为什么每家公司现在都需要像实验室团队一样思考和运作

我的论点是，每家公司都需要开始像实验室团队一样思考和运作。

My thesis is that every company needs to start thinking and operating like a labs team.

每家公司肯定都需要一群人，一个团队。他们的工作就是站在前沿。他们就是那种在什么服务上都订了八个每月 200 美元订阅的人。

Every company definitely needs a set of people, a team. Their job is to be at the frontier. They're the people who have like eight $200 a month subscriptions on everything.

每个人都必须非常擅长用最新的模型尝试各种东西，在竞争对手之前、在创业公司来抢你饭碗之前，弄清楚现在什么是可能的。

Everyone has to get really good at trying a bunch of stuff with the latest models, figuring out what is now possible before your competition does, before a startup comes and eats your lunch.

你必须努力创造一个能让奇怪的东西生长的空间。如果你看看大公司创办实验室的历史，实验室通常效率低下，大约三到四年后就无疾而终。你不能只是把它安放在现有业务部门下面。它必须有自己的独立性。

You've got to try to create a space where weird things can grow. If you look at the history of a large company who starts a lab, the lab is usually ineffective and fizzles out after about 3 to four years. You can't just nestle this under an existing business unit. It has to have its own kind of independence.

你见过的被扔到墙上、被尝试、被做成原型的想法，可能比任何人都多。最好的想法来自哪里，有哪些模式？

You've seen more ideas thrown at the wall and tried and prototyped than maybe anyone else. What are some patterns of where the best ideas come from?

它们很少来自设计冲刺。它们不会出现在常规的地方。你没法用微波炉加热出好想法。

They very rarely come from design sprints. They don't come in conventional places. You can't microwave good ideas.

你发现哪些技能的价值正在上升？

What skills are you finding are trending up in value?

我现在其实非常看重人的一个特质。他们的“遗忘速率”怎么样？他们能多快学会一样东西，然后又能放下它？

I'm actually looking a lot right now for people. What's their unlearning rate? How fast can they learn something and then walk away from it?

关于产品市场契合度是什么样子，有什么可能会让人惊讶的地方？

What's something that might surprise people about what product market fit looks like?

当你向人们展示早期原型时，你要看人们的眼睛。那就是指标。

When you're showing people early prototypes, you're looking at people's eyes. That is the metric.

有什么迹象表明是时候放弃一个想法了？

What are signs that it's time to kill an idea?

团队通常比领导者先知道。

The team usually knows before the leader knows.

今天，我的嘉宾是 Josh Woodward。Josh 是 Google Labs、Gemini 应用和 AI Studio 的负责人。他在 Google 工作了超过 16 年，他的工作是试验和扩展新的 AI 产品。我这次对话的前提，也是我认为它非常有价值的原因，是每家公司都被迫像实验室团队一样思考和运作。因为现在可能的事情变化得太快了。你必须非常擅长把玩最新技术、进行大量实验，并在竞争对手或创业公司之前发现新机会。Josh 运营着世界上持续时间最长、规模最大的实验室团队。他分享了很多非常具体的经验，关于最好的想法来自哪里、如何知道何时放弃一个想法、产品市场契合度是什么样子、当今时代哪些技能变得更有价值、为什么角色实际上并没有模糊成一个构建者角色，以及更多内容，包括一些辛辣的东西。非常感谢 Steven Johnson、Sophie Miller、Jeff Hong 和 Logan Kilpatrick 为这次对话建议主题和问题。在我们开始之前，我注意到很多人没有听完节目，这完全没问题，但你会错过最精彩的部分。所以，为了帮助你，我创建了一个新的 Lenny's Most Replayed Moments YouTube 频道，内容正是如此，是我们长篇节目中重看和分享最多的片段。去看看并在 lennispodcast.com/mostreplayedmoments 订阅。描述中也有链接。那么，我为你带来 Josh Woodward。Josh，非常感谢你来这里。欢迎来到播客。

Today, my guest is Josh Woodward. Josh is head of Google Labs, the Gemini app, and AI Studio. He's been at Google for over 16 years, and his job is to experiment with and scale new AI products. My premise for this conversation, and why I believe it is so valuable, is that every company is being forced to think and operate like a labs team. Because what is now possible is changing so quickly. You have to get very good at playing with the latest technologies, running tons of experiments, and uncovering new opportunities before your competition or startups do. Josh runs the longest lasting and biggest labs team in the world. And he shares a ton of very specific lessons about where the best ideas come from, how to know when to quit an idea, what it looks like when you have product market fit, what skills are becoming more valuable in today's era, why roles aren't actually blurring into one builder role, and so much more, including some spicy stuff. A huge thank you to Steven Johnson, Sophie Miller, Jeff Hong, and Logan Kilpatrick for suggesting topics and questions for this conversation. Before we get into it, I've noticed a lot of people don't finish the episodes, which is totally fine, but you end up missing the best stuff. So, to help you, I've created a new Lenny's Most Replayed Moments YouTube channel that is exactly that, the most rewatched and shared segments from our long-form episodes. Check it out and subscribe at lennispodcast.com/mostreplayedmoments. There's also a link in the description. With that, I bring you Josh Woodward. Josh, thank you so much for being here. Welcome to the podcast.

谢谢。很高兴来到这里。

Thank you. So great to be here.

能请到你来更好了。我想先为这次对话铺陈前提，并想听听你的看法，你是否同意。

It's even better to have you here. I want to first lay out the premise for this conversation and I want to get your take if you agree with this.

好的。好的。听起来不错。

Yeah. Yeah. Sounds good.

世界观。我的论点是，每家公司都需要开始像实验室团队一样思考和运作，因为我们所有人所依赖的底层技术变化得太快了。这意味着我们能做的事情变化得太快了。这意味着现在每个人都必须非常擅长用最新的模型尝试各种东西，基本上就是在竞争对手之前、在创业公司来抢你饭碗之前，弄清楚现在什么是可能的。所以感觉现在越来越重要的技能，是你们已经非常擅长的东西，就是找到好想法、弄清楚如何运行大量实验、弄清楚该在什么上加倍投入、建立能以这种方式运作的团队，同时不让公司其他部分被各种花哨的东西分心，让他们保持专注。所以总的来说，这引起你的共鸣吗？

Worldview. So my thesis is that every company is needs to start thinking and operating like a labs team because the underlying tech that we're all building on is changing so fast. Which means what we can do is changing so fast. Which means that now everyone has to get really good at trying a bunch of stuff with the latest models and basically uh figuring out what is now possible before your competition does, before a startup comes and eats your lunch. And so it feels like the skills that will matter more and more now are things that you all have gotten really good at, which is finding great ideas, figuring out how to run a ton of experiments, figuring out what to double down on, uh building teams that can operate this way, at at the same time not distracting the rest of the company from all the shiny stuff and letting them focus. So broadly, uh how do you does that resonate?

是的，我认为你的前提完全正确。嗯，我认为你刚才说的所有事情，细节才是关键。所以我觉得容易的是，你知道，某种程度上每家创业公司都是一个实验室，真正的问题是，你如何把同样的方法论、想法、能量、兴奋感带入更大的团队，甚至是中型团队。嗯，但我绝对认为这是需要的，然后问题就是，是的，你如何建立那种环境，并培育和培养既能产生想法、又能让真正能在那里茁壮成长的人。

Yeah, I I think your premise is spot on. Um I think the devil's in the details with all those things you just said. So I think what's easy for you know in some ways every startup is a lab and the real question is like how do you bring some of that same methodology ideas energy excitement into bigger teams or even medium-sized teams. Um but I absolutely think it's needed and then the question is yeah how do you build that environment and nurture and cultivate the kind of both ideas but also the people uh that can really thrive there.

太棒了。好的，这正是我们要讨论的。

Awesome. Okay that's exactly what we're going to talk about.

是的。

Yep.

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This episode is brought to you by our season's presenting sponsor, Work OS. What do OpenAI, Anthropic, Cursor, Replit, Sierra, Clay, and hundreds of other winning companies all have in common? They are all powered by work OS. If you're building a product for the enterprise, you've felt the pain of integrating single sign on, 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. 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 a seedstage startup trying to land your first enterprise customer or a unicorn 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, comprehensive docs, and a smooth developer experience. Go to works.com to make your app enterprise ready today.

那么，我将从产生想法、找到好想法开始。如果你回顾一下从实验室甚至整个 Google 中涌现出的最好的想法，最好的想法来自哪里，有哪些模式？

So, I'm going to start with coming up with ideas, finding great ideas. If you were to reflect back on the best ideas that emerged out of labs and even in Google in general, what are what are some patterns of where the best ideas come from?

是的，这很有趣，因为很多想法——我希望书后面有答案，只有一件事，也许一个观察，Lenny，就是它们来自各种地方。所以我一直觉得有一个教训，就是你总是必须留意那些吸引你眼球的东西。也许我们稍后再回到这一点。至少在我的经验中，它们很少来自设计冲刺，或者你在日历上留出的时间，说“好，这就是我们要想出下一个想法的地方”。

Yeah, it's interesting because a lot of them I wish there was an answer in the back of the book where there was one thing the maybe one observation Lenny is there the they come from a variety of places. So one lesson I've always felt is like you always have to be watching for something that catches your eye. Maybe we come back to that in a second. They very rarely, at least in my experience, have come from design sprints or times where you set aside on a calendar, okay, this is where we're going to go come up with our next idea.

它们通常出现在人们在走廊里游泳的时候，也许是周末，哦，常常是在假期。我们 Labs 的很多团队会一直在写代码、做东西，他们就是忍不住，然后会回来，或者分享一个视频说：“看看这个了不起的东西。”所以我觉得一个教训是：始终保持警觉。第二个教训是：好点子不会出现在常规的地方。你没法用微波炉加热好点子。也许这引出我看到的第三点：有时候重点不在于点子本身，而在于那些有趣的人是谁，更重要的是他们那些有趣的小项目和热爱的事情，以及围绕这些营造出的化学反应。因为通常我们发现，至少在 Labs 过去四五年里，所有这些点子——无论是 Notebook、Flow、AI Studio、Google Beam 还是别的什么——都是由一小群痴迷的人发起的，他们通常对某件事非常好奇，就是停不下来。所以你要想，怎么创造一个能让这种事发生的空间，然后保持警觉去捕捉它，试着把它往前推进。

They usually come when people are swimming in the hallway, maybe on a weekend, oh, often over a break. A lot of our labs teams will be hacking and building on stuff and they just can't help themselves, and they'll come back, or they'll share a video and be like, "Look at this amazing thing." So I think one lesson is: always be on alert. Second lesson is: they don't come in conventional places. You can't microwave good ideas. And maybe that leads to a third thing I've seen: sometimes it's less about the idea and more about who are the interesting people, and more importantly, what are their interesting little side projects and passion things, and creating the chemistry around that. Because usually what we've found, at least in Labs over the last four or five years, is that all these ideas — whether they're Notebook or Flow or AI Studio or Google Beam or any of this stuff — they get started by very small groups of people who are just obsessed and usually very curious about something, and they just won't stop. And so you kind of think, how do you create a space where that can happen, and then be on alert to catch it and try to funnel it forward.

所以我听到的很有意思，并不是设计冲刺那种东西。我没听到头脑风暴会议是产生好点子的地方。

So what I'm hearing here is interestingly not like design sprints. I didn't hear brainstorm meetings in there as a place good ideas come from.

