now on designers. I've always felt that too as it is so easy to build and all the work that AI produces is so like you can tell this was cloud design. I know what you did here.

是啊，他在 Instagram 当过一阵子资深 IC。我很喜欢见到他。他现在天天泡在 Threads 上，简直像是 Claude Code 的「门面」，成了个名人，真的成名人了，有他自己的一片小天地，没错。在这个「当下一切都着了火」的世界里——不，我觉得品味真的太重要了。所以说，当造东西变得更容易时，确保你的时间花在「先想清楚到底该造什么」上，就更重要。其实现在很多设计师对自己的角色非常焦虑：你有这些通才在做设计，有工程师在做设计，有 product staff 在做设计。但我其实相当看好设计、看好设计师，因为他们往往有品味，而品味这东西，我觉得要被自动化掉要难得多。设计有时也有别的挑战，但我现在挺看好设计师的。

[9:09] Lenny

This is codeex.

这个是 Codex 做的。

[9:10] Adam

Well, they all have their vibe, right? Like you vibe code your apps. We call it vibe coding. You're all like, "Oh, that's a codeex app." Or, "Oh, that's a cloud app."

嗯，它们各有各的「调调」（vibe），对吧？就像你 vibe code 你的应用——我们管这叫 vibe coding。你一看就知道，「哦，这是个 Codex 做的应用」，或者「哦，这是个 Claude 做的应用」。

[9:17] Lenny

Right. And that's replet. That's lovable. Like you can

对。那个是 Replit，那个是 Lovable。你就能——

[9:20] Adam

Yeah.

是的。

[9:20] Lenny

You can predict these things. You like I've always thought that too that design should be thriving already now. For some reason, it hasn't yet. If you look at jobs for designers, they're kind of flatlining. I feel like the missing piece is like the PM piece of deeply understanding the business and what will grow it and what success, you know, like all that stuff, the business side of it versus the taste side of it.

你就能预判出这些东西。我一直也是这么想的——按理说设计现在早就该迎来春天了，但不知为什么还没有。你去看设计师的岗位需求，其实是走平的、没怎么涨。我感觉缺的那块拼图，是 PM 那一块：深入理解业务、理解什么能把它做大、什么算成功……就是这些偏商业的那一面，而不是品味那一面。

[9:40] Adam

Yeah. I think you're going to see like, you know, um we have a senior designer uh at Instagram uh called Nate who just transferred into product stuff. So, I think I think some of what you'll see is, you know, it will be harder to talk about design roles and who's a good designer because they're not going to just stay in traditional design roles. You know, if you're an amazing designer, you might you probably have strong opinions outside of just the interaction in visual design. You probably have strong opinions on product strategy, even on the business, on the go to market. And so I actually think some of our strongest product staff are going to be converts from design and from data science who are just looking to expand their reach. And they were influential across functional boundaries before, but this world where those functional boundaries are just wildly blurred just allow them just to jump in. And so sure they'll be technically a generalist on paper, but they're they're clearly have a a uniquely, you know, strong ability in one one type of craft. Um, but they've got the ability and strong opinions to make informed decisions across other parts or other crafts. And so, you know, I don't know that all the strongest designers I have will all be in design. They they probably will be the majority, but I can imagine a bunch of really strong ones, you know, moving roles, but I mean, I should also check my own bias here, though, because I started as a designer at Facebook way back when, and I'm I switched roles. Um,

是啊。我觉得你会看到——我们 Instagram 有位资深设计师叫 Nate，他刚转岗做了 product staff。所以我觉得你会看到的一点是：以后想谈「设计岗位」「谁是好设计师」会变难，因为他们不会只待在传统的设计岗位里。如果你是个了不起的设计师，你多半在交互和视觉设计之外也有很强的观点——你很可能对产品策略、甚至对业务、对 go-to-market 都有很强的看法。所以我其实觉得，我们最强的一些 product staff，会是从设计、从数据科学转过来的人，他们本来就想扩大自己的影响半径。他们过去就能跨职能边界施加影响，而如今这些职能边界被极度模糊化了，正好让他们能一跃而入。所以纸面上他们确实算通才，但很明显，他们在某一类手艺上有独一无二的强能力，同时又有能力、有很强的观点，能在别的领域、别的手艺上做出有依据的判断。所以我不确定我手下最强的设计师是不是都会留在设计岗——大多数大概还是会，但我完全能想象一批非常强的人转岗。不过话说回来，我也得警惕一下自己的偏见，毕竟我当年在 Facebook 也是设计师出身，后来才换的岗。

[11:05] Lenny

no, designers are great. I'm a big fan. So, this is really interesting. There's always been this like GM model where different types of functions can become GMs. It's like this product staff role feels like a similar situation where different functions can become product staff.

不不，设计师很棒，我是他们的铁杆粉。所以这真的很有意思。一直以来都有那种 GM（总经理）模式——不同职能的人都能成长为 GM。感觉这个 product staff 角色也是类似的情况：不同职能的人都能变成 product staff。

[11:17] Adam

Yeah. Yeah. And that was true of PM before, but it's just so much more true now. Um and it'll I mean in some ways it's probably the age of the generalist, but I I still think there's going to be a real important role for these really amazing specialists who are just they're all about going I wish I was like that. I always had this like I romanticized like the phenomenal machine learning engineer or AI researcher or shoe maker. Like I think that's the coolest thing in the world, but it's never been my shape. I've always been um I've never been great at anything. I've always just had range. That's always been my strength. Same. [laughter] Okay. So this idea of product staff, so the idea is on these new pods. So this is like a new thing you guys are doing. So there's these pod teams, product staff, engineers, and maybe one specialist that's going deep on say pricing algorithm or something like that. So what this tells me is there's these like adjacent roles that are maybe uh more in trouble over the years. Uh data science for example, user research for example, you talked about designers being anxious. Is there is there anything there of just like oh these maybe folks in these groups should think about shifting to other roles?

对，对。这一点其实在 PM 身上早就成立了，只是现在成立得更彻底。某种意义上，这大概是个「通才的时代」，但我还是觉得，那些真正了不起的专才会有一个非常重要的位置——他们就是一门心思往深里钻。我一直挺希望自己也能那样。我一直很憧憬、甚至有点浪漫化那种顶尖的机器学习工程师、AI 研究员，或者做鞋的匠人。我觉得那是世上最酷的事，但那从来不是我的形状。我从来没在任何一件事上做到极致，我的强项一直是「广」，这一直是我的强项。（Lenny：我也一样。〔笑〕）好，说回这个 product staff 的概念。这是你们在这些新的 pod 里在搞的新东西：有这些 pod 团队，里面有 product staff、工程师，也许再加一个在比如定价算法之类的某件事上深钻的专才。那这让我听出来的是：有些「相邻」的角色，这些年可能日子会更不好过——比如数据科学、比如用户研究，你也提到设计师很焦虑。有没有这么一层意思：这些岗位上的人，也许该考虑转去别的角色？

[12:27] Adam

I I mean there's anxiety everywhere. I mean, I I I've talked to a lot of people at a lot of other companies, and it just seems like this is a lot of concern right now about competition, about job displacement, about unintended or unforeseen consequences of all this technology and all this moving so quickly. So, that's definitely happening. I I think that I think that you will see the functional lines continue to blur, but I still think there will be room for functions. They'll just be shaped differently. They'll be more they won't all be senior IC's necessarily, but they'll all be either senior or on their way to being senior. Like you can't just have a bunch of super senior data scientists and like no new ones because then who's going to be the new super data scientists in the future. So you need to basically hire and mentor and grow talent. You know, maybe the team is smaller overall and then that those who aren't on their way to being super senior move into more of a generalist role. I think that's like a reasonable soft landing, but I do think you're going to want to make sure you're investing not only in today's senior talent for each specific function, but in tomorrow's. Um, otherwise, I think you're going to regret it in a couple years. My take. That said, who knows what the world looks like in a couple years. Um, so my big thing and is generally like don't over don't be overly confident in whatever your predictions are because there's just too much flux right now. the Benedict Evans was on was on the podcast recently said the same thing. We don't know anything about what's going on.

我是说，到处都弥漫着焦虑。我跟很多别的公司的人聊过，感觉现在大家对竞争、对岗位被取代、对这项技术以及这一切飞速变化带来的意外或未曾预料的后果，都有很多担忧。所以这确实在发生。我觉得你会看到职能之间的界线继续模糊，但我仍然认为职能会有存在空间，只是形态会不一样。他们不会都是资深 IC，但要么已经资深、要么正走在通往资深的路上。你不能只养一堆超资深的数据科学家，然后完全不进新人——那将来谁来当下一批超级数据科学家？所以你基本上得招人、带人、把人才养起来。也许团队整体更小了，而那些暂时还没走在通往超资深路上的人，就转去更偏通才的角色。我觉得这是个还算合理的「软着陆」。但我确实觉得，你会想确保自己不只投资于今天每个职能里的资深人才，也要投资于明天的。否则我觉得过几年你会后悔——这是我的看法。话说回来，谁知道几年后世界长什么样。所以我的大原则通常是：别对自己的任何预测过度自信，因为现在的变数太大了。（Lenny：Benedict Evans 最近上节目也说了同样的话——我们对正在发生的事其实一无所知。）

[13:56] Adam

Yeah. Yeah. I like I like I like him a lot. Um I'll make sure I listen to the podcast.

是啊，是啊，我很喜欢他。我一定会去听那期播客。

[14:00] Lenny

Yeah. So you talked about taste. This makes me think about So you're interviewing a lot of people, hiring a lot of people. What are some traits that you're that are like trending up in things that you look for more and more now in this world? And what are some traits that are trending down and maybe less important to you?

好。你刚聊到品味，这让我想到——你在面试很多人、招很多人。在如今这个世界里，有哪些特质是你越来越看重、越来越想找的？又有哪些特质是重要性在下降、对你来说没那么要紧了？

[14:17] Adam

I mean there are some things that are the same, right? So, for the longest time, almost no matter what the function, I always look for three things. Do you have sort of grit? Like, you know, you're kind of like you're really gonna you've got some drive, some fire in your belly. Are you a quick learner? And are you, you know, are you reasonably, ideally, very self-aware so that you can actually take feedback and know what you're good at, know what you're good at? Because if you're those three things, if you got fire in your belly, you learn quickly, and you're self-aware, you can kind of get good at anything eventually. Um, and but if any of those things are missing, there's usually an issue. So that's sort of like the baseline right now for hiring, but just for I think people who are going to be more successful over these next five or 10 years as things change so significantly. I think two things that I I'm continuing to encourage myself to do are to stay curious and to put yourself out there. I just think you got to try things, right? This is like, you know, to that point before where that no one really knows what's going on. You just have to be willing to try things. It's almost I don't know. Do you speak another language?

有些东西是不变的，对吧？很长时间以来，几乎不管什么职能，我都会看三样东西。第一，你有没有那股韧劲（grit）？就是你是真的有股冲劲、肚子里有团火。第二，你是不是学得快？第三，你——最好是非常——有自我觉察，这样你才能真正接住反馈，知道自己擅长什么、不擅长什么。因为如果这三样你都有：肚里有火、学得快、有自我觉察，那你基本上最终什么都能学好。但只要缺了其中任何一样，通常就会出问题。这算是我现在招人的基线。不过，对于未来这五到十年、在这么剧烈的变化中会更成功的人，我觉得有两件事我一直在提醒自己去做：保持好奇，以及把自己豁出去、去试。我就是觉得你得去试，对吧？就像前面说的——没人真的知道正在发生什么，那你就必须愿意去试。这几乎……我说不好。你会说另一门语言吗？

[15:24] Lenny

Uh, Russian. Yeah.

呃，俄语，会的。

[15:26] Adam

Yeah. So, when you learn another language, I think one of the most important things, one of the best predictors, this is my guess. I don't have any research on this about, you know, are you going to get good at speaking is are you willing to sound like an idiot? Are you willing just to say it and be corrected and not be offended and then just get better and better? You just have to put yourself out there. And with all of these new tools and models and technologies, I think you just have to be willing to try stuff. Um, so if you're curious and you try stuff, I think that'll, you know, you'll learn, you'll adapt. But if you're not curious or you're not willing to make mistakes or try things, I think you're in a ton of trouble. Uh, or at least I think it's going to be a really difficult time. So those I think are premiums, not just for hiring at a company like Meta or a team like Instagram, but I just think across the industry and multiple industries over the next 10 or 20 years. Is there something that maybe we're looking for less of for some of these functions? Um, I think that there's some that are still going to be very large teams and so you need people who are really good at managing large organizations. Large organizational leadership is its own craft and skill. It's actually different than management. Um, but I do think there'll be less of those roles. I think we'll have more smaller teams and there'll be less people who manage thousands of people. Um, and so that's not that that job will go away, but that will be less of what I'm looking for in hires because I'm going to have less roles like that.

