AI 的第三纪元：持久同事，而不是更长的对话

主持人 If you think about the first era of AI products as chat, the second era of these products working with 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. There's this idea of the overhang of what AI is capable of and what we're actually doing with it. So hard to understand what is going to emerge in the future. You fail if you build for where the models are now. Tara：如果你把 AI 产品的第一个时代看作是 chat，第二个时代是和 agents 一起工作，那么可能很快到来的第三个时代，就是你如何与一个能和你一起把事情做完的 persistent co-worker 共事。主持人：这里有一个 overhang 的概念：AI 真正能做到什么，和我们实际在用它做什么，两者之间是有落差的。 Tara：很难判断未来会出现什么。

You fail if you build for where you think the models will be in a year. Both outcomes are equally wrong. Only way to build is 2 to 3 months. What if you had to most adapt to and adjust in how you operate as a PM in this world? 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 as fast as possible. 如果你按模型现在的能力去构建，你会失败现在这样构建，你会失败。如果你按你认为模型一年后会达到的水平去构建，你也会失败。两种结果同样错。唯一的构建方式是按两到三个月来。主持人：作为 PM，在这个世界里，你最需要适应和调整的工作方式是什么？ Tara：多产、empirical，远比 academic 或 theoretical 更重要，而不是先写一份很长的 reasoning doc。

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. Elevating others ambitions or reminding them of what's possible here is a huge part of the product management role. I'm curious what's most surprised you about what it's actually like to work at OpenAI. I came into the company expecting that there was a treasure trove of OpenAI secret strategy and actually OpenAI is open. 相反，问题是：我怎样尽快做出一个能拿去和用户试用、测试的东西。感觉我们不仅能够更有野心，我们几乎必须更有野心，而这对外很多人来说并不自然。主持人：把别人的野心拉高，或者提醒他们这里什么是可能的，这是 product management 角色里很大一块。主持人：我很好奇，真正在 OpenAI 工作，最让你意外的是什么。

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. Tara：我进公司时以为会有一座 OpenAI 秘密策略宝库，结果 OpenAI 其实是 open 的。主持人：今天的嘉宾是 Tara Seshan。 Tara 负责OpenAI 的 Codex 和 ChatGPT Work 产品。

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. 我认为这是目前增长最快、对 knowledge workers 来说 arguably 也最重要的 AI 产品。 Tara 和 Andrew Ambrosino 一起工作，Andrew 最近刚上过这档播客。

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. 他是她的 engineering manager。加入 OpenAI 之前，Tara 在 Stripe 待了六年，当时她是最早的五位 product managers 之一；在那几年里，她多次被评为整个 Stripe 组织里 top three Stripes 之一。

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. Thank you, Lenny. I'm so glad to be here. It's so nice to see you. I'm even more glad. 她还曾负责Watershed 的产品，做过 founder，也是 Thiel Fellow。最重要的是，Tara 还是三位 Lenny's Newsletter Fellows 之一。那是我几年前办的一个项目，用来突出一些最出色的、正在崛起的 product leaders。

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. Yes. 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. 看到 Tara 走到这个极其重要、影响很大的新角色，我非常兴奋。开始之前，别忘了去 lennysproduct.com 看一看：那里有一整年最热、做得最精美的 AI 产品，免费提供，仅限 Lenny's newsletter 订阅者。接下来，有请 Tara Seshan。 Tara，非常感谢你来，欢迎来到这档播客。

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. Tara：谢谢你，Lenny。我很高兴能来。见到你真好。主持人：我更高兴。你在 OpenAI 大概刚满一年。在大多数地方，这会显得很短。按 AI 的时间尺度，这几乎是一辈子。

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. Tara：是的。主持人：我想象你加入 OpenAI 时，你对在 Frontier Lab 工作会是什么样子，心里已经有个感觉。我很好奇，真正在 OpenAI 工作，最让你意外的是什么，最好好的和不好的都说说。 Tara：在 OpenAI 工作的很多事情，对我来说其实很熟悉，因为我以前也在那种高增长、高人才密度、高强度、hyperscaling 状态的地方待过。所以有些感觉，比如同事们特别厉害，或者urgency 非常高，都觉得很熟悉。

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. 真正最让我意外的是：我以前待过的很多公司，其实是我待过的所有公司，都是 founder-led；而 OpenAI 其实是 founders-led。意思是，公司里的每个人，尤其在自己负责的领域，本质上都有点像 founder。那种自上而下的方向，在 OpenAI 比我以前待过的地方少得多。所以我刚到公司时，这既让人高兴，也因为我自己以前走过 founding 的路，我会想：好，我可以继续觉得自己是这个产品方向、这个团队的 founder。

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 operations and actually open AAI is open 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. 我和市场之间的距离非常非常薄。有时候在更大的公司，你会觉得自己被隔开了，听不到用户要什么，也感觉不到市场在要求什么；但在 OpenAI，完全不是这样。你要像 founder 那样，做一切该做的事，去给你的产品找到 product-market fit。但反过来，或者说更让人意外的一面是：我进公司时以为会有一座OpenAI 秘密策略宝库，我能像在以前的公司那样理解它。你一进去就会觉得：啊对，这就是 payments bible，这就是我们怎么看 payments 和 operations。结果 OpenAI 是 open 的（笑）。

And so that to me was incredibly um both positively surprising and just like a change in my operating mode for sure telling us there's not like the secret room with the AGI running there with the master plan that has all the answers or at least I'm not in that room for sure. 任何关于世界应该是什么样、产品应该怎么建、模型应该怎么运转的想法，都会很快变成公开产品的一部分，或者公开对外表述的一部分。所以这对我来说既是非常正向的意外，也确实改变了我的工作方式。

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. 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. 主持人：你是在说，并没有一间密室，里面跑着 AGI，还有一份写着全部答案的 master plan。 Tara：或者至少我不在那间房间里，这是肯定的。但真正让我受到启发的是：OpenAI 做的很多东西，会立刻变成用户能在产品里摸到、感受到的东西，而且这个循环比我见过的任何地方都更快。主持人：本期由本季 presenting sponsor WorkOS 赞助。

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. OpenAI、Anthropic、Cursor、Replit、Sierra、Clay，以及另外几百家成功公司，有什么共同点？它们都由 WorkOS 提供支撑。如果你在做面向 enterprise 的产品，你一定感受过接入 single sign-on、SCIM、RBAC、audit logs，以及其他大公司会要求的功能有多痛苦。

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. WorkOS 把这些成交阻碍变成可直接接入的 APIs，并提供专为 B2B SaaS 打造的现代 developer platform。说真的，我投资的每一家开始向上市场扩张的创业公司，最后都会和 WorkOS 合作。因为他们就是最好的。无论你是想拿下第一家 enterprise 客户的种子轮创业公司，还是正在全球扩张的独角兽，WorkOS 都是最快变成 enterprise ready、打通增长阻碍的路径。