对。

Yeah.

有没有一个例子？因为听这期节目的人——我在想他们能从中学到什么来帮自己找到好点子，比如他们是创业公司创始人，或者在大公司里玩最新模型。你觉得哪些条件最有帮助？

Is there an example? Because someone listening to this — I'm trying to think about what they can take from this to help them find great ideas, say they're a startup founder or at a big company playing with the latest models. What are some of the conditions that you find most helpful?

是的，是的。我们经常做的一件事，我觉得在任何那种情况下都适用，就是：你怎么让自己站到前沿？这既包括玩模型，也包括观察哪些类型的体验刚刚变得可能。我们团队有个说法——我们谈“几乎可能的东西”——我们实际上有一个清单，试着追踪这些东西。当某一个跨过临界点，几乎就像相变，就像从固态变成气态，或者从液态变成气态之类的。你会说：“哦，这刚刚变得可能了。”我两天前看到一个这样的东西，到现在还在想。

Yes. Yes. One thing we try to do a lot, and I think this would apply in any of those situations, is: how do you get yourself to the frontier? And that can be both playing with the models, but also just watching what types of experiences have just become possible. We have a phrase on the team — we talk about "what's almost possible" — and we actually have a list where we're trying to track those things. And when one crosses over, it's almost like a phase shift, when something goes from solid to gas or liquid to gas or something. You're like, "Ooh, that just became possible." I saw one of these two days ago and I can't stop thinking about it.

你能告诉我们吗，还是说——

Are you able to tell us, or is it a—

呃，也许很快吧。但就是，你有点——如果你在前沿玩模型，观察正在发生什么，而且你有这个清单，那么当你看到某个东西时，无论是在 X 上还是别的地方，你就会说：“好，这刚刚变得可能了。”然后我们试着想怎么围绕它组建一个团队，直接开干。所以这可能是——当你在创业领域，如果你在思考，或者你开始向风投推销点子之类的——这就是我会尝试去思考的方式。当然，光有技术还不够；你得把它匹配到一个有趣的用户问题上。理想情况下，如果你能把这两者结合得足够好，人们会愿意为此付费。这就是我们很早就开始寻找的那种组合。

Uh, maybe soon. But it's like, you kind of — if you're at the frontier playing with the models, watching what's happening, and you kind of have this list, then when you see something, whether it's on X or wherever, then you're like, "Okay, that just now has become possible." And then we try to think about how do we get a team around that and just go. And so that may be — as you're kind of in startup land, if you're thinking, or maybe you're starting to pitch ideas to VCs or whatever — that's kind of how I'd be trying to think about it. And then of course tech alone isn't enough; you've got to match that to an interesting user problem. And ideally, if you can put those together in a way that's so good, people will pay for it. That's kind of the combination of things we start looking for pretty early.

所以这是一个有趣的策略：列一个“几乎可能”的清单，然后留意，“好，哇，现在这变得可能了，我们来探索一下。”

So that's an interesting tactic there: make a list of what is almost possible, and then watch for, "Okay, wow, this is now possible, let's explore this now."

对，没错。

Yeah, that's right.

那个清单上有没有什么你能分享的——那些还没可能但几乎可能、你在等待和观察的东西？

Is there anything on that list you can share — things that are not yet possible but almost possible that you're waiting for, watching for?

嗯，也许我可以分享几个领域。因为我觉得我们在 Labs 的思考方式是，我们会做一个思想实验，想某个东西的未来会是什么样？比如软件设计和开发的未来，或者创造力的未来，工作或知识的未来。我们现在非常密切关注的一个领域就是：娱乐的未来会是什么样？围绕沉浸式娱乐的整个想法，从技术层面就非常有趣，原因很多，但你也想想用户行为，娱乐去年、今年和明年或三年后看起来会是什么样。所以这是一个我们下面有一整个清单的领域，我们会说：“哦，好，如果模型能达到这种延迟、这么多语言、这么多模态，你就可以开始思考从技术角度什么会有趣。”然后我们在 Labs 做了很多关于行为和趋势走向的工作。为此，有些当然可以在湾区研究，但对我们很多团队来说，我一直在想怎么走出湾区，想想还有哪些城市、教室、其他地方可以像挖矿一样挖掘点子和这些行为变化。

Well, maybe I can share a few areas. Because I think how we think about it in Labs is we have kind of a thought experiment we go through, where we're like, what is the future of a certain thing going to look like? So the future of software design and development, or the future of creativity, the future of work or knowledge. One area we're watching very closely right now is just like, what is the future of entertainment going to look like? And this whole idea around immersive entertainment is super interesting just at a technical level for many reasons, but also you think about just kind of the user behaviors and like what does entertainment look like last year, this year versus next year or maybe in three years. And so that's one where we've got a whole list underneath that, where we're like, "Ooh, okay, well, if a model can get to this kind of latency and this amount of languages in this amount of modality, you can start to think through what would be interesting from the tech side." And then we do a lot of work in Labs around where are just behaviors and trends going. And for that, some of it, of course, you can study in the Bay Area, but for a lot of our teams, I'm always thinking about how do we get way outside the Bay Area, and thinking about where are the other cities, the classrooms, the other places to almost mine for ideas and these behavioral changes.

所以这里一个有趣的收获是：你不只是等灵感降临。你在做大量前期工作去思考：这是几乎可行的东西，这是我们觉得未来可能走向的地方，这些是将要成熟、容易被颠覆的领域。

So an interesting takeaway here is this: you're not just waiting for inspiration to strike. You're doing a lot of pre-work to think about, here's what is almost working, here's where we think the future might be going, here's areas that are going to be ripe for disruption.

没错，是的。在我谈到的那份文档里，我们有 82 条预测，全都以“我们相信未来是”或“我们预测”开头。这很危险——做一个预测就已经够危险了，更别说 82 个。但我觉得你几乎必须对未来有一个观点，同时知道十有八九，或者十有九点九，你都会错。但我觉得这正是我们真正想在团队里培养的东西之一：我们怎么追逐未来？这是价值观之一，就是试着去追逐它。你几乎必须把自己抛出去，试着在其中生活一点。

That's right. Yeah. In this doc I talked about, we have 82 predictions that all begin with "we believe the future is" or "we predict." This is dangerous — ever to make one prediction, let alone 82. So, but I think you have to almost have a point of view about the future, knowing that nine out of 10, or maybe 9.9 out of 10, you're going to be wrong. But I think that's one of the things we really try to cultivate in the team: how do we chase the future? That's one of the values, and sort of trying to chase it. You almost have to throw yourself out there and try to live in it a little bit.

对你来说，一个点子值得追求的信号是什么？当你在洗澡时，你有了这个点子。什么信号说明，好，这至少值得一开始押注？而什么往往只是假信号，就像，好吧，不，这其实行不通。

What are signs to you that an idea is worth pursuing? When you're in the shower, you have this idea. What's a sign that, okay, that's worth betting on, at least to start with? And what's often just like a false signal, like, okay, no, that's actually not going to work.

是的。我觉得对我来说，尤其是当你有这些清单、在思考未来时，一个信号是当你看到某个让你惊讶的东西，或者以某种方式让你非常感兴趣的东西。如果你能对自己描述它——比如我大约 48 小时前看到的那个东西，我离开那个演示后想，这太令人兴奋了。我觉得这也许是我会稍微使用的一个信号：试着站在前沿，然后看什么让我感兴趣或兴奋，再和团队一起从中汲取能量。

Yeah. I think one thing for me, especially when you've got these lists going and you're thinking about the future, is when you see something that surprises you, or maybe that's very interesting to you in a certain way. And if you can describe it to yourself — like this thing I saw about 48 hours ago, I left that sort of demo and I thought, this is so exciting. And I think that's maybe a signal I use a little bit: trying to be at the frontier, and then what makes me interested or excited, and then feeding off that kind of with the team together.

我觉得现在这个门槛太低了，因为一切都太神奇了。或者说现在反过来了——一切都变成，好吧，很棒，这东西在帮我报税，当然了，本来就该这样。

I feel like that bar is too low these days, because everything is so magical. Or it's the opposite now — everything is like, okay, great, this thing is doing my taxes for me, of course, that's just the way it is.

对，对。我觉得这是其中一点——显然那种兴奋感可能算是科技圈的特点，现在每隔一天、甚至每隔一小时就有令人眼花缭乱的演示。但接下来我觉得要去想，哪些用户行为可能是普适的，或者那一侧是不是正在发生某种转变。然后我们思考变现的方式也是：你能不能触达一群人，他们就是离不开它——他们真的会付钱给你，因为它对他们太有价值了。然后你如何把这些拼在一起。不过，有时候它必须来自这些领域之一，我会这么说。

Yeah, yeah. I think this is one of the things — obviously that excitement is maybe a tech thing, and there are dazzling demos every other day, or every other hour right now. But then I think trying to think through where's the user behavior that maybe is universal, or maybe there is some shift on that side. And then the way we think about monetization too is, can you get to a group of people that just can't live without it — like they literally will pay you because it's so valuable to them. And then how you can put those pieces together. But yeah, sometimes it's got to come from one of those areas, I would say.

有没有一个很好的例子或故事，讲某个产品就是这样诞生的？

Is there a great example or story of a product that emerged in this way?

有。我还记得第一次听到第一版 NotebookLM 播客的时候。我清楚记得我站在哪儿——就在这个房间外面。大概是某个周二下午 6 点半左右，团队里有两个人走过来，说：“你得听听这个。”内容是英国议会辩论的记录。这素材可不是以引人入胜著称的，但这两个 AI 主持人聊它的方式真的很有意思。那就是一个让我们觉得“我们得拿这个做点什么”的时刻。那是一个例子。我还记得第一次看到 Google Flow 产出的东西。在那之前我们有个项目叫 Whisk，你可以把多张图片揉在一起，然后开始让它们动起来。那是一种前所未有的控制力和创作引导力，而且我让它变得触手可及。所以也许这就是两个例子。我们也有别的例子：我们很兴奋，试着做某个产品，结果就是不行。所以这也是另一面——这里面也有一点碰运气的成分。

Yeah, I mean, I still remember the first time I heard the first NotebookLM podcast. I remember exactly where I was standing — it was right outside this room. And it was probably at like 6:30 p.m. on a Tuesday or something, and there were two people on the team who came over and were like, "You got to listen to this." And it was the proceedings of the British Parliament debates. Not known for its riveting material, but these two AI hosts were talking about it in a way that was literally interesting. And that was one where we're like, we got to just do something with this. And that was one. I remember the first time I saw something come out of Google Flow. We had a project before that called Whisk, where you could whisk together multiple images and then start to animate them. And it was a level of control and creative channeling that had never been possible, that made it accessible. So maybe those are two examples. We also have other examples where we get excited, we try to build some product, and it's just not good. So that's the other thing — it's a little bit of a game of numbers in this as well.

我们来聊聊产品市场契合，以及某件事确实在起作用的迹象。我感觉你见过的、被扔到墙上试过的、被做成原型的点子，可能比任何人都多。我不知道这是不是真的，但感觉是真的。对你来说，什么迹象表明这是我们需要加倍投入的东西？关于产品市场契合长什么样，有什么可能会让人意外的地方？

Let's talk about product-market fit and signs that something's actually working. I feel like you've seen more ideas thrown at the wall and tried and prototyped than maybe anyone else. I don't know if that's true, but it feels true. What are signs to you that this is something we need to double down on? And what's something that might surprise people about what product-market fit looks like?