对。所以，当你学一门新语言时，我觉得最重要的一点、最能预测你会不会把口语学好的一个指标（这是我的猜测，我没有任何研究支撑）是：你愿不愿意把自己说得像个傻瓜？你愿不愿意就那么开口、被纠正、不觉得受冒犯，然后越说越好？你就是得把自己豁出去。面对所有这些新工具、新模型、新技术，我觉得道理一样，就是得愿意去试。所以如果你既好奇又肯动手试，我觉得你就会学、会适应。但如果你不好奇，或者不愿犯错、不愿尝试，那我觉得你就有大麻烦了——至少我觉得那会是段相当难熬的日子。所以这些特质我觉得是「溢价」项，不只是对 Meta 这样的公司、Instagram 这样的团队招人而言，我觉得在整个行业、在未来一二十年的多个行业里都成立。那有没有什么是我们对这些职能反而看得更少的？嗯，我觉得有些团队还是会非常大，所以你需要真正擅长管理大型组织的人。管理大型组织本身就是一门独立的手艺和技能，它其实和「管理」不是一回事。但我确实觉得这类角色会变少。我觉得我们会有更多更小的团队，管着成千上万人的人会更少。所以那份工作不会消失，但在我招人时，它会占我要找的东西里更小的比重，因为我这类岗位本身就变少了。

[16:48] Lenny

Something I'm hearing from a few folks is AI is almost kind of resetting people's impact and success in terms of some people that were maybe low performers pre-AII can now do like things they were bad at or AI now allows them to do and now they're thriving, building all these things, helping other people. Do you see that at all? Just like AI is just like lifting other people up, maybe lowering some people down.

我从好几个人那里听到一种说法：AI 几乎在重置人们的影响力和成就。有些在 AI 之前也许算是低绩效的人，现在反而能做那些他们原本不擅长、或者说 AI 现在替他们打通了的事，于是他们如鱼得水，造出各种东西，还能帮到别人。你有看到这种现象吗？就是 AI 把一些人往上抬，也许也把一些人往下压。

[17:12] Adam

Yeah. I mean the job is just different. I mean take take us take um take engineering. Engineering used to be maybe not majority but a large percentage 40 50 60% writing code. You know it's not now especially if you talk to anybody at these labs they're spending most of their time planning and reviewing code. That is a very different job. You might hate that and you might have loved just writing code or you might have you might love that and you might not have been that fast at writing code. So you know who who succeeds is a function of whose strengths are aligned with the tools needs and the business's needs. And so this is definitely happening. Another thing is you've had people who had good ideas about how to contribute to other functions but didn't have the mechanical or technical skills to do so and AI reduces the boundary to do that and then all of a sudden they can't like you know I it's for me it's kind of funny because when I got hired at Facebook we all the designers had to be able to program that was like our I had I went through a technical loop we gave up on that because it was too hard to hire people um but I now get to program again for the first time in maybe 10 years and you know I am not a good engineer. I'm a mediocre engineer on a good day but now I can write code responsibly which is just an amazing thing. You're seeing this across all sorts of levels and seniority and functions. you know, designers who are programming, uh, engineers who are pulling data and doing strong analyses, data scientists who are putting together proposals for designs. You know, the tools aren't all great. By the way, I think too often we have this really polarized binary outlook on the state of AI, like are you AI pill or are you anti- AI? It's like people aren't binary. I said that to the team yesterday and the state of the tools isn't binary either. You know, they're amazing at some things and remarkably bad at others.

是啊。我是说，工作本身就变了。拿工程来说，工程师以前——也许不算多数，但很大一部分时间，40%、50%、60%——是在写代码。现在不是了，尤其你去问那些大模型实验室里的人，他们大部分时间在做规划、在 review 代码。这是一份非常不一样的工作。你可能讨厌这样，你可能原来就爱纯写代码；也可能你恰恰喜欢这样，而你原本写代码也没那么快。所以谁能成功，取决于谁的强项跟工具的需要、跟业务的需要对得上。这确实正在发生。还有一点：有些人本来对「怎么给别的职能出力」有很好的想法，只是没有那种机械性或技术性的手艺去落地，而 AI 把这个门槛降下来了，于是他们突然就能上手了。对我来说这挺好笑的，因为我当年进 Facebook 时，我们所有设计师都得会编程——那是我们的……我当时是走了技术面试那一套的。后来我们放弃了这个要求，因为这样太难招到人了。但现在，可能十年来我第一次又能写代码了。我不是个好工程师，状态好的时候也就是个平庸工程师，但现在我能负责任地写出代码，这本身就是件很神奇的事。你会看到这种情况横跨各种层级、各种资历、各种职能：设计师在编程，工程师在拉数据、做扎实的分析，数据科学家在给设计方案出提案。顺带说一句，这些工具也不是都好用。我觉得我们太经常用一种非常两极化、非黑即白的眼光看 AI 的现状了——你是「吃了 AI 药丸」那派，还是「反 AI」那派？但人本来就不是非黑即白的。我昨天还跟团队这么说。工具的状态同样不是非黑即白——它们在有些事上厉害得惊人，在另一些事上又差得离谱。

[19:33] Lenny

And the people who I think are going to make the most of it are the ones who are cleareyed about what AI is good at and what it's not good at and also have an instinct or a nose for what it will be good at and not good at, you know, not, you know, next month or in a couple months from now. you mentioned um that AI writes all our code now. Someone tweeted this that's this idea that stuck with me for like months now of just like remember we used to be able to just write code for free. [laughter]

而我觉得，真正能把 AI 用到极致的人，是那些看得很清楚的人——清楚 AI 现在擅长什么、不擅长什么，同时还有一种直觉、一种嗅觉，能预判它下个月、或者再过几个月会变得擅长什么、又还搞不定什么。你刚提到，现在我们的代码基本都是 AI 写的。有人发过一条推特，这个说法我记到现在，好几个月了——「还记得以前咱们写代码是不要钱的吗。」（笑）

[19:52] Adam

I think you'll still be able to write code for free. It'll just be with a smaller model. But yes,

我觉得你还是能免费写代码的，只不过是用一个更小的模型罢了。不过话说回来——

[19:58] Lenny

I guess that's true. Like there's models that are close to free but it's like yeah that's crazy. Now it's just like

这倒也是。确实有些模型的成本已经接近于零了，但……对，太疯狂了。现在就变成了——

[20:03] Adam

but just think about think about the cost. Think about what you pay for a a model now and how and what the level of intelligence you're getting from that model is and then at that same price point a year ago what were you getting at some point they will just the the incremental value is will be won't matter like you know you know we're getting there I think with small projects and programming like I I think the models will matter even beyond you know this week you've got fable and obviously mythos from Enthropic, but I spent a lot of time with that this week. I'm it's for the first time I'm like, "Oh, I'm just talking to a much more technical, much smarter engineer than I am." You know, the next version, you know, you know, a year out of that model. Do I need to pay for Frontier tokens, you know, for whatever, you know, anthropic model 6.0 is or is Fable just fine for all of my side projects? Probably just fine. probably pretty pretty cheap by then, too.

但你想想成本这件事。想想你现在为一个模型付多少钱、能从它那儿拿到什么水平的智能，再对比一年前同样的价位你能拿到什么。到某个时候，这点增量价值就……就无所谓了。你懂的，我觉得在小项目、写程序这块，我们已经快到那一步了。我甚至觉得模型的意义还会更大——就说这周吧，你有 Fable，当然还有 Anthropic 的 Mythos，我这周在它上面花了很多时间。这是第一次，我的感觉是——「哦，我这是在跟一个比我技术强得多、也聪明得多的工程师聊天。」那再往后一年，等这个模型的下一代出来，我还需不需要为前沿 token 付费——不管那指的是 Anthropic 6.0 还是别的什么——还是说 Fable 就足够应付我所有的业余项目了？大概率是够了。而且到那时候，估计也已经相当便宜了。

[21:04] Lenny

Yeah. When Kevin Whale was on the podcast when he was CPO at uh OpenAI, he's he famously said, "This is the worst the model will ever be."

对。Kevin Weil 上我们播客的时候——他那会儿是 OpenAI 的 CPO——他说过一句名言：「你现在用的这个模型，已经是它今后最差的样子了。」

[21:12] Adam

Yeah.

对。

[21:13] Lenny

Yeah.

对。

[21:13] Lenny

Still hard to comprehend that. Wow. That's it's only going to get better.

到现在还是很难真正体会这句话的分量。哇。它只会越来越好。

[21:17] Lenny

So, on this point of uh token spend, ROI, and things like that,

那，说到 token 花费、ROI 这类东西——

[21:21] Lenny

uh Meta was famous for this like leaderboard of token spend. Um

呃，Meta 当年有件挺出名的事，就是搞了个 token 消耗排行榜。嗯——

[21:25] Adam

it's a terrible idea. No leaderboards for token spend.

那是个糟糕透顶的主意。千万别搞什么 token 消耗排行榜。

[21:28] Lenny

Okay. talk about that and just how do you think about just like budgets for engineers and product teams at this point? You just like spend as much as you want? Is it like there's a cap we have? Is there any sort of thing you've kind of figured out that works well?

好。就聊聊这个吧——你现在是怎么看工程师和产品团队的预算的？是想花多少就花多少？还是有个上限？你有没有摸索出什么行之有效的做法？

[21:39] Adam

Right now we've managed to get the costs rained in a little bit by like shutting down the silly things that we were doing. And so, you know, it's not that hard to build a token incinerator and that doesn't create a lot of value. And as soon as you actually look at the dollars in and value out, you might just be like, "Oh, that's just a bad idea." And so right now we don't have um token limits for for for our engineers actually I think for anybody really. Uh I think that'll eventually have to happen um particularly if costs go up before they go down. I think they'll eventually go down because for the reasons that we just talked about but I think of it like as any other resource right like I have to decide how to deploy capacity to my different teams because I have a limited number of GPUs and CPUs and storage and RAM etc. I have to decide how to deploy opex for labeling budgets across my teams. I have to decide how to deploy payroll for headcount across my teams. I think that you can imagine at least in an year or two coming that the the burn rate of a strong engineer might be the same as their salary or their cost of employment. And if in that world like you're going to probably need to put in some caps. the cap should probably be com like a proportional to your sort of you know the company's sort of trust in your ability to use them in an ROI positive way but I can imagine caps being healthy right now we're not there uh I think costs will go up because we'll just be using more tokens not because prices will necessarily go up but then I think prices will come down because all of these frontier models are going to be in a bit of a pricing more. Um, so we'll see. I think it'll be a bit of a roller coaster.

眼下我们把成本稍微控制住了一点，办法就是把之前那些犯傻的事儿给关掉。你知道的，造一个「token 焚化炉」并不难，但它创造不了多少价值。一旦你真去算投入的钱和产出的价值，你可能立马就会想：「哦，这纯粹是个馊主意。」所以现在我们其实没给工程师设 token 上限——我想对谁都没设。呃，我觉得这早晚得来，尤其如果成本在下降之前先涨上去的话。我相信成本最终会降下来，原因就是我们刚聊的那些。但我把它当成跟其他资源一样看待，对吧——就像我得决定怎么把算力分配给不同的团队，因为我的 GPU、CPU、存储、内存等等都是有限的；我得决定怎么在各团队之间分配用于数据标注的运营开支；我得决定怎么在各团队之间分配招人的薪资预算。我觉得你可以想象，至少在未来一两年内，一个顶尖工程师烧掉的 token 成本，可能会跟他的薪水、或者说雇佣他的成本持平。到了那种情况下，你大概就得设一些上限了。这个上限，大概应该跟……跟公司对你「能不能把这些 token 用出正向 ROI」的信任程度成正比。但我能想象上限是件健康的事。眼下我们还没到那一步。呃，我觉得成本会上涨，是因为我们会用掉更多 token，而不一定是因为单价会涨；但接着我觉得价格又会降下来，因为所有这些前沿模型都会陷入一场价格战。嗯，走着瞧吧。我觉得这会像坐过山车一样起起伏伏。

[23:23] Adam

So, coming back to this idea that as you said, we've evolved from we used to write all our code to now we're approaching all code will be written by AI. And it feels like now the transition is it's not just written by AI, but it's like oneshotted by AI. Like coding now is steering AI and it's like how often you have to correct it is is coding now. And then there's uh so it's like the software development life cycle slowly being eaten by AI. Uh it'll start helping us come up with ideas I imagine more and more. The question I like to ask people is where do you think human brains will continue to be most valuable as AI continues to eat more and more of that product development life cycle. taste like we talked about um judgment particularly around strategy right like you're you're not you might get feedback from an AI on a strategy but you're not asking an AI to come up with a strategy anytime soon or if you are then it's within the context of bounds you set so here's my goal here's my vision here are my constraints here's my job here's my budget I think that you know it looks more like management right like you are trying to define what success looks like decide how prescriptive you want to be about the path to success and then giving feedback along the way and that is its own craft you know and you it'll be interesting to see how Matt you know you know some of the same dynamics come up like I believe that if you are too prescriptive as a leader with a team you end up stifling good ideas but if you're too open-ended sometimes teams just waste time um going in the wrong direction. And so that level of autonomy you give a team like maybe that applies to, you know, agents in the future. Um, particularly when we're talking not just about building something, but deciding what you build in the first place. But I think of I think of vision as an articulation of the world or the or the state of the product you want to get to. Then I think of strategy is an opinionated path to achieve that vision. If a strat strategy can't be like be the best or be amazing.

