AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)

频道: Lenny's Podcast
视频: https://www.youtube.com/watch?v=zMvBMfj4cSQ
原文语言: en
统计: 共 198 轮 · Tara 100 · Lenny 98

[0:00] Tara

If you think about the first era of AI products as chat, the second era of these products working with [music] agents, that third era that might come soon is how do you work with a persistent co-worker who is able to get things done with you.

如果把 AI 产品的第一个时代看作「聊天」，第二个时代是这些产品开始跟 agent 一起干活，那么很快可能到来的第三个时代，就是：你怎么跟一个常驻的同事协作——一个能真正跟你一起把事情做完的同事。

[0:14] Tara

There's this idea of the overhang of what AI is capable of and what we're actually doing with it.

有个说法叫 overhang——AI 实际能做到的，和我们真正拿它在做的，中间悬着一大截没被用上的余量。

[0:19] Tara

So hard to understand what [music] is going to emerge in the future. You fail if you build for where the models are now. You fail if you build for where you think the models will be in a year. Both outcomes are equally [music] wrong. Only way to build is 2 to 3 months.

太难判断未来会冒出什么东西了。你照着模型现在的样子去做产品，会失败；你照着你以为一年后模型会有的样子去做，一样会失败。这两种结局错得一样离谱。唯一能建的，是照着往后两三个月来建。

[0:34] Lenny

What if you had to most adapt to [music] and adjust in how you operate as a PM in this world?

在这样一个世界里做 PM，你在工作方式上最需要适应和调整的是什么？

[0:38] Tara

Being prolific and empirical is way more important than being academic or theoretical rather than writing out some long reasoning doc. Instead, it's like how do I get to something I can try out and test with users [music] as fast as possible. It feels like not only are we able to be more ambitious, we almost need to be more ambitious, which is not natural for a lot of people.

高产、讲实证，比学术、讲理论重要得多。与其写一份长长的推理文档，不如想：我怎么最快做出一个能拿给用户试、拿去测的东西。感觉不只是我们「能够」更有野心，我们几乎是「必须」更有野心——而这对很多人来说并不是自然的状态。

[0:58] Tara

Elevating others ambitions or reminding them of what's possible here is a huge part of the product management role.

把别人的野心往上抬一抬，或者提醒他们「这里其实还能做到什么」，是产品经理这个角色里非常重要的一部分。

[1:03] Lenny

I'm curious what's most surprised you about what it's actually like to work at OpenAI.

我很好奇，真正在 OpenAI 工作之后，最让你意外的是什么？

[1:07] Tara

I came into the company expecting that there was a treasure trove of OpenAI secret strategy and actually OpenAI is open.

我进公司时以为里面藏着一大堆 OpenAI 的秘密战略，结果发现 OpenAI 是真的「open」。

[1:18] Lenny

Today my guest is Tara Sash. Tara leads product for both codeex and JBT work at OpenAI. I believe this is the fastest growing and arguably most important AI product for knowledge workers today. Tara works alongside Andrew Amberino who was a recent podcast guest. He's her engine manager. Prior to OpenAI, Tara spent six years at Stripe where she joined as one of the first five product managers and for many of those years she was named one of the top three stripes across the entire organization of Stripe. She also led product at Watershed, was a founder and a teal fellow, and most importantly of all, Tara was one of the three Lenny's newsletter fellows, which is a program that I ran a few years ago to highlight some of the most amazing upand cominging product leaders. I am so excited to see Tara in this new incredibly important and impactful role. Before we get into it, don't forget to check out lennisproduct.com for a free year of the hottest and most beautifully crafted AI products in the world available exclusively to Lenny's newsletter subscribers. With that, I bring you Tara Station. Tara, thank you so much for being here and welcome to the podcast.

今天的嘉宾是 Tara Seshan。她在 OpenAI 同时负责 Codex 和 ChatGPT Work 的产品。我认为这是当下面向知识工作者、增长最快、也可以说最重要的 AI 产品。和 Tara 搭档的是 Andrew——他前不久也上过这档播客，是她这边的工程负责人。加入 OpenAI 之前，Tara 在 Stripe 待了六年，是 Stripe 最早的五名产品经理之一；在其中好几年里，她都被评为整个 Stripe 排名前三的员工。她还在 Watershed 带过产品，自己创过业，是 Thiel Fellow。而最重要的是，Tara 是三位「Lenny's Newsletter Fellow」之一——那是我几年前办的一个项目，用来发掘一批最出色的新生代产品领导者。看到 Tara 现在做着这么重要、这么有影响力的事，我特别兴奋。进正题之前，别忘了去 lennysproduct.com 看看：那里有一整套全世界最火、做得最漂亮的 AI 产品，免费用一年，只对 Lenny's Newsletter 的订阅者开放。好，下面有请 Tara Seshan。Tara，太感谢你来了，欢迎来到播客。

[2:25] Tara

Thank you, Lenny. I'm so glad to be here. It's so nice to see you.

谢谢你，Lenny。我特别高兴能来，见到你真好。

[2:28] Lenny

I'm even more glad. So you've been at OpenAI for just about a year now, which in most places would be a very short amount of time. In AI time, that's like a lifetime.

我更高兴。你到 OpenAI 差不多一年了——在大多数地方，这点时间短得可以忽略不计；但按 AI 的时间尺度，这简直是一辈子了。

[2:39] Tara

Yes.

是的。

[2:40] Tara

I imagine when you joined OpenAI, you had a sense of what it was going to be like to work at a Frontier Lab. I'm curious what's most surprised you about what it's actually like to work at OpenAI and ideally both good and bad stuff. So many things about working at OpenAI felt familiar to me because I had worked at other places that were, you know, high growth, high talent, high intensity, hyperscaling mode places before. And so some of the things like, oh, my colleagues are so awesome or the urgency is really high felt very familiar. The part to me that actually felt the most surprising is that many companies I've worked for, in fact all the companies I've worked for in the past, have been founder-ledd and OpenAI is actually founders le um which is that everyone inside the company especially in their area is in essence kind of a a founder to some extent. the level of like top- down direction at OpenAI is extremely limited relative to places I've worked for prior. And so I think when I first got to the company that was both delightful and that I had come from like a founding journey before and I was like yes I can continue to feel like the founder of this product area or this or this uh team and you know the the distance between me and the market is very very thin you know and sometimes at a larger company you feel insulated from what users want or feel insulated from like what the market demands but actually at OpenAI that you do not at all. you are doing everything it takes to get product market fit for your product akin to how a founder might. But the the counter to this is that or maybe the the the more uh surprising side of this is I came into the company expecting that there was a treasure trove of like open AI secret strategy that I would be able to understand akin to how you know at past companies you come in and you're like ah yes this is like the payments bible and this is how we think about uh payments and

我猜你加入 OpenAI 的时候，心里对「在一家前沿实验室工作是什么感觉」是有预期的。我很好奇，真正在 OpenAI 工作之后，最让你意外的是什么？好的坏的都想听。——在 OpenAI 工作，很多东西对我来说其实挺熟悉的，因为我之前待过的地方也是高增长、人才密度高、强度高、正在超高速扩张的公司。所以像「同事怎么这么强」「紧迫感真的很高」这些，我一点都不陌生。真正最让我意外的是：我过去待过的公司——其实是全部——都是 founder-led（创始人主导），而 OpenAI 其实是 founders-led（一群创始人在带）：公司里每个人，尤其在自己那块地盘上，某种意义上都是个创始人。跟我之前待过的地方比，OpenAI 自上而下的指令少得离谱。所以刚进公司时，这一点让我特别惊喜——我之前有过创业的经历，我就想：太好了，我可以继续把这块产品、这个团队当成自己创的东西来带。而且你和市场之间那层膜非常非常薄。在大一点的公司里，你有时会觉得自己被隔在「用户想要什么」之外、被隔在「市场需要什么」之外；但在 OpenAI 完全不会，你就像创始人那样，为了让自己的产品拿到 PMF，什么都干。不过反过来说，或者说更让我意外的另一面是：我进公司时以为里面有一大堆 OpenAI 的秘密战略等着我去消化——就像你去别的公司，进去之后会拿到一本「支付圣经」，告诉你我们是怎么理解支付、怎么理解

[4:39] Tara

operations and actually open AAI is open [laughter] like every sort of thought that exists in terms of this is how like the world should look like or this is how product should be built or this is how the model should operate very very quickly becomes a part of the public product or a part of like the public messaging. And so that to me was incredibly um both positively surprising and just like a change in my operating mode for sure

运营的。结果发现 OpenAI 是真的 open（笑）。任何一个关于「世界该长什么样」「产品该怎么做」「模型该怎么运转」的想法，都会非常非常快地变成公开产品的一部分，或者变成对外表达的一部分。这一点让我又惊喜，也确实逼我换了一套工作方式。

[5:09] Lenny

telling us there's not like the secret room with the AGI running there with the master plan that has all the answers

所以你是说，并不存在一个秘密房间，里面跑着 AGI，手里攥着一份写满所有答案的总规划。

[5:14] Tara

or at least I'm not in that room for sure. But um I I think the the piece that is really inspiring to me is that so much of what OpenAI does immediately becomes something that users can touch and feel in the product and that cycle is faster than anywhere else I have seen.

至少我肯定不在那个房间里。不过真正让我很受触动的一点是：OpenAI 做的很多东西，几乎立刻就变成用户在产品里能摸到、能感受到的东西，这个周期比我见过的任何地方都快。

[5:33] Lenny

This episode is brought to you by our season's presenting sponsor, WorkOS. What do OpenAI, Anthropic, Cursor, Replet, 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 signon, skim, arback, 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 workos.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.

本期节目由本季的冠名赞助商 WorkOS 带来。OpenAI、Anthropic、Cursor、Replit、Sierra、Clay，还有数百家跑赢的公司，有什么共同点？它们背后都跑着 WorkOS。如果你在做面向企业的产品，你一定体会过接 SSO 单点登录、SCIM、RBAC、审计日志这些大客户必备功能的痛。WorkOS 把这些「卡单」的东西变成可以直接接入的 API，配一套专为 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打企业市场的创业公司，最后都用上了 WorkOS。因为他们就是最好的。不管你是想拿下第一个企业客户的种子轮公司，还是正在全球扩张的独角兽，WorkOS 都是让产品达到「企业级就绪」、把增长堵点打通的最快路径。它本质上就是企业级功能领域的 Stripe。去 workos.com 上手，或者直接去他们的 Slack——那儿有真的工程师在等着回答你的问题。WorkOS 让你能靠舒服的 API、齐全的文档和顺滑的开发体验跑得更快。今天就去 workos.com，让你的应用达到企业级。

[6:43] Lenny

You've been a PM at a lot of different places, a longtime PM leader. What do you lose in this new world?

你在很多地方做过 PM，也当了很久的产品负责人。在这个新世界里，你失去了什么？

[6:49] Tara

When a market is more static or a market is more slowm moving, you have the chance to actually like do some grand strategyesque work because it's more predictable or you can at least like understand all the pieces. Like as an example, payments is a certainly a dynamic market to some extent, but it's also an established market and you're able to say ah yes, if like I take this bet, my competitor might take this other bet or reason from first principles very rigorously through what all the next actions might be. And in fact, um the nature of that market mandates that you do that like winners will think more rigorously than everybody else. And if you aren't thinking rigorously, it shows up as sort of like carelessness because a lot of those decisions that you made could have been predicted. But in this market, it's so hard to understand like what is going to emerge in the in the future. It's very emergent. It's very fast changing. It's really dynamic. And most importantly, it's like very very important to stay tied to the research. And so actually being prolific and being um more like empirical is way more important than being um like maybe more academic or theoretical. And I think lots of the past companies I've worked at have been very academic and theoretical places. And it was a real switch to go from rather than writing out some like long reasoning doc almost like a PhD thesis of what I think should be the plan for the next like end amount of time instead it's like how do I get to something I can try out and test with users as fast as possible. And so yeah that that switch from theoretical to empirical felt very jarring at first. I was like oh am I not doing my due diligence here? Am I not being thoughtful enough? Like shouldn't I be like thinking through all of this in a ton of rigor? But actually you got to you got to try stuff and learn as much as possible. And what that means is the

当一个市场比较静态、或者走得比较慢的时候，你是有机会做那种「大战略」式工作的，因为它更可预测，或者至少所有的牌你都能看明白。比如支付，它当然在某种程度上也是个动态市场，但它同时是个成熟市场，你可以说：好，如果我下这个注，我的竞争对手可能会下另一个注——你能非常严谨地从第一性原理推演出接下来所有可能的动作。而且那个市场的性质本身就要求你这么干：赢家就是比所有人想得更严谨的那个。你要是想得不严谨，表现出来就是「你不上心」，因为你做的很多决策本来是可以被预判的。但在现在这个市场里，你根本没法判断未来会冒出什么。它是涌现的、变化极快、非常动态。而最重要的是，你必须跟研究贴得非常紧。所以高产、讲实证，比学术、讲理论重要得多。我过去待过的很多公司都非常学术、非常理论化，所以这个切换对我来说是个真正的转变：与其写一份长长的推理文档——几乎像一篇博士论文，论证我认为接下来这段时间的计划该是什么——不如想：我怎么最快做出一个能拿给用户试、拿去测的东西。所以从理论派切到实证派，一开始真的很不适应。我会想：我是不是没做足功课？我是不是不够深思熟虑？我难道不该把这些都严谨地想一遍吗？但其实你就是得去试、去尽可能多地学。而这意味着，你真正需要做的

[8:41] Tara

thinking you need to do is being as pointed as possible about what your core hypothesis is. And that hypothesis definition is the most important thing. Like what is actually uh to use the um Shashir Rahul phrase like the iigen question. What is like that specific most important thing to test and everything else like any other grand strategy you concoct is not relevant. I'd love to hear more about that because that's really interesting as almost like here's the thing of the PM role that is not changing. So much is changing. The world is changing but like there's still this piece that is even more important. Speak more to that of what specifically that uh you think people need to focus more on.

思考，是把你的核心假设定义得尽可能锋利。假设的定义才是最重要的事。借用 Shishir Mehrotra 的说法，就是找到那个「本征问题」（eigenquestion）：到底哪一件最关键的事需要被验证。除此之外，你编出来的任何宏大战略都不相干。——我很想多听听这一点，因为这特别有意思：这几乎是在说「PM 这个角色里没变的那部分是什么」。变的东西太多了，整个世界都在变，但恰恰有这么一块，反而变得更重要。你能不能再展开讲讲，具体是哪些地方你觉得大家该更聚焦？

[9:19] Tara

Yeah, there were so there are so many trappings around the PM role of like you know running um like execution on time and and writing all these specific docs and presentations etc. But the core of it has always been about what is like the most essential question you need to ask about your product. Like what is the thing that will determine whether your product works or doesn't work? How do you test that? How do you look at the results? And how do you feed that back into a loop of like refining your hypothesis and running it again? Like that that truly has always been the PM job. Um, and that involves of course like trying to understand users, trying to understand the market, trying to understand the actual technology you're building, pulling those three things together to make the most sharp hypothesis you can, and then making the test as fast and effective as possible. And I think that is not only not changed, but it's become the most important thing at the company to be able to do. Like ems are like thinking this way, engineers are thinking this way, like data scientists are thinking this way, designers are thinking this way. Like everyone is sort of moved to focus their efforts on this really really important like problem definition and and testing loop like what are we actually doing and how do we know if it's working thing and from a PM standpoint like it's great because PMs have always been really focused on trying to get that stuff right. Um, and that has always been the core of the job and actually many of the other just trappings of the job have like fallen away and that remains like the key thing to get right every time. you mentioned this idea of a loop and there's a lot of talk these days like loops were so hot I don't know a few weeks ago on Twitter and it feels like it continues to be a topic of discussion for knowledge work broadly and the way I understand a loop essentially AI here's what success looks

嗯。PM 这个角色外面裹着太多花架子了——比如盯执行按时交付、写各种具体的文档和演示稿等等。但它的内核一直都是：关于你的产品，最本质的那个问题是什么？什么东西会决定这个产品成或不成？你怎么去验证它？你怎么看结果？又怎么把结果喂回一个循环里，去打磨你的假设、再跑一遍？这才一直是 PM 真正的工作。这当然包括去理解用户、理解市场、理解你正在造的这项技术本身，把这三样拧到一起，得出你能得出的最锋利的假设，然后把验证做得又快又有效。我觉得这一点不但没变，反而成了公司里最重要的一项能力。EM 在这么想，工程师在这么想，数据科学家在这么想，设计师也在这么想——所有人都把力气转移到了这个特别重要的「问题定义 + 验证循环」上：我们到底在做什么？我们又怎么知道它有没有用？从 PM 的角度看这挺好的，因为 PM 一直就是最在意把这件事做对的人。这一直是这份工作的内核，而工作里其他那些花架子反而慢慢掉光了，剩下的就是这件每次都必须做对的关键事。——你提到了「循环（loop）」这个概念。最近关于它的讨论特别多，我记不清了，大概几周前 loop 在 Twitter 上火得一塌糊涂，而且看起来它会继续成为整个知识工作领域的话题。我理解的 loop，本质上就是告诉 AI：这就是成功长什么样

[11:07] Lenny

like go off and build and figure it out until you this is what this you achieve success how do you think about just this idea of loops expanding from just software engineering to product management all knowledge work. Do you think that's going to be a thing?