主持人 Go to works.com to make your app enterprise ready today. You've been a PM at a lot of different places, a longtime PM leader. What do you lose in this new world? 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. 它本质上就是 enterprise 功能里的 Stripe。去 workos.com 开始使用，或者直接去他们的 Slack，那里有真正的工程师在等着回答你的问题。 WorkOS 让你能用令人愉快的 APIs 更快地构建，文档完整，developer experience 也很顺。

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. 现在就去 workos.com，让你的应用变成 enterprise ready。主持人：你在很多不同地方做过 PM，也是长期的 PM leader。在这个新世界里，你会失去什么？ Tara：当市场更静态、变化更慢时，你有机会去做那种偏 grand strategy 的工作，因为更可预测，或者你至少能把各个部分都看清楚。

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. 举例来说，payments 在某种程度上当然是动态市场，但它也是一个已经成型的市场。你可以说：好，如果我下这个注，竞争对手可能会下那个注；或者从 first principles 非常严谨地推演接下来所有可能的动作。事实上，那个市场的性质要求你必须这么做：赢家会比所有人想得更严谨。如果你想得不够严谨，就会显得有些草率，因为你做过的很多决定本来是可以预见到的。

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. 但在这个市场里，很难判断未来会出现什么。它非常 emergent，变化非常快，非常动态。最重要的是，必须紧紧贴着 research。

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? 所以实际上，多产、更 empirical，远比那种更academic 或 theoretical 的方式重要。我以前待过的很多公司，都非常 academic、非常 theoretical。真正的转变是：不再写出一份很长的 reasoning doc，几乎像一篇关于未来一段时间计划的 PhD thesis；而是：我怎样尽快做出一个能拿去和用户试用、测试的东西。

Like shouldn't I be like thinking through all of this in a ton of rigor? But actually you got to try stuff and learn as much as possible. And what that means is the 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. 所以，从 theoretical 转到empirical，一开始非常刺耳。我会想：我是不是没有做足 due diligence？是不是想得不够周到？难道我不该把这一切都想得极其严谨吗？但实际上，你必须去试，尽可能多地学习。这意味着你需要做的思考，是尽可能尖锐地抓住你的核心 hypothesis。 hypothesis 的定义才是最重要的事。

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. 真正的问题是，用Shishir Mehrotra 的话说，什么是 eigenquestion。那个最具体、最需要测试的关键点是什么；其他所有你编出来的 grand strategy，都无关紧要。主持人：我想多听你讲讲这个，因为这很有意思：它几乎像是 PM 角色里没有在变的那一块。那么多东西在变，世界在变，但这块反而更重要了。再具体说说，你觉得人们更需要把注意力放在什么上。

Tara Sash 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? Tara：是的。 PM 角色周围有太多 trappings，比如保证执行按时完成、写各种特定的 docs 和 presentations 等等。但核心一直是：关于你的产品，你必须问的那个最本质的问题是什么？什么会决定你的产品成不成立？你怎么测试它？你怎么看结果？

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. 你又怎么把结果喂回这个循环，去 refine 你的 hypothesis，然后再跑一轮？那才真正一直是 PM 的工作。这当然包括试着理解用户、理解市场、理解你正在构建的技术，把这三件事拉到一起，做出你能做出的最锋利的 hypothesis，然后让测试尽可能快、尽可能有效。我认为这一点不仅没有变，而且已经变成公司里最重要的能力。

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. EMs 在这样想，工程师在这样想，data scientists 在这样想，设计师也在这样想。所有人都把精力集中到这个非常重要的 problem definition 和 testing loop 上：我们到底在做什么，我们怎么知道它有没有用。

Like everyone is sort of moved to focus their efforts on this 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. 从 PM 的角度看，这很好，因为 PMs 一直非常专注于把这些事情做对。这一直是这份工作的核心；而工作里其他那些 trappings 已经脱落了，留下来的，就是每次都必须做对的那一件关键事。

Tara Sash 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 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. 主持人：你提到了 loop 这个概念。最近大家谈得很多，loops 在 Twitter 上几周前特别热，而且对更广义的 knowledge work 来说，它好像还在被继续讨论。按我的理解，一个 loop 本质上是： AI，成功长什么样，你去构建、去搞清楚，直到你达到这个成功。你怎么看 loops 从 software engineering 扩展到 product management、扩展到所有 knowledge work？

Do you think that's going to be a thing? 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. 你觉得这会成为现实吗？ Tara：我确实认为，未来的工作会越来越像 steering，而不是 rowing。意思是，会有 agents，你能和它们一起工作，它们做大量的 rowing；你的角色越来越变成把船舵向正确的方向，指向正确的方向。

And to that point, I think that that steering might grow 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. 说到这一点，我认为这种 steering 可能会升到越来越高的层次。以前的 steering 是：我写了这一行代码，按 tab；哦等等，现在我在指挥一件更完整的事；也许到 goal 这一层，也许到更高一层。我认为 steering 会继续往上走，穿过一层层 abstraction。但归根结底，仍然需要一个人去判断：我们要把这件事指向哪个方向；有了反馈和额外数据之后，我下一步想把它带到哪里。 steering 的一部分当然来自数据告诉你什么，但很大一部分是做出一个有立场的判断。

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. 我觉得我们有时低估了那种intuition 的力量，甚至那种正向的 determinism：我们想要未来长什么样。比如想象：我希望产品是这个样子，不是因为反方向就不是同样可行的策略，而是因为我希望世界朝我正在推动的那个方向走。我认为，至少现在，这仍然需要来自一个人的意见。

And that I think will always remain 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 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. 所以我觉得 loops 很棒。让 agents 在越来越大的 loops 里运行，替你做越来越多的 rowing，这很好；但现在你仍然真的需要去 steer。

And I think work will also look like steering with other people over a group of agents that you guys work with together. 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. That's such an interesting way of describing it. There's also like there's two thoughts here that come up. 我认为工作也会变成：你和其他人一起，共同 steering 你们一起使用的那一组 agents。把其他队友拉进你和 agent 的互动里，agent 在 rowing，你在steering，这同样极其有价值。主持人：这个说法很有意思。我这里冒出两个想法。一个是：如果每个人都能用到同样的工具，把你们区分开的就会是人本身。

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. 否则我们都会做出同样的东西。你可以问、每个人都可以问：我们怎么赢？我们该做什么？然后几乎不公平的优势，几乎就是人脑。 Tara：是的。这让我很想起fashion。在某些方面很像。当然有功能性的衣服，人人都能穿，也能把事办了；但你穿什么，至少我怎么想自己穿什么，很大程度是关于我想对个性做什么陈述，或者我想向世界反射出什么。

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. 让它有说服力的很大一部分，是它和其他人的表达形成对比。比如我做的这件衬衫之所以能构成一个陈述，只是因为它也许和所有其他人正在做的不一样，或和某一群人正在做的不一样，或者它在陈述我的群体归属之类的东西。

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. 我认为我们构建的很多产品，同样带着立场，也带着艺术性。 Patrick Collison 有一句很好的话，也许是 John Collison 说的，关于 software：software 不像 real estate。