那回到你刚说的这个观点：我们已经从「过去所有代码都是自己写」，走到了「现在几乎所有代码都快由 AI 来写」。而且感觉现在这个转变是——不只是 AI 来写，而是 AI 一次就搞定（one-shot）。现在所谓的写代码，就是给 AI 掌舵；你得多频繁地纠正它，这本身就成了「写代码」。所以就好像整个软件开发生命周期正被 AI 一点点吃掉。呃，我猜它还会越来越多地帮我们想点子。我特别喜欢问大家一个问题：随着 AI 不断吞掉产品开发生命周期里越来越多的环节，你觉得人脑在哪些地方会继续最有价值？——品味，就像我们聊过的；还有判断力，尤其是在战略层面。你可能会让 AI 给一份战略提提反馈，但短期内你不会让 AI 从头替你想出一整套战略；就算你让它想，也是在你设定的边界内：这是我的目标、这是我的愿景、这是我的约束、这是我要干的事、这是我的预算。我觉得，这更像是在做管理，对吧——你要去定义成功长什么样，决定自己对「通往成功的路径」要规定得多细，然后在过程中不断给反馈——这本身就是一门手艺。而且会很有意思，你会看到一些同样的规律又冒出来：比如我相信，作为领导，如果你对团队规定得太死，最后会扼杀掉好点子；但如果你放得太开，团队有时又会把时间白白浪费在错误的方向上。所以你给团队多大的自主权——这套逻辑，或许将来也适用于 AI agent。嗯，尤其是当我们谈的不只是「把东西做出来」，而是「一开始到底该做什么」的时候。不过我把愿景理解为：对你想抵达的那个世界、或者说那个产品状态的一种清晰表述；而战略，我理解为实现那个愿景的一条有主张、有取舍的路径。一套战略，不能只是「做到最好」或者「做到很棒」——

[25:40] Adam

It has to be controversial that you have to be a reasonable person should be able to disagree with it because otherwise you're probably just trying to compete on raw execution and I think there both vision and strategy I think are going to be where our brains are spending a lot of our more and more of our cycles and I think less on on execution. Something I have always thought is AI should be incredibly good at strategy. Because you would think here's the market, here's all the information on the market, our competitors, our metrics, our numbers, our growth, all these things. Help me figure out how to win. You think AI knowing all that would be really good at this. I think it could be. I I have found it's not unless you steer it pretty aggressively. And I don't mean towards an answer. I mean based on the constraints. It turns out when you're trying to come up with a strategy, there's a lot of things to consider, right? You need to consider the state of the technology, the personnel on the team and what's motivating them and what you can get. You know, sometimes coming up with a idea that is on the bubble, you know, it's going to actually attract some of the best talent and so that kind of like that kind of the push then goes to the idea. uh obviously the competitive landscape, the regulatory landscape for companies as large as ours and the compliance landscape, the identity and reason to exist for the brand. Um, you know, you have to consider all of these things. I think if you ask an AI just for a strategy lazily, you're not going to get something great. You're going to get something pretty predictable that probably the competition would expect you to do. I think if you want a really more effective one, you need to think long and hard about what are all the different inputs that need to be considered. Make sure you steer the AI in a way that it's considering those as well. And it needs to be a conversation and the back and forth. But I think if you're willing to put in the work and the time, it can definitely be helpful and definitely be clarifying. Um, particularly if you tell it to be critical. Different models have very different vibes though on Yeah.

它必须带点争议性——得让一个明事理的人也完全可能不认同它。否则的话，你多半只是在拼纯粹的执行力。我觉得愿景和战略这两块，会是我们的脑力越来越多投入的地方，而在执行上会越来越少。我一直有个想法：AI 本该极其擅长做战略。因为你会觉得：这是市场、这是市场上所有的信息、我们的竞争对手、我们的指标、我们的数字、我们的增长，统统给你——帮我想想怎么赢。你会以为，掌握这一切的 AI 应该很擅长这件事。我觉得它有这个潜力。但我发现，除非你相当强势地去给它掌舵，否则它做不好。我说的掌舵不是把它往某个答案上引，而是基于各种约束条件去引导。事实证明，当你要想出一套战略时，需要考虑的东西非常多，对吧？你得考虑技术的现状、团队里的人、是什么在驱动他们、以及你能招到什么样的人。你知道，有时候你想出一个还悬而未决、颇有冒险性的点子，反而恰恰能吸引到一些顶尖人才，于是那股劲儿就会朝这个点子涌过来。呃，当然还有竞争格局；对我们这种体量的公司来说，还有监管环境、合规环境，以及这个品牌的身份认同和存在的理由。嗯，这些你都得考虑进去。我觉得，如果你偷懒地直接让 AI 给你一套战略，你不会得到什么好东西——你会得到一个相当可预测的方案，而那大概正是竞争对手预料你会做的。我觉得，如果你想要一套真正更有效的战略，你得好好花心思去想：到底有哪些不同的输入是必须纳入考量的，并确保你在引导 AI 时，让它也把这些都考虑进去。而且这得是一场对话，需要来来回回。但我觉得，只要你愿意花功夫、花时间，它绝对能帮上忙，也绝对能帮你把思路理清。嗯，尤其是当你要求它对你保持批判、专挑毛病的时候。不过不同的模型，气质差别很大，就看它们……

[27:38] Adam

How willing they are to be pushed back. So [laughter] I I recommend picking one that likes pushing back.

……有多愿意跟你顶回来、唱反调。所以（笑）我建议挑一个爱唱反调的。

[27:44] Adam

Yeah. Mythos has gotten really good at being like, I can't do this. Let's let's move on. Like uh there's all these

对。Mythos 现在已经很擅长这一手了——它会说「这个我做不了，咱们翻篇吧。」就……有一堆这样的——

[27:49] Lenny

fun has always been a little bit of a jerk in a way that I actually appreciate.

Fable 一直有点儿「刺头」，但那种劲儿，我其实还挺欣赏的。

[27:55] Lenny

I truly

我是真的——

[27:55] Lenny

I appreciate it. I really do because I don't want one that's just like, "Oh, you're so right. I'm so sorry I said that." It's like, "No, hold on. I want I want, you know, I want the real real sort of intelligence. I don't want the pleaser. This point you made about people being excited about the strategy is such an interesting one. There's this idea that I read I think Cy Corey Doctr wrote this. There's this kind of concept of a centaur centaur and a reverse centaur. So centaur is a human body horse. This is going somewhere I promise. Uh human body uh horse sorry human upper part lower part

我真的很欣赏这一点。因为我不想要那种张口就是「哦你说得太对了，真抱歉我刚那么说」的模型。我要的是那种「不，等等」——我要真正的、货真价实的智能，我不想要一个只会讨好的应声虫。你刚说到人们会为一套战略而兴奋，这一点特别有意思。有个概念我读到过——我记得是 Cory Doctorow 写的——叫「半人马（centaur）」和「反向半人马（reverse centaur）」。半人马呢，就是人的身体加上马——我保证这是有下文的。呃，人的身体、马……不对，是上半部分、下半部分——

[28:28] Adam

horse body. Yeah. Yeah. Yeah.

是马的身体。对对对。

[28:29] Lenny

Horse body where the human is in charge. And that's kind of we prefer that we want to be in charge. reverse end chart, which is what we want to avoid with AI, is where the AI is controlling us and we're just doing its bidding.

马的身体，由人来主导。这正是我们偏爱的——我们想当那个掌控者。而「反向半人马」——就是我们在 AI 这件事上要极力避免的那种——是 AI 在控制我们，我们只是在替它跑腿、任它使唤。

[28:40] Adam

It's a horse head on a human body.

就是一颗马头长在人的身体上。

[28:42] Lenny

Yeah, exactly.

对，没错。

[28:43] Adam

It's terrifying.

那画面太吓人了。

[28:44] Lenny

Like in a sense like Uber drivers and Door Dash people kind of this is their life, which is not great

某种意义上，Uber 司机、DoorDash 送餐员的生活，多少就是这样，这可不太妙——

[28:50] Lenny

and [clears throat] this is the danger thing for a lot of people is like like if it's giving us the strategy and telling us here's what we're built, like no one's gonna want to do that. So that's a really interesting counterpoint to we don't want AI to be telling us the strategy almost.

而且对很多人来说，这才是真正危险的地方——如果 AI 直接把战略甩给我们，告诉我们「喏，你们要做的就是这个」，那没人会愿意干。所以这其实是个很有意思的反面论据，几乎是在说：我们并不希望 AI 来替我们定战略。

[29:02] Adam

Yeah. No, I I I think there's a lot of things to be careful about right now. And I would certainly not just assume that because you might be able to outsource some workflow to AI that you should. Um there are certain ones where I think it's really just a win-win. There are certain ones where I think is the risk outweighs the benefits. This episode is brought to you by Mercury. Radically different banking loved by over 300,000 entrepreneurs and now with command. I've been a customer of Mercury's for over 6 years. I have never once thought about leaving. Mercury is basically what happens when banking is built by product people, not by bankers. [music] They make it so easy, dare I say fun, to send invoices, move money around, set up virtual cards for folks on my team. Does your bank have an API, a terminal [music] native CLI, or an AI ready MCP server? I don't think so. And just recently, they launched Command, a conversational interface built directly into Mercury, which acts as your financial operator. I've been using [music] Command to transfer money around to figure out what categories I've been spending the most money [music] in, analyze my cash flows, and just today, I used it to find out how much I've made from a specific sponsor over the past year. I just asked, "How much have I made from X over the past year?" 10 seconds later, I have an answer. It [music] is so freaking cool. Visit mercury.com to learn more and apply online in minutes. Mercury is a fintech company, not an FDIC insured bank. Banking services provided through Choice Financial Group and column NA members FDIC. Okay, going back to product leadership, things you've learned along your journey. Uh, we were chatting ahead of this about just things you've learned and one thing that you said about some of the product the best product leaders you've worked with is that they're less visionary and more curators. I'd love to hear more along these lines. Yeah, I mean you do sometimes find amazing product leaders who are who are just like idea machines, just prolific idea machines.

对。不，我觉得眼下有很多地方需要小心。我绝不会因为「某个工作流也许能外包给 AI」，就想当然地认为「那就该外包」。嗯，有些流程我觉得确实是双赢；但也有些，我觉得风险大于收益。——本期节目由 Mercury 赞助。一种截然不同的银行服务，深受超过 30 万创业者喜爱，如今还带来了 Command。我做 Mercury 的用户已经六年多了，从没有一刻想过要离开。Mercury 基本上就是「当银行由产品人、而不是银行家来打造」时会长成的样子。（音乐）他们让开发票、转账、给团队成员配虚拟卡这些事变得无比简单，甚至可以说——好玩。你的银行有 API 吗？有终端里的原生 CLI 吗？有为 AI 准备好的 MCP server 吗？我看是没有。而且就在最近，他们推出了 Command——一个直接内建在 Mercury 里的对话式界面，充当你的财务操盘手。我一直用 Command 来回转账、搞清楚自己在哪些类别花钱最多、分析现金流；就在今天，我还用它查了过去一年我从某个特定赞助商那儿一共赚了多少。我就问了一句：「过去一年我从 X 那儿赚了多少？」10 秒钟后，答案就出来了。这也太酷了。访问 mercury.com 了解更多，在线几分钟就能申请。Mercury 是一家金融科技公司，并非受 FDIC 保险的银行。银行服务由 Choice Financial Group 和 Column N.A. 提供，两者均为 FDIC 成员。——好，我们回到产品领导力，聊聊你这一路学到的东西。呃，我们录之前聊到你的一些心得，其中你提到——你共事过的那些最优秀的产品负责人，与其说是「有远见的空想家」，不如说更像是「策展人（curator）」。我很想多听你讲讲这方面。对，我是说，你确实有时会遇到特别厉害的产品负责人，他们简直就是「点子机器」，源源不断地往外冒点子。

[31:11] Adam

But I do think a lot of the best are have have taste are have something about them that really makes wants makes really strong talent want to work with them but end up sort of being curators. curators of people, curators of ideas, curators of technologies, curators of strategies, because I don't really care if I'm hiring a strong lead for an area if the strategy comes from them or comes from somebody else. I just care that there is a amazing strategy and everyone has bought into it and that the and then we're executing against that strategy well. And so I think that some of the best product leaders, yes, have ideas. It's hard to be a great curator if you don't have some of your own ideas, but are that embrace the reality that they can't come up with everything themselves. And so they need to create an environment in which great ideas bubble up and are uh chosen or decided upon. And so, you know, I think it's not just about curating ideas, but it's sometimes about curating teams and people.