——你去做、去想办法，一直做到达成这个成功为止。你怎么看「循环」这个概念从软件工程扩展到产品管理、扩展到所有知识工作？你觉得这真会发生吗？

[11:22] Tara

I do think that increasingly the future of work will look more like steering than rowing in the sense that there will be agents that you'll you'll be able to work with that do a lot of the rowing and your role increasingly becomes steering the ship in the right direction and pointing it in the right direction. And to that point, I think that that steering might grow higher and higher and higher level. the steering used to be at the level of I wrote this line of code press tab to oh wait now I'm directing something a little bit more comprehensive to maybe the goal level maybe to like an even higher level I think the steering will continue to um maybe go up layers of abstraction but ultimately I think it's still on a person to be able to find like which direction are we pointing this in and given feedback and additional data where do I want to take this thing next some of steering I think is about certainly like what the data tells you, but a lot of it is about making an opinionated call. I think sometimes that we underrate like that power of like intuition or even um sort of like positive like determinism of what we want the future to be like. Like like picturing, hey, I would like the product to look this way, not because the converse is not an equally viable strategy, but because I would like the world to look like the direction that I would I'm pushing it in. And that I think will always remain a a opinion at least right now that is like required from a person. And so I think that loops are awesome. Running like running agents in increasingly increasingly larger loops where they're doing more and more of that rowing for you is great, but right now like you really still need to to steer. And I think work will also look like steering with other people over a group of agents that you guys work with together.

我确实认为，未来的工作会越来越像「掌舵」而不是「划桨」：会有一堆 agent 跟你一起干活，大量的划桨由它们来做，而你的角色越来越是把船往对的方向开、把船头指对。顺着这个说，我觉得掌舵的层级会越来越高。以前的掌舵是在「我写了这行代码、按 Tab 补全」的层级；后来变成我在指挥一个更完整一点的东西；再往上可能到目标层级，甚至更高。我觉得掌舵会一层层往上爬抽象层级，但最终，判断「我们要把它指向哪个方向」，以及拿到反馈和新数据之后「下一步我想把这东西带到哪儿去」，还是得靠人。掌舵里有一部分当然来自数据告诉你的东西，但很大一部分是做一个有主张的判断。我觉得我们有时候低估了直觉的力量，甚至低估了那种正向的「决定论」——就是我们想让未来变成什么样。比如说：我希望这个产品长成这样，不是因为反过来那条路不是同样可行的策略，而是因为我希望世界朝我推的这个方向走。我觉得这种主张，至少在当下，永远是需要人来给的。所以我觉得 loop 很棒，让 agent 在越来越大的循环里跑、替你划越来越多的桨，这很好，但眼下你真的还是得掌舵。而且我觉得未来的工作也会变成：你和其他人一起，去给一群你们共同协作的 agent 掌舵。

[13:13] Tara

um bringing in other teammates into that like interaction between you and the agent where it's rowing and you're steering feels also incredibly valuable.

把其他队友也拉进「你和 agent」的这层互动里——它划桨、你掌舵——我觉得也非常有价值。

[13:20] Tara

That's such an interesting way of describing it. There's also like there's two thoughts here that come up. One is if everybody has access to the same tools, the thing that will separate you is this is the h is human the person basically. Otherwise, we're all just going to be building the same thing. You could use it. You could everyone could be asking how do we win? What do we do? And then the thing that almost unfair advantage almost is the human brain. Yeah, I I think it it reminds me a lot of fashion actually in in some ways. Like there are certainly functional clothes that everybody can wear and uh gets gets the job done, but so much about what you wear at least or how I think about what I wear is about what statement I want to make about my individuality or what how I want to reflect to the rest of the world. And a lot of what makes that compelling is how it contrasts with other people's expression. like the shirt I make makes a statement only because it is maybe different than what everybody else is doing or different than some cohort of people are doing or makes a statement about my group membership or something of that kind. And I think a lot of the products that we build feel similarly opinionated and artistic like Patrick Hollen has this really nice statement or maybe it's John Collin has this really nice statement about software which is that software is not like real estate.

这个说法太有意思了。我这儿冒出两个想法。第一个是：如果所有人都能用上同样的工具，那真正把你区分开的，就是「人」这个变量了。不然我们做出来的东西都会一样。工具谁都能用，谁都可以去问「我们怎么赢」「我们该做什么」，那最后那个近乎不公平的优势，就是人的大脑。——对，我觉得这在某些方面很像时尚。确实有一类功能性的衣服，谁都能穿，也能把事办了；但穿什么这件事——至少对我来说——很大程度上是关于我想就自己的独特性发出什么声明、想向外界呈现什么。而这件事之所以有吸引力，很大程度上来自它和别人的表达之间的反差：我穿的这件衬衫之所以是一种表达，是因为它可能跟别人都不一样，或者跟某一群人不一样，又或者它表明了我属于哪个群体。我觉得我们做的很多产品也是这种有主张、有艺术性的东西。Patrick Collison 有一句话说得特别好——也可能是 John Collison 说的——关于软件：软件不像房地产。

[14:30] Tara

You don't like put money in and get value out. It is a little bit more like film making where you can put a lot of money into a film but that doesn't guarantee that the film is successful or good. There is some like aur statement or is some opinionation and artistry that goes along with it. And I think that relies on you having something interesting to say or your team having something interesting to say about your product. There's something um Marty Kagan is big on which is this idea that when you have an idea for a product or feature, rarely is that idea the thing that ends up being. There's this whole process you go through to kind of figure out what the hell actually it should be. And it feels like that's kind of what you're saying here is like you need to go through that process as a human to understand what it really is and what people actually want. It's never going to be like, "Okay, got it. Go build this thing. I got it from the beginning."

不是你把钱投进去，就能把价值取出来。它更像拍电影：你可以往一部片子里砸很多钱，但这并不保证片子好看或者成功。里面有一种作者性的表达（auteur），有主张，有手艺和艺术的成分。而我觉得这依赖于你——或者你的团队——对自己的产品有点有意思的东西可说。——Marty Cagan 特别强调一件事：当你有了一个产品或功能的点子，这个点子最后几乎从来不会就是它最终的样子。中间有一整套过程，你得靠它去搞明白这东西到底该是什么。感觉你现在说的也是这个意思：你得作为一个人走完那个过程，才能明白它真正是什么、用户真正要什么。绝不可能是「好，明白了，照这个做就行，我一开始就想清楚了」。

[15:19] Tara

Yeah. For sure. For sure. And that loop, those loops are moving faster and faster and faster. And so your ability to like form those intuitions, get the information you need to form those intuitions, and then use that with people and agents to put that into action is is the key.

对，绝对是。而且这些循环转得越来越快。所以你能不能形成这些直觉、能不能拿到形成直觉所需要的信息，然后带着人和 agent 把它落成行动——这才是关键。

[15:36] Lenny

I'm curious what you think the next shift will be in how we work just broadly as knowledge workers. It feels like not only do you have access to the most advanced tools that some people that other people don't yet also you work around the most AI pill AI forward people in the world. How are people working internally that you think will become kind of a more normal way we all work using these AI tools in the next I don't know 3 to six months?

我很好奇，就我们作为知识工作者整体的工作方式而言，你觉得下一个转变会是什么。感觉你不但能用上别人还用不到的最先进工具，你周围还都是全世界最「AI 上头」、最激进的一群人。你们内部现在的工作方式里，有哪些你觉得会在接下来——我不知道——三到六个月里，变成我们所有人用 AI 工具的常态？

[16:02] Tara

Yeah, I think there's there's two aspects to this. One is continuing to work with agents at higher and higher levels of abstraction. So letting the agent do more and more for you independently coming in providing that steering and then letting the agent continue to cook like let the agent cook and provide details at higher order of orders of abstraction feels like the way people are increasingly thinking about agents that are persistent that feel like teammates that feel like co-workers where you can work with them the way I might work with someone on my team which is they do a whole bunch of work I provide input and then they do work again and we sync up at different cad es look at each other's in progress work and provide more and more feedback. It feels like that that co-worker model is the way that things are certainly going feels like a much more natural interface for us to be able to work with agents and we already see a lot of that internally as well. The second is that a lot of my work with agents thus far has been one-on-one that I work with my agent. Maybe it's spawned some sub aents to get some tasks done, but it's me and my agent together. And that is potentially divorced from what my colleagues are doing with their agents.

我觉得有两个方面。第一是继续在越来越高的抽象层级上跟 agent 协作：让 agent 越来越独立地替你干更多事，你进来给个方向，然后让它接着煮——让 agent 自己 cook，你只在越来越高的抽象层级上补细节。大家现在越来越把 agent 想成常驻的、像队友、像同事一样的存在：你可以像跟团队里某个人合作那样跟它合作——它干一大堆活，我给输入，它再接着干，我们按不同的节奏碰头，互相看对方还没做完的活，再给更多反馈。感觉这种「同事模式」肯定是趋势，也确实是我们跟 agent 协作更自然的界面，我们内部已经能看到很多这样的用法了。第二是，到目前为止我跟 agent 的协作基本都是一对一的：我和我的 agent 一起干活，它可能会 spawn 出一些 sub-agent 去完成任务，但归根到底就是我和我的 agent 两个。而这跟我的同事们在拿他们的 agent 做什么，是完全脱节的。

[17:16] Tara

And so there was a time where everyone internally was just like sending their codeex threads, screenshots of their codeex threads to each other on Slack. We're like, okay, well, I wanted to share with you how I got to this number. Here's how I got to this number. Here's a screenshot of of what I did. But that's also not quite the most natural way for someone to collaborate together. And so as more and more work gets done with our agents, shouldn't we be able to get work done with our agents together? Um, and what is the most natural interface to make that happen? And those are some of the things that we're we're thinking about.

所以有一阵子，公司内部所有人都在 Slack 上互相发自己的 Codex 会话、发 Codex 会话的截图。就是那种：好，我想告诉你这个数我是怎么算出来的，这是我的过程，这是我操作的截图。但这显然也不是人跟人协作最自然的方式。所以，既然越来越多的工作是跟我们的 agent 一起完成的，那我们是不是应该能够「带着各自的 agent 一起」把活干了？以及，什么样的界面能最自然地做到这一点？这些就是我们现在在琢磨的一些事情。

[17:50] Lenny

Chat is what I'm picturing. Uh, that makes so much sense. It's like, okay, here's Tara's agent. Here's my agent. She did some work on some analysis. I'd be, hey, my agent, Lenny's agent, go check make sure this is legit and connects to the way I think about the world.

我脑子里想的就是聊天这种形态。嗯，这太说得通了。就像：好，这是 Tara 的 agent，这是我的 agent。她那边做了些分析，我就可以说，嘿，我的 agent、Lenny 的 agent，你去核一下这东西靠不靠谱、跟我看世界的方式对不对得上。

[18:03] Tara

Ideally, work feels like a multiplayer game where all of us together are getting stuff done, steering our agents as our agents continue to take care of more and more of those like rowing tactical tasks.

理想状态下，工作会像一场多人在线游戏：我们所有人一起把事情推进，各自操控自己的 agent，而 agent 则接手越来越多那些机械的、战术层面的活儿。

[18:14] Lenny

It's interesting how it's just been this like slow progression of trust and um just like awareness that this can be how we work. Just this like, okay, go work for longer, you can take on more. It's just like it feel there's been this talk of like the slow takeoff, the fast takeoff scenarios and everyone's afraid of this fast AI takeoff where it's like way too smart and now we're in big trouble. It feels very much like we're on the slow takeoff scenario which is good where it's just like slowly iterating. doesn't feel that slow, but in a sense, you know, we're not like some 300 IQ AI like, you know,

有意思的是，这一路就是信任在慢慢往前挪，以及慢慢意识到「原来可以这么干活」。就是那种：好，你多跑一会儿；好，你可以多接一点。大家一直在聊慢起飞、快起飞这两种情形，所有人都怕 AI 快速起飞——聪明得离谱，然后我们就麻烦大了。而现在的感觉非常像我们走在慢起飞这条路上，这是好事，就是一点一点迭代。当然也没那么慢，但从某种意义上说，我们还没冒出个 300 IQ 的 AI，你懂的，

[18:47] Tara

I mean, the models are the models are incredibly smart, but I think a lot of the things that have enabled us to then work with our agents together or have the agents take care of higher and higher order abstraction things certainly are about the intelligence, their ability to perform longunning tasks and how long they can stay on tasks, but also actually there are very meat and potatoes tactical things that make this possible like agents working locally are really convenient because they have access to all the data that's on your machine. To make an agent successful in the cloud, there is a ton of cloud infrastructure that you have to build to make that possible. And just like access to your systems like how can agents talk to all these thirdparty systems that have all of your data just like a colleague who you hire who you like lock into a room never give them access to like Google Docs and Slack and I don't know the company database would not be that useful to you. Similarly, like a cloud agent that is similarly isolated will will not be that effective. And so a huge part of making these agents useful and achieving some of these futures are are on the intelligence side certainly, but a lot of it is also just really tactical like data access like cloud infrastructure and reliability pieces that feel um yeah, they feel much more prosaic than some of the the broader intelligence questions, but matter in some ways just as much for end effectiveness.

我是说，模型确实聪明得不得了。但我觉得，让我们能和 agent 一起干活、能让 agent 接手越来越高抽象层级任务的那些因素，当然跟智能有关——它们执行长周期任务的能力、能在一件任务上待多久——可另外还有一些非常朴素、非常战术的东西在起作用。比如 agent 跑在本地就特别方便，因为它能拿到你机器上的所有数据；而要让一个 agent 在云上跑得好，你得先搭一大堆云基础设施。还有对系统的访问权限：agent 怎么去跟那些存着你全部数据的第三方系统对话？这就好比你招了个同事，把他锁在一个房间里，不给 Google Docs、不给 Slack、也不给公司数据库的权限，那他对你的用处就很有限。同理，一个被同样隔离起来的云端 agent，效果也好不到哪儿去。所以，让这些 agent 真正有用、让我们说的这些未来成真，很大一部分当然在智能这一侧，但也有很大一部分其实特别战术——数据访问、云基础设施、可靠性这些。这些听上去确实比那些宏大的智能问题平庸多了，但对最终效果来说，某种意义上一样重要。

[20:05] Lenny

This touches on something else that has been coming up a bunch on this podcast. this word ambition. I know you think a lot about this too. It feels like not only are we able to be more ambitious because of these AI tools, we almost need to be more ambitious, which is not natural for a lot of people because everybody can now do all these easy things really easily. Like the easy stuff is super easy. The hard stuff is easy. And the thing that separates people now and companies now is just how ambitious they can be. talk about what comes up when I talk about the the need and the kind of the emergence of this need for ambition.

这就带到了另一个在这档播客里反复出现的词——ambition，野心。我知道你也常琢磨这件事。感觉不只是这些 AI 工具让我们有条件更有野心，我们几乎是「必须」更有野心；而这对很多人来说并不自然，因为现在人人都能轻松搞定那些简单的事。简单的事变得超级简单，难的事也变简单了。现在把人和公司拉开差距的，就只剩野心能有多大。聊聊当我说到「需要野心」、说到这种需求正在浮现时，你脑子里冒出来的是什么。

[20:42] Tara

Yeah, I think the people that we see who are most effective at using AI tools don't simply use it to automate wrote tasks but use it to expand the set of things that they are capable of doing. Like back in the day, you know, before before all this uh before all this AI stuff, the like unicorn person was someone who was a really thoughtful Product sense person who also happened to be an engineer who may also have been a designer. That person was always the like unicorn hireer because they were able to really flatten the layers of translation needed between all these functions and were able to like build something or ideulate something really quickly and easily themselves and get it up and running and then were able to like work with a team and collaborate with the team on it. And I think the most compelling thing I found that certainly I try to be able to do with these tools and I've seen some of my like most successful like colleagues be able to do with these tools is really expand the set of things that are quote unquote within their range of possibilities so that they can start realizing more and more of what's in their head into the reality the way that someone who was previously like jack of all trades was able to do. We kind of all have that superpower now that I can like spin up a set of designs on something and I can like go build an initial prototype of it and I can you know figure out the right pricing model for it and model out all the scenarios.