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. 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. 你不是把钱投进去，价值就出来。它更像拍电影：你可以往一部电影里投很多钱，但那并不能保证电影成功或好看。里面有某种 auteur 的陈述，有立场，也有 artistry。我认为这依赖于你、或者你的团队，对产品有话可说，而且说得有意思。

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. Marty Cagan 很强调一个观点：当你有一个产品或功能的 idea 时，那个 idea 很少会原样变成最终的东西。中间有一整套过程，你得走过去，才能搞清楚它到底应该是什么。感觉你现在说的也是这个：你需要作为人去走完那个过程，才能理解它真正是什么、人们真正想要什么。从来不会是：好，懂了，去把这个做出来，我从一开始就全清楚了。

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." Yeah. For sure. For sure. And that loop, those loops are moving faster and faster and faster. Tara：对，当然，当然。而且那些 loops 转得越来越快。所以你形成这些 intuitions 的能力，拿到形成这些 intuitions 所需信息的能力，然后和人以及 agents 一起把它付诸行动，这才是关键。主持人：我很好奇，你觉得 knowledge workers 更广义的工作方式，下一次转变会是什么。

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. 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. 感觉你不仅能用到别人还没有的最先进工具，而且周围都是世界上最 AI-pilled、最 AI-forward 的人。你们内部现在怎么工作，你觉得会在接下来不知道，三到六个月里，变成我们大家更平常的工作方式？ Tara：是的，我觉得这里有两个方面。一个是继续在越来越高的 abstraction 层次上和 agents 工作。

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? 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. 让 agent 越来越独立地替你做更多事，你进来提供 steering，然后继续让 agent cook。

Tara Sash 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. 让 agent cook，并在更高阶的 abstraction 上提供细节，感觉就是人们越来越会这样看待 agents：它们是 persistent 的，像队友，像同事。你可以像和团队里的人一起工作那样和它们工作：他们做一大堆工作，我提供输入，然后他们再做，我们按不同 cadence 同步，看彼此进行中的工作，再给出更多反馈。感觉这种 co-worker 模型就是事情正在走的方向，也感觉是一种自然得多的界面，。让我们能和 agents 一起工作。我们内部已经看到很多这样的情况。

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. 第二点是：到目前为止，我很多和 agents 的工作都是一对一的，是我和我的 agent。也许它 spawn 了一些 sub-agents 去完成任务，但仍然是我和我的 agent。而这可能和我的同事们跟他们的 agents 在做什么是分开的。

And that is potentially divorced from what my colleagues are doing with their agents. 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. 所以有一段时间，内部所有人都只是把自己的Codex threads、Codex threads 的截图发到 Slack 上给彼此看。我们会说：好，我想告诉你我是怎么得到这个数字的，这是我怎么得到的，这是我做了什么的截图。但这对人们一起协作来说，也不是最自然的方式。所以，随着越来越多的工作是和我们的 agents 一起完成的，我们难道不该能和我们的 agents 一起把工作做完吗？

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. 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. 让这件事发生的最自然界面是什么？这些就是我们正在思考的问题。主持人：我脑子里出现的是 chat。这太说得通了。就像：这是 Tara 的 agent，这是我的 agent。她做了一些分析。我会说：嘿，我的 agent，Lenny 的 agent，去核对一下，确保这是靠谱的，并且能接到我看世界的方式上。

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. 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. Tara：理想情况下，工作会像一款多人游戏：我们所有人一起把事情做完，steering 我们的 agents，而 agents 继续承担越来越多那些 rowing 式的战术任务。

主持人 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. 主持人：有意思的是，这只是信任和意识的缓慢推进：原来我们可以这样工作。就是：好，去工作更久一点，你可以承担更多。大家一直在谈 slow takeoff、fast takeoff 这些情景，所有人都害怕那种 fast AI takeoff：它聪明得过头，然后我们就有大麻烦了。

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,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. 感觉我们非常像处在 slow takeoff 情景里，这是好事，就是在慢慢迭代。虽然也并不觉得那么慢，但某种意义上，你知道，我们并不是面对一个 300 IQ 的 AI，你知道。 Tara：我的意思是，模型已经极其聪明了。但我认为，很多让我们能和 agents 一起工作、或者让 agents 处理越来越高阶 abstraction 事情成为可能的，当然包括智能、它们执行长任务的能力、以及它们能在任务上待多久；但实际上也有很多非常肉土豆式的战术事情，让这一切成为可能，比如。 agents 在本地工作非常方便，因为它们能访问你机器上的所有数据。

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. 要让一个 agent 在云端成功，你必须构建大量 cloud infrastructure 才可能做到。还有对你各个系统的访问：agents 怎么和所有这些装着你数据的第三方系统说话。就像你雇来一个同事，却把他锁在房间里，永远不给他 Google Docs、Slack，还有，我不知道，公司数据库的权限，那他对你就不会那么有用。

Similarly, like a cloud agent that is similarly isolated will not be that effective. And so a huge part of making these agents useful and achieving some of these futures 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. 同样，一个被同样隔离起来的 cloud agent 也不会那么有效。所以，让这些 agents 真正有用、真正实现其中一些未来，很大一部分当然在智能这边；但很多也只是非常战术的事情，比如 data access、cloud infrastructure 和 reliability。

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. 它们感觉比那些更宏大的智能问题平凡得多，但对最终有效性来说，在某些方面同样重要。主持人：这碰到了这档播客里反复出现的另一个词：ambition。我知道你也想得很多。感觉因为这些 AI 工具，我们不仅能够更有野心，我们几乎必须更有野心，而这对外很多人来说并不自然。因为现在所有人都能非常轻松地做完那些容易的事。容易的事情超级容易。难的事情也变容易了。

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. 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. 现在把人和公司区分开的，就是他们能有多野心。说说当我谈到这种对 ambition 的需要、以及这种需要正在出现时，你想到什么。 Tara：是的。我们看到最会用 AI 工具的人，不只是用它去自动化那些 rote tasks，而是用它去扩大自己能做的事情集合。

主持人 Like back in the day, you know, 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. 以前，你知道，在所有这些 AI出现之前，那种 unicorn 是：一个 product sense 非常强、想得很深的人，同时又碰巧是工程师，也许还是设计师。

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. 那种人一直是 unicorn hire，因为他们能把这些职能之间需要翻译的层压得很薄，能自己很快、很容易地构建或构思出东西，把它跑起来，然后还能。和团队一起协作。我认为这些工具最有说服力的一点，也是我自己努力想做到、也看到一些最成功的同事能做到的，就是真正扩大那些所谓“在自己可能性范围内”的事情，好让他们能把脑子里越来越多的东西变成现实，就像以前那种。

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. jack of all trades 能做到的那样。某种程度上我们现在都有了这种超能力：我可以很快做出一组设计，可以去做一个初始 prototype，可以搞清楚合适的定价模型，把各种情景都 model 出来。可能性的集合被极大地拓宽了。