但我确实觉得，很多最顶尖的人，身上都有一种「品味」，有某种特质，让真正强的人才愿意跟着他们干，而他们最终扮演的，其实是「策展人」的角色。策展人才、策展点子、策展技术、策展战略。因为如果我在为某个领域招一个强力负责人，我其实并不在乎那套战略是出自他本人、还是别人——我在乎的只是：有一套极好的战略，所有人都认同它，然后我们把它执行到位。所以我觉得，最优秀的那批产品负责人，没错，他们是有自己的点子——如果你自己一点想法都没有，也很难成为一个出色的策展人；但他们同时坦然接受一个现实：不可能所有东西都靠自己想出来。所以他们需要营造一种环境，让好点子能够自然冒出来，再从中挑选、拍板。所以你看，我觉得这不只是在策展点子，有时更是在策展团队、策展人。

[32:13] Lenny

I love that. I so agree. I feel like everyone's always joining a team and they just want to do vision strategy just like not actually hands-on work and no AI is coming in here. Let me do the strategy.

我太喜欢这个说法了，我完全同意。我总感觉，每个人加入一个团队，都只想做愿景、做战略，而不想真的撸起袖子干活。就好像——「这块 AI 别进来，让我来定战略。」

[32:24] Lenny

Exactly.

没错。

[32:26] Lenny

And I love this point that there's so much power and value and people underestimate just the the need for just like a really good curator of of the team's ideas.

我特别喜欢这个观点——大家都低估了「一个能把团队各种想法梳理、筛选好的优秀策展人」到底有多大价值和能量。

[32:35] Adam

Yeah. Sometimes it's also sometimes it's not just who's good or what idea is good. It's also what is going to work given the broader context. So for instance on team building a huge thing that I'm always considering is not just like is this person a really strong candidate for this role. it is how does this person fit into their leadership team you know so if I you know for some an area like trust and safety you know I have an engineering lead I have a product staff lead I have a data science lead I have a design lead I have a research lead you know I need to make sure that those five complement each other I need to make and that's you know about what skills each one has what weaknesses each one might have I also need to make sure that they um this is more art than science have a good vibe, right? You know, you need, you know, trust and rapport. A leadership team with strong trust and rapport can work through most anything. A leadership team without trust or rapport, like anything can become an issue. And so that that chemistry bit is is is like I said much more art than science, but that also matters. And so I think some of the best leaders and product leaders specifically also either do that instinctively or consciously, but you know they have a they have a nose for for building teams that are going to have good energy and um good collaboration,

对。而且有时候，关键不只是谁厉害、哪个想法好，还得看在更大的背景下什么才真正行得通。比如说搭团队的时候，我一直特别在意的一点，不只是「这个人是不是这个岗位的强候选人」，而是「这个人放进他所在的领导团队里合不合适」。举个例子，像 trust and safety（信任与安全）这块，我下面有工程负责人、有产品负责人、有数据科学负责人、有设计负责人、还有研究负责人。我得确保这五个人是互补的——这既关乎每个人有什么技能，也关乎每个人可能有什么短板。同时我还得确保他们之间——这事儿更像艺术而不是科学——氛围要对，对吧？你需要彼此的信任和默契。一个信任和默契都很强的领导团队，几乎什么难题都能扛过去；而一个缺乏信任和默契的领导团队，任何一件小事都可能变成大问题。所以这种「化学反应」的部分，就像我说的，更像艺术而非科学，但它同样很重要。所以我觉得，那些最顶尖的领导者、尤其是产品领导者，要么凭直觉、要么有意识地在做这件事——他们对「怎么搭出一个有好能量、协作顺畅的团队」有一种天生的嗅觉。

[33:59] Lenny

warm and fuzzy stuff.

就是那些温情脉脉、讲感觉的东西。

[34:01] Adam

Yeah. Yeah. Well, the flip is also true, right? Like I've I've had many times in my career I've had two people who I think are amazing and I even adore them and love them and they just can't get along. [laughter] You're like this isn't a competency issue. This is just a personality issue and you just have to just sometimes call it and split them.

对对。不过反过来也成立，对吧？我职业生涯里好多次遇到这种情况：两个我都觉得特别棒、甚至打心底喜欢和欣赏的人，可他们俩就是合不来。[笑] 你会意识到，这不是能力问题，纯粹是性格不合，有时候你只能果断认了，把他俩分开。

[34:23] Lenny

I want to transition talk to talk about Instagram the product the platform things you guys have learned there. Let me start with this question. What's something that the Instagram algorithm knows about human behavior that people may not realize?

我想把话题转到 Instagram 上——聊聊这个产品、这个平台，以及你们在其中学到的东西。先问你这么个问题：Instagram 的算法对人类行为有什么了解，是大家可能意识不到的？

[34:38] Adam

One of the most common misconceptions is actually in the opposite direction. I think people assume that there's a much more detailed semantic understanding of everybody's interests and preferences in the algorithm than there is. Most of what's really driven the progress in the world of recommenders over the last 5 10 years have been, you know, these large embedding models and these other techniques that basically produce artifacts that cannot be read by people. They're not legible. They're like giant vectors. It's like, sure, I can show you the vector, but it's just going to be a bunch of numbers in like a seven dimensional space. It's like, and so when when we talk about does the algorithm know something, usually we think in these more semantic terms. It knows I like surfing and it's like it doesn't. It just has this big ass number that happens to correlate with surfing. Um, that said, I think that is starting to change, right? I think that what one of the things that LLMs are enabling is they can describe in you know words you know English for or whatever language you prefer what some of those previously illeible artifacts um are at least approximate to if not mean directly right so this is like the thing I've been really I posted about this this week this thing called your algorithm basically the idea is we take a look at all of the stuff that you've interacted with. And then you know we all of that is in an embedding space. You can think of embedding space as a map. You can map a bunch of videos into the same map. And so videos that are close or similar. And now we can just have an LLM just be like describe that part of the map. And it can be like oh that is like deep pourover coffee snobbery. Um and that's kind of amazing.

最常见的一个误解，其实方向正好相反。大家以为算法对每个人的兴趣和偏好，有一种非常细致的语义层面的理解，但实际上远没有那么细。过去五到十年，真正推动推荐系统进步的，主要是那些大型 embedding 模型以及其他一些技术，而它们产出的东西基本上是人类没法读懂的，是不可读的。它们就是一堆巨大的向量。我当然可以把向量给你看，但那不过是七维空间里的一串数字而已。所以当我们讨论「算法是不是知道某件事」时，我们通常是用语义的方式在想——比如「它知道我喜欢冲浪」。但其实它并不知道，它只是有一串巨大无比的数字，恰好和「冲浪」相关联而已。不过话说回来，我觉得这一点正开始改变。LLM 带来的一个改变是：它能用文字——英文也好、你喜欢的任何语言也好——把那些原本不可读的东西描述出来，就算不是精确对应，至少也能给出一个近似的意思。这正是我这周发帖聊的一个东西，叫「你的算法」。基本思路是：我们把你互动过的所有内容看一遍，这些内容都存在一个 embedding 空间里。你可以把 embedding 空间想象成一张地图，把一堆视频都映射到同一张地图上，靠得近的视频就是相似的。然后我们就可以让 LLM 去描述地图上的某一块区域，它可能会说「哦，这块是那种骨灰级手冲咖啡挑剔党」。这挺神奇的。

[36:29] Lenny

That is so cool

这也太酷了。

[36:30] Lenny

that like you can ask the LM to look at these numbers and extrapolate. here's like the topic that you're interested in.

就是说，你可以让 LLM 去看这些数字，然后推断出「这就是你感兴趣的主题」。

[36:36] Adam

Yeah. Or look at the videos.

对。或者让它去看那些视频。

[36:38] Adam

And so the way you um both So you can also embed concepts into that same space. And so I mean embeddings are really the underlying technology underneath LLMs, right? That's how all the whole thing works. And so you know, so what what we what we what we do now is we let you, you know, quote unquote see your algorithm. You can see what topics we think you're interested in. Um and you can adjust it. You can add and remove things, but the idea here giving people some agency back in a world where, you know, these social media apps are getting taken over by recommendations, but we can't do a lot of other things yet, which we will be able to do. You know, you could there's things that aren't topical that you might ask for. I want more fun content. I want to see my friends more. I don't want to see my high school's kids friends kids photos. You know, I don't know. We can come up with I don't want to see seven photos in a row, but I'm happy to see six photos in a whatever your heart can, you know, whatever your mind can come up with. So, we have a lot of work to do. And so, I'm excited about that. But, um, I think a misconception historically is until recently, we don't really know as much about you as you think. We were just like, oh, like you liked these photos, this these people also like those same photos and they like these other photos, so you might like those other photos. Like that's kind of how I'm oversimplifying, but that's like

而且你也可以把「概念」本身嵌入到同一个空间里。我的意思是，embedding 其实就是 LLM 底层的核心技术，整套东西就是靠它运转的。所以我们现在做的，就是让你可以——打个引号——「看见你的算法」：你能看到我们认为你感兴趣的那些主题，而且你可以调整它，可以增加或删掉一些主题。但这背后的想法是：在这个社交媒体越来越被推荐算法主导的世界里，把一部分掌控权还给用户。只是目前还有很多别的事我们做不到，但将来是能做到的。有些需求其实跟「主题」无关，但你可能也想提，比如「我想多看点有意思的内容」「我想多看到我朋友的动态」「我不想再看到我高中同学的孩子的照片」。或者「我不想连着看到七张照片，但连看六张我没问题」——反正就是你心里、你脑子里能想到的任何需求。所以我们还有很多事要做，我对这个方向挺兴奋的。但我想说，一直以来的一个误解是——至少直到最近为止——我们其实并没有你以为的那么了解你。我们无非是这么想的：「哦，你喜欢了这些照片，而另一些人也喜欢这些照片，同时他们还喜欢另外那些照片，所以你可能也会喜欢那些照片。」我这么说是把它简化了，但大致就是这么回事。

[37:59] Lenny

yeah,

嗯。

[38:00] Adam

kind of how it worked. Now only now are we actually getting as sophisticated as I think people have assumed we've been for many years.

大致就是这么运作的。直到现在，我们才真正做到了大家多年来一直以为我们早就具备的那种精细程度。

[38:06] Adam

That is really interesting. One that comes to mind is kind of this transition everyone eventually goes through to this like algorithmic broad global feed. Uh everyone it always feels like people think I just want to see chronologically everyone I know and follow and that's going to be my favorite feed and it continues to be proven wrong. No, you actually engage a lot more a lot more when it's this algorithmic feed of things we think you will love. Yeah, it's tough because I mean I get I mean I posted this week this thing about agency and I just got destroyed in the comments which is just part of the job. I get it right. Um do you there's but there are a couple issues with the algorith with the chronological feed. So one is and some of this is the tension between an individual's interests and what works when you scale it up, right? So if you do a pure chronological feed, the incentive for everybody is to just post as much as possible uh because it will always be at the top of everyone who follows you's feed as soon as you post. So what ends up happening is that the feed gets overwhelmed with professional content with usually large company content and publishers because they get, you know, the New York Times can pump out 50 things a day. your your best friend won't you might get one thing a week from them and so your fee just gets taken over. Um so part of it is the incentives that emerge because when you when you design these systems it's almost like designing a city. You need to think about okay here's the here are the here's how the mechanics work. What are the incentives that arise? How are people going to act within those incentives? And then what happens? And the other thing is sometimes the most interesting thing was just not the most recent thing. Recency is an important input into relevance, but it's not the only one. My sister got engaged last night and you know she's in Germany.