对，我觉得其中最棘手的部分之一是，它更像是艺术而非科学。我希望它是科学——我们懂得怎么做科学实验、做数据驱动的决策、设定 OKR，所有这些流程都有帮助。但有时候在早期，Lenny，真的就是团队里几个人，他们可能只是有信念，他们就说，我觉得未来会是这样，我没法解释。这就是难的地方——这种建议其实没那么有用。但我会说，这也算是一部分。也许更有用的一点是：我们经常讨论怎么走出办公楼，直接给人看原型。当你给人看早期原型时，我一直在做的一件事就是看人的眼睛，那就是指标。它不是 DAU，不是 DAU 除以 MAU，不是 7 日留存。全都不是。它就是，嘿，Lenny，你看到这个了吗？你觉得怎么样？如果你的眼睛亮了起来，如果你身体前倾，这些就是早期你要找的信号。也许第三点，这一点可能也是你问题的另一面，就是那些对事情感到兴奋的人——通常我们会试着去想我们爱上的是哪个问题，而不是哪个产品。因为我发现，在你做出点东西、或者你只能说“就这样了，没成”之前，往往要经历三、四、五次转型。所以我认为，当人们先爱上一个具体的产品方案时，至少以我的经验，会带来糟糕的结果。所以这也是我们试着多想的一点。通常人们谈 PMF，说你有它的时候你就知道了。我觉得这是对的。在过去大概一年左右，当 Nano Banana 在 Gemini 上爆火，当 NotebookLM 播客火起来，当 Flow 或 Stitch 或其他项目出现这些小高潮时——你真的就是全员扑上去，拼命抓住不放。它既让人精疲力尽，又非常有趣。但没错，你几乎必须多打很多枪，我会这么说。而且在早期，它感觉更像是艺术、热情驱动，而不是科学，很遗憾。

Yeah, I think one of the maybe trickiest parts of it is it is way more art than science. I wish it was science — like we know how to run science experiments, make data-driven decisions, set OKRs, all this process that helps. Sometimes in the early days, Lenny, it's literally a couple of people on the team who might just have conviction, and they're just like, I think the future is going to look like this and I can't explain it. That's what's hard — that advice is just not that useful or helpful. But I would say that's some of it. I think maybe a little more useful: we talk a lot about how do we get outside the building and just show people prototypes. And when you're showing people early prototypes, what I'm always doing in those is you're looking at people's eyes, and that is the metric. It is not a DAU, it's not a DAU over a MAU. It's not a D7 retention. It's none of that. It's literally like, hey, Lenny, did you see this? What do you think about this? And if your eyes kind of light up, if you lean in, these are the kind of signals you're looking for in the early days. Maybe the third thing I would say, and this one's also maybe on the flip side of your question, is the people who get excited about things — usually we try to think about what's the problem we're falling in love with, not the product. Because what I found is it takes three, four, five pivots before you either got something or you're just like, that's it, didn't work. So I think when people fall in love with an actual product solution first, it's going to, at least in my experience, lead to a bad time. So that's the other thing I think we try to think a lot about. And usually people talk about PMF, you sort of know it when you have it. I think that's true. In the last, I don't know, year or so, when Nano Banana went viral on Gemini, when the NotebookLM podcasts have gone, when stuff's happened on Flow or Stitch or other projects that have had these mini moments — you're literally just swarming it and holding on for dear life. And it is both so exhausting and so fun. But yeah, you almost have to take a lot of shots, I would say. And in the early days again, it feels a little more art, passion-driven than science, unfortunately.

这些其实是非常具体、非常明确的观察点。眼睛——眼睛会不会亮起来。我听别人描述过的一种说法是，他们的瞳孔会放大。

Those are actually very concrete, specific things to look for. The eyes — whether eyes light up. A way I've heard someone else describe this is their pupils dilate.

对。没错。而且你也知道，对吧，当你跟人说话时，他们是聊得开心、很投入，还是你给他们看某个蠢产品时他们无聊到极点。所以关键就是，你能不能击中他们生活中某个痛点的那根神经，让他们就想，我要这个。我的意思是，这正是这份工作如此有趣的原因——去搞清楚你能击中多少根这样的神经。

Yes. That's right. And you know too, right, when you're talking to someone, if they're having a good time, if they're into it, or if they're just bored out of their mind and you're showing them some dumb product. So it's really like, can you hit a nerve with a pain point in their life where they're just like, I want that. And I mean, that's what makes this job so fun — is trying to figure out how many of those nerves you can hit.

那么，有了这个背景——当事情达到产品市场契合、眼睛亮起来时是很清楚的——什么迹象表明该砍掉一个点子了？

So having that context of it's clear when things are product-market fitting and the eyes are lighting up — what are signs that it's time to kill an idea?

对。关于这一点，有一件事，我也经常跟团队聊，就是有时候团队会期待领导者来做决定，事情好像就该这么来。但我发现恰恰相反。团队通常比领导者更早知道，迹象就是：热情是不是开始消退了？你是不是把能想到的都试过了，它就是不行？人们知道一个项目不行了，或者一段关系不行了——你知道，这是人们看得出来的。所以作为领导者，我试着做的，比如在 Labs 或者我们在 Gemini 的一些功能上，就是你怎么营造一个环境，让人们能问那些让人不舒服的问题，能说出，嘿，我觉得这个不行。举个例子，昨天我们在 Gemini 上有个功能，我们非常兴奋，本来要发布了，结果拿到一些早期数据，大家出去看了看人们的眼睛，就是没有那种反应。我特别为团队里那位 PM 感到骄傲，因为她说，我觉得我们不该发布这个。它不够好。于是我回复了所有人，说，这太棒了。

Yeah. One of the things on this one, and I talk a lot to the team about this too, is sometimes a team is looking for the leader to make the decision, and that's kind of where it comes from. What I found is the opposite. The team usually knows before the leader knows, and the signs are like, does the passion start to run out? Have you tried everything you can think of and it just isn't working? People know when a project's not working or a relationship's not working — you know, that's something that people see. And so as a leader, what I try to do, say in Labs or even some of our features in Gemini, is how do you create an environment where people can ask those uncomfortable questions and be able to say like, hey, I don't think this is working. And yesterday, just as an example, we had a feature we were really excited about in Gemini, we were going to launch, and we got some of the early data back, people went out and looked in the eyes, and it just wasn't there. And so I was so proud of the PM on the team because she was like, I don't think we should launch this. It's not good. And so I replied all, was like, this is great.

感谢你做这个。所以，如何创建一种文化，让团队既能指出好的事情，也能指出坏的事情？我想，作为领导者，就我而言，我非常信任团队。因为他们每天都在努力推动这件事。我认为，如果他们觉得“嘿，这行不通”，那么就像，“好吧，没关系。让我们转向。做点不同的。”

Thank you for doing this. And so it's like, how do you create a culture where the team can call both good things and bad things out? And I guess in that way, as a leader, in my case, I trust the team a lot. Because they're the ones every day trying to make this thing go. And I think if they're like, "Hey, it's not going." Then it's like, "All right, that's okay. Let's pivot. Let's do something different."

我必须问你这个问题。我本来打算晚点问，但我太好奇了。你负责 labs，那是从 0 到 1 的实验，尝试全新的东西。还有 Gemini，Gemini 应用，它是世界上最受欢迎的应用之一，可能有十亿用户。为什么会这样？为什么你的团队下会有这样的结构？

I have to ask you this question. I was gonna ask it later, but I'm so curious. It's so interesting that you oversee labs, which is zero to one experiments, try stuff that's totally new. And then Gemini, the Gemini app, which is one of the most popular apps in the world with probably a billion users. Why how did that come to be? Why is that the structure under your team?

是的。是的。嗯，我想在某些方面，它们是非常不同的两端。你说得对，Gemini 有超过十亿用户。它是全球性的。而 labs，你知道，我们在 labs 开玩笑。有时我们的早期项目，从 0 到 1 的东西，我们会为 1 万用户兴奋不已，而大多数其他产品的仪表盘都不统计这么低的数字。所以这是团队里的一个笑话。但我认为也许有一些共同点，尽管规模不同。我认为第一，被这些东西吸引的人的类型，即使 Gemini 尽管规模很大，也充满了从 0 到 1 的心跳。所以我认为部分原因是构建者的类型，你吸引的人的类型，这些模糊了界限，需要什么，我们都是 AI 的疯子和狂人，我们热爱这个东西，我们永远不够，我们一直在构建。第三点，我想说，是团队中的每个人。我们稍微谈过我们如何思考优先级的顺序，我们团队的口号是用户第一，谷歌第二，我们的产品第三，所以 labs 第三或 Gemini 第三，我认为这也让我们团结起来，我们不会为自己的团队做事，我们非常是谷歌团队的一部分，但最终也是，是否有人在产品的另一端喜欢这个？所以这确实把一切联系在一起，但它们在规模上肯定处于不同的两端，就像传统数字一样。

Yeah. Yeah. Well, I guess in some ways they are very different ends of the scale. You're right, Gemini. Over a billion users. It's global. Like labs, you know, we joke on labs. Sometimes our early projects, the zero to one stuff, you know, we'll get so excited about 10,000 mouse and like most other products dashboards don't count that low. So this is kind of the joke on the team. But I think maybe there's a few common pieces though, even though the scale is different. I think one the type of people that are attracted to these things even Gemini despite its size is very much got a zero to one heartbeat all over it and so I think part of it is like the type of builder the type of person you're attracting these like blurring lines between what what it takes two we're all like AI kind of nuts and maniacs we love this stuff like we we we can't get enough of it we're building all the time um the third one though I would say is like a little bit of everyone on the team. We talk a little bit about like the order of how we think about our priorities and we like the mantra on the team is like users first, Google second and like our product third and so like labs third or Gemini third and I think that unites us too and that's like we don't try to do things like for our own team we're very much part of team Google but also ultimately it's like is someone loving this on the end other end of this product? Um, and so that does kind of tie it all together, but they are on Yeah. different ends of the spectrum for sure on terms of size like conventional numbers.

是的，作为局外人，这很令人困惑，但我明白。你现在在 labs 做的所有事情都是基于 AI 的吗？现在 labs 里有什么非 AI 驱动的东西吗？

Yeah, it's quite confusing as an outsider, but I get it. Is everything you're doing in labs now AI based? Is there anything non AI driven in labs now?

是的，嗯，现在肯定都是 AI 驱动的。当我们四五年前开始的时候，我们还在探索其他几个领域，我们做出了决定，至少在可预见的未来，全力投入 AI。不过我们不只是做软件。我的意思是，Google Beam 是我们正在做的项目之一，就像这个不可思议的魔镜，可以创建 3D 版本。我们应该给你一个。嗯，我会接受的，你可以和某人交谈，几乎就像他们在另一边的全息图。是的。所以我们在探索 AI 的其他相邻领域，你知道，你可以认为那几乎像是 AI 硬件。我会接受的。谢谢。我会把我的地址发给你。

Yeah, it's um it's all AI driven right now for sure. when we started, you know, four or five years ago, we had a few other areas we were exploring and we kind of made the call, at least for the foreseeable future, go all in um on AI. We we don't just do software stuff though. I mean, Google Beam is one of the projects we're working on is like this incredible kind of magic mirror that kind of can create like a 3D version. We should get you one. Um I'll take where you can kind of talk to someone almost like they're a hologram on the other side. Yeah. Uh so we are we're exploring kind of other adjacent things to AI like you know you could consider that almost like AI hardware in a way. I I will take it. Thank you. I'll send you my address.