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. like really the set of possibilities have widened dramatically. 这在很多方面意味着，我更有能力，像前面说电影那样，在把事情做成时更像一个 auteur，把我的愿景实现到更高的保真度。对我来说，这就是在追求新 ideas、新产品时，能把你的野心拉高的一部分。

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. 因为所有这些事情现在都够得着了，因为这套新能力现在都在你够得着、可以去试、可以去用的范围内。你不再那么受限。你的野心不再受限于你自己能执行什么、你能沟通什么。它可以宽得多、宽得多。我认为做这件事最难的部分，只是把你的思考打开。实际上能力已经扩大得非常剧烈；真正难的是，在短得不合理的时间里，把你对“什么是可能的”的思考打开。

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. 对我来说，最好的尝试方式是：Patrick Collison 的网站 patrickcollison.com/fast，我想是这个，上面列了所有这些野心不合理、却在非常短的时间里被执行出来的项目。现在让我觉得那份项目清单格外惊人的是：它们都出现在这些工具让你几乎能立刻学会怎么构建东西、或者用一个问题就能问它之前。

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. 嘿，你能立刻帮我总结这篇非常复杂的文本、或者这本非常复杂的书吗？或者我能试着去做所有这些以前对我来说不可能、现在却能做的事吗？比如，你能按我脑子里的这个 idea，给我做一个 CAD model 吗？

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? 真的那些以前完全够不着的能力，现在都在我够得着的范围内。所以，如果那些 fast projects 在我们以前拥有的能力下就已经可能，那有了 AI 给我们的这些东西，我们难道不该看到那种执行得快得不合理、又有效的事情，数量出现指数级增加吗？

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 unreasonably quickly and effectively executed things um with what AI has given us? 主持人：说到你的点，最难的部分只是记得去试一下：哦对，让我看看 Codex 能不能帮我做这个。这只是一个新习惯，一件我们必须在脑子里建立起来的新东西。 Tyler Cowen 在他的网站上有一句话：大多数人低估了走到别人面前说这些话的影响——嘿，你正在做的事情，更有野心的版本会是什么？你能不能试得更快？你能不能按大十倍的规模去试？

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. 在某些方面，当我再想到 PMs 现在怎样做会极其有效，或者他们现在能做的什么会极其有效，我认为把别人的野心拉高，或者提醒他们这里什么是可能的，这是 product management 角色里很大一块。

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? 当人们说：嘿，我觉得我们可以用这种方式做完，或者我们可以在这个时间线上做完，或者也许这是它的第一个版本。你现在工作的一部分，就是把每个人的野心拉高，说：实际上，可能性的天花板是不是明显更高？我们难道不该对正在尝试的事情更有野心吗？或者，我们难道不能试得更快吗？我觉得这是一个，对，这是一个很好的位置可以处在。就你能构建什么、什么是可能的，以及这份工作变得有多令人兴奋而言，这都是一个很好的位置。主持人：这太有意思了。我记得 Nick Turley 上过这档播客，也许他之前做过你这个角色。我想他现在在做 enterprise 相关的事。他内部有一个 meme：is this maximally accelerated？

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. 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? Tara：是的。主持人：Slack 里好像还有一个 emoji。 Is this maximally accelerated？ Tara：Is this maximally accelerated？这完全是一个 OpenAI meme。另一个 OpenAI meme，Andrew Ambrosino 和我很喜欢问团队的是：are you mainlining it yet？

Yes,there's like an emoji I think inside the Slack. Is this maximally accelerated? 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. 意思是，你是不是整天、每天都在用这个产品把你的事情做完。我认为它和“我们是不是尽可能有野心”——这关乎你尝试的事情的 scope 和 scale——合在一起。 Is this maximally accelerated？我们是不是在这件事上尽可能快地推进？

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 just have to spread as much as possible now. 然后，are you mainlining it yet？你在用它吗？你有没有把你全部的 taste 带到这件事上，去判断它有没有用、是不是人们真正想要的东西，并把那个反馈循环收得尽可能紧。对我来说，这就是产品开发的三个 memes，我们现在必须尽可能把它们传开。

I love that. That's like the new dog fooding instead of dog fooding. You got to mainline it. 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. 主持人：我喜欢这个。这就是新的 dogfooding：不再是 dogfooding，你得 mainline it。 Tara：对，就是这样。而这深深地体现在那些 tweets 里。我主要是这样看到你们团队在对外沟通：他们有多沉迷这个产品，不断在问我们还能做得更好什么，现在什么让你烦，这是我们正在构建的东西。

主持人 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. 结合你前面说的，每个人都是自己产品的 founder，这一点非常清楚；作为外部观察者，他们怎么行动也非常清楚。内部还有其他 memes 吗？这些已经很有意思了。还有别的，我不知道。

Tara Sash 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. Tara：是的，我在想还有没有其他好的文化 memes。一个确实很重要的是 feeling the AGI，或者说意识到 AGI 正在到来。关于它可能长什么样、一个人可以怎么想，有非常多的结果。但把大多数人留在这家公司的很大一部分，是相信那个使命：让 AGI 是 beneficial 的，并且尽一切努力让它成为可能。

Both realization of AGI and ensuring that it is beneficial 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. 既要实现 AGI，也要确保它对人类是有益的。在构建产品时，我脑子里必须一直记住的另一句反复出现的话是：我们是不是在为两到三个月后模型会到达的位置而构建？如果你按模型现在的能力去构建，你会失败。

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. 如果你按你认为模型一年后会到达的位置去构建，你也会失败。两种结果同样错。我相信很多人都谈过这一点，但两种结果真的同样错。如果你太早，你是错的。如果你构建的东西过度聚焦于过去模型的能力，你完全是错的。唯一的构建方式是两到三个月，并且带着这束光：模型会好得多。

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? 我需要把模型能力当作这个产品的中心。我需要在我创造的产品结构上，别挡着模型的路。我怎样确保这对两到三个月后的模型是对的？

主持人 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? Yeah, certainly communicating really tightly with research on where they think things are going is incredibly important. 主持人：你怎么知道两三个月后会是什么样？这很难理解，尤其是我们还处在这条指数曲线上。是凭直觉吗？研究人员会给你什么感觉吗？这是怎么运作的？ Tara：是的，和 research 非常紧密地沟通、了解他们认为事情会往哪走，这极其重要。

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. 这些事情也不是完全的黑箱，因为你大概知道：嘿，我们正聚焦在这些特定事情上，比如我们希望模型在 coding 的这些具体方面变得更好，或者在 writing 的这些具体方面变得更好。所以我们确实有聚焦的努力，让模型在特定 capabilities 上变得更好。

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. 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. 知道那在哪里，并确保产品开发尽可能紧贴 research 的议程和 roadmap，这非常重要。主持人：有一句话我永远忘不了。 Kevin Weil 上这档播客时，他当时是 chief product officer。他说：这会是模型有史以来最差的时刻。听起来这么简单，但就是很难真正把这句话装进脑子里：这会是它们有史以来最差的时候。

Like it's such a cliche almost now to say that, but it's true. It's absurd. This is like Yeah, it's it's absurd. It's absolutely absurd. Oh man. Okay. Um I want to talk about Chad GBT the app briefly. Uh okay. So I have it open right now. 现在说这话几乎已经成了 cliché，但它是真的。这很荒谬。这就像——Tara：是的，这很荒谬。绝对荒谬。主持人：哦天。好。我想先简短谈谈 ChatGPT 这个 app。好，我现在就打开着。

Tara Sash Yes. Uh okay.