（Lenny：这真的很有意思。我想到的一个例子，是几乎每个平台最终都会经历的那种转变——转向一个由算法驱动的、更宽泛的全局 feed。大家总觉得「我就想按时间顺序看到我认识、我关注的所有人的动态，那才是我最爱的 feed」，可这个想法一次又一次被证明是错的。事实是，当 feed 变成算法推给你的那些「我们觉得你会喜欢」的内容时，你的参与度反而高得多。）对，这事儿挺难的。我懂大家的心情——我这周发了篇讲「用户自主权」的帖子，评论区把我喷得体无完肤，不过这也是这份工作的一部分，我理解。但按时间顺序排列的 feed 其实有几个问题。第一个问题，部分源于「单个用户的利益」和「放大到整个平台规模后什么才行得通」之间的张力。如果你做一个纯时间顺序的 feed，那对所有人来说，激励就是拼命多发——因为你一发，它就会立刻出现在所有关注你的人的 feed 顶部。最后的结果就是，feed 被专业内容淹没，通常是大公司的内容和各种发布方——因为他们产能高，比如 New York Times 一天能发 50 条，而你最好的朋友做不到，你一周可能才收到他一条动态，于是你的 feed 就被那些机构内容占领了。所以一部分原因在于系统里冒出来的这些激励。设计这类系统，几乎就像在规划一座城市：你得想清楚「这套机制是怎么运转的」「它会催生出什么样的激励」「人们在这些激励下会怎么行动」「然后又会导致什么后果」。另一件事是，有时候最有意思的内容，恰恰不是最新发布的那条。「新近程度」是判断相关性的一个重要输入，但它不是唯一的。比如我妹妹昨晚订婚了，你知道她人在德国。

[39:57] Lenny

No, she didn't. If she did, she's married.

不，她没订婚吧。她要真订了，那不早就成已婚了嘛。

[40:00] Adam

She got married last year. That's why it was top of mind.

她去年结的婚，所以这事儿才一直在我脑子里。

[40:02] Lenny

All right.

好吧。

[40:02] Adam

But if she got engaged, you know, and I missed it because she lives in Europe and you know, we're different time differences. Like, do I really want to see a picture of like my brother's pobo sandwich, you know, poboy sandwich, or do I want to like see my sister's things first? So, I I It's tough. It's tough. I'd love to figure out a way to find the right balance. I want to give people agency over the experience, but I think it needs to be in a way that creates a system that makes sense, not just for us as a business, which matters. I'm not pretending that's not an issue, but also for the overall community because we've done chronological by default and where you can make it default and you see not only does usage go down, overall sentiment goes down. the individual who made that choice might be happy at the moment, but when you just get pummeled with stuff you're less interested in over the course of months, we ask, we run surveys at massive scales, we just see people start to become less and less satisfied with Instagram.

但假设她真订婚了，而我因为她住在欧洲、有时差就错过了，那这时候，我到底是想先看到我哥晒的一张 po'boy 三明治的照片，还是想先看到我妹妹的动态？所以说，这事儿很难，真的很难。我特别想找到一种办法，把这个平衡拿捏好。我想把体验的掌控权交给用户，但我觉得这得用一种能让整个系统合理运转的方式来做——不光是对我们这门生意合理（这当然重要，我也不装作这不是个问题），也得对整个社区合理。因为我们试过把「按时间顺序」设为默认，也试过让用户可以自己设成默认，结果你会发现：不仅使用时长下降了，整体满意度也在下降。做出这个选择的人，当下可能是开心的，但当你在接下来的几个月里，不停地被那些你没那么感兴趣的内容轰炸——我们做过大规模的问卷调查——就会看到用户对 Instagram 的满意度越来越低。

[40:57] Lenny

Kind of along these lines, uh, everybody asks you about this these days, uh, AI and content and how that all impacts everything that's going on. I want to ask you something I haven't seen someone ask you. Is the rise of AI content uh a headwind or a tailwind for Instagram versus other platforms? Do you think this helps or hurts you guys?

顺着这个话题，最近大家都在问你 AI 和内容、以及这一切对现状的影响。我想问一个我还没见别人问过你的问题：相比其他平台，AI 内容的兴起对 Instagram 到底是逆风还是顺风？你觉得这对你们是利还是弊？

[41:17] Adam

I think it's going to be a tailwind, but I think it's going to be a challenge. It's And not just because it's more content. Obviously, we're an attention business driven business. We're an advertising business. More content means potentially more attention. It that's not for free, though. Like, I don't think we're very good at ranking AI content yet. There's great AI content. There's crap AI content. you should just see the stuff you're interested in and not any of the stuff you're not interested in. But I do think that in a world where or for years now and I've said this many times, power shifting from institutions to individuals across industries, the easiest example is sports where players are more relevant than teams now. And that was not the case when I was a kid. In that world, you're gonna I think it behooves us to invest in individuals and to invest in specifically for Instagram and creators. And I mean creators broadly. I don't just mean influencers who are promoting branded content and making, you know, native only videos. I mean anybody who's using platforms like Instagram to help do what they do, right? It could be you could be a journalist, you could be an artist, you could be selling scarves you sew, but like you're out there as yourself. for creating and sharing content that helps you achieve whatever it is you're trying to do. So, we've been leaning in that direction for many years now. That's been our, you know, one of our two or three most important audiences for as long as I've been on Instagram. In a world where there's an abundance of synthetic content, I actually think people are going to seek out creativity and authenticity and people [snorts] more, not less. And I think that that will help us. That doesn't mean that we won't have AI content on our platform. There's going to be bad and good AI content and we're going to try and handle that, you know, the way we normally handle content. So unsafe goes away. Interesting versus not interesting is based on ranking and personalization. Um, but I think people are going to really seek out other points of view because Instagram was never just about the content.

我认为它会是顺风，但同时也会是个挑战。而且不只是因为内容变多了。很显然，我们是一门靠注意力驱动的生意，是广告生意，内容更多就意味着潜在的注意力更多。不过这可不是白来的——我觉得我们目前对 AI 内容的 ranking 做得还不够好。AI 内容里有很棒的，也有很烂的，理想状态是你只看到你感兴趣的，而完全看不到你不感兴趣的。但我确实认为——这些年我也讲过很多次——在各行各业，权力正从机构转移到个人。最简单的例子就是体育：如今球员比球队更有影响力，而我小时候完全不是这样。在这样一个世界里，我觉得我们理应去投资「个人」，具体到 Instagram，就是去投资创作者。我说的创作者是广义的，不只是那些推广品牌内容、专做原生视频的网红，而是任何借助 Instagram 这类平台来做自己事情的人。你可能是记者，可能是艺术家，也可能是在卖自己手缝的围巾——但你是以「你自己」的身份出现，去创作和分享内容，帮你实现你想达成的任何目标。所以这么多年来，我们一直在往这个方向倾斜。自我到 Instagram 以来，创作者一直是我们最重要的两三类用户之一。在一个合成内容（AI 生成内容）泛滥的世界里，我反而觉得人们会更加、而不是更少地去主动寻找创造力、真实感，以及「活生生的人」。我认为这对我们是有利的。这并不意味着我们平台上不会有 AI 内容。AI 内容有好有坏，我们会按平时处理内容的方式来处理它：也就是说，不安全的内容会被清掉；至于有意思还是没意思，则交给 ranking 和个性化来决定。但我觉得人们会真的去寻找不同的视角，因为 Instagram 从来就不只是关于内容本身。

[43:16] Adam

It was always about to a certain degree the person behind the content, the point of view, the reason they're sharing it, their perspective. And I think that's going to become more important, not less. And I think given that we are not the best at a lot of things, but we are the largest uh creator platform, you know, you know, if you look at how we define creators and how many creators use us versus other platforms, I think it'll be a tailwind for us because I think people are going to seek out people.

它在某种程度上，一直都关乎内容背后的那个人——他的观点、他分享的理由、他看待世界的视角。我认为这一点会变得更重要，而不是更不重要。而且我觉得，虽然我们在很多方面都算不上最强，但我们是最大的创作者平台——按我们对创作者的定义，看看有多少创作者在用我们、再对比其他平台，你就明白了。所以我认为这对我们是顺风，因为人们会去主动寻找「人」。

[43:42] Lenny

And this connects to your earlier point that uh companies uh like say New York Times can pump out a bunch of AI content versus a creator. And so you're saying you kind of want to protect against that, too. Allow individuals to continue to perform well in spite of just all this AI content.

这也呼应了你前面提到的那点：像 New York Times 这样的公司可以批量生产一大堆 AI 内容，而单个创作者做不到。所以你的意思是，你们也想防范这一点，让个人在这么多 AI 内容的环境下依然能有好的表现。

[43:58] Adam

If you just love AI content, great. Like, you should be able to have a feed that's just like AI town. And if you don't, then you shouldn't have it in your feed. Like, you know, to me, it's like I don't think we should I mean, I understand why people are, right? There's a I'm not oblivious to the overall paradigm shift and sort of revolution that we're sitting in. But I don't think we should judge content based on the tool that made it. Um I think we should judge it based on the content, the point of view, the person behind the content. Like I don't I don't think we should filter out AI content. I think we should let you know if content is AI content or not. I think we should let you know more about the person who posted anything so that you can make informed decisions about whether or not to believe or trust them based on, you know, knowing who they are or where they are or how many times they've changed their profile or, you know, you know, if their profile is three days old or three years old. Um, but I don't think we should be making value judgments based on what tool you used.

如果你就是喜欢 AI 内容，那太好了，你完全应该能拥有一个像「AI 小镇」一样的 feed；而如果你不喜欢，那它就不该出现在你的 feed 里。对我来说……我并不觉得我们应该……我当然理解大家为什么会担心，对吧？我也不是没意识到我们正身处这场整体的范式转变和某种革命之中。但我不认为我们该根据「内容是用什么工具做出来的」去评判它，我认为我们该评判的是内容本身、它的观点、以及内容背后的那个人。我不觉得我们该把 AI 内容一刀切地过滤掉，我觉得我们该做的是告诉你：这条内容是不是 AI 生成的。我觉得我们该让你更多地了解发布内容的这个人，好让你能基于信息做判断——要不要相信、要不要信任他，取决于你知道他是谁、他在哪儿、他改过多少次资料、他的账号是三天前注册的还是三年前注册的。但我不认为我们该根据「你用了什么工具」来做价值判断。

[44:59] Lenny

Is there an AI uh content creator you love that you're just like, "This is so good. I love watching these AI videos." Yeah. What is she called? Plastic plastic dream sequence. Is that what it is?

有没有哪个你特别喜欢的 AI 内容创作者，让你觉得「这也太棒了，我爱看这些 AI 视频」？对了，那个叫什么来着？Plastic Dream Sequence（塑料梦境）？是这个名字吗？

[45:11] Adam

Um I think I'll check the name. Yeah. Plastic dream. Uh

嗯，名字我回头确认一下。对，Plastic Dream。

[45:15] Adam

um plastic dream sequence. I have it on my phone. I'll double check. Um it's these like uh like sort of dolls, Barbies, but they're like singing songs and these little tiny little silhouettes and snippets. And it's just it's just amazing. It's like a little weird, but like also kind of amazing. And it's it's very clearly AI. It's not pretending not to be, but it's has a very clear creative and aesthetic point of view. And every time I come by one, I'm like, "Yep, we're doing this now. I'm going to watch this for 30 seconds."

嗯，Plastic Dream Sequence，我手机里存着，回头我再核对下。它做的是那种……有点像玩偶、芭比娃娃，但它们在唱歌，还有那些小小的剪影和片段。真的特别惊艳。是有点怪，但也确实挺神的。而且它非常明显就是 AI 做的，它并不假装自己不是 AI，但它有一套非常清晰的创意和审美主张。每次刷到，我都会想：「行吧，那我就看它个 30 秒。」

[45:47] Lenny

I have it pulled up here. And I don't I want to watch it, but I'm not going to. [laughter]

我这会儿正把它调出来了。我……我挺想看的，但还是忍住不看。[笑]

[45:52] Adam

That's awesome.

太棒了。

[45:53] Adam

If Only AI, that's another one. He's out of He's in France. I think he's in Paris. He uses multiple different tools and models, but he kind of tries to create these dreamscapes and animate them. So he create uses one model to create the image, another one to create the video, music, etc. Uh he's like very clearly got his own aesthetic. Um u and he's just like you could you could think of him as a painter, but like this is his tool.