嗯，我觉得我们看到那些用 AI 工具用得最好的人，不是拿它去自动化重复性的活儿，而是拿它去扩大自己「能做的事」的边界。想想以前，在所有这些 AI 东西出现之前，所谓的独角兽人才，是那种产品感觉特别好、同时又恰好是工程师、说不定还会做设计的人。这种人永远是最抢手的招聘目标，因为他们能把各职能之间那层层翻译成本压扁，能自己非常快地把东西做出来、把想法迅速落成原型跑起来，然后再拉着团队一起往下推。而我发现最让人心动的一点——也是我自己努力用这些工具去做到的，还有我身边那些做得最出色的同事在做的——就是真正扩大那个所谓「可能性范围」的集合，让自己能把脑子里越来越多的东西变成现实，就像以前那种「样样都会」的人那样。现在我们某种程度上人人都有了这个超能力：我可以就某件事快速起一套设计稿，可以去做一个初版原型，还能琢磨出合适的定价模型、把各种情形都建模跑一遍。

[22:03] Tara

like really the set of possibilities have widened dramatically. And actually what that means in so many ways is that I have the ability to like be a to that point earlier about film like be more of an aur as I try to get something done and like realize my vision maybe to higher fidelity. And that to me is part of what can elevate your ambitions while pursuing new ideas and new products. that because all of these things are now within reach because this new set of capabilities is now within your reach to be able to try and access. You're not really limited. Your ambitions are no longer limited by like what you're capable of executing yourself, what you're capable of communicating. It can be so much so much wider. I think the hardest part about doing this is simply just expanding your thinking. Actually, the capabilities have expanded so dramatically. is is really expanding your thinking of what's possible in an unreasonably short time frame. And to me, the best way of trying to do that is um Patrick Hollen has like on his website, patrickzen.com/fast, I think, which is all of these projects that were unreasonably ambitious that were executed in a really really short time period. And what for me is now remarkable about that list of projects is that they all existed before these tools made it possible for you to learn how to build something almost instantly or ask it with one question. and hey, can you summarize this very complicated text or this very complicated book for me um immediately? Or can I try to do all of these things that were previously impossible to me, but now I'm able to do? Like, can I spin up a can you make for me like a CAD model of this idea that I might have? Like really capabilities that were truly beyond my reach are now in my reach. And so if those fast projects were possible before with the capabilities we used to have, shouldn't we just see an exponential increase of the number of those types of

可能性的集合真的是急剧变宽了。这在很多层面上意味着——回到前面聊电影的那个点——在我把一件事做成、把心里的构想尽可能高保真地实现出来的过程中，我更像一个 auteur（作者型创作者）。在我看来，这正是能把你的野心往上抬一层的东西，让你敢去追新想法、新产品。因为所有这些现在都触手可及了，因为这一整套新能力现在就摆在你手边、随时可以调用。你不再真的受限。你的野心不再被「你自己能执行到什么程度」「你能沟通到什么程度」卡住，它可以宽得多得多。我觉得这件事最难的部分，其实只是把你的想象撑大。能力已经扩张得非常剧烈，真正难的是撑大你对「在短得不合理的时间里能做成什么」的想象。而做到这一点最好的办法，在我看来是——Patrick Collison 在他网站上有个页面，我记得是 patrickcollison.com/fast，上面全是那些野心大得离谱、却在极短时间里就做成的项目。现在回头看那份清单，让我觉得最了不起的一点是：它们全都发生在这些工具出现之前——在你可以几乎瞬间学会怎么做一个东西、或者只用一句话去问它之前；在你可以说「嘿，帮我马上把这段极复杂的文本、这本极复杂的书总结一下」之前；在你可以去做那些以前对我完全不可能、现在却做得到的事之前。比如：你能不能帮我把脑子里这个想法做成一个 CAD 模型？真的是那些原本远超我能力范围的事，现在进了我的能力范围。那么，如果那些「快项目」在我们过去那点能力下都做得成，我们不是应该看到这类事情呈指数级增长吗——

[23:52] Tara

unreasonably quickly and effectively executed things um with what AI has given us?

——那些以不合理的速度、又高效地被执行完成的事，在 AI 给了我们这些之后？

[23:57] Lenny

To your point, the hardest part is just remembering to even to try just to be like, "Oh yeah, well let me see if Codex can do this for me." It's just like a new habit, a new like thing we have to build in our brain. Tyler Cowan has this statement on his site which is that you most people underrate the impact of going to someone else and saying hey couldn't you what is like the more ambitious version of what you're doing or couldn't you try this faster or couldn't you try this at a 10x bigger scale and in some ways again when I think of like what what do PMs do that is incredibly effective now or what can they do that is incredibly effective now I think elevating others ambitions or reminding them of what's possible here is a huge part of the product management role like when folks say, "Hey, I I think we can get this done in this way, or we can get this done by this timeline, or maybe this is the first version of it." Um, part of your job now is to elevate everyone's ambitions and say, "Actually, isn't the possibility ceiling meaningfully higher?" Like, shouldn't we be more ambitious about what we're attempting here? Or like, couldn't we try this faster? And I think that's a yeah, it's a it's a great place to be. It's a great place to be in terms of what you can build, what's possible, and in terms of um yeah, how exciting the job becomes.

照你这个说法，最难的其实只是记得去试一下，就是那种「哦对，我看看 Codex 能不能帮我把这个搞定」。这就是一个新习惯，一个我们得在脑子里重新长出来的东西。Tyler Cowen 在他网站上有句话：大多数人都低估了这么做的作用——去找另一个人说，嘿，你手上这件事，更有野心的版本会是什么样？你能不能试着更快一点？能不能试试放大十倍的规模？某种意义上，当我再想「现在 PM 做什么是特别有效的」「他们现在能做什么是特别有效的」，我觉得抬高别人的野心、提醒他们此刻什么是可能的，是产品经理这个角色里非常大的一块。当有人说「嘿，我觉得我们可以这么做」「我们能在这个时间点做完」「也许这就是第一个版本」的时候，你现在工作的一部分，就是把所有人的野心往上抬，问一句「其实，可能性的天花板是不是明显更高了？」「我们对自己要做的这件事，是不是该更有野心一点？」或者「这个能不能更快点试出来？」我觉得这是个很好的位置——无论从你能造出什么、什么变得可能来说，还是从这份工作变得多让人兴奋来说。

[25:08] Lenny

That is so interesting. I remember Nick Turley was on the podcast who was maybe had the role before you. Uh I think he's working on enterprise stuff now. He had this uh meme internally, is this maximally accelerated?

太有意思了。我记得 Nick Turley 上过这档播客，他大概是你现在这个岗位的前任。嗯，我记得他现在在做企业那块。他在公司内部搞了个梗：这件事是不是已经最大化加速了？

[25:20] Tara

Yes,

对，

[25:20] Lenny

there's like an emoji I think inside the Slack. Is this maximally accelerated?

我记得 Slack 里还有个对应的 emoji。「这件事是不是最大化加速了？」

[25:24] Tara

Is this maximally accelerated? Is totally a OpenAI meme. The other OpenAI meme that uh Andrew Embraino and I love to ask the team is like are you mainlining it yet which is like are you using this product all day every day to get your thing done and I think that in combination with are we being as ambitious as possible which is about like the scope and the scale of what you're trying to do. Are are is this maximally accelerated? Are we moving as fast as possible on it? And then are you mainlining it yet? Are you using it? and are you bringing all your tastes to bear on whether this thing works and is something that people really want and tightening that feedback loop as much as possible. Those to me are like the three memes of product development uh that we we just have to spread as much as possible now.

「这是不是最大化加速了？」完全是 OpenAI 的一个梗。另一个 OpenAI 的梗，是我和 Andrew 特别爱拿去问团队的：你已经开始 mainline 它了吗？意思是，你是不是每天、整天都在用这个产品来完成你自己的活儿？我觉得这个，加上「我们是不是已经足够有野心了」——后者讲的是你想做的这件事的范围和量级；「这是不是最大化加速了」讲的是我们推进得够不够快；然后「你已经在天天用它了吗」讲的是你到底用没用、有没有把你全部的品味都投进去，去判断这东西行不行、是不是人们真正想要的，并且把反馈闭环收得越紧越好。对我来说，这就是做产品的三个梗，我们现在必须尽可能地把它们传播出去。

[26:08] Lenny

I love that. That's like the new dog fooding instead of dog fooding. You got to mainline it.

我太喜欢这个说法了。这就是新版的 dog fooding——光「吃自己的狗粮」不够了，你得直接 mainline（当主线用）。

[26:14] Lenny

Yeah, exactly. And that shows so deeply in the the tweets. This is mostly how I see your team communicate of just like how obsessed they are with the product and are just constantly asking what can we do better? What's bugging you now? Here's the thing we're building. It's like it's very clear how to your point earlier that everyone is just the founder of their product and it it's very clear how they act as an external observer. Are there any other memes internally? Those are so interesting. any other uh I don't know.

对，就是这样。而且这一点在推文里体现得特别深。我主要就是从这儿看你们团队怎么沟通的：他们对产品痴迷到什么程度，一直在问「我们哪里能做得更好？」「现在什么最让你别扭？」「这是我们正在做的东西」。就像你前面说的，每个人都是自己那块产品的创始人——从一个外部观察者的角度，这一点看得非常清楚。内部还有别的梗吗？这些都太有意思了。还有别的吗？我也不知道。

[26:44] Tara

Yeah, I'm trying to think if there's other good cultural means. Certainly a a really important one is like feeling the AGI or just being conscious of of AGI coming. Um there are so many outcomes for for what it could look like or how one thinks about it. But a huge part of what puts most people at this company is believing in that mission of AGI being beneficial and trying to do whatever it takes to make that possible. Both realization of AGI and ensuring that it is beneficial for for humanity. And in building products, another just constant refrain I have to keep in the back of my mind is are we building for where the models are going to be in two to three months? You fail if you build for where the models are now. You fail if you build for where you think the models will be in a year. Like both outcomes are equally wrong. And I'm sure many people have have talked about this, but both outcomes are really equally wrong. If you're too early, you're wrong. If you build something that was overly focused on a past model's capabilities, you're entirely wrong. The only way to build is two to three months and having this beam of like models are going to get way better. I need to think about the model capability is the center of this product. I need to get out of the way of the model in terms of the product constructs that I create. How do I ensure that this is right for the model in two to three months time?

嗯，我想想还有没有别的好的文化梗。有一个肯定很重要，就是 feel the AGI，或者说时刻意识到 AGI 正在到来。关于它会长成什么样、该怎么理解它，可能的结局有很多种。但让大多数人来这家公司的很大一部分原因，就是相信「让 AGI 造福人类」这个使命，并且愿意为让它成真做任何必要的事——既要真的实现 AGI，也要确保它对人类是有益的。而在做产品这件事上，我必须一直搁在脑后的另一句口头禅是：我们做的东西，是不是面向两三个月后模型的样子？如果你按模型现在的样子做，你会失败；如果你按你以为一年后模型的样子做，你也会失败。这两种结局同样错。我相信很多人都讲过这个，但这两种结局真的同样错。你太早，你就是错的；你做的东西过度围绕上一代模型的能力，你就完全错了。唯一对的做法是面向两三个月后，同时心里揣着这么一个信念：模型会变得好太多。我得把模型能力当作这个产品的中心去思考；在我设计的那些产品结构上，我得给模型让路。我要怎么确保这东西放到两三个月后，对那时的模型仍然是对的？

[28:05] Lenny

How do you know what two or three months is like? It's like a challenging understanding uh especially while when we're on this in exponential. Is it like just a gut feeling? Is there anything the researchers give you a sense? How does that work?

你怎么知道两三个月后会是什么样？这挺难判断的，尤其我们正处在一条指数曲线上。是纯凭直觉吗？还是研究团队会给你们一些信号？这是怎么运作的？

[28:17] Tara

Yeah, certainly communicating really tightly with research on where they think things are going is incredibly important. Um, like these things aren't entirely a like a black box in that you kind of know, hey, we're focused on these particular things like we would like models to be better at at coding in these specific ways or better at writing in these specific ways. Um, so we we certainly have focused efforts on making the model better at specific capabilities. And so knowing where that is and ensuring that product development is as tied as possible to what research has as its agenda and its roadmap is is really important.

嗯，跟研究团队非常紧密地沟通、了解他们认为事情会往哪儿走，这肯定极其重要。而且这些东西也不完全是个黑箱，你大致知道：嘿，我们现在重点攻这几件事，比如我们希望模型在这些具体的编码方式上更强，或者在这些具体的写作能力上更强。所以我们确实会有针对特定能力的集中投入。因此，知道这些投入落在哪儿，并且让产品开发尽可能紧扣研究的议程和路线图，非常重要。

[28:54] Lenny

A quote that I'll never forget is when Kevin Wheel was on the podcast. He was chief product officer at that time. Uh he said that this is the worst the models will ever be. And it sounds so simple, but it's just like it's hard to just like wrap your head around that that this is the worst there will ever be. Like it's such a cliche almost now to say that, but it's it's true. It's absurd. This is like

有一句话我永远忘不了，是 Kevin Weil 上播客时说的，他当时是首席产品官。他说：今天的模型，是它这辈子最差的时候。听起来特别简单，但你真的很难把这件事完全消化——今天就是最差的了。现在这么说几乎快成陈词滥调了，但它是真的。太荒谬了。这简直是——

[29:17] Tara

Yeah, it's it's absurd. It's absolutely absurd.

对，太荒谬了。绝对荒谬。

[29:21] Lenny

Oh man. Okay. Um I want to talk about Chad GBT the app briefly. Uh okay. So I have it open right now.

天啊。好。嗯，我想简单聊聊 ChatGPT 这个 App。好，我现在就开着它。

[29:28] Tara

Yes.

好的。

[29:28] Lenny

Uh okay. So here's what I see in it. chat GPT and then there's a drop down and there's chat GPT and codeex and then there's this toggle chat and work tara what is going on what are all these things help us understand what each of these things are for and where does this where do you think this goes is it going to stay like this is there like a next step that you're imagining already

嗯好。我看到的是这样：ChatGPT，然后有个下拉菜单，里面是 ChatGPT 和 Codex，然后还有一个 chat / work 的切换开关。Tara，这都是些什么？帮我们理解一下这几样东西各自是干嘛的，以及你觉得它会往哪儿走？会一直保持这样吗？你脑子里是不是已经有下一步的设想了？

[29:50] Tara

our north star here is that users do not need to make decisions between picking between all these different options I there is no there's no toggle here that you go to the box you type in your task like I would like to build a really awesome app that um I don't know helps my podcast guests like do research before episodes or something and it will

我们这里的北极星是：用户根本不需要在这些选项之间做选择。这里不该有什么开关，你就是打开输入框，把你的任务打进去，比如「我想做一个特别棒的 App，帮我播客的嘉宾在录制前做点资料准备」之类的，然后它就会——

[30:12] Tara

it it will just pick the right harness. It'll pick the right model for you to be able to get that thing done. Ideally the the choice here is like not on our users to have to pick between all these different concepts and understand not only what are they trying to do but understand the limitations and capabilities of our products. So that is certainly where we want to go in the in the near term. Picking between chat, GPT and codecs is really a choice for are you a do you want to stay in sort of like more development oriented UI or do you want to have the same power and capabilities in the chat GBT mode? And so if you're a Codeex user, keep using codeex. You're not missing out on anything. Like continue using it as much as possible. But if you're a chat GBT user who is like what are these new agent capabilities you should probably be in chat GBT mode. And then when you're in chat GPT if you want to have conversations if you want to search that's where chat mode is the right thing. It's the you know same chat mode you know and love with better and better models and newer and newer capabilities every time. But in work mode that's where under the covers this is codeex. We've removed some of like the coding UI like you don't you're not going to see a work tree pop up all of a sudden in in work mode but it is the same power to get things done to um for example generate like a really complex financial model that's all possible in work mode and we see people especially I mentioned our corporate finance team um use work mode to do incredible incredible things that were previously either manual or required deep expertise from one person on the team become things that the whole team can be able to execute or just elevate the ambitions of everyone on the team in terms of timeline or capabilities or frontier of what they can get done.

它就会自动挑对的 harness，自动帮你挑对的模型，把这件事做完。理想情况下，这个选择不该落在用户头上——不该让他们在这一堆概念里挑，还得既清楚自己想干什么，又搞明白我们产品的能力边界在哪儿。所以那肯定是我们近期要去的方向。至于在 ChatGPT 和 Codex 之间选，其实是在选：你想留在一个更偏开发取向的界面里，还是想在 ChatGPT 模式里拿到同样的威力和能力。所以，如果你是 Codex 用户，就继续用 Codex，你不会错过任何东西，尽管接着用。但如果你是 ChatGPT 用户，想知道这些新的 agent 能力是什么，那你多半应该待在 ChatGPT 模式里。而在 ChatGPT 里，如果你想聊天、想搜索，那 chat 模式就是对的选择——还是你熟悉和喜欢的那个 chat 模式，只是模型一次比一次好、能力一次比一次新。但在 work 模式下，底下跑的其实就是 Codex。我们把一些编码相关的 UI 拿掉了，比如你不会在 work 模式里突然看到冒出来一棵 worktree，但它同样有把事情做成的那份能力：比如生成一个非常复杂的财务模型，在 work 模式里完全做得到。我们看到有人这么用——我前面提到我们公司的财务团队——他们用 work 模式做出了很不可思议的东西：那些事以前要么纯靠手工，要么得靠团队里某一个人的深厚专长，现在变成了整个团队都能执行的事，或者说，把团队里每个人在时间线、能力、能做到的边界上的野心都往上抬了一层。

[31:58] Lenny

Okay, that's really helpful. So there's kind of like these three modes currently. There's like the engineering mode, the chat mode, and then the do knowledge work mode. And the knowledge work mode is actually Codex doing all that work, but people may not know what codeex is. May not may may be afraid of it. Is there anything in that work mode that's not just Codex? Because that's actually really interesting. Is it like is there like additional harness tweaks to make it feel a little different or is it just the same thing with a little different UI?