Tara Sash 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 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 it it will just pick the right harness. Tara：好。主持人：好，我现在看到的是：ChatGPT，然后有一个下拉，里面有 ChatGPT 和 Codex，然后还有这个 toggle：chat 和 work。 Tara，这是怎么回事？这些东西各自是干什么的？帮我们理解一下。你觉得这会往哪走？会一直保持这样吗？你脑子里是不是已经在想象下一步了？ Tara：我们这里的 north star 是：用户不需要在这些不同选项之间做决定。这里没有 toggle。你走到那个框里，输入你的任务，比如：我想做一个非常棒的 app，帮我的播客嘉宾在节目前做 research，之类的，然后它就会——主持人：它会直接选对的 harness。

It'll pick the right model for you to be able to get that thing done. Ideally 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. 它会为你选对的模型，好让你能把那件事做完。 Tara：理想情况下，这里的选择不该落在用户身上，让他们必须在这些不同概念之间挑选，并且不仅要理解自己想做什么，还要理解我们产品的限制和能力。这当然是我们近期想去的地方。

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. 在 ChatGPT 和 Codex 之间挑选，真正的选择是：你是想待在更偏 development 的 UI 里，还是想在 ChatGPT 模式里拥有同样的能力和力量？所以如果你是 Codex 用户，继续用 Codex。你不会错过任何东西。尽可能继续用它。但如果你是 ChatGPT 用户，在想这些新的 agent capabilities 是什么，那你大概应该待在 ChatGPT 模式里。

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. 然后当你在 ChatGPT 里，如果你想聊天、想搜索，那 chat mode 就是对的。它就是你熟悉、喜欢的那个 chat mode，只是模型越来越好，能力也一次次更新。但在 work mode 里，那底下其实就是 Codex。

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. 我们拿掉了一些 coding UI，比如你不会突然在 work mode 里看到一个 worktree 弹出来；但它拥有同样把事情做完的力量。比如生成一个非常复杂的财务模型，这在 work mode 里完全可以。我们看到人们，尤其我提到过我们的 corporate finance 团队，用 work mode 做出非常惊人的事情：以前要么是手工做，要么需要团队里某一个人的深厚专业能力，现在整支团队都能执行，或者把团队里每个人的野心都拉高，无论是时间线、能力，还是他们能做到的 frontier。

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. 主持人：好，这很有帮助。所以目前大概有三种 mode：engineering mode、chat mode，然后是做。 knowledge work 的 mode。而 knowledge work 那个 mode 其实是 Codex 在做那些工作，但人们可能不知道 Codex 是什么，也可能对它有点怕。 work mode 里有没有什么不只是 Codex 的东西？

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? 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. 这其实很有意思。是不是有额外的 harness tweaks，让它感觉有点不一样，还是只是同一件事、UI 稍微不同？ Tara：这真的主要是在 UI 层面。所以 work mode 和 Codex mode。如果你去 Codex，让它生成一个很棒的财务模型来给你的产品定价，或者告诉我、预测我未来六个月的收入之类的，Codex 会做得和 work mode 一样好。

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. 真正的区别是：当它在做这些时，你想在 chain of thought 里看到什么样的 UI？你想暴露给自己多少技术细节？它同样极其强大。所以 Codex 用户不会因为不切换 mode 而错过任何东西。事实上我们也不希望他们切：继续待在 Codex 里，做你想在 Codex 里做的所有事，我们会根据你问的事情，给你看合适的 UI。

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. 我们真正的 north star 是把这些东西合并起来，让用户不必做任何这些决定。现在的分离，更多是关于我们怎样尽可能在人们所在的位置与他们会合：就他们使用的产品、他们对概念的熟悉程度而言，并确保我们能让每个人都用上和 agents 一起工作这件事。这件事已经彻底改变了每一个developer 的工作方式。

We should do the same thing with knowledge work. It makes sense. 我们应该在 knowledge work 上做同样的事。

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. 主持人：这说得通。只是因为事情走得太快，我能想象有人会说：我们试试 Codex，这会很棒；然后它起飞了，有一千万 monthly active users；然后他们又说：等等，我们在干什么，我们有 ChatGPT，我们有 Codex，我们怎么——所以这就能理解，为什么这些东西暂时不会感觉一目了然、完美无缺，因为你必须随着什么有效、什么无效去调整，中间会有这些过渡期：好，现在让我们把人们往这个 super app 的愿景上推。

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. 好。好。我想象你工作里最难的部分之一，就是平衡这个也许有一千亿 MAU 的产品 ChatGPT——也许是历史上最成功的消费级产品——和 Codex 这个新东西，以及你们还想尝试的其他新东西。

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. 你怎么看这件事？就是，怎么平衡这些非常创新、走得很快的团队和产品，和这种：好，有十亿人在用这个，我们不能大幅改它。

Yeah, I think one of the most interesting things here is that 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. 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. Tara：是的。我觉得这里最有意思的事情之一是：我们把 work 放到 ChatGPT web 上、放到 desktop app 里、把这些东西带到一起，其中一个目标就是看着那十亿正在用 ChatGPT 的人，把越来越多的 agents 力量带给他们。如果你把 AI 产品的第一个时代看作是 chat，第二个时代显然是和 agents 一起工作，而且你知道，到目前为止主要是 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. 我们希望把它带到更多领域，当然包括 knowledge work。这也是把 work 的力量给到这十亿chat 用户的目标之一。当然，落在我们身上的产品挑战是：我们怎样不仅把它带给他们，还让它自然、容易被采用。

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. 让它不是一个他们必须明确做的决定，我们就能帮他们做对的事。我们怎样把它去复杂化，让他们不必去想 harnesses 这类对十亿消费者来说感觉很疯狂的概念。所以那主要就是挑战。然后当然，那个可能很快到来的第三个时代，就是你如何与一个能和你一起把事情做完的 persistent co-worker 共事，也许还和其他人一起协作。

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. 所以近期挑战的一部分是：我们正在把 agents 介绍给十亿可能还没体验过它们的人。我们怎样用最容易、最自然、最好用的方式做到这一点？

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. 当然，我们还有很多事要做才能让它发生。但这里也有一个我学到的教训，也许是把前 AI 时代、或者过去的产品经验和这一次对照：在以前的公司，polish 为王。把每一个 UI 交互、每一件小事都完全做对，远比早点 ship 更重要，因为时间对结果没有那么大的影响。