所以感觉消费者领域现在处于一个非常有趣的位置，一直有一种感觉，好像消费者已死。你无能为力。Facebook 有 Google，你知道，就像无法与这些已经占领消费者世界的巨头竞争。但 AI 感觉正在解锁消费者领域的许多机会。我很好奇你对下一个重大突破可能发生在消费者应用中的假设是什么。

So it feels like consumer right now is in a really fun place where there's always been the sense of like consumer's dead. There's nothing you can do. Facebook got Google, you know, like there there's no way to compete against these juggernauts that have taken the consumer world. But AI feels like it's unlocking a lot of opportunity in consumer. I'm curious what your hypothesis is for where the next where a major breakthrough might happen in a consumer app.

是的，我觉得消费者领域是最令人兴奋、竞争最激烈的领域之一，现在所有事情都在发生。所以从那种观点来看，我觉得完全相反。嗯，我认为有几个领域挺有趣的。我的意思是，第一，我认为有一个大问题，我们之前稍微谈过，娱乐将走向何方？嗯，我们会永远看着不同类型的 feed 吗，或者有没有办法让这项技术让我们在现实世界中更紧密地联系在一起，或者与其他人一起做事？我的意思是，对于那可能走向何方有不同的看法。是更多围绕机器人还是更多围绕人？嗯，所以我认为那是一个非常有趣的空间。嗯，我认为我们现在正在目睹，整个消息聊天空间感觉像是，嘿，那可能已经解决了。现在在谷歌内外都有很多不同的实验在进行。嗯，所以感觉那是一个全新的领域，也许不再像以前那样固定。嗯，然后也许第三个我要提出的是，我仍然觉得回到问题，人们在这个世界上面临的一些大问题是什么？我认为，嗯，你知道什么是超级稀缺的？地球上的时间，人们有多少钱以及他们如何省钱。嗯，这些记忆或人们可以一起在现实中拥有的体验之类的。所以我确实觉得也许有新的消费者产品可以构建，可以追求很多这些东西，你知道，无论它采取聊天机器人还是个人智能体的形式，或者无论那会是什么样子，我认为在很多方面还有待发明。

Yeah, I I feel like consumer is one of the most like exciting competitive all the things happening right now. So it feels completely opposite to me uh from that kind of view. Um a couple of areas I think that are kind of interesting. I mean, one, I think there's a big question, we talked a little bit earlier of just like where's entertainment going to go? Um, are we going to be looking at like different types of feeds forever or are there ways that this technology can bring us maybe closer together in the real world or do things with other people? I mean, there's different views on where that could go. Is it like more around bots or more around people? Um, and so I think that's a very interesting space. Um I think we're watching right before us now like the entire kind of messaging chat space felt like hey that was sort of maybe solved. There's lots of different experiments happening on that right now both inside Google and outside. Um so that feels like a whole another area that maybe is like no longer as fixed as it once felt. Um, and then maybe the third one I would throw out is I still feel like going back again to the problems like what are some of the big problems people face in the world? And I think like um you know what are things that are super scarce? Time on earth, how much money people have and how they can save money. Um these kind of memories or like experiences that people can have kind of IRL together and that kind of thing. So I do feel like there's maybe like new consumer products to be built uh that can go after a lot of that stuff that you know whether it takes the form factor of a a chatbot or a personal agent or whatever that's going to look like I think is kind of yet to be invented in a lot of ways.

好的。让我沿着这些思路问你一个辛辣的问题。我非常好奇你的看法。所以，感觉现在每个推出的 AI 助手应用基本上都吸入了 Gmail、Google 日历和 Docs，所有谷歌数据，所有这些 juicy 的谷歌东西。嗯，连接并利用它在谷歌内部做所有这些神奇的事情。我无法做任何这些事情。构建任何东西都太难了，首先，你可能正在做 AI 助手，但据我所见，那里还没有任何东西。然后一般来说，感觉每个人都拿走了所有这些 juicy 的数据并用它做神奇的事情，而谷歌却没有。是什么阻止了你们做类似的事情？是隐私问题吗？是官僚主义吗？它要来了吗？你能说什么？

Okay. Let me ask you a spicy question along these lines. I'm so curious to get your take. So, it feels like every every uh AI assistant app that's launching these days basically sucks in Gmail and Google Calendar and Docs, all the Google data, all this juicy Google stuff. Uh connects and does all these magical things with it within Google. I cannot do any of these things. It's so hard to build anything uh like there's first of all, you may be working on AI assistant, but there's nothing there yet as far as I can see. And then just generally it feels like everyone's just taken all this juicy data and doing magical things with it and Google hasn't. What is what's kept you guys from doing something like that? Is like privacy concerns? Is it works bureaucracy stuff? Is it coming? What what can you say?

是的。是的。是的。所以，嗯，今天已经有部分功能了，比如如果你在 Gemini 或 Gemini Spark 中，你实际上可以连接所有这些东西，而且它相当强大。我认为我们正在迭代的地方是，我们一直处于一个世界，即使你看一些其他竞争对手，也几乎有不同的模式可以进入，我认为即使从过去几周的经验教训是，忘记模式和切换，就像一个提示框，告诉它你想要什么，它就会为你做事。所以那绝对是不仅我们要去的地方，也是其他人要去的地方。

Yeah. Yeah. Yeah. So um there's parts of it out there today like if you're in Gemini in Gemini Spark, you can actually connect all that stuff and it's quite powerful. I think where we're iterating on that though is we've been in a world where even if you look at some of the other competitors there different modes almost that you go into and I think the lesson even from the last couple of weeks is forget the modes and toggles just like one prompt box tell it what you want and it just does stuff for you. So that that's definitely where not only where we're headed where others are are headed.

我觉得这算是整个行业正在发生的一种更广泛的、几乎可以说是 UX 简化。关于数据那部分，其实挺有意思，因为人们最常来 ping 我或者其他人的一件事就是：“天哪，Google，我所有东西都在你那儿，你就让这东西能用起来吧。”而且实际上很多人不太愿意把它连接到其他竞品上。所以请持续关注。我们听到了，听得很清楚。这方面有很多工作——如果你上网搜一下“个人智能”这个方向，那就是我们思考这件事的方式。你想要的 Gemini 是个人化的、主动的、强大的，能为你所用。这就是过去一年左右我们一直在朝着的愿景。我们现在正在打磨很多东西，很快就会推出。

I think that's kind of a broader, almost like UX simplification happening across the industry. On the data bits there, it's interesting because actually one of the main things people will ping me about or others is like, "Oh man, Google, I've got all my stuff with you. Just make the thing work." And there's a lot of reluctance actually to be connecting it to a lot of other sort of competitor products. So watch this space. We hear you loud and clear. There's a lot of work — if you go online and just look under kind of personal intelligence, that's sort of the way we think about this stuff. You want a Gemini that is personal, proactive, powerful, that sort of works for you. And so that's been the vision for the last kind of year or so that we're headed towards. And there's a lot of stuff we're playing with right now that'll be out soon.

好。我很期待。感觉就像——是啊，我邮箱里跑着那么多小日程和各种东西。我就想，天哪，Google 怎么不直接做这个？确实感觉你们的优势就是分发。所以一旦有类似最近 Muse 那样的东西出来，要把它做大、说服人们去用会非常容易，就像在 AI 模式里那样。总之，好，我很期待。事情在发生。事情确实在发生。你怎么看？换个方向。你觉得现在 AI 里什么被低估了，什么被高估了，如果有被高估的话？

All right. I'm excited. It just feels like — yeah, like I have so many little schedules and things running within my email. I'm just like, man, why didn't Google just do this? It does feel that the advantage you all have is distribution. So once something happens similar to Muse recently, it's going to be very easy to grow it and convince people to use it, similar to within like AI mode. So anyway, okay, I'm excited. Things are happening. Things are definitely happening. What do you think? So kind of going a different direction. What do you think's underhyped in AI right now and what do you think is overhyped, if anything is overhyped?

哦，是的。是的。被低估的——这个夏天我想了很多。我最后在公司内部写了一份文档，讲的是实验室的原则，关于我们如何、以及几乎是为什么要构建我们所构建的东西。所以也许被低估的是更多围绕原则、价值观的讨论。我坚信，无论你在 Google、是创业公司创始人，还是介于两者之间，你都是通过你的产品在说话，你的产品实际上代表并几乎编码了那些原则。所以我希望行业里能有更多围绕这个的讨论。以及我们到底想构建什么样的东西？我们想要什么样的未来？总之，这就是我认为被低估的。因为我觉得，是的，这方面可以更多。我认为被高估的——我想我已经说了一年左右了，但我仍然觉得它被高估了——模型基准。而且我仍然——你知道，很多朋友、很多实验室，大家基本上还在看同一套基准。但我觉得，你知道，我长大的地方、我的出身，以及我思考产品开发的方式是：世界上大多数人永远不会、永远不会、永远不会在意一个 ELO 评分。他们甚至可能不知道怎么念 ELO。就像，你知道吗？这根本不重要。所以这就是我回到的——我觉得现在 AI 里很多讨论都是关于速度和参数、基准，这些显然是现状和能力的代理指标。但我仍然觉得，有时候作为一个行业，会过度偏向那一边，而忽略了这东西为什么对某个人有用，以及那个能带来真正价值、真正帮到人的产品或功能是什么。总之，这就是我的高估和低估。

Oh yeah. Yeah. Underhyped — I was thinking a lot about this over the summer. I ended up writing kind of a doc internally just around like labs' principles of like how and almost like why are we building what we build? And so maybe the underhyped thing is more of a discussion around principles, values. I believe very strongly whether you're at Google or a startup founder or anywhere in between, you speak through your products and your products actually represent and almost encode those principles. And so I wish there was a lot more discussion in the industry happening around that. And sort of what kinds of things do we want to build? What kind of future do we want? So anyway, that would be my underhyped one. Because I think, yeah, there could be more of that. I think the overhyped one — I think I've been saying this maybe for a year now, but I still think it's overhyped — model benchmarks. And I still — you know, a lot of friends and a lot of labs and everyone's still looking at the same set of benchmarks for the most part. But I think, you know, where I grew up and where I'm from and I guess how I think about product development is like most people in the world are never ever ever going to care about an ELO rating. They may not even know how to pronounce ELO. It's like, do you know what? It just doesn't matter. And so that's where I kind of get back to — a lot of I feel like the talk in AI right now is about speeds and feeds and benchmarks, and these are proxies obviously for where things are and capabilities. But I still feel like sometimes as an industry it can kind of over-rotate to that and kind of lose sight of like why is this useful to someone and what's the product or the feature that's going to deliver real value to help people. So anyway, those would be my over-unders.