好，这特别有帮助。所以现在大致是三种模式：工程模式、chat 模式，还有做知识工作的模式。而知识工作模式其实全是 Codex 在干活，只是大家可能不知道 Codex 是什么，甚至可能有点怕它。work 模式里有没有什么东西不只是 Codex？因为这个其实挺有意思的。比如是不是对 harness 做了额外的调整，让它感觉不太一样？还是就是同一个东西换了个 UI？

[32:23] Tara

It's it's really at the UI level. Um so work mode and codeex mode. If you go to Codex and ask it to generate a amazing financial model to price your product or something like that or like tell me predict my revenue for the next six months or something like that, Codex will do as good a job as work mode. It's like really about whilst it's doing so, what kind of UI do you want to see in the chain of thought? what kind of technical detail do you want exposed to you? The it's like incredibly it's similarly powerful and so CEX users aren't missing out on anything by not switching modes. In fact, we do not want them to like stay in codeex and do all the stuff you want to do in codeex and we will show you the appropriate UI based on the things you asked for. Truly, our northstar is to like merge all these things so that users don't have to make any of these decisions. The separation is really more about how can we meet people where they are as much as possible in terms of the products that they use, in terms of their familiarity with concepts and make sure that we are enabling everyone to take advantage of working with agents which has transformed entirely the way every single developer works. We should do the same thing with knowledge work.

其实真的就是 UI 层面的区别。work 模式和 Codex 模式，如果你去 Codex 里让它生成一个漂亮的财务模型来给你的产品定价，或者说「帮我预测接下来六个月的收入」，Codex 做得跟 work 模式一样好。区别真的只在于：它干活的过程中，你希望在思维链里看到什么样的界面，希望把什么程度的技术细节暴露给你。两边强大程度是差不多的，所以 Codex 用户不切模式并不会错过什么。事实上我们并不希望他们切——就待在 Codex 里，把你想做的事都在 Codex 里做，我们会根据你提的需求给你展示合适的界面。说实话，我们的北极星是把这些东西全部合并，让用户根本不用做这些决定。现在的区分更多是为了尽可能在人们所处的位置上接住他们——按他们用的产品、按他们对这些概念的熟悉程度接住他们，并确保我们让每个人都能享受到「和 agent 一起工作」的红利。这件事已经彻底改变了每一个开发者的工作方式，我们应该在知识工作上做成同样的事。

[33:29] Lenny

It makes sense. Uh there's just like because things move so fast like it would I imagine somebody's like let's try codeex this is going to be awesome and then it takes off and there's 10 million monthly active users and then they're like wait what are we doing here we got chatpt we got codeex how do we so it makes sense why these things you know like it's not going to feel obvious and perfect for a while because you have to kind of adjust as things work and things don't work and there's these kind of transition periods of like okay cool now let's get people moving towards this vision of the super app let's Okay. Um, okay. I imagine one of the hardest parts of your job is balancing this 100 billion MAU product chat GBT maybe the most successful consumer product in history with codeex which is this new thing and other new things that you guys want to try. How do you think about that? just I don't know just balancing these very innovative fastmoving teams and products with this like okay there's a billion people using this we can change this dramatically. Yeah, I think one of the most interesting things here is that we we one of the goals of launching work in chat GBT web and launching it in the desktop app and bringing these things together was to look at those billion people who are using chat GBT and bring them more and more of the agents power.

说得通。就是因为一切变得太快了，我能想象有人说「咱们试试 Codex 吧，这肯定牛」，然后它就起飞了，做到一千万月活，接着大家一愣：等等，我们这是在干嘛？我们有 ChatGPT，又有 Codex，接下来怎么办？所以就能理解为什么这些东西在一段时间里不会显得那么理所当然、那么完美——你得边跑边调，有的行、有的不行，中间就会有这种过渡期：好，现在我们把大家往「超级 App」这个愿景上带。好。嗯，好。我猜你工作里最难的一部分，是要平衡 ChatGPT 这个坐拥十亿级月活、可能是史上最成功的消费级产品，和 Codex 这个全新的东西，以及你们想尝试的其他新东西。你是怎么想这件事的？就是，怎么在这些创新的、跑得飞快的团队和产品，跟「已经有十亿人在用、我们不能随便大改」之间做平衡。嗯，我觉得这里最有意思的一点是，我们把 work 放进 ChatGPT 网页版、放进桌面端，把这些东西整合到一起，目标之一就是看着那十亿在用 ChatGPT 的人，把 agent 的能力越来越多地带给他们。

[34:51] Tara

Like if you think about the first era of AI products as chat, the second era of these products is clearly working with agents and you know primarily has been coding agents. We'd like to bring it to more more domains certainly like knowledge work and that is part of the goal of giving all these billion chat users the power of work. Certainly the product challenge that it that's on us is how do we not only bring it to them but make it natural and easy to adopt. Make it not a decision they have to explicitly make. We can just help them do the right thing. How do we take decomplexify it so they don't need to think about things like harnesses which feel like crazy concepts for a billion consumers to understand. So that that is primarily the the challenge. And then of course like that third era that that might come soon is how do you work with a like persistent co-worker who is able to get things done with you maybe collaboratively with other people. And so part of this challenge in the near term is we're introducing agents to a billion people who may not have experienced them yet. How do we do so in the easiest, most natural and most usable way possible? Certainly, there's a lot more for us to do to to make that happen. But part of this is also a lesson I've had maybe contrasting like preAI era or past product experience with this one, which is at previous companies like polish was king. uh getting every UI interaction or getting every little thing completely right was way more important than shipping something early because time didn't make as much of a difference in terms of the outcome. And so as such like if every corner wasn't like perfectly polished and everything was wasn't exactly correct, you might as well not ship it.

如果你把 AI 产品的第一个纪元看作 chat，那这些产品的第二个纪元显然就是「和 agent 一起工作」，而且到目前为止主要是编码 agent。我们希望把它带到更多领域，比如知识工作，这也是把 work 的能力交给这十亿 chat 用户的目标之一。当然，落在我们头上的产品难题是：不仅要把它带给他们，还得让它自然、容易上手，让它不是一个必须显式做出的决定——我们可以直接帮他们做对的事。我们怎么把复杂度去掉，让他们不用去想 harness 这种概念？对十亿消费者来说，这种概念简直是天书。所以这主要就是我们的挑战。然后当然还有那个可能很快到来的第三个纪元：你要怎么和一个常驻的同事一起工作？它能和你一起把事情做完，也许还能和其他人协作。所以近期这个挑战的一部分是：我们正在把 agent 介绍给十亿个可能还没体验过 agent 的人，怎么用最简单、最自然、最好用的方式做到？要让这件事成真，我们肯定还有很多要做。但这里面还有一课，是我拿 AI 之前那个时代、拿过去的产品经验跟现在对比得来的：在以前的公司，打磨是王道。把每一个 UI 交互、每一个小细节都做到完全正确，比早点发出去重要得多，因为时间对结果的影响没那么大。也正因为这样，如果哪个角落没打磨到位、有哪里不完全对，那你干脆就别发了。

[36:43] Tara

But I think what's been really compelling and interesting about this era and this product experience has been getting the product in the hands of users when you have so much conviction that hey it's transformative like is way better than perfect and that urgency and that uh introduction of that product is is so important. So we have a lot to do to make it more usable and easier for chat users certainly especially for folks who are not maybe even using it for productivity but using it for like consumer tasks but um yeah done is better than perfect and we have so much more to do. Yeah, I remember when uh this app first launched, there was a lot of uh comments about the confusion and seeing how quickly the team iterated and respond to the feedback is exactly what what I'm hearing here is get it out, figure out what the hell's what what's not working, how people are using it, iterate quickly. Feels like that's the the model now.

但这个时代、这段产品经历里，真正让我觉得有说服力、有意思的是：当你有足够强的信念，觉得这东西是变革性的，那么把产品交到用户手里，远比做到完美更重要——那种紧迫感、那个把产品推出去的动作，实在太重要了。所以要让它对 chat 用户更好用、更容易，我们肯定还有一堆事要做，尤其是对那些可能压根不是拿它来提升生产力、而是拿来做日常消费级任务的人。但，嗯，做完比做完美强，我们要做的还多得多。对，我记得这个 App 刚上线的时候，有一大堆关于「看不懂、搞混了」的评论，而看到团队迭代和回应反馈的速度之快，正好印证了我在这儿听到的：先发出去，搞清楚到底哪儿不对、大家是怎么用的，然后快速迭代。感觉现在的模式就是这样。

[37:36] Tara

And of course, there are things that you can continue to iterate and get that feedback prior to launching. And there's a lot that we can and should always do better. But um iterating as quickly as possible and listening to the right signals is regardless of whether that's pre-launch, post-launch, ideally pre-launch um is is the is the key thing.

当然，有些东西你可以在上线之前就一直迭代、一直拿到反馈。我们能做得更好、也永远应该做得更好的地方还有很多。但不管是上线前还是上线后——最理想当然是上线前——尽可能快地迭代、听对的信号，这才是关键。

[37:55] Lenny

This episode is brought to you by Mercury. Radically different banking now with spend. I've been a Mercury customer for so many years now. I switched all my business banking to Mercury and honestly, I could not be happier. It's what online banking feels like when it's built by product people, not by bankers. And now with Spend, you can give your team individual cards, set spending limits per person or per team, [music] and have expense receipts automatically pulled in from Gmail or over text. You can even give your AI agents their own cards with their own limits and policies. Most founders start out the same way. One card used by everybody at the company. It works until it stops working. Someone goes over, a receipt disappears. You spend two days trying to figure out who spent what and why. Spend is expense management built directly into Mercury. All your team's cards, budgets, and reimbursements. All live in the same place as your business thinking. No chasing, no manual reviews, no end of month scramble. The result is a team that can move fast and a founder who is no longer the bottleneck. Learn more and get signed up at mercury.com. Mercury is a fintech company, not an FDICured bank. banking services provided to Choice Financial Group in column NA members FDIC. The IO card is issued by Patriot Bank NA member FDIC pursuant to a license for Mastercard International Incorporated. Something I've noticed on Twitter is there's definitely been this vibe shift from Claude Code to Codeex in the past few months. It used to be everyone was cla.

本期节目由 Mercury 赞助。彻底不一样的银行服务，现在还多了 Spend。我做 Mercury 的用户已经很多年了，我把公司所有的银行业务都搬到了 Mercury，说实话没法更满意。它就是「网上银行如果由做产品的人、而不是由银行家来做」会长成的样子。现在有了 Spend，你可以给团队里每个人发独立的卡、按人或按团队设消费额度，（音乐）还能让报销票据自动从 Gmail 或短信里抓进来。你甚至可以给你的 AI agent 发它们自己的卡，配上各自的额度和规则。大多数创始人一开始都一个样：全公司共用一张卡。这套能凑合，直到有一天凑合不下去——有人刷超了，某张票据不见了，你要花两天去查谁花了多少、花在哪。Spend 就是直接内建在 Mercury 里的费用管理：团队所有的卡、预算、报销，全都和你的公司资金放在同一个地方。不用追着人要，不用手工审，不用月底手忙脚乱。结果就是团队能跑得快，创始人也不再是瓶颈。想了解更多、注册就去 mercury.com。Mercury 是一家金融科技公司，不是有 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。IO 卡由 Patriot Bank N.A.（FDIC 成员）依据 Mastercard International Incorporated 的授权发行。我在 Twitter 上注意到一件事：过去这几个月明显有一波风向转变，从 Claude Code 转向了 Codex。以前所有人都是 Cla

[39:26] Lenny

More recently, it just feels like people are leaning now towards Codeex, at least on Twitter, which is a bubble, but it's where a lot of tech people are. I'm curious what's shifted internally in the past, I don't know, 3 to six months, other than Tara joining and shaping up the ship. Uh, is there anything that you can share that's just like, okay, we figured this thing out, we shifted this, we cut this thing, what what helped shift the vibes and uh, help Codex become as successful as it as is becoming? You know, I think there's like this phrase which is uh before enlightenment uh carry wood or carry water chop wood post enlightenment uh carry water chop wood sort of thing. And actually with the CEX app um the team who initially got it up and running and were working on it uh were super again user focused tight iteration loop really dog fooded the thing like mainlined the app as much as possible to get get everything right. folks started to realize that was happening on externally and on Twitter and users started to really notice but the team was always really focused on users really focused on that iteration and it was merely the and to some extent like the market catching up that was the change and that process has not changed internally everyone still constantly uses the app everyone in the who's building it obviously is a developer using it for development and is constantly fixing not only their own problems but trying to listen to other people in the company's problems and user problems. Actually what's sort of remarkable is that the mode of operating hasn't changed. It's always been the same thing I had mentioned earlier like are we like are we elevating our mission sufficiently?

最近感觉大家开始倒向 Codex 了，至少在 Twitter 上是这样——Twitter 是个泡泡，但很多科技圈的人都在那儿。我很好奇，过去，我不知道，三到六个月里，内部到底变了什么，除了 Tara 你加入、把这摊子整顿起来之外。有没有什么可以分享的，比如「好，我们把这件事想明白了、我们调整了这个、我们砍掉了那个」——是什么让风向变了、让 Codex 做到今天这么成功？我觉得有句话是这么说的：开悟之前，砍柴挑水；开悟之后，还是砍柴挑水。其实 Codex 这个 app 也是这样——最早把它跑起来、一直在做它的那批人，同样是极度以用户为中心、迭代循环咬得特别紧，把这个产品当主力天天用（dogfood），能多用就多用，为的是把每个细节都做对。后来外面的人、Twitter 上的人开始注意到这件事，用户也真的开始注意到了；但团队始终就是聚焦用户、聚焦迭代，变的只是市场终于追上来了而已。这个过程在内部并没有变——所有人还是天天用这个 app，做这个产品的人本身就是开发者，用它来做开发，不停地修，不只是修自己碰到的问题，还努力去听公司里其他人的问题、用户的问题。其实挺不可思议的一点是，做事的方式根本没变过。一直都是我前面提到的那件事：我们有没有把我们的使命抬得足够高？

[41:09] Tara

Are we maximally accelerating progress and are we mainlining it as much as possible? And I think it's great that uh users and folks on Twitter have noticed, but that that operation like the full credit to the team like that hasn't changed.

我们有没有在最大限度地加速进展？我们有没有尽可能把它当主力来用？我觉得用户和 Twitter 上的人注意到了，这很好，但那套做事的方式——功劳完全归团队——是一直没变的。

[41:24] Lenny

What's really interesting about this answer is it's the very human part of it. It's you, it's Andrew, it's Tibo, it's the team just like being obsessed with the the customer, the product. And it's not like it's not like AI was the answer. It's the humans that made the difference.