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. 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 so important. 因此，如果每个角落都没有打磨到完美，如果每件事都不完全正确，你还不如不 ship。但我认为这个时代、这次产品经验真正有说服力、也有意思的地方是：当你对它有很强的 conviction，嘿，这是 transformative 的，那就把它交到用户手里，这远远好过完美。那种 urgency，以及把产品介绍出去，非常重要。

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. 所以我们还有很多事要做，才能让它对 chat 用户更好用、更容易，尤其对那些也许甚至不是用它来做生产力、而是用它做消费级任务的人。但，对，done is better than perfect，我们还有非常多要做。

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 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 model now. And of course, there are things that you can continue to iterate and get that feedback prior to launching. 主持人：是的。我记得这个 app 刚上线时，有很多关于混乱的评论；而看到团队多么快地迭代、回应反馈，正是我现在听到的：先拿出去，搞清楚到底什么不行、人们怎么在用，然后快速迭代。感觉这就是现在的模式。 Tara：当然，有些事情你可以在上线前继续迭代、拿到反馈。有很多我们始终可以、也应该做得更好的事。

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. 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. 但尽可能快地迭代，并听对信号，无论那是上线前还是上线后——理想情况下是上线前——这才是关键。主持人：本期由 Mercury 赞助。彻底不同的 banking，现在加上 Spend。我做 Mercury 客户已经很多年了。我把所有企业银行都转到了 Mercury，说实话，再高兴不过。

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, 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. 这就是由产品人而不是银行家做出来的线上 banking 该有的感觉。现在有了 Spend，你可以给团队发个人卡片，按人或按团队设置支出限额，费用收据会自动从 Gmail 或短信里拉进来。你甚至可以给你的 AI agents 发它们自己的卡，配上它们自己的限额和策略。大多数 founders 一开始都一样：全公司共用一张卡。

Tara Sash 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. 这能用，直到它不再能用。有人超支了，一张收据消失了。你花两天去搞清楚谁花了什么、为什么。 Spend 是直接做进 Mercury 的费用管理。团队所有的卡、预算和报销，都和你的企业账户待在同一个地方。不用追，不用手工审核，不用月底手忙脚乱。结果是：团队能走得快，founder 也不再是瓶颈。去 mercury.com 了解并注册。

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. Mercury 是一家 fintech 公司，不是 FDIC 承保的银行。银行服务由 Choice Financial Group 和 Column N.A. 提供，它们是 FDIC members。

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. IO card 由Patriot Bank N.A.（FDIC member）根据 Mastercard International Incorporated 的许可发行。主持人：我在 Twitter 上注意到，过去几个月确实有一种 vibe shift，从 Claude Code 转向 Codex。

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. 以前大家全是 Claude。最近，至少在 Twitter 上，感觉人们开始偏向 Codex。 Twitter 是个泡沫，但很多科技圈的人都在那里。我很好奇，内部在过去不知道，三到六个月里，除了 Tara 加入并把船稳住之外，发生了什么变化。

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. 有没有什么你能分享的：好，我们把这件事想清楚了，我们转了这个，我们砍了那个。是什么帮着把 vibes 转过来，并帮 Codex 变得像它正在变得那么成功？ Tara：你知道，有一句话：悟道前，挑水砍柴；悟道后，挑水砍柴，大概是这个意思。实际上，就 Codex app 来说，最初把它做起来、一直在做的团队，再次非常 user focused，迭代循环很紧，真正 dogfood 了这个东西，尽可能 mainline 这个 app，把每件事做对。外面的人、Twitter 上的人开始意识到这件事正在发生，用户也开始真正注意到。但团队一直非常聚焦用户，非常聚焦那轮迭代。某种程度上，变化只是市场赶了上来。

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? 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. 内部这个过程没有变：每个人仍然不断在用这个 app。每一个构建它的人，显然都是 developer，用它来做开发，并且不断在修不只是自己的问题，也试着听公司里其他人的问题和用户的问题。真正值得注意的是，运作方式并没有变。一直就是我前面说的那些：我们是不是把使命拉得足够高？

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. 我们是不是在 maximally accelerating 进展？我们是不是尽可能在 mainlining it？我觉得很好，用户和 Twitter 上的人注意到了；但那种运作方式，全部功劳属于团队，那并没有变。

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. 主持人：这个回答真正有意思的地方，是它非常 human 的那一面。是你，是 Andrew，是 Tibo，是团队，就是对客户、对产品着迷。并不是 AI 给出了答案。是人造成了差异。 Tara：是的。我会把全部、全部功劳给团队。团队里每个人都极其 thoughtful，也极其独立。说到OpenAI 有很多 founders：那个团队里几乎每个人，尤其 desktop 团队，都像 founders 那样提问，关心每一块、每一个细节。

But that loop is full credit to like people on the team and and individuals for making that happen. 当他们注意到某个地方应该更好，他们会非常独立地去构建，把东西跑起来。

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 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. 如果内部测下来不好，如果人们不用，如果人们不觉得有用，他们会继续迭代，然后才对外 ship。但那个 loop，全部功劳属于团队里的人，属于让它发生的那些个人。主持人：你碰到过一个点：角色在重叠。比如工程师在做 PM 的工作，你大概也在 ship prototypes，也许还 ship 到 production，我不知道。感觉这也会带来很多挑战。我从很多人那里听到：作为 designer，我现在的工作是什么？我负责什么，不负责什么？作为 marketer，我在做什么？这是你注意到的事吗？是你正在处理的事吗？沿着这些方向，你有什么想法？ Tara：我想我一直最喜欢在创业公司工作的一点——有时我加入的是一家创业公司，它不小心长成了大公司，但主要还是在创业公司工作——是你的角色周围边界非常少。一切都是、也什么都不是你的责任。最终你要对成功负责。实际上，Stripe 非常非常是这种方式：工程师能做什么、product manager 能做什么、设计师能做什么，之间没有边界。

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? 每个人什么都能做。所以感觉上，我一直很喜欢那种心态，而现在终于是能力赶上了那种心态。但我真正在意的是：必须有人去照看，或者对这件事有核心问责：这个产品有没有被用户使用？

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. 它是不是人们想要的东西？质量高不高？有没有效果？无论那个人是工程师、设计师、PM，还是谁，总得有人是 DRI。然后，为了让那成为可能，需要做的任何工作，人们当然可以按自己的 affinity、按自己的能力去捡起来。

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. 但我喜欢一支不太在意个人角色之间边界的团队，所有人都只是聚焦于让结果发生。反过来，我也非常喜欢做 PM 的 craft 那一面。 PM craft 有非常多方面，我知道像 Shreyas、也许 Marty Cagan、Shishir，这些人都大力倡导过，我认为它们非常好。有时也许这些问题来自：等等，我那么爱自己领域的 craft，如果用这种更流动的方式去做团队合作和协作、把事情做完，我会不会？

Do I lose out on getting better and polishing my craft? 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. 因此失去把 craft 打磨得更好的机会？我真的没有这个问题的答案。我觉得这是我们正在一起经历的事：我们 craft 的某些部分，实际上正在被模型抽象掉，因为模型能非常有效地做它，也许比。