是的。也是沿着这个思路。总是——也很难知道什么更好。比如你怎么知道发生了什么？你有了这个新模型。它是有史以来最好的模型。但实际用起来，它跟上一个大家也认为是有史以来最好的模型并没有那么大差别。每次有模型发布，我们就有了 AGI。我们现在就有 AGI。所以基准想向你展示的是：这里它更好。但如果你没有——你就坐在那儿。好吧。这还行。这更好。我喜欢它这里做的。

Yeah. And it's also along those lines. It's always — it's also hard to know what is better. Like how do you know what's going on? Like you have this new model. It's the best model ever. It's like in practice it's not that much different than the previous model that also everyone thought was the best model ever. We have AGI every time there's a model launch. We have AGI now. And so like the benchmarks like are trying to show you here's where it's better. But if you didn't — like you're just sitting there. Okay. This is okay. This is better. I like what it's doing here.

是的，不过我觉得这也是——我感觉很多关注你、听你节目的人都在说，拜托拜托拜托，去想些了不起的产品吧，因为归根结底，所有这些模型能力、基准和智能，最终都要转化成：你能不能做出人们想要的东西？所以对我来说，作为一个产品人，这是多么好的时代，因为你面前有一份巨大的菜单，上面是那些曾经几乎可能、而现在正一周比一周更多地变成可能的东西。

Yeah, I think this is also though where — I feel like a lot of folks that like follow you and listen to you is like, please please please think of amazing products, like because ultimately all these model capabilities and benchmarks and all the intelligence gets translated into just like, can you build something people want? And so to me it's like what a time to be alive as a product person, because you have kind of this like huge menu of things that were almost possible that are now possible more and more with each passing week.

你刚才说的第一点，最近和 OpenAI 的 Tara 的一次对话里也提到过，就是既然我们现在什么都能做，而 AI 对往哪走又有那么多意见。你说的完全正确，就是：我们想让世界变成什么样？我们想要什么——我们想要的未来愿景是什么？而不是：好，这些我们都能做，很棒，也许我们并不需要做所有这些事。

The first point you made there was something that came up recently in a conversation with Tara from OpenAI about how now that we could just build everything and AI has so many opinions about where to go. What you said is exactly right, which is what do we want the world to look like? What do we want — what is the vision of the future we want? Not okay, we can do all these things, that's great, let's maybe we don't need to do all these things.

对。

Right.

所以我觉得那是一个非常重点。

So I think that's a really important point there.

是的，绝对。绝对。

Yeah, definitely. Definitely.

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在你共事的人当中，你发现哪些技能的价值在上升，哪些你觉得在下降？当你看到现在做得非常好的人时，他们身上有哪些特质和技能，相比那些现在可能没那么重要的东西？

What skills are you finding are trending up in value in the people that you're working with and what do you feel are trending down when you look at people are doing really well now? What are the kind of the attributes and skills of those people versus things that are maybe less important now?

是的，我觉得外面关于品味、判断力和 vibe coding 之类的讨论已经很多了。我想找的东西——我一直在试图找出哪些是被错误定价的信号。所以比如一个我觉得是——你有时会听到人们谈论某人的学习速率，比如他们有没有成长型思维，他们的学习速率是多少。我现在其实更看重的是——他们的“遗忘速率”是多少？就是他们能多快学会一样东西，然后又基于他们测试产品时看到的东西之类，把它放下、走开。遗忘速率是其中之一。

Yeah, I feel like there's a whole lot out there on taste and judgment and vibe coding and all of that. I guess the things I'm looking for — I'm always trying to find like what are the mispriced signals. And so like one I think is — you'll hear sometimes people talk about like what's someone's like learning rate, like do they have a growth mindset, what's their learning rate. I'm actually looking a lot right now for people — what's their unlearning rate? Like how fast can they learn something and then walk away from it, based on maybe what they're seeing when they test their product or something. Unlearning rate is one.

另一件我感兴趣的事：大约一年前我读了一本关于罗杰·费德勒的书，那位了不起的网球选手。书里有个说法，说费德勒拥有“爆发式耐力”。这个措辞太美了，还有头韵什么的。但它讲的是人们如何照顾自己和身边的人，从而能够非常拼命——这就是爆发的那部分——但他们能持续一段时间，并找到方法调整节奏。在实验室里，我们有“实验室季”，会讨论这个。所以我认为那种爆发式耐力，这种“遗忘率”……

Another one I'm interested in: I read a book a year or so ago about Roger Federer, the amazing tennis player, and there was this phrase about Federer having 'explosive endurance.' It's just this beautiful turn of phrase, with the alliteration and everything. But it's about how people take care of themselves and the people around them so they can go really hard—that's the explosive part—but they can do it over a while, and they find ways to pace themselves. In labs we have seasons of labs where we talk about this. So I think that explosive endurance, this unlearning rate...

然后也许另一个我想说的是：尽管编程和其他事情的趋势是你可以指挥很多智能体，不必和那么多人合作，但我仍然觉得协作以及你如何与人合作现在更加重要。我们非常看重的一点是：一个人能否融合并桥接这两个世界——既能与一个智能体或一群智能体出色协作，也能与人出色协作？我想我们在实验室团队和 Gemini 团队所相信的是，与人合作仍然有太多乐趣。但问题在于，如何找到合适的化学反应？所以也许我要说的一点是，能够建立信任、能够规模化信任的人——这是一切伟大协作的基础。所以这也是我一直在寻找的另一个信号：这个人能多快与人建立信任，并创造那种环境，如果这说得通的话。

And then maybe another one I would say is: as much as coding and other things are trending towards you being able to direct lots of agents and not having to work with as many people, I still feel like collaboration and how you work with people matters even more now. One of the things we look a lot for is: can someone blend and bridge these worlds where they're an incredible collaborator with an agent or a swarm of agents but also with people? And I guess what we believe on the labs team and on the Gemini team is that there's still just so much joy in working with people. But it's like, how do you find the right chemistry? So maybe one thing I'd say there is people that can build trust, that can scale trust—that underpins any kind of great collaboration. So that's another signal I'm always looking for: how fast can this person build trust with people and create that kind of environment, if that makes sense.

是的，这些太有意思了。关于最后一点，随着 AI 的崛起，你是否发现这是一种不断增长、新兴、甚至更重要的技能？我很好奇为什么。

Yeah, these are so interesting. On that last one, is that kind of a growing, emerging, even more important skill you're finding with the rise of AI? And I'm curious why.

我认为是的，有几个原因。我的意思是，一个可能是 Google 独有的：它是一个更大的组织，所以你必须能够做到这一点。但那些不觉得是 Google 独有的原因：第一，感觉随着制造产品的执行成本下降，我们将能够制造更多产品——你可能用同样的人制造同样的产品，但我认为会有更多——你可能也看到了——人们会与不同的人组队来制造东西。所以当我们考虑几乎像是为实验室项目组建一个新团队时，这非常有趣。我们过去说大约五到七个人。现在大约是两到三个人。也许四个。但这就像那些人——你几乎可以想象成超级有才华的音乐家，他们与不同的人组队，然后一起演奏不同的歌曲。歌曲就是产品。但那些就是实验室里的 MVP，你可以说，嘿，放弃这种 PM 角色，他们也能编码和设计，因为所有角色都在与他人模糊化，然后看看他们如何一起即兴创作。所以我认为这就是我的预测：这种技能的重要性几乎会增加，因为会有更多产品，因为会有更多这种自由球员一起即兴创作。

I think so, for a couple of reasons. I mean, I would say one maybe is uniquely Google: it's a larger organization, so you've got to be able to do that. But the ones that don't feel uniquely Google: one, it feels like as the execution cost of making products goes down, we'll be able to make more products—which you may make the same products with the same people, but I think there's a lot more—you probably see this too—people will team up with different people to make stuff. And so it's very interesting when we're thinking about almost like fielding a new team for a labs project. We used to say it's about five to seven people. Now it's about two to three people. Maybe four. But it's kind of like those people—you can almost imagine like super talented musicians who team up with different people and then they play different songs together. The songs are the products. But it's like those are the MVPs in labs where you can be like, hey, drop this sort of PM that can also code and design because all the roles are blurring with other people, and kind of see how they jam on stuff together. So I think that's where my prediction is that skill will almost increase in importance because there will be more products and because there'll be more of this kind of free agents jamming on stuff together.

顺着这个思路，我想你一直在把设计师、工程师、PM 拉进实验室，他们一起工作，有时不同职能会牵头。在领导实验室团队的产品创意方面，你是否发现谁最有影响力、最成功，比如 PM 与设计的比例？比如，PM 是否变得更有价值或类似的情况？

Along those lines, I imagine you have been pulling designers, engineers, PMs into labs and they kind of all work together and sometimes different functions take leads. Has there been a shift in who you find is most impactful and successful in leading product ideas in labs teams, in terms of the ratio of PM versus design, for example? Like, are PMs becoming more valuable or something like that?

是的，这很有趣。我们一直在大量研究这个，实际上也在大量测试。总的来说，我想说 PM 恰好可能是天生更适合的职能，因为它更横向。感觉它可能更快地适应了其他一些职能。当我们全公司进行小型构建者试点时，我们看到了这一点。反馈回来的情况是，哦是的，那就像——也许我不想说更容易，但也许 PM 更习惯于，好吧，我在这个会议里。我得模拟律师或 BD 人员或销售，你明白我的意思吗？所以我认为在某种程度上，选择进入这个职能的人可能有一些内在特质。所以这绝对是真实的。但我想说，我们最优秀的人可以来自任何职能。而且我甚至想扩大范围，Lenny，我们看到战略和运营人员、BD 人员和营销人员，你知道，在实验室里成为构建者，他们真的很棒。而且我认为——也许这是另一个被过度炒作或炒作不足的事情——我认为现在人们可能过度炒作“每个人都是构建者”，这只是这个新工作职能，一切都有点相同。我实际上觉得，至少我们看到的是，人们仍然有自己的专长。就像大学里的主修或辅修之类的。我觉得如果每个人都成为构建者，你可能会失去很多尊重和欣赏，以及显然来自那些专长的专业知识。所以我认为当我们组建团队时，即使我们可能说这更像是一个构建者团队，我们仍然在考虑专长在哪里，这最终也非常重要。

Yeah, it's interesting. We've been studying this a lot and actually testing a lot of this too. I would say in general, PM happens to be the function maybe by nature because it's a bit more horizontal. That feels like it's maybe been able to adapt to some of the other functions faster. And we see this when we'll run little builder pilots across the company. What comes back is like, oh yeah, that's like—maybe I don't want to say it's easier, but maybe PMs are more accustomed to like, all right, I'm in this meeting. I got to simulate something as a lawyer or as a BD person or as a sales, do you know what I mean? So I think in some way maybe there's some inherentness in who selects into that. So that definitely is true. But I would say our best people can kind of come from any function. And though I would also even widen it, Lenny, we're seeing like strategy and ops people and BD people and marketing people, you know, kind of be like builders in labs and they are really good. And I think—what maybe this is another overhyped underhyped thing—I think right now people are maybe overhyping like everybody's a builder and it's just this new job function and everything's kind of the same. I actually feel like, well, at least what we're seeing is that people still have their specialty. It's like their major or minor in college or something. And I feel like there's a risk if everybody becomes a builder that you lose a lot of respect and appreciation and obviously the expertise that comes from those specialties. And so I think when we set up teams, even though we may be like this is more of like a builder crew, we're still thinking about like where are the specialties and that ends up being super important as well.