这个回答里特别有意思的一点，是最关键的恰恰是「人」的部分。是你，是 Andrew，是 Tibo，是整个团队对客户、对产品的那种较真。并不是说 AI 就是答案，真正做出差别的是这些人。

[41:39] Tara

Yeah, I'll I'll give the the team deserves like full full credit here. the everyone on the team is incredibly thoughtful and independent and to the point of like there are you know many founders at OpenAI like almost everyone on that team like the desktop team especially like asks like founders and cares about every piece and every detail and when they notice an area that should be better they go build it very independently and and get the thing up and running and if it doesn't test well internally like people aren't using it if people don't find it useful they'll iterate on and then finally like ship it externally. But that loop is full credit to like people on the team and and individuals for making that happen. Something you touched on is this idea of roles overlapping this idea of like you know engineers are doing a PME work you're doing probably shipping prototypes and building maybe shipping to production I don't know just it feels like that also creates a lot of challenges I hear from a lot of people like what is my job now as a as a designer what am I what am I responsible for what am I not responsible for as a marketer what am I what am I doing is that something you notice is that something that you're dealing with um just any thoughts along those lines

对，这里的功劳我要百分之百归给团队。团队里每个人都极其有想法、极其独立——OpenAI 里有很多创始人型的人，那个团队几乎人人如此，尤其是桌面端团队，每个人都像创始人一样，在意每一块、每一个细节。他们一发现哪里应该做得更好，就自己去把它做出来，非常独立地把东西跑起来；如果内部试用效果不行——大家不用、大家觉得没价值——就继续迭代，最后才对外发布。这个闭环，功劳完全属于团队里的人、属于一个个具体的个体。你刚才提到一个点，就是角色在互相重叠：工程师在干 PM 的活儿，你自己大概也在做原型、甚至可能直接发到生产环境。我不知道，感觉这也带来了不少困扰。我听很多人说：那我这个设计师现在的工作到底是什么？我该为什么负责、不该为什么负责？我是做市场的，那我现在到底在干嘛？这个你有没有注意到？你自己有没有在应对这件事？就是这方面有什么想法都行。

[42:48] Tara

I think the thing I've always liked the most about working at startups and sometimes I've started at a startup that accidentally grew into a large company but largely primarily working at startups is that there are very few boundaries around your role that like everything and nothing is your responsibility ultimately you're accountable for success actually like stripe was very very much this way where there are no boundaries around what a engineer could do versus a product manager could do versus a designer could do everyone could do anything and so actually it kind of feels Like I've always really loved that mentality and now finally capability is catching up to that. But the thing I really care about is that someone needs to look after the or have core accountability for is this product being used by users? Is it something that people want? Is it uh high quality? Is it effective? And whether that person is like an engineer or a designer or a PM or whomever, like someone is the DRRi and then whatever work needs to be done to make that possible, you know, certainly people can pick it up based on their affinity, based on their capability, but I like a team that doesn't really mind what the boundaries are between individual roles, but everyone's just sort of focused on making the outcome happen. The converse of this is I also really love like the craft aspects of like being a PM. Like there are so many aspects to PM craft that I know folks like Shreas or maybe Marie Kagan or Shashir like all these people have really espoused that I think are are wonderful. And sometimes um maybe some of these questions are come from wait I I so love the craft of my domain by taking this more fluid approach to teamwork and collaboration to get something done. Do I lose out on getting better and polishing my craft?

我一直最喜欢在创业公司工作的一点——虽然有几次我进的创业公司不小心长成了大公司，但主要还是在创业公司——就是你的角色几乎没有边界：所有事都是你的责任，也都不是你的责任，说到底你只对结果负责。Stripe 就特别是这样，工程师能做什么、产品经理能做什么、设计师能做什么，中间没有边界，谁都可以做任何事。所以其实感觉挺妙的，我一直特别喜欢这种心态，而现在「能力」终于追上这种心态了。但我真正在意的是：得有人去盯着、或者说对这些负核心责任——这个产品到底有没有人在用？是不是大家想要的东西？质量高不高？有没有效果？至于这个人是工程师、设计师、PM 还是别的什么人，不重要，总得有个 DRI；然后为了把事做成需要干的活儿，大家当然可以按各自的兴趣、按各自的能力去接。我喜欢那种不太在意个体角色之间边界的团队，所有人只盯着把结果做出来。反过来说，我也真的很喜欢做 PM 这门手艺本身的那些部分。PM 的手艺里有太多讲究，像 Shreyas、Marty Cagan、Shishir 这些人一直特别推崇的那些东西，我觉得都非常棒。有时候这类问题的来源可能就是：等等，我这么热爱我这个领域的手艺，如果我用这种更流动的方式去协作、去把事做成，我是不是就失去了精进和打磨手艺的机会？

[44:40] Tara

And I truly don't have an answer for that question. I think it's like something we're all experiencing together, which is some pieces of our craft are actually getting abstracted by models being able to do it really effectively, maybe better than than individuals can. And your craft moves from, you know, being able to do that very specific task you did in the past to now applying it to some other part of the product or the discipline. But yeah, that that is still a question I'm thinking about, which is how do I balance my desire to be part of a team and use these tools and feel so um compelled by how effective one can be now with all these products with my love of like the Yeah, it's it's really fun handwriting code for an engineer all the time and one doesn't really do that anymore.

这个问题我是真的没有答案。我觉得这是我们所有人正在一起经历的事——我们手艺里的某些部分确实正在被模型抽象掉，模型能做得非常好，甚至可能比人做得还好。于是你的手艺就从「能把过去那件很具体的活儿做好」，变成把它用到产品或这门学科的另一些部分上。但说实话，我到现在还在琢磨这个问题：怎么去平衡？一方面我想成为团队的一部分、想用这些工具，也确实被「现在有了这些产品，一个人能这么高效」这件事深深吸引；另一方面我又热爱那种……对，对工程师来说，一直手写代码是真的很爽，而现在基本没人这么干了。

[45:28] Lenny

Yeah, that's where I was going to go. It's just like unbelievable how different the engineering role is now.

对，我正想往这儿说。工程师这个角色现在变得有多不一样，简直难以置信。

[45:34] Tara

Yeah.

嗯。

[45:35] Lenny

It's like you used to write code all day. That was your job and that is no longer your job.

以前你一整天都在写代码，那就是你的工作，而现在那已经不是你的工作了。

[45:39] Tara

Yeah.

对。

[45:39] Lenny

And that happens so quickly

而且这个变化来得太快了

[45:41] Lenny

like people mourn like the flow state of writing code.

大家甚至会怀念写代码时那种心流状态。

[45:44] Tara

Yeah.

对。

[45:45] Lenny

Manually yourself versus now what what one does.

自己一行行手写，跟现在的做法完全是两回事。

[45:49] Tara

But I think it is a um Yeah. It's a it's a it's a tough transition.

但我觉得这确实是个……对，这确实是个挺难熬的转变。

[45:54] Lenny

Yeah. And you know some people love it, some people don't. And that's a whole other topic. Kind of along those lines, something I'd like to ask people at the frontier of AI is where do you think human brains will continue to be valuable in the future? It's impossible to predict long term. Will we need humans? Hopefully, but I'd say in the I don't know, next couple years just like where do you think human brains will continue to be most valuable?

对。而且有人很喜欢，有人不喜欢，那又是另一个话题了。顺着这个思路，我特别想问问身处 AI 前沿的人一个问题：你觉得未来人脑还会在哪些地方继续有价值？长期是没法预测的——我们还需要人类吗？但愿需要吧。但就说接下来，我不知道，几年吧，你觉得人脑在哪些地方会最有价值？

[46:18] Tara

I think humans will continue to be most valuable as a certainly as a um like an entity of accountability. So, who ultimately owns the outcome here? In some ways, you can think of your agent that you're working with as like your your report. Um, ultimately, who owns like what's what was the end product? Was it high quality? Was it the thing that you wanted it to do and say like that that will certainly remain a person at least at least for now. And especially in industries and places that are um highly regulated or require like a direct human interface like that that makes a ton of sense to me. I think the human brain is also really valuable for expression. I'd mentioned earlier that analogy of uh software is not like real estate. It is more like a film where you could put money and a great film does not come out. Like the greatest films are not the ones with the biggest budgets. And given that there's a certain there's a certain artistry and opinionation and expression in building software where you feel like there is some authorship by a by a person or a group of people. And that part remains to me so human like what you choose to build and how it feels feels like such a such a human question. Um I also think the human brain continues to be valuable in like how we care for each other and relate to one another. Um that piece of my work has remained so human and remained actually has actually become more important than ever. the part where you talk to other people on your team and collectively figure out how you can be enthusiastic about a area, how you learn and work together, how you elevate each other's ambitions. All of that feels and remains such a human thing to do. Yeah, I think the human brain will will continue to be so valuable in that regard. That said, I, you know, can't predict what'll happen with the models, but those pieces feel to me to be incredibly incredibly human.

我觉得人会继续最有价值的地方，首先肯定是作为一个「担责的主体」。也就是说，这件事最终归谁负责？某种意义上，你可以把跟你协作的 agent 当成你的下属。最终谁来对交付物负责？质量高不高？是不是你想让它做、想让它说的那个东西？至少在现阶段，这一定还是人。尤其在那些强监管的行业和场景，或者需要真人直接对接的场景，这对我来说太说得通了。我觉得人脑在「表达」这件事上也非常有价值。我前面提过那个类比：软件不像房地产，它更像电影——钱砸下去，未必就能出一部好片子，最伟大的电影并不是预算最高的那些。既然如此，做软件这件事里就存在某种艺术性、某种鲜明的主张和表达，你能感觉到背后有一个人、或者一群人的「作者身份」。这部分在我看来始终是极其人性的——你选择造什么、它给人什么感觉，这本身就是个非常「人」的问题。我还觉得人脑在「我们怎么彼此关照、怎么相处」这件事上会继续有价值。我工作里的这一部分一直非常「人」，而且实际上比以往任何时候都更重要了：你和团队里的其他人聊，一起想清楚怎么才能对某个方向真正兴奋起来，怎么一起学习、一起把事做成，怎么把彼此的野心往上抬。这一切都是、也依然是非常人类的事。对，我觉得人脑在这方面会继续非常有价值。话说回来，我也没法预测模型会发展成什么样，但这几块在我看来是极其、极其人性的。

[48:18] Lenny

I love that answer. There's this idea that you talked about this idea of the this overhang of what AI is capable of and what we're actually uh doing with it. People are always like, it feels like one of the biggest gaps is like, okay, what should I do with it? I'm curious, what are some ways that you use AI in your work that may inspire people like oh wow I didn't think about using it that like there's kind of two buckets here. One is just like what's like the most how your PM job has changed most thanks to AI that you're just like okay now I use AI for this stuff and then what's like is there any like super interesting creative uses of AI recently that you're like oh yeah I should try this. One of the most exciting ways that I use AI in work is um I actually build sites all the time now. I don't know if you've tried building sites in

我很喜欢这个回答。你刚才提到一个概念，就是 AI 的能力和我们实际拿它做的事之间存在的那段「过剩」。大家老是说，最大的落差之一就是：好吧，那我到底该拿它做什么？我很好奇，你在工作里有哪些用 AI 的方式，可能会让人一听就「哇，我都没想过还能这么用」？这里其实有两桶东西：一桶是，你的 PM 工作因为 AI 发生的最大改变是什么，就是「现在这些事我交给 AI 干了」；另一桶是，最近有没有什么特别有意思、特别有创造性的 AI 用法，让人一听就想「对，我该试试这个」。我在工作里用 AI 最兴奋的一件事，是我现在动不动就做 sites。不知道你有没有试过做

[49:05] Lenny

I haven't. Talk about sites.

没有。讲讲 Sites。

[49:06] Tara

Sites is a really fun amazing product. Um you can basically build a site certainly in work as a presentational artifact, but I also build sites for literally anything. I built a site um for the team as like a as a game uh where we all played a game together using a site because sites have a database. Uh you can build site I actually built a site because I went on a backpacking trip recently. I built a site of the route that like tracked the elevation of everywhere we were going. Everyone on our our trip like inputed all their food. Um it was like super fast and effective. sites kind of realized the dream of like malleable personal software that Alan K, you know, flagged in the in the 60s of like the true personal computer is one that has personal software. In some ways, sites are like the tangible way to make that possible. We had all once dreamed of like making personal software and certainly people with tools like notion etc. try with all these blocks to configure what that could be. But with a site, it is literally a prompt. I literally with a prompt say like build me this exact tool that I need to get this thing done and it just does it. Um they're sharable. Uh they can use they can auto update. You can use like internal data to build like a dashboard for example with lots of metrics. And rather than like painstakingly laboring over some sort of like slide deck, a site is just a way more dynamic surface for presentation.

Sites 是个特别好玩、特别厉害的产品。你基本上可以做一个 site，工作上当然能拿它当汇报展示的产物，但我真的什么都拿它做。我给团队做过一个 site，是个游戏，我们用它一起玩，因为 site 是带数据库的。我最近去徒步露营，还专门做了一个 site，把整条路线画出来，一路上每个地方的海拔都跟着标；同行的每个人都把自己带的食物录了进去。特别快，特别管用。sites 某种程度上把那个梦想实现了——Alan Kay 在六十年代就提出的、可随手改造的个人软件：真正的个人电脑，是那种有个人软件的电脑。某种意义上，site 就是让这件事落地的具体形态。我们都曾幻想过自己做个人软件，当然也有人用 Notion 这类工具，拿各种 block 拼来拼去去逼近那个东西。但对 site 来说，它就是一句 prompt——我真的就用一句话说「给我做一个我需要的这么个工具，把这件事搞定」，它就直接做出来了。而且可以分享，可以自动更新。你还能接内部数据，比如做一个带一堆指标的 dashboard。与其吭哧吭哧折腾一份幻灯片，site 是个动态得多的展示载体。

[50:30] Lenny

How do you use a site? Do you have to do anything special or you tell it make create a site

你怎么用 site？需要做什么特别的操作，还是直接跟它说「做一个 site」

[50:33] Tara

in codeex be like create a site that um is a I don't know is a mafia game for my team and it will just do it

在 Codex 里就说「做一个 site，是个……我不知道，给我团队玩的狼人杀」，它就直接做出来了

[50:40] Lenny

and like like I'm thinking capital S site but doesn't matter I imagine

而且，我脑子里想的是大写 S 的 Site，不过应该无所谓，我猜

[50:44] Tara

it just knows what sites are

它自己就知道 sites 是什么

[50:46] Lenny

so it's yeah because it used to be here's a here's some source code go figure out where to deploy it yeah

所以，对，因为以前是这样：这儿有一堆源代码，你自己去想办法部署吧。对

[50:50] Lenny

and what you're saying here is it just host it for you and

而你现在说的是，它直接帮你托管好了，而且

[50:53] Tara

host you can choose whether it's public you can choose whether it's with your team or choose whether it's private to you

托管。你可以选它是公开的，还是只给团队看，还是只有你自己能看

[50:59] Tara

um they're great they've The easy reach of building a site all the time has changed what my day-to-day looks like which often in in previous worlds used to look like creating lots of artifacts like docs and sheets and whatever it might be. Now I just make sites all the time.

嗯，它们特别好用。随手就能做一个 site 这件事，改变了我日常工作的样子——放在以前，日常往往是产出一堆东西：文档、表格，什么都有。现在我就是一直在做 sites。

[51:16] Lenny

And you could do that through I imagine work or can you do it through through all the services codeex work?

这个我猜可以在 work 里做？还是说所有入口都行——Codex、work 里都能做？

[51:21] Tara

You can do it through work. You can do it through codeex. You can do it in the web. You can do it on mobile. [laughter] You can do it anywhere.

work 里可以，Codex 里可以，网页端可以，手机上也可以。（笑）哪儿都能做。

[51:27] Lenny

Okay. I just kicked off a create a site about Terra Sean.

好。我刚起了一个任务，让它建一个关于 Tara Seshan 的网站。

[51:30] Tara

Great.

很好。

[51:31] Lenny

Is that how you pronounce your last name by the way? I haven't asked.

顺便问一句，你姓氏是这么念的吗？我一直没问。

[51:33] Tara

Uh Tara Sash like station

呃，Tara Seshan，那个音就像 station 里的

[51:36] Lenny

s. Okay cool. Okay cool. Um sites. Okay. Any other quick tips uh while we're on this topic for PE? Like that was a great tip because I don't think a lot of people know about sites. That's um very useful.

「sh」音。好，明白了。行，酷。嗯，sites。好。趁着聊到这个话题，还有别的什么快手小技巧能给 PM 的吗？刚才那条特别好，因为我觉得很多人压根不知道 sites 这个功能。太有用了。

[51:47] Tara

Yeah, sites are awesome. Um the other thing I really love is using visualize in codeex. Have you used slash visualize?

对，sites 特别棒。另外我非常喜欢的是 Codex 里的 visualize。你用过 /visualize 吗？

[51:53] Lenny

No.

没有。

[51:54] Tara

Oh, slash visualize is incredibly exciting. Ask you can just do slashvvisualize. Visualize my chatbt usage until now or something like that and it will pull in like all the things that you've done and create like an amazing visualization for it. the number of times that I've been thinking about how do I not only pull in a bunch of charts and data but present them in a way that is understandable and useful for the story I'm trying to tell has been infinite and visualize makes that incredibly simple. It is like surprisingly delightful to use visualize.

哦，/visualize 太让人兴奋了。你只要打一个 /visualize，比如「把我到目前为止的 ChatGPT 使用情况可视化一下」之类的，它就会把你做过的所有事情都拉进来，给你生成一个特别漂亮的可视化。我脑子里琢磨过无数次这件事：怎么才能不光是把一堆图表和数据拉出来，还能用一种别人看得懂、又服务于我想讲的那个故事的方式把它们呈现出来——这种时候多到数不清，而 visualize 让这件事变得极其简单。用起来意外地让人愉悦。

[52:25] Lenny

It's just like it's just these are such good examples of there's so much power here we don't even know about or understand and that's the challenge you have here. Help us for sure

这就是……这些例子太好了，说明这里面有太多能力是我们根本不知道、也理解不了的，而这恰恰就是你们面对的挑战。真得帮帮我们

[52:34] Lenny

help us know all these things. That's why podcasts like this are also useful. Can't put it all in the product. Uh, I'm going to go in a totally different direction. I want to talk about writing. I asked uh Brie Wolson, who knows you well, what to ask you. Uh, funny enough, she suggested questions for the previous podcast uh conversation I did with Adam Ward from Ger. Uh, so she said, "Okay, you should ask her about writing slashthinking. A Terra brief is iconic. help us understand just uh what makes your writing your briefs iconic and any tips that might be helpful for people that are maybe trying to get better at writing and writing documents.