If Only AI 是我喜欢的另一个。他在法国，我记得是在巴黎。他会用好几种不同的工具和模型，专门去创作那种梦境般的场景并让它们动起来：用一个模型生成图像，再用另一个生成视频、配乐等等。他显然有一套非常鲜明的个人审美。你完全可以把他看成一个画家，只不过这些 AI 工具就是他的画笔。

[46:18] Lenny

Is there kind of a vision of AI versus human in the feed? Do you think it'll like you said you maybe want to market like how do you think about people? Are they going to be like AI count, not AI count? How do you think about or is that still kind of a work in progress?

关于 feed 里「AI 内容」和「真人内容」的关系，你们有没有某种设想？你刚才提到可能想给内容做标注——那你是怎么看待「人」这件事的？会不会分成「AI 账号」和「非 AI 账号」？你是怎么想的，还是说这块目前还在摸索中？

[46:31] Adam

Maybe we'll end up in the same place, but there's a difference between marking content and marking accounts and they're both useful and interesting. So, if content was created with AI, I think you should be able to know that. That's hard by the way because we can detect that right now, but as these models get better, we might lose the ability to detect that. So, we should also be very careful to be honest with you about how confident we are in our own sort of assessment. Um, but I think you should be able to just ask be like, "Hey, is this AI?" And we should be able to tell you. We think it probably is or we're not sure or it's definitely not or it definitely is. I actually think we might be might be more practical to to label camera captured content like basically non-AI content as opposed to labeling AI content long term for a couple of reasons.

也许我们最后会殊途同归，但「标注内容」和「标注账号」是两回事，两者都有用、也都值得做。如果一段内容是 AI 生成的，我觉得你应该有权知道。不过说实话这很难，因为现在我们能检测出来，可随着这些模型越来越强，我们可能会失去检测能力。所以我们也得非常诚实地告诉你，我们对自己的判断到底有几分把握。但我觉得你应该能直接问一句「嘿，这是 AI 吗？」，而我们就该能回答你——我们认为它多半是、或者我们不确定、或者它肯定不是、或者它肯定是。其实我觉得长期来看，更实际的做法可能是去标注「相机拍摄的内容」，也就是标注「非 AI 内容」，而不是去标注 AI 内容，这里面有几个原因。

[47:17] Adam

But then at the account level, I think it also matters. There is definitely an a new spam vector which is these fake accounts which by the way an AI creator that's fine there's nothing wrong with that necessarily but there is there are these spam vectors which are trying to abuse that and you know they're selling like you know bogus supplements and it's like an AI monk and it doesn't present it's not obvious that it's an AI and it's just trying to like take advantage of you know a certain aesthetic or a certain sort of stereotype like we need to figure out how to crack down on that And so I do think I do think we should be making sure that you know basically you just need to know and then you can make your own informed decision. Is the account a real person or not? Is the content a real piece of content or not?

但在账号这个层面，我觉得同样重要。现在确实冒出了一种新的垃圾信息套路，就是这些假账号——顺便说一句，一个 AI 创作者本身完全没问题，这没什么不对；但确实有人拿它来钻空子、搞垃圾营销，比如卖那些没用的保健品，弄一个 AI 生成的「僧人/大师」人设，还不明说、根本看不出来是 AI，就是想利用某种审美调性、某种刻板印象来占你便宜——这种东西我们得想办法整治。所以我确实觉得，我们要做的基本就是：让你能知道真相，然后你自己去做明智的判断。这个账号背后到底是不是真人？这段内容到底是不是真实的内容？

[48:01] Lenny

When you think about other platforms uh in the space social you know content platforms are there any um features or just or like ways of of of approaching stuff that they do well that you're kind of jealous of or really impressed by?

说到这个领域里的其他平台——那些社交、内容平台——有没有哪些功能，或者哪些做事的思路，是他们做得特别好、让你有点羡慕、或者真心佩服的？

[48:15] Adam

Yeah, there's a bunch. everybody. So many people do so much because I mean for me like one of the things that we are finally catching up with but I've been always very impressed with is Tik Tok and their recommenders ability to break small talent. Um, in the world of ranking and recommenders and rank, um, you can talk about exploitationbased ranking. That sounds terrible, but it just means like using the data you have. And then you can talk about exploration based ranking, going and trying to figure out, you know, what someone might be interested in that they might even not know they're interested in yet. And it is much easier to move engagement by showing people stuff that, you know, they'll probably like because lots of people like it. it's much harder to go and figure out how to essentially test content so that we can see like hey maybe you sure you like Bieber but you might also like Afrounk and so we're just going to like show you some Afrounk and see what happens. If you do the latter, this exploration based ranking, you can I think it's really good for niche creators and small creators because you give them a chance to find an audience that either wasn't going to see them before or didn't even know that they were interested before. So, we've invested a lot over the last couple years in ranking, not just increasing engagement, but increasing originality, increasing the number of uh pieces of content that break out, uh increasing recency to stay culturally relevant. And so a lot of that has been inspired by by Tik Tok and bite dance. I think we're catching up. Um there's actually a couple of those areas where we I think by best we can tell we're ahead of them. There's a couple where we're still behind, but for we have line of sight to I think being the best in class at recommendations for the first time um during my tenure. Uh so that's I think and they get a lot of credit for inspiring a lot of their work.

有不少。太多了，很多人都做得很好。对我来说，有一点是我们现在才终于追上、但我一直特别佩服的，那就是 TikTok，以及它的推荐系统捧红素人创作者的能力。在排序和推荐这个领域里，有一种叫「利用型排序」（exploitation-based ranking）——这词听着挺吓人，但意思其实就是拿你手头已有的数据去推。另一种叫「探索型排序」（exploration-based ranking），就是主动去摸索那些你可能感兴趣、甚至你自己都还不知道会感兴趣的东西。给人推那些「反正很多人都喜欢、你大概率也会喜欢」的内容，是很容易拉动互动的；但要搞清楚怎么去试探性地投放内容就难多了——比如「嘿，你确实喜欢 Bieber，但说不定你也会喜欢 Afro-funk，那我们就给你推点 Afro-funk，看看会怎样」。如果你做的是后者这种探索型排序，我觉得它对小众创作者、小创作者特别有利，因为你给了他们一个机会，去找到那些原本根本刷不到他们、甚至自己都还不知道会感兴趣的受众。所以过去这几年我们在排序上投入了很多，不只是提升互动，还要提升原创性、提升「出圈」内容的数量、提升内容的时效性以保持文化相关性。这里面很多灵感都来自 TikTok 和字节跳动（ByteDance）。我觉得我们正在追上来。其实有那么几个方面，就我们目前所能判断的，我们已经领先他们了；还有几个方面我们仍然落后，但我们已经看得到路径——我觉得在我任内，我们第一次有望在推荐这件事上做到业界最佳。所以这一点上他们功不可没，是他们启发了我们很多工作。

[50:05] Lenny

Nice job.

干得漂亮。

[50:07] Adam

Well, we'll see. We're not there yet. [laughter] They call me disappointed dad. My team is always like, "Can you ease up on the disappointed dad vibe?" So, I'm I'm trying to trying to be a little bit more um generous about giving people their flowers.

还得再看吧，我们还没到那一步。（笑）他们都叫我「失望老爸」。我的团队老是跟我说：「你能不能收一收那个失望老爸的气场？」所以我在努力，努力做得更大方一点，多给别人应得的肯定。

[50:22] Lenny

Like you say that, but that's an interesting common thread across really successful leaders is just never being satisfied.

你嘴上这么说，但这其实是所有真正成功的领导者身上一个挺有意思的共同点——就是永远不满足。

[50:29] Adam

Yeah.

对。

[50:29] Lenny

Always feeling a blessing and a curse.

永远觉得这既是福气也是诅咒。

[50:31] Adam

Here's all the problem. It is. Yeah. on this creator piece. I think that's also, you know, people uh complain about this global algorithm not showing them all their friends, but I feel like this is a benefit of what happens when you do this now that you can break new creators into wide audience if you have this kind of global algorithmic feed, which is really great for a lot of people.

问题就在这儿，确实是这样，对。就说创作者这块吧，我觉得——你知道，有人会抱怨这种全局算法没把他们好友的内容都推给他们，但我倒觉得这恰恰体现了这么做的好处：一旦你有了这种全局算法信息流，你就能把新创作者推到很广的受众面前，这对很多人来说其实非常棒。

[50:55] Adam

I mean, I'm out there talking about a lot of these contentious issues and I get beat [clears throat] up a lot in the comments, which is fine. My main thing here is just to try to communicate that there's almost always trade-offs, right? There's that, you know, you can't just have all of the things, unfortunately. You know, you want to have um you you want to never see something you're not interested in, then you're also just going to see like the most basic general lowest common denominator stuff all the time. You know, you want to discover new and interesting things. you're occasionally going to see stuff that was just a miss, you know. You know, but this isn't just true about ranking. These all all these major debates have trade-offs, right? You know, uh privacy and safety, those two things are intention. You know, do you do you want a company scanning your messages or not? There's some really significant trade-offs on both sides of that debate. Um and so generally speaking, when I argue and engage in debate with people who feel really strongly about things, I'm not usually trying to convince them. They usually their mind is usually made up. I'm just trying to enumerate all of the different puts and takes for the rest of the people watching the conversation.

我经常公开去谈这些有争议的话题，评论区里我没少挨骂（清嗓子），这没关系。我的核心诉求就是想传达一点：几乎任何事情都存在取舍，对吧。很遗憾，你没办法什么好处都占了。你想永远不刷到自己不感兴趣的东西，那你就只能天天看到那些最基础、最大众、最没门槛的内容。你想发现新鲜有趣的东西，那你偶尔就会刷到一些纯属失手的推荐。而且这不只是排序的问题——所有这些重大争论都存在取舍，对吧。比如隐私和安全，这两件事本身就是相互冲突的。你希不希望一家公司扫描你的私信？这个争论的正反两面都有非常实打实的代价。所以总的来说，当我跟那些对某些事情立场特别强硬的人争论、交锋时，我通常并不是想说服他们——他们一般主意早就定了。我只是想把各种利弊、各种正反考量都一条条摆出来，给那些在旁边看这场对话的其他人看。

[52:06] Lenny

Speaking of getting torn apart in the comments, like you're so in the middle and thick of all of these really hairy situations, changing the feed, you're like in the Cambridge Analytica lawsuit, all this just like you're in the center of so much controversy and is that some

说到在评论区被撕，你可是身处所有这些特别棘手的处境的正中央——改信息流、卷进 Cambridge Analytica 的官司，诸如此类，你就处在这么多争议的风暴眼里。这是不是……

[52:24] Lenny

Yep. [laughter] Oh man. Is that just like you I will lean into this. This is the thing I need to do. Or was it like Zuck being like Adam you got to be the front face of all the stuff and get in there? Like where does that come from?

（笑）哎哟。这到底是——是你自己那种「我就要迎难而上、这是我必须做的事」？还是 Zuck 跟你说「Adam，你得去当这一切的门面，你上」？这是从哪儿来的？

[52:38] Adam

It started on newsfeed. So I used to run newsfeed at Facebook and I my take was that the debate was going to happen with or without us. So we might as well participate. And so I started being really active on Twitter specifically because that's where journalists really lived at the time. And I thought it would be show some humility to show up on their turf, so to speak. My Twitter ended up being like the most the darkest place in my life because I just followed all of our biggest critics. That's not a dig on Twitter. That was just what I did.

这事是从 Newsfeed 开始的。我以前在 Facebook 负责 Newsfeed，我当时的想法是：这场争论无论有没有我们参与都会发生，那我们还不如亲自下场。所以我开始特别活跃地泡在 Twitter 上，专门泡 Twitter，是因为那时候记者们真的都在那儿。我觉得跑到他们的地盘上、算是放低姿态、展现一点谦逊。结果我的 Twitter 变成了我人生中最黑暗的地方，因为我把我们最大的那些批评者全关注了个遍。这不是在黑 Twitter，纯粹是我自己作的。

[53:07] Adam

Um, and that's where it started and it kind of slowly built from there. For better, for worse, we've become a really important part of daily life for a lot of people. We touch a lot of people. We have a lot of responsibility and there's a lot of change and there's with change means there's going to be anxiety and stress and scrutiny. We've made great decisions. We've made mistakes. Um we've been criticized for things that I think um we've been criticized unfairly. We've been criticized fairly. And so we just need to accept that this debate is gonna happen broadly. So I just think it's better for us to talk about it um and just be clear about what we're doing, why we're doing it, what the trade-offs are. If people disagree, that's okay. We're not necessarily, you know, winning over friends when we talk about what we do. But I think over the long run, people are fundamentally more afraid of things that they don't understand um and about things where people are more secretive and less accessible. And so I've been tried I've tried to show up in an accessible and authentic way. Um and I've made mistakes and I [snorts] have enjoyed it at times and hated it at other times. Um but that's kind of how it started. There was also kind of a fun debate in Mark's sort of senior leadership team a long time ago where we were just talking about how we're a social media company where we had like a very sort of conventional approach to communication and like press releases and why don't we just use our platform. So, um, I was not in that debate, but I stuck myself into that debate, trying to mediate it. And I think, um, but that was also a reason why I ended up getting sucked in, because Mark was like, "All right, well, let's see. Like, why don't you try and see how it goes?"