我完全同意。是的，我喜欢这个。我喜欢这个主修和辅修的比喻。这是一个非常有趣的思考方式。就像你可以更擅长构建，但你仍然——你的 PM 技能仍然是你最擅长的主要事情。

I completely agree. Yeah, I like that. I like this metaphor of the major and minor. That's a really fun way to think about it. Like you can be better at building, but you're still—your PM skills are still the primary thing you're amazing at.

当然。我认为这是我们给团队中许多新 PM 的建议，比如 APM 或职业生涯早期的人：你在氛围编程并制作所有这些原型，这很棒，但要做这些是为了成为一个卓越、非凡的 PM。不要丢掉那个主修——那是你需要磨练的，尤其是在早期。

Definitely. And I think that's the advice we give especially to a lot of new PMs on the teams, like APMs or people earlier in their career: it's great you're vibe coding and you're making all these prototypes, but do that in service of becoming an exceptional, extraordinary PM. And don't lose that major—that's what you need to hone, especially when you're early on.

我喜欢你描述的方式，PM 非常擅长模拟其他职能，比如像 AI 那样思考协作。

I love the way you described it where PMs are really good at simulating other functions, such as like an AI way of thinking about collaborating.

是的。是的。

Yeah. Yeah.

还有这个爆发式耐力的想法。最近有人发推文。他们说，当它既是马拉松又是冲刺时，叫什么？

And this idea of explosive endurance. Someone tweeted this recently. They're like, what's it called when it's both a marathon and a sprint?

那就是像和罗杰·费德勒谈谈。是的。是的。

It's that like talk to Roger Federer. Yeah. Yeah.

我觉得现在每个人都处于这种状态。这就像这个播客和现在科技界的一个持续主题和趋势，就是每个人都处于这种马拉松加冲刺模式。

And I feel like everyone's in that right now. That's just like a constant theme and trend on this podcast and just in tech right now is just everyone's in this marathon plus sprint mode.

是的。是的。

Yes. Yeah.

天哪，我猜你有什么办法帮助人们应对这种情况吗，因为感觉它永不停歇。

Man, I guess is there anything that you do to help people deal with that because it feels like it's non-stop.

是的。

Yeah.

Yeah, one of the things we try to do — I mentioned it a little bit earlier, but I can unpack it some — is we think of seasons in labs. At any given point there are 20 or 30 experiments running simultaneously, but for each individual little team, we try to create a little bit of a milestone or a rhythm to the work. Sometimes it's just flat-out full-on. The best lesson I've learned as a leader is almost to name that, declare that — people opt in or opt out of that. But also be very clear when a team is not in that mode. And I think it's about how you architect almost a rhythm to the year where it's like, hey, we've got a big model coming. These five products are super important to showcase this model. We think this model will propel them. Like U5 is explosive time. Do you know what I mean? So it's trying to create a common language around that. In a lot of ways, PMs can be very effective if they can come up with the shorthand or the common language. We actually put a lot of thought into that too: all right, you all are on right now. Whereas after they go through that — say after a Google I/O — a lot of labs teams will sprint after I/O. June is like, hey, just go hack, go rediscover what's new, go build, have fun. And then it's so interesting, Lenny, because the instinct or the temptation is like, oh man, it's June, it's unproductive, we're not shipping. And it's like, no, actually those are where all the new seeds are coming from for the next season. Do you know what I mean? So trying to think through the rhythm of that is one way we try to do it. I don't think we always get it right, by the way. And one of the things we're talking a lot about on the team is — I guess in the past people would talk about work-life balance, and there were other ways this conversation got framed. I think why I like things like explosive endurance or concepts like that is we want to be doing this as a team for many, many years. So you can't just empty the tank in 9 months and kill yourself, right? You have to have a view towards the long term, but also recognize the moment you're in is fast.

I love the tactic of just naming it, having a lot of power, and just making it clear: this is the mode we're in now. It won't be forever.

Right. Right.

And something I found is the opposite also is dangerous. When you have too little to do and too little stress and too little pedal on the metal, people get bored and start looking for other jobs. They're just like, this sucks.

Yeah. Yeah. Yeah. I think there's always something there though. You're right. We talk on the team a little bit about never waste an event or a date. You can think about even as a startup: where's that moment you want to intersect with something in the world? Whether for us that's a Google I/O or a model release or whatever, I think that's always healthy to be thinking about. I got a question the other day on Gemini: they're like, what's our two-year roadmap? And I was like, uh, we have a six-month roadmap on this thing. We have a multi-year vision, but the world has changed so much too. Some of it is like the thing I saw two days ago is now a project that happened in 48 hours. You can't plan for that in a way. So that's the other element — you almost have to recognize in the moment.

Yeah. So along those lines, how has planning changed in the past couple years? You guys are different from the rest of Google because everything is new, but just what have you seen in terms of timelines and time frames shift in planning with the rise of AI?

Yeah, we usually are thinking somewhere on the order of about six months. And usually I say that because that's almost the possible window where you assume every lab is cranking out some new pre-training model a couple times a year. There are individual points in between. So you kind of have an overall cadence of where the models are, and then I think we're almost imagining in about a hundred days — we always think about where you can move your product meaningfully forward. Our best labs teams all do that. They'll go from idea to some meaningful milestone in like 50 to 100 days. And part of that is also how do you design a culture and an environment where you unblock a lot of stuff so you can just let people cook. So that's the other part — creating that environment. But we think about planning as kind of almost like rolling six months, maybe, is to answer your question.

So I had this Lenny and Friends Summit — it was last week of the today we're recording this — and Dan Shipper gave this really interesting talk about how to build where the tech is just constantly changing underneath you. And his advice is to have a frontier team that's dedicated to testing out the new stuff, and basically it's their job to try all the new stuff, report on what we need to pay attention to, so that the rest of the company can not have to be distracted and focus on the task at hand. How do you feel about that as a model for companies?

I think every company definitely needs a set of people, a team, however you want to manifest it, whose job is to be at the frontier. They're almost like — if they haven't heard about the latest hot thing viral on X in the last 24 hours, it's like, what are you doing at your job? You know what I mean? So I think there's definitely an element of wanting people plugged in to the hive mind of how people are building and thinking in all the model releases. They're the people who have like eight $200-a-month subscriptions on everything. Do you know what I like? So you have to architect the organization where that can exist. I think the second thing though that's just as important is the environment in which those people can build. So that's the other part of that. And then I think the third part, which is honestly where — if you look at the history, and I've read a bunch of books on this, because most — if you just look at the data, a large company who starts a lab, the lab is usually ineffective and fizzles out after about 3 to 4 years, or they have duration but the company can never commercialize the things coming out of the lab. And so you get things like someone comes by and sees the future and then they do it as a separate company or whatever, right? And there are famous examples throughout history of that.

所以我认为存在一种有趣的平衡：你能否拥有一支生活在前沿的团队，就像 Dan 说的，他们在构建前沿的东西，但又能以某种方式桥接或连接整个大公司，而不是让人觉得“哦，那只是一群古怪的研发小组，总是搞些噱头和玩具”。你明白我的意思吗？所以我认为需要某种特定的人或一群人，他们能够说：“嘿，那东西现在看起来像个玩具，但五年后它将对我们的未来至关重要。”而实际上，至少从历史来看，有时这些前沿想法会失败。你可能把前两件事做对了，但第三件事失败了，那么整个事情就真的无关紧要了。你明白我的意思吗？

And so I think there is this interesting balance of: can you have a team of people who live at the frontier, like Dan says, who are building frontier things, but can somehow bridge or connect across the bigger company in a way that it's not, oh, that's just some weird R&D group always coming up with gimmicks and toys? Do you know what I mean? And so I think it takes a certain person or a certain set of people who can actually be like, "Hey, that thing looks like a toy right now. That's going to be essential to our future in five years." And that's actually where, at least studying history, sometimes these frontier ideas fall short. You can get the first two things right and then fail on the third one, and then the whole thing really doesn't matter. Do you know what I mean?

是的。这很有趣。我刚才在想，就连 Anthropic 也有一个 labs 团队。作为最前沿的公司，他们已经在最前沿了。他们说，好吧，但我们还需要一个 labs 团队来真正关注前沿中的前沿。

Yeah. It's interesting. I was just like, even Anthropic has a labs team. Like the most cutting edge company, they're just like at the frontier already. They're like, okay, but we also need a labs team to actually watch the frontier frontier.

是的，没错。我们内部也开玩笑说——现在 labs 已经发展壮大了，我们有几个项目幸运地取得了成功，用户很多并且在增长——我们内部实际上已经形成了一种共同语言。我们开始发现，像 Notebook 这样用户量更大的项目，或者 Flow、AI Studio，或者这些从 labs 中成长起来的东西——嗯，它们在某种程度上存在一种风险，会挤占从 0 到 1 的东西。

Yeah, that's right. Well, one thing we joke about too inside—as labs has grown now, and we've had a few projects thankfully have kind of hit and are, you know, lots of users now and growing—we've actually internally to this point of like common language. What we started to find was a bigger project like Notebook in terms of users, or Flow, or AI Studio, or these things that are like kind of grown out of labs—um, they were in some ways there's a risk they crowd out the zero to one stuff.

所以我们开始使用的术语是：有从 0 到 1 的 labs，有从 1 到 10 的 labs，还有从 10 到 100 的。这些可能对你的听众来说没什么意义，但对我们来说，我们实际上编码了这些是实验室生命周期的不同阶段。我们希望所有这些产品都有这种共同的创新能量。但在每个阶段内部，挑战非常不同，你优化的东西也非常不同。在从 0 到 1 的阶段，你关注的是眼球，就像我们讨论过的。而在从 10 到 100 的阶段，你可能关注的是瀑布图和 CPA，思考我们如何真正将人们转化为产品中的这些神奇时刻，这在很多方面是一个规模扩张的游戏。

And so the terms we've started using is like there's zero to one labs, there's one to 10 labs, and there's like 10 to 100. And these may not mean anything to your audience, but to us, we actually kind of encoded like these are different stages of like the lab's life cycle. And we want all of these products to have this like innovative energy that's common. But inside each of those stages, there's very different challenges and very different things you're optimizing for. And in zero to one, you're looking at eyeballs like we talked about. And maybe 10 to 100 you're looking at like waterfalls and CPAs and thinking about like how are we actually converting people to like these like magic moments in the product, and it's a scaling game in a lot of ways.

有听众可能确信他们应该建立一个前沿团队，一个 labs 团队，而且感觉 labs 团队已经有所演变。过去像是“建立下一个大业务单元”是这里的想法。现在更像是：好吧，有什么新技术能解锁我们核心业务的某些东西？我怀疑这是否属实，但对我来说感觉就是这样。不过，考虑到这一点，对于想在公司内部建立 labs 团队的人，有什么三个建议吗？

Someone listening is convinced they should set up a frontier team, a labs team, and it feels like labs teams have evolved a little bit. Used to be like build the next big business unit is like the idea here. It's like, okay, what's like a new technology that is unlocking something our core business? I wonder if that's true, but that's what it feels like to me. But I guess just with that in mind, what are maybe three tips for someone that wants to set up a labs team internally?