帮我们把这些都搞明白。所以这种播客也有它的用处嘛，你没法把所有东西都塞进产品里。呃，我要转到一个完全不同的方向。我想聊聊写作。我问了很了解你的 Bri Wolfson，该问你点什么。有意思的是，我上一期跟 Ger 的 Adam Ward 那场对谈的问题也是她出的。她说：「你该问问她写作、问问思考。Tara 的 brief 是传奇级的。」帮我们理解一下，你的 brief 凭什么这么出名？另外，对那些想把写作、把写文档这件事做得更好的人，有没有什么用得上的建议？

[53:13] Tara

I really strongly believe that I do two types of writing at work. One is writing as thinking and the other is writing as reporting. Writing is thinking is me writing a like a brief about why we should build a certain product or why we should take a certain strategy or why like maybe a spicy take. Um but writing is reporting is things like oh I'm summarizing the status of what our team has been up to this week and I'm sending over a report about it or this is our plan for this particular launch or announcement or something like that. Writing is reporting I happily automate or I use I use the models all the time to make that as as simple as it can be. But writing is thinking is something I never will automate. I really strongly believe that the at least for me the act of going through and outlining something, turning it into some level of pros, cutting it and editing it, continuing to iterate on it is one of the most important steps for me to get my ideas in line. I think most people actually uh will paint with a really broad brush like I will never use them use the models for writing or I always use the models for writing and actually to me like that both those broad brushes are wrong. I think you should use the models as much as possible for writing as reporting and in as much as you think with writing as I really do and I think a lot of people do you should not use it you shouldn't replace your thinking with it but my briefs in the past um because I write so much um as a way of thinking uh is that I will write a I will like go into a hole write a brief for a new idea or a or a product spend a ton of time refining that particular idea shop it around with people and have them attack the ideas in it as much as possible and poke holes, make it stronger, and then take it to the next person and do the same thing. And so at Stripe, this is something I did many, many, many, many times over, whether

我非常坚信一点：我在工作里的写作分成两种。一种是「写作即思考」，另一种是「写作即汇报」。写作即思考，是我写一份 brief，论证我们为什么该做某个产品、为什么该采取某个策略，或者抛出一个可能有点辛辣的观点。而写作即汇报，是那种「我在总结我们团队这周做了什么，然后发一份报告出去」，或者「这是我们这次发布或公告的计划」之类的东西。写作即汇报，我很乐意自动化，我一直在用模型把这件事做得尽可能省事。但写作即思考，是我永远不会自动化的。我非常坚信——至少对我是这样——先列提纲、把它变成有点成文的样子、再删、再改、不停迭代，这整个过程是我把自己的想法理顺最重要的步骤之一。我觉得大多数人其实是一刀切的：要么「我写东西绝不用模型」，要么「我写东西全用模型」，而在我看来这两种一刀切都不对。写作即汇报，你应该尽可能多地用模型；但只要你真的像我这样、也像我相信很多人那样靠写作来思考，那你就不该用它——你不该拿它替代你的思考。说回我过去那些 brief，因为我写得非常多、把写作当成思考的方式，我的做法是：钻进洞里，为一个新想法或一个产品写一份 brief，花大量时间打磨那个想法，然后拿去找人聊，让他们尽可能地攻击里面的观点、挑毛病，把它变得更结实，然后再拿给下一个人，重复一遍。在 Stripe，这件事我做过非常非常非常多次，不管是

[55:10] Tara

that was like to kick off a new product area or to suggest a big change in direction or to analyze like a problem and suggest like a path forward. And Stripe is incredibly oriented as a writing culture. And there are many people like Jeff Weinstein who are also very into writing and sharing briefs at Stripe. SH is one of the few places where like a brief will go viral um inside the company. And so writing is thinking there is really prized and that's where I did like the majority of of that writing work. Um, at OpenAI, I think I I still write as thinking all the time. Um, but the sharable artifact here is not really a long dock or a sort of proof of work in that way. Um, partially because times have changed and a long dock is not a signal that you thought through something because you can easily produce a long dock that indicates that you haven't. And so actually the the point maybe one of the biggest changes I've experienced personally in my day-to-day which has been a big maybe jarring change is that I used to think in a document and then do some translation of that into a presentational artifact and that would be my indication that I thought through a problem and this is what we're going to do and the team moves in that direction and now I am way more on mocks not docs or prototypes not docs and if I have something that people can try and interact with or even better. I have like results where we tried this, we ran an AB, here's like the results. This is why I think we should like go in this direction. That is a way better communication tool than like the the doc itself. And so I still write hundreds of docs all the time, but I do it for me.

为了开一条新的产品线，还是为了提议一次大的方向调整，或者分析某个问题、给出一条往前走的路径。Stripe 是一家极度以写作为导向的公司。那儿还有很多人，比如 Jeff Weinstein，也非常热衷于写 brief、分享 brief。Stripe 是少数几个「一份 brief 能在公司内部刷屏」的地方。所以「写作即思考」在那里是真正被珍视的，我那部分写作工作大多也是在那儿做的。嗯，到了 OpenAI，我觉得我依然一直在用写作来思考。但在这里，能拿出去分享的产物已经不太是一份长文档、不太是那种意义上的「工作量证明」了。一部分原因是时代变了：长文档已经不能证明你把一件事想透了，因为你可以轻轻松松产出一份长文档，反而说明你没想透。所以说，我个人日常里体验到的最大变化之一——可能也是最让我错愕的一个变化——是：我以前在文档里思考，然后把它翻译成某种可展示的产物，那份东西就是我的凭证，证明我把这个问题想清楚了、这就是我们要做的，然后团队照这个方向走；而现在我更信「要 mock，不要 doc」「要原型，不要文档」。如果我手上有个东西是别人能直接试、能直接交互的，那就更好；更好的是我手上有结果——我们试过了，跑了个 A/B，结果在这儿，所以我认为我们应该往这个方向走。这是比文档本身好得多的沟通工具。所以我现在还是一直写几百份文档，但我是写给自己的。

[56:58] Tara

Um, and I no longer do it for other people really. Like that no longer is the best way to to talk and communicate. That is probably the biggest change I've experienced personally in u this era versus the previous era. That is so interesting. I really liked your tip of getting tons of feedback on a doc. Like, you know, it sounds obvious, but you know, you can get to an iconic doc, brief by just cheating almost and getting lots of feedback on it as you're iterating. Yes. to make it stronger and stronger and stronger versus like cool here it is first time and it's rarely

嗯，我基本上不再为别人写了。那已经不再是最好的沟通和交流方式。这大概是我个人在这个纪元、相比上一个纪元感受到的最大变化。这太有意思了。我特别喜欢你说的那条——把文档拿去疯狂收反馈。听上去像句废话，但你确实可以靠这个「作弊」，一边迭代一边大量收反馈，最后就能得到一份传奇级的文档、传奇级的 brief。对，让它一次比一次更结实，而不是「行了，第一稿在这儿」——那样很少

[57:30] Tara

I previously had a manager who told me that the right thing to always do is write a doc to 70% completion and then take it to the people that you need buyin from and get it from 70% to 100%. And that still is like a thing that I I do all the time because very few great people want to interact with like a perfectly polished finished idea. Like a perfectly polished idea, their new ideas just like bounce off of it versus something that has more crags and more um rough edges that they too can polish with you together. And I think that um like bringing people into the process that way where like a doc is like an underlying artifact for that is one of the best ways to collaborate that I found.

我以前有个 manager 跟我说，永远正确的做法是：把一份文档写到 70% 的完成度，然后拿去找那些你需要争取支持的人，让他们帮你把这 70% 推到 100%。这件事我到现在也一直在做，因为很少有厉害的人愿意跟一个打磨得完美无缺、已经成型的想法互动——想法太光滑了，他们的新点子会直接弹开；而一个还带着棱角、还有毛边的东西，他们才能和你一起去磨。我觉得用这种方式把人拉进过程里、把文档当成承载这一切的底层载体，是我找到的最好的协作方式之一。

[58:08] Lenny

How do you think about uh AI brain rot and starting to over rely on AI. This just a challenge everybody's gonna have. Why not use this magic to help look at something and then we start to lose our ability to write read long documents. Is there anything you do that you are trying to avoid that?

你怎么看「AI 脑腐」，以及开始过度依赖 AI 这件事？这是每个人都会遇到的挑战：既然有这么个魔法能帮你把东西看一遍，为什么不用？可用着用着，我们就慢慢丧失了写作、读长文档的能力。你有做什么来刻意避免这一点吗？

[58:28] Tara

Yeah, I think this writing is thinking discipline is one of the main pieces that I employ in my day-to-day to make sure I'm not overly atrophying my my thinking abilities. I think I will again outsource all writing is reporting as much as possible to the model but writing is thinking I have to do myself and I have this like personal um belief that if I'm going to make someone read my document I have to at least read it first that number of times. Um or I think about this in meetings too that if I'm going to call a meeting with with a set of people I need to have prepped the collective amount of time that people are going to spend in that meeting before the meeting. And so when it comes to like keeping my thinking sharp, like I do that writing for the document myself first and make sure I've invested like the collective amount of time I expect people to read it at least in writing it and producing it. And I don't really rely on the model either for polishing my pros, which I don't think it it really it really does, or um especially not in like generating the the first version. But I do I do of course have the model help me a lot when it's like summarization or like translation of content from one format to the other all the time.

有，我觉得「写作即思考」这条纪律，就是我日常里用来确保自己的思考能力不至于萎缩的主要手段之一。我会尽可能把所有「写作即汇报」的活儿外包给模型，但「写作即思考」必须我自己来。我还有一个很个人的信条：如果我要让别人读我的文档，那我自己至少得先把它读那么多遍。开会我也是这么想的：如果我要召集一群人开会，那我在会前的准备时间，得等于大家在这场会里将要花掉的时间总和。所以说到保持思维锋利，我就是先自己把那份文档写出来，确保我在写它、产出它上面投入的时间，至少等于我预期大家读它所花的时间总和。我也不太靠模型来润色文字——我觉得它其实润色得并不好——尤其不会让它生成第一版。但我当然会在很多地方让模型帮大忙，比如做总结，或者把内容从一种格式转成另一种，这我一直在用。

[59:42] Lenny

So what I'm hearing is uh write the idea, the brief, the plan yourself as a human. Write it yourself. Don't start with AI. Don't and and even don't use it to improve on the writing. Just keep that all human.

所以我听下来是：想法、brief、计划，作为人自己写。自己动笔，别从 AI 开始，甚至连改稿润色都别用它，这一整块都保持纯人工。

[59:56] Tara

Yeah. At least at least for me, I start myself and I end myself. I might use AI in the middle to research specific elements or drop in some data or go pull some data or help

对。至少对我来说，开头是我自己，收尾也是我自己。中间我可能会用 AI 去研究某些具体的点、塞点数据进来、让它去拉点数据，或者帮我

[1:00:07] Tara

push back on some ideas.

反驳一些想法。

[1:00:09] Lenny

Yeah, push back on some ideas, but start yourself and yourself with a piece of writing and that doesn't deteriorate your thinking.

对，帮你挑战一些想法。但一篇东西自己开头、自己收尾，这样你的思考就不会退化。

[1:00:16] Lenny

Okay, one last uh question I want to ask about Setter Hill. You had this very unusual career step. You went to your PMP founder person and then just like okay eir at Sutter Hill Ventures which is a iconic VC. Uh I'll people can look it up. A lot of amazing companies came out of Setter Hill. It was it has a very unique way of approaching founding where basically they incubate companies. Snowflake as an example. Um what was that? What was that about? What did you learn from that experience?

好，最后一个问题，我想聊聊 Sutter Hill。你的职业路径里有一步非常不寻常：你先是做 PM、做创始人，然后忽然就跑去 Sutter Hill Ventures 当 EIR 了——那是一家传奇级的 VC，大家可以自己去查，很多了不起的公司都是从 Sutter Hill 出来的。它做创业这件事的方式非常独特，基本上是自己孵化公司，Snowflake 就是一个例子。嗯，那到底是怎么回事？你从那段经历里学到了什么？

[1:00:45] Tara

Sutter Hill is an iconic firm and is intentionally a very illegible firm. Like if you go to the Sutter Hill website, you will see nothing on the website. It is a a firm that doesn't operate loudly. It tries to operate as under the radar as possible as modestly as possible yet is somehow responsible for some of the most iconic successes that Silicon Valley has seen. And they have this very unusual incubation model which Mike Spiser who is the like one of the amazing partners there started and um has rolled out success after success. I think the thing that was most iconic to me about Setter Hill is that people look at finding product market fit as a dark art or building like a tens of billion dollar company as a dark art like oh it's luck oh it's chance oh it's all these like things that must come together yet Mike Spiser has done it multiple times and so there is there's like clearly a way to do it there's clearly a roadmap for making that possible there's like a set of things one can do to get this repeatably it's not just luck it's not just a dark art. There is a there is a playbook as it were and that playbook lives inside of the firm Sutter Hill and they have figured out how to be right a lot in terms of like calling shots and making bets and they've learned how to be right a lot in terms of the like daily compounding things that one does to create a successful company whether that's how you set up your enterprise sales team, how you like position your product, how you like build the initial founding team, the recruit Recruiting at Sutter Hill is like an unparalleled excellent thing. They have a secret tool called Reticle where they have a map of, you know, everyone in uh that they've interacted with and the 10 best people that those people have interacted with.

Sutter Hill 是一家传奇级的机构，而且是刻意让人「读不懂」的一家。你去 Sutter Hill 的官网看，上面几乎什么都没有。这家机构不喜欢大声张扬，它尽可能低调、尽可能不出现在雷达上，可偏偏硅谷最标志性的一批成功案例都跟它有关。他们有一套非常特别的孵化模式，是那里几位了不起的合伙人之一 Mike Speiser 开创的，而且一次又一次地做成了。对我来说，Sutter Hill 最传奇的一点是：大多数人把找到 product-market fit 看成一门玄学，把做出一家几百亿美元的公司也看成一门玄学——哦，那是运气，那是机缘，那是一堆条件恰好凑到了一起。可 Mike Speiser 做成了不止一次。所以显然是有方法的，显然是有一张路线图的，显然存在一套动作能让这件事可复现——它不只是运气，也不是什么玄学。是有一套 playbook 的，而那套 playbook 就活在 Sutter Hill 这家机构内部。他们摸索出了怎么在「判断大势、下注」这件事上高频率地对，也摸索出了怎么在「那些每天复利累积的小事」上高频率地对——比如你怎么搭企业销售团队、怎么给产品做定位、怎么组建最早的创始团队。招人这块，Sutter Hill 做得好到没有对手。他们有个秘密工具叫 Reticle，里面是一张图谱：他们接触过的每一个人，以及这些人各自接触过的最优秀的十个人。

[1:02:32] Tara

Um that helps them be so so effective at this. Um, so I went to Sutter Hill because in some way my career has been about how do I try to find product market fit as many times as possible, whether that was as a founder or in starting new products at Stripe or in like joining a startup like Watershed. And so Sutter Hill is a place where they've figured out how to find product market fit on B2B products. And I wanted to learn what I could from them.

嗯，这让他们在这件事上效率高得离谱。所以我去 Sutter Hill，是因为我的职业生涯某种意义上一直围绕着一件事：怎么让自己尽可能多次地去找到 product-market fit——不管是作为创始人，还是在 Stripe 内部做新产品，或者加入 Watershed 这样的创业公司。而 Sutter Hill 恰恰是一个已经摸清了「怎么在 B2B 产品上找到 PMF」的地方，我想从他们那儿尽可能多学点东西。

[1:02:56] Lenny

What'd you learn? What's one thing you took away from that experience other than they know how to do it?

那你学到了什么？除了「他们确实会做」之外，你从那段经历里带走的一件事是什么？

[1:03:00] Tara

They they definitely know how to do it. I think um one thing that was very surprising to me that I learned there is that product market fit is sure important but actually I really underrated product marketing fit. The idea that the way you talk about the product and the way you market it can precede actually even building the product. It should probably come from some sort of bringing together of understanding the technology deeply and then understanding like the enterprise sales process and then that product marketing fit that narrative that positioning is actually even before you build a product experience the right thing to test. So you should go like pitch 100 people figure out how to refine that pitch as much as possible. get the marketing narrative of why this thing is transformative right and then and only then go commit the okay this is exactly the product shape and Mike Spiser is like unbeatable at this art previously I'd always kind of underrated PMM work I was like it's whatever like it's the glue between these functions it's fine and then I realized how transformative that work done excellently is to a company's outcome and in fact can be the element that makes a company successful.