就是从那儿开始的，然后慢慢地一点点发展起来。不管是好是坏，我们已经成了很多人日常生活里非常重要的一部分。我们触达了很多人，肩上有很多责任，而且一直在变——有变化就意味着会有焦虑、压力和审视。我们做过很棒的决定，也犯过错。有些批评我觉得是不公平的，有些批评则是公道的。所以我们只能接受：这场争论早晚都会发生。那我觉得更好的做法就是我们主动来谈它，把我们在做什么、为什么做、代价是什么讲清楚。别人不认同，那也没关系。我们谈论自己在做的事，不一定能赢得什么朋友。但我觉得长远来看，人本质上更害怕的是他们不理解的东西，是那些别人捂着藏着、越发接触不到的东西。所以我一直努力以一种可接近、真实的方式出现在大家面前。我也犯过错，有时候乐在其中，有时候又恨得牙痒痒。但大概就是这么开始的。还有一段挺有意思的插曲：很久以前，在 Mark（扎克伯格）的高管团队里，我们讨论过——我们明明是家社交媒体公司，对外沟通却用着一套非常传统的做法，发新闻稿之类的，那我们干嘛不直接用自己的平台呢？我本来没在那场讨论里，是我自己硬挤进去想当个「和事佬」去调和。我觉得——但这也正是我后来被卷进去的原因之一，因为 Mark 当时就说：「行啊，那咱们就看看。要不你来试试，看看效果怎么样？」

[54:49] Lenny

What's something that helps you deal with the the hate that flows at you every time you say something that people disagree with,

有什么办法能帮你应对——每次你说了些别人不认同的话，就会朝你涌来的那些恶意？

[54:55] Adam

you try to put it in perspective, right? You know, like, so it started with I did the redesign of Newsfeed in 2009. We launched it, March of 2009 for Facebook. I was a designer. I was a front like an IC designer, front, you know, entry- level designer. And the first comment that came in was something pretty derogatory. I think it was like it was like homophobic and anti-semitic, you know, it was just like literally we're all sitting there. We launched this thing and we're just looking at the stream of comments and it's like the first one and it was specifically about they don't know me but it was like what exploive expletive um sensor sensor uh designed this [ __ ] [laughter] and I was like oh it was me. Um and I was like devastated. I was like 25-year-old kid and I don't know I thought about it and I came I came to this idea that if you spent 30 40 50 minutes a day at a at your desk and you organized your photos there and you wrote letters to your friends there and you read there and then I just came and I rearranged your desk and I didn't tell you I didn't warn you. I didn't even explain why. Like you would be pissed and that would be reasonable. Um, and that was what was happening just, you know, with millions of people. Um, so I try to put things in perspective. Um, and then I try to step away from it. Um, get time with my kids, get time outside. Uh, there there are months where it's really not hard at all and there are months where it's really really grinds on me.

你会试着把它放到一个更大的视角里去看，对吧。这事最早要追溯到——2009 年我做了 Newsfeed 的改版，我们上线了，2009 年 3 月，给 Facebook 上线的。我当时是个设计师，就是个一线的 IC 设计师（个人贡献者），入门级的设计师。上线后飘进来的第一条评论就相当难听。我记得那条又恐同又反犹，就……我们当时全都坐在那儿，刚把这东西发出去，盯着评论流一条条看，然后第一条就来了，而且矛头很明确——虽然他们并不认识我——大意是「哪个（消音）（消音）设计了这坨（脏话消音）」（笑），我心想：哦，那就是我啊。我当时整个人都崩了，才 25 岁的毛头小子。后来我反复琢磨这件事，想通了一个道理：假如你每天在自己书桌前坐上三四十、五十分钟，在那儿整理照片、给朋友写信、在那儿阅读，然后我突然跑过来把你桌子重新摆了一遍，没告诉你，没提前打招呼，甚至都不解释为什么——你肯定会火大，而且这很合理。而这正是当时正在发生的事，只不过对象是几百万人。所以我会努力把事情放到更大的视角里看。然后我会试着从中抽离一下，多陪陪孩子，多到户外走走。有些月份其实一点都不难熬，但也有些月份是真的把我磨得够呛。

[56:31] Lenny

Along those lines, there's a famous kind of reversal when you redesign the feed into this kind of video scrolly experience. There's this whole

顺着这个话题，有一次著名的「大反转」——你把信息流改成那种视频满屏下滑的体验，结果引发了整个……

[56:39] Lenny

protest. the world protested.

抗议。全世界都在抗议。

[56:41] Adam

Yeah, that was pretty rough.

对，那次是挺难受的。

[56:43] Lenny

Uh, what was kind of like, okay, wow, we're actually not right and we should go back. What was kind of what helped you decide, okay, let's change course.

那当时是怎么走到「好吧，哇，我们其实错了，应该改回去」这一步的？是什么帮你下决心说「行，咱们掉头」？

[56:50] Adam

So, actually that one got that one three or four things got conflated. We had a redesign of feed that went to the video viewer that was a test to 4% of users on iOS. It was a not it was not going to roll out. It was just like an early test to get some sense and feedback on the idea. We were also leaning into reels a lot. We were also leaning into recommendations, so posts from accounts you don't follow a lot. And there were also creators who were upset about the fact that their reach was going down and they were blaming ranking changes on that. Those four things got all conflated. We had some pretty bigname creators publicly like slap us. Then the press covered that creator sort of backlash which then got more creators doing it. So we ended up with this little bit of like a multiplier effect or echo between the creator community and the press back and forth, but we were never going to launch that. That was an early test. We were we knew it was needed work. Um we actually have continued to grow video and invest in creative tools and invest in ranking and invest in recommendations and that's driven in most of our growth in the years since. um

其实那一次，是三四件事情被混为一谈了。我们当时有一个改版，把信息流改成了视频浏览器那种形态，那只是在 iOS 上对 4% 的用户做的一个测试。它并不打算全量推出，就只是个早期测试，想对这个想法拿点感觉和反馈。同时我们当时也在大力押注 Reels，也在大力押注推荐内容——也就是你没关注的账号发的帖子——量很大。再加上还有一批创作者对自己触达量下降很不满，把这归咎于排序算法的改动。这四件事被混成了一锅。有几个挺有名气的大创作者公开「打脸」我们，然后媒体又报道了这波创作者的反弹，这又带动更多创作者跟着一起来。于是就形成了创作者群体和媒体之间来回放大、互相回声的一点「乘数效应」。但我们本来就从没打算上线那个东西，那只是个早期测试，我们自己也清楚它还需要打磨。而实际上，之后这些年我们一直在做大视频、投入创作工具、投入排序、投入推荐——我们后来大部分的增长正是靠这些驱动的。嗯……

[58:03] Adam

I think we were pushed well I don't know doesn't feel like but like it I think we were I think my real takeaway wasn't that we should have not tested that design necessarily I think we could have been we could have done a bunch of things better to explain and maybe move a little fast move a little slower I think we were just pushing things a little bit too fast and when you are responsible for a platform like Instagram you need to be reasonable and realistic about how much you can evolve it Now, I would much rather have backlashes like that every couple years or continue to evolve and continue to stay relevant than the alternative, which would have been like we didn't have video, we didn't have DMs, we didn't have stories, we didn't have ranking, and we wouldn't be on having this podcast right now. Um um but the cost of leaning in is that you're going to occasionally like make a mistake and you're going to definitely um pay for it. It's interesting how running experiments now is like very risky for companies at your scale. One person spots it and they're like, "Oh shit."

我觉得我们当时是被推着走的——嗯，我也说不好，感觉不太像，但——我觉得我真正的教训并不是说我们当初就不该测那个设计。我觉得我们本可以有很多地方做得更好：把事情解释清楚，也许有些地方再快一点、有些地方再慢一点。我觉得我们当时只是把事情推得稍微太急了。而当你要为 Instagram 这样一个平台负责时，你必须对「你能以多快的速度去改造它」保持理性和现实的判断。相比之下，我现在宁愿每隔几年就经历一次那样的强烈反弹、但能持续进化、持续保持相关性，也不要另一种结局——那种结局是：我们没有视频、没有私信（DM）、没有快拍（Stories）、没有排序算法，那我们现在也就不会坐在这儿录这期播客了。但「迎难而上」的代价，就是你偶尔会犯错，而且你一定会为此付出代价。挺有意思的是，如今对你们这种体量的公司来说，做实验变得风险特别高——一个人一发现，就会惊呼「哦，糟了」。

[59:04] Adam

You kind of need to have a press. You don't need to be proactive about communicating it, but you need to have a calm strategy. Like we can't for any for any design change or any test that could be controversial. We we talk about it beforehand and be like, "Okay, not if it leaks, when it leaks, what are we saying?" You know, are we, you know, should we talk about proactively, should we talk reactively? Either way, what's the message? Because you can't you can't you can't launch something to three billion people and not test it first, but you can't test something at our scale and not expect people to cover it and not and be so you have to be ready to talk about it before you even know you want to launch it. Um so it's um it makes the development cycle more complicated than it used to be.

你得准备好一套公关口径。你不一定要主动去传播它，但你必须有一套沉着的策略。就是说，对任何可能引发争议的设计改动或测试，我们都会提前把它拿出来讨论：「好，这事不是『如果』泄露，而是『当』它泄露的时候，我们要怎么说？」我们到底是主动去谈，还是被动回应？无论哪种，口径是什么？因为你没法把一个东西直接推给 30 亿人却事先不测试；可你又没法在我们这种体量上做测试还指望没人报道。所以你必须在自己都还没确定要不要上线之前，就已经准备好怎么去谈它。这就让整个开发周期比过去复杂多了。

[59:54] Lenny

Yeah. the uh head of growth at Enthropic launched an experiment with pricing and it just went crazy on Twitter. He's like hold that 1% of people were just trend stuff like noic

对。Anthropic 的增长负责人搞了个定价实验，结果在 Twitter 上直接炸了。他还想说「等等，其实才 1% 的用户看到而已」——可就那点人就足够把它顶成热门话题了。

[1:00:04] Adam

pricing particularly that one is a real you got to be real careful with that one. I've I've learned we've all learned these lessons. We should all share notes more. That's what I think.

定价——尤其是定价这一块，那真的是你得格外格外小心的东西。我已经……我们都吃过这些亏、学到了教训。我觉得我们大家应该多互相通通气、交流交流经验，这是我的想法。

[1:00:12] Lenny

Here's one not to how to avoid the internet hating you for the day.

教你一招：怎么才能不让全网在这一天里都恨你。

[1:00:15] Adam

Yeah. Yeah. I'm happy to talk to that more than [laughter]

对，对。这个我很乐意多聊聊——（笑）

[1:00:20] Lenny

I think he's all right. He's all right. Okay. Okay, I'm going to take us to two recurring corners on the podcast. Fail corner and hot seat corner. Fail corner. What's uh what's something that you worked on that was just a huge failure that helped you become better?