是的，我认为第一，你必须尝试创造一个能让奇怪事物生长的空间，你不能只是把它安放在现有业务单元之下。它必须有自己的独立性。嗯，这是第一点。在某些公司，这意味着它需要向 CEO 汇报，或者需要保持足够的距离——嗯，如果你想我们可以深入讨论——但这非常重要。我认为第二点是一组人，在我们这里，这是用户第一，Google 第二，labs 第三，思考实验室的工作是让用户成功，让 Google 成功。而不是让自己成功。所以有一点谦逊或协作，或者这种心态：成功看起来是什么样子？我认为对我们来说，我们如何分解这一点，以及我如何鼓励公司思考这一点，就像：你这个实验室的目标是将东西毕业到现有产品，还是你的目标是去发明新的产品线和类别？在我们这里，我们开始时是一个毕业实验室，随着时间的推移，我们开始意识到 AI 真的改变和模糊了很多类别，所以它扩展了。但非常清楚你在玩什么游戏，以及赢或输看起来是什么样子，这将是第二点。所以在某种程度上是隔离的，但也是同一个团队的一部分。嗯，我认为第三点——我们在 labs 里讨论过一点——我可以想象，也许对听着的 CEO 或其他 C 级人员来说，使用你的实验室不仅用于产品开发或技术探索，甚至用于挑战公司如何运作，几乎就像事情发生的方式。嗯，这实际上是我们团队使用的短语：实验室有时在 Google 制造好的麻烦。所以有你不想要的坏麻烦。但好的麻烦——举个例子。我们是最早的团队之一，我们说，我们看到工作角色模糊了。我们必须有一个构建者职位阶梯，我们需要以不同的方式思考它，我们应该使用 labs 作为试点的地方，然后再在 Google 推广。所以这是另一种方式，你可以思考实验室的多维度性。你只是思考流程和工作方式，而不一定是产品。这真的很有趣。

Yeah, I think one, you got to try to create a space where weird things can grow, and you can't just nestle this like under an existing business unit. It has to have its own kind of independence. Uh, is one. And that in some companies that means it needs to report to the CEO or it needs to report into enough of a distance in a way—um, and we can go into that if you want—but that's super important. I think the second thing is is a set of people, and in the case of us, this was this users first, Google second, labs third, thinking where the job of the lab is to make users successful and make Google successful. It's not to make itself successful. And so there's a bit of a maybe a humility or a collaboration or kind of this mindset of like what does success look like? And I think for us how we've broken that down and how I would encourage companies to think about it is like: is your goal of this lab to graduate things to existing products, or is your goal to go invent new product lines and categories? And in our case, we started and it was a graduation lab, and it's expanded over time as we've started to realize AI really transforms and blurs a lot of categories. But being very clear about like what game you're playing and what does winning or losing look like would be the second thing. So isolated in some way but also part of the same team. Um, and I think the third thing—and we talk about this a little bit on labs—is, and I could imagine for maybe CEOs listening or other kind of C-suite people, use your lab not just for product development or technology exploration but even for challenging how the company works and almost like the way things happen. Um, and that's actually the phrase we use on the team is lab sometimes creates good trouble at Google. So there's like bad trouble you don't want to create. But good trouble—give you an example. We were one of the first teams that were like, we're seeing the job roles blur. We have to have a builder job ladder and we need to think about it differently, and we should use labs as the place to pilot it before we roll it out across Google. And so that's another way you can think of like the multi-dimensionality of a lab in a way. You just like think about the processes and ways of working, not just products necessarily. That's really interesting.

是的。是的。

Yeah. Yeah.

那么你会把什么样的人放在这个实验室团队里？你提到这个“遗忘率”是一个很有趣的思考方式。你还看重什么？在实验室团队里，你想避免什么样的人？

What about the type of people that you would put on this lab team? You mentioned this unlearning rate is a really interesting way to think about. What else what do you look for and what's like a person you want to kind of avoid on the lab team?

是的。是的。太好了。嗯，天哪，我们痴迷于寻找那些就是无法停止构建的人。我之前提到过。我们有一个完整的文档，团队 labs 的概述。嗯，我们也有一个关于 Gemini 的。Gemini 的概述，当有人加入团队的第一周，我会通过电子邮件发给他们，而且他们中的大多数人在我们的招聘筛选中已经看过它了。他们一直在构建。他们充满求知欲。他们在阅读，他们在 X 上，他们在听播客。他们痴迷于解决人们的问题，而不是自己的 ego 或荣耀。他们是那种当你和他们在一起时，他们会增加能量的人。你离开谈话后，你会想，我想和那个人在一起。就像，我会和那个人一起穿墙。你明白我的意思吗？嗯，我们有大约 17 或 18 个这样的人。也许之后我可以把其中一些发给你，如果你想的话，如果你想包括在节目笔记中。嗯，

Yeah. Yeah. Great. Um, man, we are we are obsessed about finding people who just like can't stop themselves from building. I mentioned that earlier. We have a whole doc on the team, labs in a nutshell. Uh, we have one on Gemini, too. Gemini in a nutshell, the first week someone joins the team, I email it to them, and most of them have seen it before as part of some of our hiring screening, too. They build all the time. They are intellectually curious. They're reading, they're on X, they're listening to podcasts. They are obsessed about solving people's problems, not about their own ego or glory. They are the people when you're around them, they add energy. You leave a conversation, you're like, I want to be with that person. It's like, I'll run through a wall with that person. Do you know what I mean? Um, we've got like 17 or 18 of them. Maybe I can send some of them to you after if you want if you want to include in the show notes. Uh,

是的，但这是非常重要的一部分。我谈到的第三点，作为建立实验室的建议。这不仅仅是关于职位阶梯之类的。这实际上关于你试图引进的未来之人，他们会以不同的方式思考，以不同的方式挑战，这是一种不同的类型，我们还发现，随着这些产品的成长，从 0 到 1 的人与从 1 到 10 和从 10 到 100 的人也有点不同。

Yeah, but it's it's um it's such an important part. And that third thing I talked about as like a tip for setting up a lab. It's not just about job ladders and stuff. It's literally about who are the people of the future that you are trying to bring in that are going to think different and challenge things different and it is it's a different type and what we've also found as these products have grown the zero to one people are different a little bit than the one to 10 and the 10 to 100 too.

所以，这就像是你如何创造一些共同点？但我确实认为，当你和某人交谈时，比如在面试中，如果我在和某人交谈，他们说：“嘿，让我给你看看我刚做的这个东西”，立刻就有了可信度。或者，如果我问他们关于未知的、非结构化的黑暗洞穴，这些事件，而他们说：“我不知道哪条路是前进的方向，我该怎么弄清楚？”那些对此充满活力的人，可信度会大大提升。所以，是的，你肯定在寻找某种特定类型的人。

So it's like how do you kind of create some commonality? But I do think when you're talking to someone, you're looking at, like in an interview, if I'm talking to someone and they're like, 'Hey, let me show you this thing I just built,' instant credibility. Or if I ask them questions about unknown, unstructured dark caves, these events, and they're like, 'I don't know which way is forward, how do I figure it out?' People that are energized by that, huge credibility boost. So yeah, there's definitely a certain type that you're looking for.

在组织结构方面，人们犯的最大错误是什么？

In terms of the org structure, what's the biggest mistake people make?

是的，我认为，实际上我给你一个我们正在讨论的现场例子，就是我们正在试图弄清楚，你多大程度上隔离不同的子团队去追求目标，而不是尝试创建主题性的分组。例如，我们讨论过互动娱乐作为一个领域，或者像一个我们感兴趣钓鱼的池塘。那么，你是如何做到这一点的？是让五个人分别尝试五次吗？所以，有时候我认为人们可能急于组建一个团队，也许有一种倾向于整合、让它变得整洁。而我认为我多年来可能以艰难的方式学到的是，实际上有时候你必须在混乱中生活一点，几乎就像看看会出现什么，但仍然愿意做出那些改变。这些是组织设计团队之类的事情。另一个变化，或者另一件我要说的事情，有时候一个常见的错误是，你雇用了太多人太快。这发生在大公司，也发生在初创公司。有时候看着，哦，我们的团队在上个季度或六个月或随便什么时间里翻倍或三倍，这可能会让人上瘾。而这些只是虚荣指标，大多数时候真的很糟糕。所以我认为这是另一件事，就像一个常见的错误。我记得多年前我在一个项目上，我们达到了大约 30 名工程师，我非常高兴，但我们没有产品市场契合度，却有一个非常鼓舞人心的愿景。你可能知道最终结果如何。

Yeah, I think you know it's actually I'll give you a live one we're talking about right now is like we're trying to figure out how much you kind of isolate different sub teams and going after things versus try to create groupings of like thematic things. For example, we've talked about like interactive entertainment as like an area or like a pond we're interested in fishing in. And it's like how does that do you do that as one set of people doing that? Is like five people just take like five shots at it. So that like a mistake sometimes I think is people maybe rush to a group and maybe the bias is towards like consolidate, make it clean. And I think what I've learned maybe the hard way over the years is like actually sometimes you kind of have to live in the messiness a little bit and almost like see what emerges but still be willing to kind of make those kind of changes. Those are like org design team kind of things. The other change or the other thing I'd say sometimes is a common mistake in a you know you hire too many people too fast. This happens at big companies. It happens at startups too. And it's like it can be so addicting to like sometimes look at like, oh, our team doubled or tripled in the last quarter or six months or whatever. And these are just vanity metrics that are really bad most of the time. So I think that's the other thing is like a common mistake. I remember I was on a project years ago and we got to like 30 engineers and I was so happy and we had zero product market fit but a very inspiring vision. And you probably know where you know the outcome of how that ended basically.

在最后几分钟，我要问你一个 Logan Kilpatrick 建议问你的问题。

I'm going to in our last few minutes I'm going to ask you a question Logan Kilpatrick suggested to ask you.

我想他说的是 AI Studio，对吧？我忘了他的当前职位。好的，酷。

I think he said of AI Studio, right? I forget his current. Okay, cool.

太好了。他是一位很棒的前播客嘉宾。

Great. He's a great former podcast guest.

我不知道这个问题具体从何而来，但我很好奇。他的问题是：五年后，你认为 Google 会有 10,000 个产品还是五个？

I don't know exactly where this question is coming from, but I'm so curious. His question is in five years, do you think Google is going to have 10,000 products or five?