他们是真的会做。我觉得在那儿学到的、让我特别意外的一件事是：product-market fit 当然重要，但我其实严重低估了 product-marketing fit——也就是「你怎么谈这个产品、怎么把它讲出去」，这件事甚至可以发生在真正把产品做出来之前。它大概应该来自两件事的结合：一是对技术的深刻理解，二是对企业销售流程的理解。而那个 product-marketing fit、那套叙事、那个定位，其实是在你做出产品体验之前就该去验证的东西。所以你应该先去跟一百个人讲一遍，把这套说法尽可能打磨到位，把「这东西为什么是颠覆性的」这个市场叙事讲对，然后——也只有到那个时候——才去敲定「产品就长这个样子」。Mike Speiser 在这门手艺上几乎无人能敌。以前我一直有点低估 PMM 的工作，觉得「无所谓吧，不就是各个职能之间的胶水嘛，还行」。后来我才意识到，这块活儿做到极致，对一家公司的结局有多大的颠覆性影响，它甚至可以成为决定一家公司成不成的那个要素。

[1:04:12] Lenny

Amazing. Uh I so agree with that positioning. We talk a lot about that on this podcast.

太棒了。关于定位这点我完全同意，我们在这档播客里聊过很多次。

[1:04:16] Tara

Mhm.

嗯哼。

[1:04:16] Lenny

Okay, I'm going to show you what uh sites got created real quick. It was running while we were talking. Check this out. Look at this.

好，我快速给你看看刚才那个 sites 生成出来的东西。我们聊天的时候它一直在跑。你看这个，看看这个。

[1:04:22] Lenny

Oh man.

天啊。

[1:04:23] Lenny

As like as like make it more awesome and it made it more awesome.

我就说了一句「把它做得更炫一点」，它还真就做得更炫了。

[1:04:27] Lenny

Multiroduct. Beautiful. Look at this. This is like legit design.

Multi-product。漂亮。你看这个，这设计是真专业。

[1:04:32] Lenny

Look at you got quotes. Big conviction. Small teams. Start with the buyer.

瞧瞧，还给你配了金句：「强信念。小团队。从买家出发。」

[1:04:37] Lenny

How do you feel about this being your website? your new website.

你觉得把这个当成你的网站怎么样？你的新官网。

[1:04:40] Tara

I do think that the picture of me at maybe 19 years old at the top is really funny. But yeah, otherwise I love love the site.

我确实觉得，顶上那张我大概 19 岁时的照片挺搞笑的。不过除此之外，我太喜欢这个网站了。

[1:04:49] Lenny

Okay, good job.

好，干得漂亮。

[1:04:49] Lenny

Looking good.

挺好看的。

[1:04:51] Tara

I think that was that's my that was my badge photo from Stripe.

我记得那张……那是我在 Stripe 的工牌照。

[1:04:54] Lenny

Oh wow. Amazing. I love that it built I already unshared it, but I love that it built a whole like little thing around your head. So cute. Uh Tara, is there anything else that you wanted to share? Anything else you want to uh touch on before we get to our very exciting lightning round? Yeah, one thing that we've been thinking about a lot in product building, especially with ChachiBT work in this new era, is how knowledge work and coding are actually fundamentally different. And one of the surprising things we learned as a part of that is that coding is so output oriented that when you um ask it to do a coding task, you can verify whether it did the task correctly or well via tests. You can try it out and see if it works. Like there is a way to validate it based on the output. But knowledge work is different in that I can't simply look at the deck in the end and see the numbers. Oh, it's like 90% success or whatever in the deck and actually believe that. I really need to think about the process and the inputs and the reasoning and how it went along the way. And so in terms of how that looks in the product, like a lot of work that we have done and have to continue to do is continue to adapt the product to knowledge work, which means way more focus on making chat GBT your collaborator, allowing you to see all the inrogress work, see its citations and inputs, help you go on the journey with the model to get to that end output such that you know in the end that oh wait, this thing is right, this thing is good, this thing is useful.

哇，太厉害了。我特别喜欢它——我已经把屏幕共享关掉了——但我特别喜欢它还围着你的头像做了个小装饰，太可爱了。呃，Tara，在我们进入超级刺激的快问快答之前，你还有什么想分享、想聊的吗？ 有。我们在做产品、尤其是在这个新纪元里做 ChatGPT 的时候，一直在反复琢磨一件事：知识工作和写代码在本质上是两回事。我们在这个过程中学到的一个挺意外的点是，写代码是高度以产出为导向的——你让它做一个编码任务，你可以用测试来验证它做得对不对、好不好，你可以跑一下看看能不能用，也就是说结果本身是可以被验证的。但知识工作不一样，我没法只看最后那份 PPT、看到里面写着「成功率 90%」之类的数字，就真的相信它。我必须去看过程、看输入、看推理，看它一路上是怎么走过来的。所以体现在产品上，我们已经做了很多、也还得继续做的事，就是把产品往知识工作的方向改造：这意味着要花大得多的力气，让 ChatGPT 成为你的协作者，让你能看到所有正在进行中的工作、看到它的引用来源和输入，陪你跟模型一起走完这段旅程、抵达最终产出，这样你在最后才会知道——哦，这个东西是对的、是好的、是有用的。

[1:06:23] Tara

And that shows up certainly in the UX of the product quite a bit, but also should show up in things like the reasoning and the chain of thought like should I should you see more citations along the way for example of how it got to that end state in that data? Um is the surface of a thread which is so suited to coding the right place for you to see all of that for knowledge work as well. There's so many big important product questions. And so as we think of um maybe bringing in human collaborators into your work, we also need to think about how we can make the model more of a collaborator with you as you get things done together.

这一点当然会大量体现在产品的 UX 上，但也应该体现在推理和 chain of thought 这类东西上——比如说，你是不是应该在过程中看到更多引用，看到它是怎么从那份数据一步步走到最终结论的？还有，thread（对话线程）这种非常适合编码场景的界面形态，对知识工作来说，是不是也是让你看到这一切的合适位置？这里面有太多重大的产品问题。所以在我们考虑把人类协作者引入你的工作流的同时，也得想清楚：怎么让模型在你把事情做成的过程中，更像一个真正的协作者。

[1:06:58] Lenny

That is such a good point. I'm imagining an exec meeting where you're trying to pitch the exec on here's what the plan is. Here's the here's what I think we should be doing. So much of that is helping them see here's the work I did to get there. here's all the steps and and so it makes sense that you need the AI to show you that same sort of uh work that it did the proof of work essentially versus engineering where like okay I don't need to know all of the little architectural decisions you made just what does it look like is it passing all the tests that we have so that is a really good point just how different those two models are um and also there's like the context does it have the context it needs to do the thing that you want it to do does it know does it can it see your email can it see all your and Ocean Docs.

这个点太到位了。我脑子里浮现出一个高管会议的画面：你要向高管推销——这就是我的计划，这就是我认为我们该做的事。这里面很大一部分，其实是帮他们看到「我是怎么一步步得出这个结论的」，把所有步骤摊开给他们看。所以完全说得通：你需要 AI 也把它做过的这些功课展示给你看，本质上就是「工作量的证明」；而工程那边就不一样了——行吧，我不需要知道你做的每一个细枝末节的架构决策，我只要知道它长什么样、有没有跑通我们所有的测试。所以这一点真的很好，这两种模式差别太大了。另外还有 context 的问题——它有没有拿到完成你交代的事所需要的 context？它知不知道、能不能看到你的邮件，能不能看到你所有的 Notion 文档？

[1:07:43] Tara

Mhm.

嗯。

[1:07:43] Lenny

Uh, such a good point. So, I see the challenge in your job. I think all this work is one product. Tricky, tricky. Uh, amazing. Anything else before we get to our very exciting lightning round?

呃，这一点太好了。所以我能理解你这份工作有多难。我觉得这些活儿最后全都要装进同一个产品里。难办，太难办了。呃，太棒了。在我们进入超级刺激的快问快答之前，还有什么要补充的吗？

[1:07:54] Tara

Yeah. Let's jump into it.

没有了，我们直接开始吧。

[1:07:55] Lenny

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

那我们就进入超级刺激的快问快答环节。我有五个问题要问你，准备好了吗？

[1:08:00] Tara

Yes.

好了。

[1:08:02] Lenny

What are two or three books that you find yourself recommending most to other people?

有哪两三本书，是你最常推荐给别人的？

[1:08:06] Tara

One book I really recommend to people is Barbarian Days by William Finnegan. I don't know if you've read it. It's about a life of a man who is a New Yorker reporter, but how he fell in love with surfing as his passion. The thing I took away from the book is that uh one can be deeply passionate and dedicated and have something be your life purpose without you being good at it. And it is about the art of like falling in love with surfing and his striving for excellence and perfection whilst knowing that he will like never reach it. It is such a compelling and transformative story for for how I think one should continue to to live our lives. I I I really really love that book. Um, another book that I might recommend as a as like a book that people should read. Um, I really love uh Anacarina. I've been rereading the classics lately and I love Anacredina because it's like a book of layers and I think that a huge part of what we're going to have to do in this new era is like transform ourselves or like take ourselves on a journey to do different things than what we were used to. And when I think about that book, I think about when I was 13 and I read it, I understood basically the plot. When I read it at like 17, I understood the European history dynamics and like the class warfare. And then when I read it at 30, I was like, "Oh, this is like a story about like a woman and uh humans." And it just reminds me of like growth and that it is possible to look at the same thing through multiple different lenses as you continue to grow. Um which I think is kind of the challenge that's ahead all of us ahead for all of us as we consider our careers as well.

我特别常推荐给别人的一本书，是 William Finnegan 写的《Barbarian Days》（《野蛮岁月》）。不知道你读过没有。它讲的是一个《纽约客》记者的一生，讲他怎么爱上冲浪、把冲浪当成自己此生的热爱。我从这本书里带走的东西是：一个人完全可以对一件事怀着极深的热情、全身心投入、把它当作人生意义，哪怕自己并不擅长它。这本书讲的就是那种「爱上冲浪」的艺术，讲他明知道自己永远达不到卓越与完美，却依然一路追求。对于我心目中「人该怎么过这一生」来说，这个故事太有感染力、也太有改变力了。我真的、真的非常爱这本书。呃，另一本我会推荐、觉得大家都该读的书——我特别喜欢《Anna Karenina》（《安娜·卡列尼娜》）。我最近在重读经典，我喜欢《安娜·卡列尼娜》是因为它是一本有很多层次的书。我觉得在这个新纪元里，我们很大一部分要做的事，就是改造自己，或者说带着自己走上一段旅程，去做一些跟以前习惯完全不同的事。而我一想到那本书就会想起：13 岁读它的时候，我基本上只读懂了情节；17 岁再读，我读懂了欧洲的历史脉络和阶级冲突；等到 30 岁再读，我才反应过来——哦，这是一个关于一个女人、关于人的故事。它一直提醒我什么叫成长：随着你不断长大，同一样东西是可以用很多不同的视角去看的。我觉得这大概也是摆在我们所有人面前的挑战，包括我们在思考自己职业的时候。

[1:09:47] Lenny

It's interesting on both these like I could connect to AI in the time we're living in now too. Uh I also read recently read an

有意思的是，这两本书我都能跟 AI、跟我们现在所处的这个时代连起来。呃，我最近也刚读了……

[1:09:54] Tara

what did you think

你觉得怎么样？

[1:09:55] Lenny

earlier this year. Amazing. I've never read it before. I saw it on a book list of like here's what the smartest people in the world have read and it's like a whole list of books and that was one that I hadn't read. So I'm like I got to read that. Yeah. Uh it was amazing. Uh someone gave away the ending which kind of made it less like surprising. I don't want to give anything away. No spoilers. Uh and I also felt like it was very long and but now I'm reading the Power Broker which is like set the set the new president for a long been reading it for half my life at this point.

就今年早些时候读的。太棒了，我以前从来没读过。我是在一份书单上看到的，就那种「全世界最聪明的人都读过什么」的书单，一长串书里就这本我没读过，我心想那我必须得读。是啊。呃，读下来太棒了。呃，有人把结局剧透给我了，所以惊喜感少了一点。我不剧透啊，绝不剧透。呃，我也确实觉得它非常长——不过我现在在读《The Power Broker》（《权力掮客》），那本才是重新定义了「长」的标准，我到现在感觉都读了半辈子了。

[1:10:23] Tara

I love the I love the Power Broker. Another thing I highly recommend to people is if if anyone follows the substack um like Simon Hazel's Substack where he does a slow read of important books. So he did one of War and Peace and he's doing one of Wolf Hall I think or he did one of Wolf Hall which is a Hillary Mantel book like take it chapter by chapter. That's like the only way to read something like the Power Broker or War of Peace or even an like chapter by chapter. Speaking of that, there's a someone I forget who told me this, there's a 99 press invisible book club breakdown of the power broker where it's 13 episodes, an hour or two each, and they go through a couple chapters of the book one at a time and talk about it and they have special guests like Petage and AOC and folks that lived in that area and they talk about every, you know, the story and it was so it's so fun to read and listen to their analysis of it and then they have Robert Carroll come on a couple times on the That's amazing.

我超爱、超爱《The Power Broker》。另一个我强烈推荐的东西是：如果有人在看 Substack 的话，比如 Simon Haisell 的 Substack，他会带着大家慢读重要的书。他做过《War and Peace》（《战争与和平》）的慢读，现在在做《Wolf Hall》（《狼厅》）——我记得是这本，或者他已经做完《狼厅》了，就是 Hilary Mantel 那本书——一章一章地读。像《The Power Broker》或者《战争与和平》这种书，也只能这么一章一章地啃。 说到这个，有个人——我忘了是谁跟我说的——99% Invisible 做过一个《The Power Broker》的拆解，一共 13 期，每期一两个小时，他们一次讲书里的几章，边讲边聊，还请了特别嘉宾，比如 Pete Buttigieg、AOC，还有在那一带生活过的人，把整个故事一点点聊透。一边读书一边听他们的分析太有意思了，而且他们还请 Robert Caro 上过好几次节目。 那太棒了。

[1:11:18] Lenny

Yeah. Hot tip. Okay, we'll keep going with our very lightning round. Uh, favorite recent movie or TV show you've really enjoyed if you've had time to watch anything.

是啊，好提示。好，我们继续快问快答。呃，最近有没有特别喜欢的电影或者剧集？如果你还有时间看东西的话。

[1:11:26] Tara

Of course, I watched The Odyssey. I found it to be an incredible incredible film. It is about AI as or my hot take is that it's about AI. Um, or Christopher Nolan's view on how AI transforms society. Um, which I I loved and I highly recommend watching the Odyssey. He is like the he's just an incredible director and has bridged artistry and commercial success in a way that I think no other modern director has like done. I also recently watched the film Rashimon which is the Akira Kurasawa film um that did for the first time did that technique of telling a story through multiple people's perspectives where you never know what was true in the end like that technique in film was pioneered by Kurasawa and it reminds me what one can do under constraints that film was made in like the 50s it was black and white that like you can you know there's a guy holding the camera and yet it is so perfect and it such a tasteful, innovative, amazing example of creativity. And what I'm reminded of watching that film is like I have a hundred times the power and tools that he had making that film in my iPhone. And like what's my excuse for not elevating my ambitions and making better stuff?

《The Odyssey》（《奥德赛》）我当然看了。我觉得那是一部非常非常了不起的电影。它讲的是 AI——或者说这是我的暴论：它讲的是 AI。呃，或者说是 Christopher Nolan 对「AI 如何改变社会」的看法。呃，我太喜欢了，强烈推荐去看《奥德赛》。他就是……他就是个了不起的导演，把艺术性和商业成功结合到了一个我觉得没有任何一位当代导演做到过的程度。我最近还看了《Rashomon》（《罗生门》），黑泽明（Akira Kurosawa）的片子。是它第一次用了那种手法——通过多个人的视角讲同一个故事，到最后你也不知道到底什么才是真的；电影里这种手法就是黑泽明开创的。它也提醒了我，人在极度受限的条件下能做出什么来：那部片子是 50 年代拍的，黑白片，摄影机是人扛着的，可它依然那么完美，是那么有品位、有创新、了不起的创造力样本。看那部片子的时候我会想：我 iPhone 里的能力和工具，是他当年拍那部片子时的一百倍。那我还有什么借口不把自己的野心抬高一点、做出更好的东西来？

[1:12:42] Lenny

All comes back ambition. Uh on the Odyssey, I'm still trying to get tickets. It's so hard. I slept on it and now it's like impossible for like a month. There's no seats anywhere.

一切又绕回野心上了。呃，说到《奥德赛》，我到现在还在抢票，太难抢了。我一开始没当回事，结果现在接下来一个月都根本抢不到，哪儿都没座。

[1:12:53] Tara

Kevin Clark got us tickets at 10 PM at the Metreion earlier this week. It was so good.