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. 个人还能做得更好。于是你的 craft 从过去能做那件非常具体的任务，变成现在把它用到产品或这个学科的其他部分。

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. Yeah, that's where I was going to go. It's just like unbelievable how different the engineering role is now. 但没错，这仍然是我在想的问题：我怎样平衡自己想成为团队一部分、使用这些工具、被一个人现在能有多有效深深吸引，以及我对——对，对工程师来说，一直手写代码真的很有乐趣，而现在人们不太再那样做了。主持人：是的，我正要说到那里。工程这个角色现在变得有多不同，简直难以置信。 Tara：是的。主持人：以前你整天写代码，那就是你的工作，而那不再是你的工作了。

Yeah. It's like you used to write code all day. That was your job and that is no longer your job. Yeah. And that happens so quickly like people mourn like the flow state of writing code. Tara：是的。主持人：而且发生得那么快。主持人：人们会怀念自己写代码时的 flow state。

主持人 Yeah. Manually yourself versus now what what one does. But I think it is a um Yeah. It's a it's a tough transition. 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? Tara：是的。主持人：亲手、自己写，对比现在一个人在做的事。 Tara：但我认为这是一个，对，这是一次很难的转变。主持人：是的。而且你知道，有些人喜欢，有些人不喜欢。那是另一个完整话题。沿着这个方向，我想问处在 AI frontier 的人：你觉得未来人脑会继续在哪里有价值？

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? 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 report. Um, ultimately, who owns like what's what was the end product? 长期无法预测。我们还会需要人类吗？希望会。但我想说，在接下来不知道几年里，你觉得人脑会继续在哪里最有价值？ Tara：我认为人类会继续最有价值的地方，当然是作为问责主体。所以，最终谁拥有这里的结果？在某些方面，你可以把正在和你一起工作的 agent 想成你的 report。最终，谁拥有最终产品？

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. 质量高不高？它是不是你想让它做、想让它说的那件事？这些至少现在仍然会是一个人。尤其在高度受监管、或者需要直接人际界面的行业和场合，这对我来说非常说得通。我认为人脑对表达也仍然非常有价值。我前面提过那个类比：software 不像real estate。它更像电影：你可以投钱进去，一部好电影也不会因此出来。

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. 最伟大的电影并不是预算最大的那些。构建 software 里有某种 artistry、立场和表达，你会觉得这里有一个或一群人的 authorship。那一部分对我来说仍然如此 human：你选择构建什么，以及它给人的感觉，感觉就是这样一个如此 human 的问题。我也认为，人脑会继续在我们如何彼此关心、如何彼此相处上有价值。

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. 我工作里的那一块仍然如此 human，实际上比以往任何时候都更重要。你和团队里的其他人交谈，一起搞清楚你们怎样能对一个方向感到热情，你们怎样一起学习和工作，怎样把彼此的野心拉高。所有这些感觉、也仍然是如此 human 的事情。是的，我认为人脑在这些方面会继续非常有价值。

All of that feels and remains such a human thing to do. Yeah, I think the human brain 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. 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. 话虽如此，我无法预测模型会发生什么，但那些部分对我来说感觉极其、极其 human。主持人：我喜欢这个回答。你谈到过这个概念： AI 能做到什么，和我们实际在用它做什么，之间有一个 overhang。人们总是觉得，最大的缺口之一就是：好，我到底该拿它做什么？我很好奇，你在工作中用 AI 的一些方式，也许能启发人们：哦哇，我没想过还能这样用。

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. 这里大概有两个桶。一个是：因为 AI，你的 PM 工作变得最不一样的地方是什么，就是你现在会用 AI 做这些事；然后有没有什么最近特别有意思、特别有创造性的 AI 用法，让你觉得：哦对，我也该试试这个。

主持人 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 I haven't. Talk about sites. Tara：我在工作中用 AI 最让人兴奋的方式之一是：我现在会一直做 sites。不知道你有没有试过在——主持人：我没有。说说 sites。 Tara：Sites 是一个非常有趣、非常棒的产品。你当然可以在 work 里把 site 做成一个展示用的 artifact，但我也会为几乎任何事情做 sites。

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. 我给团队做过一个 site，像一个游戏，我们用一个 site 一起玩游戏，因为 sites 有数据库。我还做过一个 site，因为我最近去背包旅行。我做了一个路线 site，跟踪我们要去的每个地方的海拔。

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. 我们这次旅行的每个人都输入了自己带的食物。非常快，也非常有效。 sites 某种程度上实现了 Alan Kay 在六十年代提出的那个梦想：真正的 personal computer，是带有 personal software 的。某种程度上，sites 就是让这件事变得可触摸的方式。

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. 我们都曾经梦想做过 personal software，当然也有人用 Notion 这类工具，用各种 blocks 去配置那会是什么。但有了 site，它真的就是一个 prompt。我真的用一个 prompt 说：给我做这个我需要用来把这件事做完的精确工具，它就做了。它们可以分享，可以自动更新。你可以用内部数据去做一个比如带很多指标的 dashboard。

And rather than like painstakingly laboring over some sort of like slide deck, a site is just a way more dynamic surface for presentation. How do you use a site? Do you have to do anything special or you tell it make create a site 比起辛苦地打磨某种 slide deck，site 只是一个动态得多的展示表面。主持人：你怎么用 site？需要做什么特别的事吗，还是你告诉它：做一个 site？

Tara Sash 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 and like like I'm thinking capital S site but doesn't matter I imagine it just knows what sites are 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 and what you're saying here is it just host it for you and 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 Tara：在 Codex 里说：做一个 site，比如给我的团队做一款 mafia 游戏，它就会去做。主持人：我脑子里想的是大写的 Site，但应该没关系，我猜。Tara：它就是知道 sites 是什么。主持人：所以是的，因为以前是：这是一些 source code，你自己去搞清楚部署到哪里。Tara：对。主持人：而你现在说的是，它直接帮你托管，然后——Tara：托管。你可以选择公开，可以选择给你的团队，也可以选择只对你自己私有。

主持人 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. And you could do that through I imagine work or can you do it through through all the services codeex work? You can do it through work. You can do it through codeex. You can do it in the web. Tara：它们很棒。随时能轻易做一个 site，已经改变了我日常的样子。以前的世界里，日常常常是做大量 artifacts，比如 docs、sheets，无论是什么。现在我就是一直在做 sites。主持人：我猜你可以通过 work 做，还是通过所有服务都能做，Codex、work？ Tara：你可以通过 work 做，可以通过 Codex 做，可以在 web 上做，可以在 mobile 上做（笑）。