哦，是的。好的。这是 Logan 和我在团队中一直争论的问题。但有趣的是，至少对我来说，我一直在改变我的答案。所以也许我现在是个糟糕的预测者。我更倾向于这样的阵营：我不确定我们是否还会以同样的方式思考产品。所以，一种框架是 Google 有 10,000 个产品。那就像是 10,000 个有自己品牌的界面，一切都很复杂。我不确定那是否可能，就像你之前说的，什么是可能的，或者我们应该做什么？因为你可以有一个产品工厂，只是生产这些产品。所以这是你可以考虑的一件事。我越来越思考的是，是否几乎会有一些体验或东西，更加定制化，可能由模型制造，那可能意味着有实验室团队在背后制作智能体，做这件事，你可能会在一个共同的界面上体验。我不确定。但我也不是——我们有一些实验室实验正在进行，关于我们能否证明这场辩论的双方，也许这就是他提出这个问题的原因，有时候我们会这样做，我们会接受双方的观点，说好吧，如果这个东西真的整合了，有一个超级应用或一组超级应用，那个世界会是什么样子，也许如果这个东西超级碎片化，那个世界会是什么样子。所以现在，我可能更倾向于这样的阵营：我认为超级应用在一些用例中、在世界的一些地方显然非常成功，但我认为对于很多使用它们的人来说，它们可能非常复杂，很难真正驱动增加价值的行为，因为有太多的复杂性。但这也假设人类将是点击这些体验的人。所以无论如何，这是一个有趣的辩论，也是 Logan 和我最喜欢的话题之一，我们会经常讨论这个。

Oh yes. Okay. This is a long-running debate Logan and I have on the team. But it's funny, at least to me, I keep switching my answer. So maybe I'm a bad right now. I'm more in the camp of like I don't know if we're even going to think of products the same way. So I think one framing of it is 10,000 products from Google. That's like 10,000 surfaces that have their own brands and it's all complex and everything. I'm not sure that'll be possible to your earlier point. what's possible or what should we do? Because you can have a product factory that's just going to turn out these products. So that's like one thing you could think about. I'm more and more thinking about like are there almost like experiences or things that are going to be more bespoke that the models might make and that might mean there's labs teams behind it making the agent that does this thing that you experience maybe in a common surface. I'm not sure. But I also am not we have a couple of experiments in labs going on this right now of like can we prove both sides of this debate and maybe that's why he threw it in like we and sometimes that's what we'll do is we'll kind of take both sides of it and say like okay if this thing really consolidates down and there's a super app or a set of super apps what's that world going to look like and maybe if this thing super fragments what's that world going to look like and so right now I'm probably more on the camp of Like I think super apps have worked in some use cases in some parts of the world obviously extremely well but I think for a lot of people using them they can be very complex and it's very hard to actually drive kind of the behavior that adds value because there's so much complexity but this is also assuming humans are going to be the ones tapping most of these experiences as well. And so anyway, this is a fun one to debate and yeah, one of Logan and I's favorite kind of we'll we'll chat on this one a lot.

我喜欢这种不确定性，我们都在努力弄清楚。

I love that it's just unclear where we're going. Like it's just it just shows where we're just we're all just trying to figure this out.

没错。

That's right.

这是一个很好的例子。好的，在我们进入非常激动人心的闪电轮之前，Josh，你还有什么想分享的吗？还有什么想留给听众的吗？有什么想强调的吗？

That's such a good example of that. Okay. Well, before we get to our very exciting lightning round, Josh, is there anything else you wanted to share? Anything else you want to leave listeners with? Anything you want to double down on?

是的。我的意思是，我想我会考虑的一件事是，我也一直在思考这个。如果人们有想法，请在 X 上告诉我或其他方式，我仍然认为现在有很多空间关于如何获得关于你正在构建的产品和体验的反馈，无论是在 Google Labs 还是作为初创公司创始人或其他。所以这感觉像是另一个领域，关于你如何倾听、聚合、收集、从反馈循环中获得洞察和灵感。我觉得现在有很多有趣的事情发生在 AI 应用于这方面。我相信你们所有人可能也在做，Lenny 在你的东西和我的东西中，你知道智能体整夜运行，总结正在发生的一切，但我觉得有一个有趣的，比如什么让一个 PM 伟大。一个伟大的 PM 对某一类人有洞察力，知道什么类型的事情会让他们高兴或解决他们的问题。我觉得这是一个有趣的，如何用 AI 和我们正在构建的这些新型产品来破解那个反馈循环。所以无论如何，这也是我现在脑海中思考的事情。

Yeah. I mean, I guess one thing I'd think about is like and I I'm always trying to think of this too. If people have ideas, please just like let me know on X or whatever is like I still think there's a lot of space right now on how to get feedback about the products and experiences you're building whether it's in Google Labs or as a startup founder or whatever. And so that feels like another area of like how do you listen and sort of aggregate collect get insight inspiration from feedback loops. That I feel like there's a lot of interesting stuff happening with AI applied to that right now. And I'm sure all of you probably do too Lenny on your stuff and my stuff of you know agents running overnight summarizing everything that's happening and but I feel like there's an interesting like what makes a PM great. a great PM has insight about a certain type of people and the types of things that are going to delight them or solve their problem. And I feel like that's an interesting like how do you crack that feedback loop with AI and these new types of products we're building. So anyway, that's something also in the back of my mind right now.

是的。所以那里的问题就是，你如何让 AI 在识别机会和洞察方面，像一位顶尖百分位的出色 PM 一样优秀？

Yeah. Like so idea the question there is just how do you get AI to be as good as an amazing top percentile PM at identifying opportunities and insights?

是的，我认为这是其中一个分支。另一个是，是否存在一个世界，我不知道，可能有一些人在你的生活中，就像在我的生活中一样，当你和他们在一起时，洞察似乎很自然地流动，你会得到很多有趣的观点，是否有一种人与 AI 的协作模式能够实现更多这样的效果？我认为这可能是一个有趣的提示。

Yeah, I think that's one branch of it. And I think the other one is like is there a world where I don't know there's probably some people in your life just like they're in my life when you're around them insights seem to flow pretty naturally and you kind of get to a lot of interesting perspectives and like is there a collaboration model with people and AI that enables more of that? I think it's kind of an interesting prompt maybe.

听起来我们这是在 Google Labs 搞 B2B 的 SAS 软件了。我喜欢。我会买。好，我知道你很快得走了，所以我直接跳到最后一个闪电问答。我听说你给团队成员发一些特别搞笑的奖。我最喜欢的是 TPU 收割者。但还有别的。讲讲你发的这些奖，它们是什么意思。

Sounds like we're getting into B2B SAS software over here at Google Labs. I love it. I'd buy that. Okay. I know you have to run soon, so I'm going to skip to just one lightning round question. I heard you give these hilarious awards to teammates. My favorite is the TPU harvester. But there are others. Share these awards you give and what they mean.

哦，对。TPU 收割者，因为我们的产品在增长，我们就需要越来越多的 TPU。我们几个人想找出一种方式来奖励那些做脏活累活的人——提升效率、回收 TPU、收割 TPU，这样我们才能构建下一个功能、推动增长。所以我们给这些人发一把耙子，还有现金奖励。

Oh, yeah. So the TPU harvester, we just need more and more TPUs as our products are growing. And a few of us wanted to figure out a way to reward people who do the grungy work of efficiency and reclaiming TPUs, harvesting TPUs so we can build the next features and fuel our growth. So we give out a rake to these people and a cash award.

真的耙子？

Like an actual rake?

像我们在 Etsy 上做的小迷你耙子。那个特别好玩，我们把它变成了一个大庆祝。所以这是给那些节省 TPU、优化、让它们……

Like a little miniature rake we made on Etsy. And that one is really fun and we kind of turned into this big celebration. So this is people that save TPUs, that optimize, make them...

优化，而不是用最多的 token。

Optimize, not use the most tokens.

对，对。是的。是的。那个我们单独跟他们聊。但我觉得那个就是耙子。另一个：那些去修复“小伤口”的人，就是产品里那些累积起来让人烦的小问题。我们做了个金色的创可贴，发给这些人。他们把它放在桌上，作为修复小伤口的金色创可贴。我们在 Labs 有个东西。我们特别感兴趣的是那些能把模型推向前沿、以出人意料的方式推进的人。我们有个叫 LLM 低语者的奖，就像他们能对模型低语。他们得到一对巨大的耳朵，因为他们能听到别人听不到的模型里的东西，还有一个很好的机械键盘。还有更多这样的奖。但我们在试着找到方法，把这些价值编码进这些傻乎乎的符号里，但它们有意义。比如在 TPU 上变得更高效，让我们能增长、触达更多人。小伤口，这些是让产品令人愉悦和出色的东西。然后显然，带耳朵的低语者，这些会带来突破和新产品。所以是的，我们总是在想这种奇怪的东西。

That's right. That's right. Yeah. Yeah. That we talked to them separately. But I think that's one's like a rake. Another one: people that go in fix paper cuts, these little things that add up in a product that annoy people. We made like a golden band-aid and we give people that. It's like they put it on their desk as a golden band-aid for fixing paper cuts. We have a thing in Labs. We're really interested in people who can push the model to these frontier ways that are surprising. We have this thing called the LLM whisperer, like they're able to whisper to the model. They get a giant set of ears, like because they can hear things from the model that others can't, and like a really nice mechanical keyboard. And there's more of these things, too. But we're trying to find ways to encode the value in these dorky symbols, but that mean something. Like becoming more efficient with our TPUs enables us to grow and reach more people. Paper cuts, these are what make the product delightful and excellent. And then obviously like the whisper with the ears is like these lead to breakthroughs and new products. So yeah, we're always coming up with weird stuff like this.

我喜欢这个。这种传统最棒了。我听说还有一个大的感谢奖，就是你能跟领导层对话之类的。

I love this. These kinds of traditions are the best. I heard there's also like a big thank you one where you get like talk to leadership or something like that.

对，这个有点像秘密社团，基本上我们会在某人的日历上放个邀请，然后你知道，看起来有点吓人，因为团队里有四五个领导。没有议程。然后他们出现，我们轮流。我们围成一圈，就告诉他们为什么我们如此感激他们在团队里。这挺好玩，完全让人意外，我总是以这句话开场：这不是个坏会议，这是个好会议。你知道，通常你的脑子可能会往最坏处想，但我们其实是在做相反的事。这些是最有价值的一些人。

Yeah, this one is a little bit of a secret society in a way where we'll basically put an invite on someone's calendar and we'll just, you know, it looks kind of scary because there's like four or five leaders on the team. There's no agenda. And then they show up and we take turns. We go around the circle and we just tell them why we appreciate them so much for being on the team. And it's pretty fun and it totally surprises people and I always start the meeting with like this is not a bad meeting, this is a good meeting. You know, you usually, your mind may assume the worst, but we're actually doing the opposite. These are some of the most valuable people.

哇，太棒了。我喜欢所有这些。Josh，听众怎么才能帮到你？

Wow, that is awesome. I love all of these. Josh, how can listeners be useful to you?

哦，给我们发反馈。你们很多人已经在做了。我想说我们获得了很多快乐，我们非常感激所有使用我们正在构建的东西的人。如果我们在 Labs 这边或 Gemini 这边能帮上忙，也请让我们双向交流。再次感谢 Lenny 邀请我。跟你聊这段时间很棒。

Oh, send us feedback. So many of you do already. I would say we get a lot of joy and we're very grateful for all the people who use the stuff we're trying to build. And if we can be helpful on the Labs side or the Gemini side, too, please let's make it two-way. And thanks again, Lenny, for having me. It's been great to spend some time with you.

我觉得我们会帮很多人搞清楚如何构建并保持在边缘。真的很感谢你来，Josh。非常感谢。

I think we're going to help a lot of people figure out how to build and stay at the edge. I really appreciate you being here, Josh. Thank you so much.

是的，谢谢。祝你有美好的一天。

Yeah, thank you. Have a great day.

大家再见。非常感谢收听。如果你觉得有价值，可以在 Apple Podcasts、Spotify 或你最喜欢的播客应用上订阅本节目。另外，请考虑给我们评分或留下评论，因为这真的能帮助其他听众找到这个播客。你可以在 lennispodcast.com 找到所有往期节目或了解更多。下集见。

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