我觉得他没事的，他没事的。好，好，我要带我们进入播客里的两个固定环节：失败角（Fail corner）和拷问角（hot seat corner）。先来失败角——有没有哪件你参与过的事，是个彻头彻尾的大失败，但恰恰帮你变得更好了？

[1:00:33] Adam

Oh, a bunch. Um

哦，一大堆。嗯……

[1:00:35] Lenny

so any

那，有没有什么——

[1:00:36] Adam

So I'll give you two maybe. So before Instagram, my first project as a PM was on a project called Facebook Home, which was a sort of

那我给你讲两个吧。在做 Instagram 之前，我当 PM 接的第一个项目叫 Facebook Home，它算是——

[1:00:46] Adam

fork of Android um at the operating system level and and a piece of hardware with HTC. It was a spectacular failure. I learned way more in that year, year and a half, and I did it any year. I think probably in my career because I was just a design manager before that. I declared myself a PM because the PM on the project quit and I just threw myself head first in understanding carriers and OEMs and uh certification as well as Android and operating systems and just lend a ton. Um so and I'm happy I brought that project to an end because it had been going on for a long time and sometimes you the best thing you can do is execute an idea that doesn't have market fit well just to decide whether or not the idea was a good idea in the first place. Another big mistake I made um during my Instagram tenure was the first version of reels was built on top of stories. Stories had a ton of momentum. This was I think 2019 and we were trying to build reels into stories because we were trying to build in the thing that was growing the fastest. But it was not a strong foundation. Most, you know, the readthrough rate on stories is relatively low. There's way more stories than most people have time to consume. So most of the reels were never seen and then they disappeared. Um, and if we had the version of reels that we launched in like mid maybe I think it's like the summer of 2020 in the summer of 2019. I think I don't think Tik Tok isn't I think Tik Tok is still big and important, but I don't think it's as big as it is now because when they really took off was when the pandemic hit and a bunch of people had a lot of time at home and were looking for a little bit of joy and were totally fine with their phone having sound on. And so if you look at the numbers, the 2020 is when they exploded and we were out of position. And um on one hand, you know, I'm a designer. I'm trying to not add new things to the product. I'm trying to extend existing primitives and that was the idea. On the other hand, I was wrong and and it's a pretty big fork in the road if you just look at the overall business over the last eight years.

在操作系统层面对 Android 做的一个分支（fork），再加上和 HTC 合作的一款硬件。那是一次惨败。但那一年到一年半里，我学到的东西可能比我职业生涯里任何一年都多。因为在那之前我只是个设计经理，是项目原来的 PM 辞职了，我才自封为 PM，一头扎进去搞懂运营商、OEM 厂商、认证流程，还有 Android 和操作系统，学到了太多东西。而且我很庆幸是我亲手给这个项目画上了句号，因为它已经拖了很久了。有时候你能做的最好的事，就是把一个没有市场契合度的点子彻底执行一遍，好判断这个点子当初到底是不是个好主意。我在 Instagram 任期里犯的另一个大错，是 Reels 的第一个版本是搭在 Stories 之上做的。当时 Stories 势头很猛，那大概是 2019 年，我们想把 Reels 做进 Stories 里，因为我们想搭在增长最快的东西上。但那不是个牢靠的地基。你知道，Stories 的看完率其实比较低，发出来的量远远多过大多数人有时间看的量。所以大部分 Reels 根本没人看到，然后就消失了。而如果我们把 2020 年年中——我记得大概是 2020 年夏天——才上线的那版 Reels，提前到 2019 年夏天就推出，我觉得……我不是说 TikTok 就起不来了，TikTok 现在依然又大又重要，但我觉得它不会有今天这么大。因为它真正爆发是在疫情来袭那阵：一大堆人待在家里、有大把时间，想找点乐子，也完全不介意手机外放声音。所以你看数据就知道，2020 年才是他们爆发的节点，而那时我们没占到位置。一方面，你知道，我是做设计出身的，我总想着别往产品里加新东西，而是去扩展已有的基本元素（primitives），当时就是这个思路。但另一方面，我错了。而且如果你看过去八年整个业务的走向，这其实是一个相当重大的岔路口。

[1:02:55] Lenny

We created a lot of economic opportunity in the world allowing Tik Tok to to grow.

我们可是给全世界创造了大量经济机会——成全了 TikTok 的成长嘛。

[1:03:01] Adam

That's good. I'm I'm glad they exist.

那挺好啊。我很高兴有他们存在。

[1:03:03] Lenny

Okay, final question. Um I'm curious just about your screen time policy with your kids. I know you have three kids. Uh there's a lot of concern these days about Instagram not being great for people, not for kids. A lot of tech executives don't let their kids use devices while they're building the product. As head of Instagram, how do you think about screen time with your kids?

好，最后一个问题。我挺好奇你对自己孩子的屏幕时间是怎么管的。我知道你有三个孩子。现在很多人担心 Instagram 对人不好、尤其对孩子不好。很多科技高管一边做着产品，一边却不让自己孩子碰这些设备。作为 Instagram 的负责人，你怎么看待孩子的屏幕时间？

[1:03:27] Adam

The key thing for me is boundaries. Um it's also about education and being and having conversations with them. But my kids are too young to use social media. They're 10, eight, and six. Um but they each have an iPad. they get um they have to earn their time. Um so they have different ways they earn that time. It's usually about like sitting down to do your homework three times for half an hour each gets you a total of 90 minutes on the weekend and then they can use that time on the weekend. Um but you kind of have to set that boundary where it's like you can't just like you know it can't just be they ask for it and you give it to them. I think that matters a lot and then I'm pretty opinionated about what they do on it. Like I approve what apps that they have. I think parents should be approving what apps kids specifically are um downloading onto their devices. We've been advocating for this at a policy level for a long time at Meta. I think those things help a lot. Um there are some exceptions. Um one is planes. It's just like about surviving. I don't know if you've ever for those of you are parents.

对我来说，关键是边界。当然也包括教育、多跟他们聊。不过我的孩子还太小，还不能用社交媒体——他们分别是 10 岁、8 岁和 6 岁。但他们每人有一台 iPad，用的时间得自己挣。挣的方式各不相同，一般是这样：坐下来认真写作业，三次、每次半小时，加起来周末能换到总共 90 分钟，然后周末就用这些时间。但你得把这条边界立起来，不能是——你懂的，不能他们一开口要，你就给。我觉得这一点特别重要。另外我对他们在设备上干什么很有主见，比如他们装什么 App 得我批准。我认为家长就应该去审批孩子往设备上下载哪些 App。在 Meta，我们在政策层面为这件事呼吁了很久。我觉得这些做法很有帮助。当然也有一些例外。一个是坐飞机的时候——那纯粹是为了熬过去。不知道你有没有过……在座各位当爸妈的应该懂。

[1:04:30] Lenny

I'm going to be Yeah.

我也快到那个阶段了，是啊。

[1:04:31] Adam

Yeah. It's like you just like that's just like all right you know we're fly you know it's a 10-hour flight or eight hour flight. It's like, yeah, just just you just need to get through it. Um, the other one that I'm starting to experiment with my 10-year-old with is so schools are interesting because I think I'm pretty supportive of a no phone in classrooms. Um, that's happening more and more. I think that's is probably good for education. And I do also know in the world of AI that there's concern about kids using AI and not learning critical thinking skills. And I think that's a valid concern. But I also am worried about kids not learning how to leverage AI and then being sort of at a disadvantage. So that's a balance. So I think you need both. So with with my eldest, we started um vibe coding recently together. Um he's just loves video games. So I was like, "All right, let's make a video game." And so he's made this 19 level platformer game that kind of looks like an eight-bit version of Super Mario from when I was a kid. But like each level has its own theme, its own types of monsters. There's a store where you can buy different skins or weapons, and there's like uh like all it's unbelievable what a 10-year-old who still types with three fingers can do um with just, you know, a couple hours of sitting together. But that is more of like a I want you to learn how to um make things. I I want you to be thinking, not just playing games and I'm gonna sit with you and do we're going to do this together. Um so to me, these are the things that matter. Boundaries um scoping it down to the activities you think are healthy for your kid. Every kid is different. U but I do think you want your kids to be digitally literate, um AI literate, because I think if they're not, they're going to be at a disadvantage. But it's you also don't want it to be a free-for-all.

对。就是那种——好吧，你懂的，这是趟 10 小时、8 小时的长途飞行，就……对，你就是得想办法熬过去。另一个我最近开始跟我 10 岁孩子尝试的，是——学校这块挺有意思的，因为我其实挺支持课堂上禁手机的。这种做法越来越普遍了，我觉得对教育大概是件好事。同时我也知道，在 AI 时代，有人担心孩子用 AI 会学不会批判性思维，我觉得这个担忧是成立的。但我同样担心孩子不学会怎么驾驭 AI，反而会处于劣势。所以这是个平衡，我觉得两头都得要。所以我最近开始跟我大儿子一起 vibe coding。他就是特别爱打电子游戏，我就说'行，那咱们来做个游戏'。结果他做出了一个 19 关的平台跳跃游戏，看着有点像我小时候那种 8-bit 版的《超级马里奥》。但每一关都有自己的主题、自己的怪物种类，还有个商店可以买不同的皮肤和武器。一个还在用三根手指打字的 10 岁小孩，就靠跟你坐在一起花几个小时，能做出这种东西，简直难以置信。但这件事更多是——我想让你学会怎么去'造东西'，我想让你动脑子，而不是光打游戏；而且我会陪着你一起做，咱们一块儿弄。所以对我来说，重要的就是这些：立边界，把范围收窄到你觉得对孩子健康的活动上。每个孩子都不一样。但我确实觉得，你会希望自己的孩子有数字素养、有 AI 素养，因为如果没有，他们会处于劣势。不过呢，你也不希望完全放任、毫无约束。

[1:06:22] Lenny

This is selfishly useful for me as a as a I have a three-year-old and I'm trying to figure all this stuff out. So, this is useful.

这些对我来说'私心'上特别有用，因为我有个 3 岁的孩子，正想把这些事情理清楚。所以，这真的很有用。

[1:06:27] Adam

Oh, yeah. No,

哦，是啊。不——

[1:06:28] Adam

we need to figure out a strategy.

咱们确实得琢磨出一套策略。

[1:06:30] Adam

It's amaz It's a thing. And you're you're you're not that far off. You're really just not that far off. It's going to happen in a couple years.

这真是个事儿。而且你离那天真的不远了，真的不远，再过几年就来了。

[1:06:35] Lenny

Five coding next year. Let's do it.

明年就 vibe coding。走起。

[1:06:37] Lenny

I couldn't believe I tried to do it six months ago and it just totally didn't work. And then

我简直不敢相信——半年前我试过一次，完全跑不通。然后——

[1:06:42] Lenny

now with newer models, it's been amazing.

现在换了新的模型，效果好得惊人。

[1:06:44] Lenny

What's their platform of choice? Are they a clock coding team? uh person.

他们主力用什么平台？是 Claude Code 那一挂的吗？呃，那种人？

[1:06:48] Adam

Yeah, my 10-year-old is using is using cloud code right now. Um

对，我 10 岁的孩子现在用的就是 Claude Code。

[1:06:53] Adam

um but um we will see. We'll see how that goes.

呃，不过嘛，走着瞧吧，看看效果怎么样。

[1:06:56] Lenny

Adam, uh I'm going to let you go. Thank you so much for being here. This you're just like such a gem of a person. It's just so obvious how clear like how authentic you are and just like how deeply you think about everything. Uh so I really appreciate you being here.

Adam，我就不多留你了。非常感谢你来上节目。你真的是个特别难得的人，你身上那种通透、那种真诚，还有你对每件事都思考得那么深，都太明显了。所以我真的很感激你能来。

[1:07:10] Adam

I appreciate you bringing me on. Um been a fan for a long time. It's nice to finally get to have a conversation.

谢谢你请我来。我当你的听众很久了，能终于坐下来聊一次真好。

[1:07:15] Lenny

I appreciate that. I really appreciate that. Uh let me just ask you this final question to ask everyone. What's a way that listeners can be useful to you?

谢谢，真的很感谢。那我问你一个我会问每位嘉宾的收尾问题：听众有什么方式可以帮到你？

[1:07:23] Adam

I just think you don't even have to tell this to other people, but just remember that this world and technology is complicated and there are almost always tradeoffs. Um and you can totally disagree with the decisions I or we make. Um, but just remember that we are people here trying to make these decisions, trying to do the best we can. And I I actually do invite the criticism and the critique and the feedback, but um, but know that none of these contentious debates are nearly as simple as most people pretend to make them out to be.

我觉得——你甚至都不用去跟别人讲这些，只要自己记住：这个世界、这些技术都很复杂，几乎永远都存在取舍。你完全可以不认同我、或者我们做的决定。但请记得，坐在这些位置上做决定的，也是一群普通人，在尽力把事情做好。我其实是欢迎批评、质疑和反馈的，但也请知道：这些有争议的议题，没有一个像大多数人假装的那么简单。

[1:07:59] Lenny

Wise words, Adam, thank you so much for being here.

说得真好，Adam，非常感谢你来。

[1:08:02] Adam

Pleasure. Thank you, Lenny.

我的荣幸。谢谢你，Lenny。

[1:08:04] Lenny

Bye, everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennispodcast.com. See you in the next episode.

各位，再见。非常感谢你的收听。如果你觉得这期有价值，可以在 Apple Podcasts、Spotify 或你常用的播客应用上订阅本节目。也请考虑给我们打个分或留个评价，这真的能帮到更多听众发现这档节目。你可以在 lennyspodcast.com 上找到所有往期节目、或了解更多关于本节目的信息。下期再见。