Kevin Clark 这周早些时候帮我们弄到了 Metreon 晚上十点场的票。太好看了。

[1:12:58] Lenny

Next time, call me. I'm in.

下次叫上我，我一定去。

[1:13:02] Lenny

Oh man, I have like bots running on it. I have a person working on it. I have a friend. We're try We're all trying to find a

天啊，我都放机器人去抢票了，还专门找了个人帮我盯，还托了个朋友。我们都在想办法找……

[1:13:07] Tara

It's amazing. You're going to love it and I can't wait to hear what you think after you see it. If you agree with me that it is about AI and the collapse of morality.

太棒了。你一定会喜欢的，我特别想听听你看完之后的想法，看你同不同意我的说法——它讲的是 AI，还有道德的崩塌。

[1:13:14] Lenny

Okay, no spoilers. Uh hopefully by the time this comes out, I have seen it. But if not, if anyone has hookups, please tell me. And I'm trying to do like the IMAX full power matron sort of thing. Yeah. Okay. Next question. Uh favorite or interesting AI product that you've recently discovered if ideally not OpenAI product but you know you can also go there if you want. Oo. Um, I mean, of course, my favorite AI product is JGBT and using cool sites and visualize stuff in in codecs, which is amazing. But outside of OpenAI products, um, my favorite AI products are are products that my friends make for me because now actually people can do that. I think that's so cool. I'm such a huge fan of like the cozy software movement where you like make software tools for like five of your friends and you guys use it together. And so I have a friend named Sebastian who um made a really cool uh AI app that turns anything into a podcast and puts it in your like a little podcast app for you. And he also made a really great private social network for our friends and it's called GATS. It is exactly what I think the future should be which is people should make software that exactly meets their and their friends needs.

好，别剧透。希望等这期播出的时候我已经看过了。要是还没看，谁有门路一定告诉我。我想去 IMAX，搞那种火力全开的观影体验。对。好，下一个问题。你最近发现的最喜欢、或者最有意思的 AI 产品是什么？最好不是 OpenAI 自家的，不过你要说自家的也行。哦。我是说，我最喜欢的 AI 产品当然是 ChatGPT，还有在 Codex 里做些很酷的网站、把东西可视化出来，那太棒了。但要说 OpenAI 之外，我最喜欢的 AI 产品是我朋友专门做给我用的那些——因为现在人真的做得出来了。我觉得这特别酷。我是 cozy software（小圈子自制软件）运动的铁杆粉丝：你给五个朋友做个软件工具，然后你们几个一起用。我有个朋友叫 Sebastian，他做了个特别酷的 AI 应用，能把任何东西变成播客，直接塞进你的播客 App 里。他还给我们这帮朋友做了个很棒的私人社交网络，叫 GATS。这就是我心目中未来该有的样子——人应该自己做出正好满足自己和朋友需求的软件。

[1:14:26] Lenny

What does GAT stand for? Is that some inside joke? It is not. Or at least if it is an inside joke, I don't know it, but it is the place that I It's It's like private Twitter maybe for like a a group of a small group of friends. And I I learn the most interesting things on that product.

GAT 是什么的缩写？是什么内部梗吗？不是。或者说，就算是个内部梗，我也不知道。反正它就是那个地方……有点像私人版 Twitter，给一小群朋友用的。我在那个产品上学到的东西是最有意思的。

[1:14:42] Lenny

It's like a WhatsApp, but not

有点像 WhatsApp，但又不是——

[1:14:44] Tara

Yes. Exactly. Exactly.

对。就是这样，就是这样。

[1:14:46] Lenny

Uh the podcast app is interesting, but I like I feel like the version that I would love is it's actual like podcast in your feed of podcasts and then just new episodes get added of things you want to read or whatever. Yeah, that's what it does.

那个播客 App 挺有意思的，不过我理想中的版本是——它真的就出现在你的播客订阅列表里，然后你想读的东西会自动变成新一集加进来。对，它就是这么干的。

[1:14:58] Tara

It's a It drops it in your Apple podcast feeder. You watch.

它会直接丢进你的 Apple Podcasts 订阅源里。你就等着看吧。

[1:15:01] Lenny

Amazing. I want this. It's great. How do I help me? Help me subscribe to this.

太棒了。我要这个。真好。我怎么才能——帮帮我，帮我订上。

[1:15:05] Tara

For sure.

没问题。

[1:15:05] Lenny

Okay. Amazing. Okay. Two more questions. Do you have a favorite life motto that you find yourself coming back to often in work or in life?

好，太棒了。好，还剩两个问题。你有没有什么人生座右铭，是你在工作或生活里经常回头去想的？

[1:15:13] Tara

My life motto that I come back to all the time in work is actually Tony Morrison's three takes on work. Let me like pull it up really quickly.

我在工作里一直会回头去想的座右铭，其实是 Toni Morrison 关于工作的三条。我很快把它翻出来。

[1:15:20] Lenny

Amazing.

太好了。

[1:15:21] Tara

Um, okay. It's four things. It's from her essay, the work you do, the person you are. The first one is whatever the work is, do it well. Not for the boss but for yourself. The second is you make the job. It doesn't make you. The third is your real life is with your family. And the fourth is you are not the work you do, you are the person that you are.

嗯，好，其实是四条。出自她那篇文章《The Work You Do, The Person You Are》。第一条：不管是什么活儿，都把它做好——不是为了老板，是为了你自己。第二条：是你成就了这份工作，不是这份工作成就你。第三条：你真正的生活是和家人在一起。第四条：你不等于你做的工作，你就是你这个人。

[1:15:45] Lenny

I got tingles.

我起鸡皮疙瘩了。

[1:15:48] Lenny

Wow. So good. And I think that's what you have pinned to your um your Twitter profile. Yes. because I I remember seeing that.

哇。太好了。我记得这段就是你置顶在 Twitter 个人页上的那个吧。是的。因为我记得看到过。

[1:15:54] Lenny

So cool. Okay. Uh maybe we'll show that on the screen as you're talking about that. I love that.

太酷了。好。也许可以在你讲这段的时候把它放到屏幕上。我太喜欢这个了。

[1:15:58] Lenny

Uh I love that's a great way to remember something. Just stick it to the top of your Twitter because it every time I go to Twitter. Oh, there it is again.

我特别喜欢这招——这是记住一件事的绝妙办法，直接钉在你 Twitter 顶上。因为我每次打开 Twitter：哦，又看到它了。

[1:16:04] Tara

Mhm.

嗯哼。

[1:16:04] Lenny

Uh okay. Final question. Uh you were a Theel fellow back in the day. Teal fellow. Teal or Theel? Teal. Teal. Yeah.

好，最后一个问题。你当年是 Thiel Fellow。Thiel Fellow。念「Theel」还是「Teal」？「Teal」。「Teal」，对。

[1:16:12] Lenny

What an alumni group. Holy moly. Just like so. It's such a great idea and program. uh any story from that time that might be fun to share something that's like oh wow that was crazy

那批校友阵容也太夸张了，天呐。就是说……这真是个特别棒的点子和项目。那段时间有没有什么好玩的故事可以分享？那种「哇，这也太疯了」的。

[1:16:23] Lenny

I don't know any other teal fellow that you're proud of any other what was the interview like I don't know anything along those lines

我也不知道——比如有哪个 Thiel Fellow 是你特别欣赏的，或者面试是什么样的，我也说不好，反正这类都行。

[1:16:30] Tara

yeah I the teal fellowship was an inflection point in my life I wouldn't be where I am without it maybe to the point of like there are key moments where you can tell people to elevate their ambitions and they do and that changes them like that was a moment where someone came to me and elevated my ambitions and said no you can do this you don't have to, you know, take the path that you were on. And truly, I'm eternally grateful for for them being able to do that. One of the teal fellows that I get to work with all the time now is Ari Weinstein, who uh founded a company called Sky that was acquired by OpenAI. Um, and prior to this, he founded um and worked at Apple for a while because they acquired his previous company. Ari is just one of the most creative thinkers I've ever seen and is truly the expert on what are all the cool things you can do on a Mac. Um, and so Ari leads a lot of our computer use stuff at OpenAI and he's like shipped a whole bunch of great things for for computer use. But yeah, his his creativity and his like joy in what he does and his love of his craft really inspires me and like Ari's a cool guy. Um, but I'm trying to think what it's like a good story from that time that feels uh

嗯，Thiel Fellowship 是我人生的一个拐点，没有它我不会走到今天。甚至可以说，人生有一些关键时刻，有人来把你的野心往上抬一格，你就真的抬上去了，而那会改变你这个人。那对我来说就是这样一个时刻——有人来跟我说：不，你能做到，你不用非得走你原来那条路。说真的，我永远感激他们做了这件事。现在我天天一起共事的 Thiel Fellow 之一是 Ari Weinstein，他创立了一家叫 Sky 的公司，被 OpenAI 收购了。在这之前，他还创过一家公司被 Apple 收购，之后在 Apple 待了一段时间。Ari 是我见过最有创造力的思考者之一，而且是「Mac 上到底能玩出什么花样」这件事的真正专家。所以他在 OpenAI 主要带 computer use 这一块，已经在 computer use 上做出了一堆很棒的东西。他的创造力、他做事时那种快乐、他对手艺的热爱，都特别激励我，Ari 真的是个很酷的人。嗯，我在想那段时间有什么好故事，那种……

[1:17:44] Lenny

as you think about it, I'll explain the Teal Fellowship for people that don't know this and correct me if I'm wrong. Basically, Peter Teal is like, "Hey, people shouldn't go to college. Instead, they should just try building something that they want and and you get $100,000 to not do college and instead just go follow your ambition." Is that roughly correct?

你想的时候，我先给不了解的听众解释一下 Thiel Fellowship，说错了你纠正我。大意就是 Peter Thiel 说：「嘿，人不该去上大学，应该直接去做点自己真正想做的东西。」然后给你十万美元，让你别念大学，去追你的野心。大概是这样吧？

[1:18:04] Tara

Yeah, that is that is exactly right. Um, and you're with 19 other people at the time. It was like 20 people every year because it's 20 under 20.

对，完全正确。而且同一批还有另外 19 个人。当时是每年 20 个，因为叫「20 under 20」（20 个 20 岁以下的人）。

[1:18:11] Lenny

And

还有——

[1:18:11] Lenny

how many years did it go on for? Is it still

它办了多少年？现在还在——

[1:18:13] Tara

I think it's still going, but I think it was like that constrained at the 20 number for like the first four or five years or something like that.

我觉得现在还在办，不过我印象里只有头四五年是卡在 20 人这个数上的。

[1:18:20] Tara

Um, yeah. I think a really crazy thing that happened my year is that I was the second every year of the fellowship. They decided to make it all a documentary on CNBC. And so our whole uh my pitch for the fellowship uh getting up on stage and presenting the idea I was going to do, all of that is unfortunately live on YouTube. So if you really want to see me as a 19-year-old doing something embarrassing, it's there. Um, of course, one of the most amazing and successful people who came out of that batch of the fellowship is Dylan Field, who is not only a incredible talent, but also like a very kind person. Um, and yeah, feel very lucky to to be able to work with those folks.

嗯，对。我们那年有件挺疯狂的事：我是第二届——他们决定把那一届 fellowship 整个拍成 CNBC 的纪录片。所以我为 fellowship 做的那场 pitch、上台讲我打算做的那个想法，全都很不幸地一直挂在 YouTube 上。所以你要是真想看 19 岁的我干点丢人的事，那儿有。当然，从那一届 fellowship 里出来的最了不起、最成功的人之一是 Dylan Field，他不光才华惊人，人还特别好。嗯，对，能和这些人共事，我觉得非常幸运。

[1:19:03] Lenny

Amazing. Yeah, it's interesting that Dylan's like the guy I think everyone thinks of when they think of Teal Fillers.

太棒了。对，有意思的是，大家一提 Thiel Fellow，第一个想到的好像就是 Dylan。

[1:19:08] Tara

Yeah. Yeah.

对。对。

[1:19:08] Lenny

What a what a brand. Okay, Tara, this was incredible. Uh, is there anything you want to plug? Anything you want to point people to? And how can listeners be useful to you?

这品牌力，绝了。好，Tara，这期太精彩了。你有什么想推荐、想让大家去看的吗？听众可以怎么帮到你？

[1:19:18] Tara

Anything I want to plug and point people to? Maybe they should use the chatbt desktop app. Um, they should use chatbt in the web and try work. It's like unfortunately a little toggle. Um they can toggle over to it and try out work. Ask it to do some cool thing. Ask it to build a site about you. Um maybe to start or ask it to make a little visualize uh block of your chat GBT usage. It's a really cool way to start like experiencing the power of this stuff very intimately. And the list of use cases they can do from that, you know, are infinite. And I'm happy.

有什么想推荐、想让大家去看看的吗？我觉得大家可以用一下 ChatGPT 的桌面端。也可以在网页上打开 ChatGPT，试试 work。可惜它现在藏在一个小开关里，你把开关切过去就能用 work 了。让它做点好玩的事，比如让它给你做一个介绍你自己的网站。或者一上来先让它把你自己的 ChatGPT 使用情况做成一个可视化的小卡片。这是特别好的上手方式，能让你非常真切地感受到这东西的威力。从这儿出发能玩出的用例是无穷无尽的。我挺开心的。

[1:19:53] Lenny

Here's a better idea. Here's a better idea. Ask Ask it to build a site to tell you what you could do with work.

我有个更好的主意。我有个更好的主意——让它做个网站，告诉你用 work 都能干些什么。

[1:19:58] Tara

Great.

太好了。

[1:20:00] Tara

That will that will work.

这个这个能行。

[1:20:02] Lenny

Solve all the problems. Okay. I interrupted you. I apologize. Uh what else were you gonna add or say?

一举解决所有问题。好，我刚打断你了，抱歉。你本来还想补充点什么？

[1:20:08] Tara

Yeah, my main plug is yeah, go download the THB app. Go use it on web. Even more transformatively, go try it on mobile. Then take like a long subway ride or something like that or a MUN ride. And when you pop out after having no service, the thing is done for you. That's the part that feels super duper magical. You're not like wandering around with your laptop open the entire time. You've finally got these things running in the cloud doing real work.

对，我主要想安利的就是：去下载 ChatGPT 的 app，在网页上用起来。更有颠覆感的是，去手机上试试。然后你去坐一趟长途地铁，或者坐个 MUNI。等你从没信号的地方钻出来，事情已经替你办完了。这一下是最神奇的地方。你不用全程抱着打开的笔记本电脑到处跑，终于有这么些东西在云端跑着、替你干真正的活儿。

[1:20:31] Lenny

Yeah, that last piece I was going to bring up, but that's I think a really underappreciated element of the product today on mobile and it's most that's just a mobile only feature. The cloud piece.

对，最后这一点我本来也想提，我觉得这是今天这个产品在手机端特别被低估的一块，而且这差不多算是手机端独有的功能——就是跑在云上这件事。

[1:20:42] Tara

No, it's everywhere.

不，哪儿都能用。

[1:20:43] Lenny

It's everywhere. Okay. So amazing. So on your mobile app, you can go to JBT, toggle work, ask it to do some work, and you don't need to actually have the it's not running locally. It's running in the cloud. It'll go keep doing work until it's done, and then you could chat to it. So like that feels like really simple, but that's a massively powerful thing. Okay. Uh anything else, Tara, before we let you go?

哪儿都能用。好。那太厉害了。所以在手机 app 上，你打开 ChatGPT，把 work 的开关切上，让它去干点活，你其实不需要……它不是在本地跑，是在云端跑。它会一直干到干完为止，然后你再跟它对话。这听上去特别简单，但其实是件威力巨大的事。好，Tara，在我们放你走之前，还有别的想说的吗？

[1:21:07] Tara

No, that's it.

没有了，就这些。

[1:21:08] Lenny

Okay. Thanks,

好。谢谢，

[1:21:09] Lenny

this was awesome. Thank you so much for doing this.

这期太棒了。非常感谢你来做这期节目。

[1:21:11] Tara

Such a pleasure.

我也特别开心。

[1:21:11] Lenny

Uh what a journey since the fellowship back in back in the day. I'll talk about that more in the intro.

从当年那个 fellowship 到今天，这一路走得可真不容易啊。这个我会在开头的介绍里再多讲讲。

[1:21:16] Tara

Yeah.

是啊。

[1:21:16] Lenny

Uh, all right. Well, thanks for being here.

好，那就这样。谢谢你来。

[1:21:18] Tara

Thank you.

谢谢。

[1:21:19] 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. [music] 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 或者你常用的播客 app 上订阅本节目。也请考虑给我们打个分或者留条评论，这对其他听众发现这档播客真的很有帮助。（音乐）所有往期节目、以及关于本节目的更多信息，都可以在 lennyspodcast.com 上找到。我们下期见。