You can do it on mobile. You can do it anywhere. 你可以在任何地方做。

Tara Sash Okay. I just kicked off a create a site about Terra Sean. Great. Is that how you pronounce your last name by the way? I haven't asked. Uh Tara Sash like station 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. Yeah, sites are awesome. Um the other thing I really love is using visualize in codeex. 主持人：好。我刚发起了一个：做一个关于 Tara Seshan 的 site。 Tara：太好了。主持人：对了，你的姓是这样读吗？我还没问过。 Tara：Tara Seshan，像 station。主持人：s。好，酷。好，酷。 Sites。好。既然我们还在这个话题上，还有没有其他快速 tips 给大家？因为那是一个很好的 tip，我觉得很多人还不知道 sites。这非常有用。 Tara：是的，sites 很棒。另一件我非常喜欢的是在 Codex 里用 visualize。

Have you used slash visualize? No. 你用过 slash visualize 吗？主持人：没有。

主持人 Oh, slash visualize is incredibly exciting. Ask you can just do slashvvisualize. Tara：哦，slash visualize 极其令人兴奋。

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. 你可以就做 slash visualize。比如 visualize 我到现在为止的 ChatGPT usage，之类的，它会把你做过的所有事情拉进来，做成非常棒的可视化。我有多少次在想：我怎样不仅拉进一堆 charts 和数据，还把它们用一种可理解、对我想讲的故事有用的方式呈现出来，次数已经无限了。 visualize 让这件事变得极其简单。用 visualize会让人意外地愉快。

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 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. 主持人：就是，这些都是很好的例子：这里有那么多力量，我们甚至还不知道、还不理解，而这就是你面对的挑战。一定要帮我们——Tara：帮我们知道所有这些事情。主持人：这也是为什么像这样的播客也有用。不可能全放进产品里。我要完全换一个方向。我想谈谈 writing。我问过很了解你的 Brie Wolfson，该问你什么。有意思的是，她给上一期我和 Cursor 的 Adam Ward 的对话也建议过问题。

主持人 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. I really strongly believe that I do two types of writing at work. 所以她说：好，你应该问她 writing slash thinking。一份 Tara brief 是 iconic 的。帮我们理解，是什么让你的 writing、你的 briefs 变得 iconic；如果有人想把写作和写文档写得更好，有没有可能有用的 tips。 Tara：我非常坚信，我在工作中做两种 writing。一种是writing as thinking，另一种是 writing as reporting。

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 as thinking 是我写一份 brief，讲我们为什么该做某个产品，为什么该采取某个策略，或者为什么这是一个比较 spicy 的 take。而 writing as reporting 是那种：哦，我在总结我们团队这周做了什么，然后发一份报告过去；或者这是我们某个 launch、某个 announcement 的计划，之类的。

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. Writing as reporting，我很乐意自动化，我一直用模型把那件事变得尽可能简单。但 writing as thinking 是我永远不会自动化的。我非常坚信，至少对我来说，走一遍、outline 一件事、把它写成某种程度的 prose、再删、再编辑、继续迭代，这是我把想法理顺的最重要步骤之一。

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. 我认为大多数人其实会用一把很宽的刷子：我永远不会用模型来写作，或者我总是用模型来写作。实际上对我来说，那两把宽刷子都是错的。

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. 我认为你应该尽可能用模型去做 writing as reporting；而就你像我一样、也像很多人一样、用 writing 来思考而言，你不该用它去替代你的思考。但我过去的 briefs，因为我写得很多，把它当作思考的方式，我会钻进去，为一件新 idea 或一个产品写一份 brief，花大量时间 refine 那个 idea，拿去给人们看，让他们尽可能攻击里面的 ideas，戳洞，把它变强，然后再拿到下一个人那里，。做同样的事。所以在 Stripe，这件事我做过非常、非常、非常多次，无论是启动一个新产品方向，还是建议一次大的方向转变，还是分析一个问题并建议一条前进路径。

And so at Stripe, this is something I did many, many, many times over, whether 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. Stripe 作为 writing culture 的取向极其强。还有很多人，比如 Jeff Weinstein，也非常投入写作、在Stripe 分享 briefs。 Stripe 是少数 brief 会在公司内部 viral 的地方之一。

And so writing is thinking there is really prized and that's where I did like the majority 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. 所以 writing as thinking 在那里非常被看重，我也是在那里做了大部分那种 writing 工作。在 OpenAI，我想我仍然一直在做 writing as thinking。但这里可分享的 artifact并不是一份很长的 doc，或者那种意义上的 proof of work。

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. 部分原因是时代变了：一份长 doc 不再是你想清楚了某件事的信号，因为你可以轻易产出一份长 doc，而它恰恰表明你没有想清楚。所以实际上，也许我日常里亲身经历过的最大变化之一，就是一次很大的、也许让人刺耳的变化：我以前在一份文档里思考，然后再把它翻译成一个展示用的 artifact，那就是我已经想清楚一个问题、这就是我们要做的、团队朝那个方向走的证明。而现在我远远更偏向 mocks not docs，或者 prototypes not docs。

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. Um, and I no longer do it for other people really. Like that no longer is the best way to to talk and communicate. 如果我有一样人们能试用、能互动的东西，或者更好：我有结果，我们试了这个，我们跑了一个 A/B，这是结果。这就是我认为我们该朝这个方向走的原因。那是比 doc 本身好得多的沟通工具。所以我仍然一直在写几百份 docs，但我是为自己写。我不再真正为别人写。那不再是最好的交谈和沟通方式。这大概是我在这个时代相对上一个时代，亲身经历过的最大变化。

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. 这太有意思了。我很喜欢你那个大量收集文档反馈的 tip。听起来很显而易见，但你几乎可以靠“作弊”，在迭代时拿到大量反馈，把一份 doc、一份 brief 做成 iconic。

Yes. to make it stronger and stronger versus like cool here it is first time and it's rarely 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. 对，让它越来越强，而不是：酷，这是第一次拿出来的版本，而且很少——Tara：我以前有一位 manager 告诉我，永远该做的正确事情是：把一份 doc 写到 70% 完成，然后拿给那些你需要buy-in 的人，把它从 70% 推到 100%。这仍然是我一直在做的事，因为很少有真正出色的人愿意去碰一个打磨到完美、已经完成的 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. How do you think about uh AI brain rot and starting to over rely on AI. This just a challenge everybody's gonna have. 一个完美打磨过的 idea，他们的新 ideas 只会从上面弹开；而一个有更多棱角、更多毛边、他们也能和你一起打磨的东西则不同。我认为，把人们以这种方式带进过程，而 doc 是那下面的artifact，这是我发现过的最好的协作方式之一。主持人：你怎么看 AI brain rot，以及开始过度依赖 AI。这是每个人都会面对的挑战。为什么不用这种魔力来帮忙看东西，然后我们开始失去写、读长文档的能力。

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? 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. 你有没有做什么，来试着避免这一点？ Tara：是的。我认为 writing as thinking 这项纪律，是我日常里用来确保自己的思考能力不会过度萎缩的主要手段之一。我再说一遍，我会尽可能把所有 writing as reporting 外包给模型，但 writing as thinking 必须自己做。

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. 我有一个个人信念：如果我要让别人读我的文档，我至少得自己先读过那么多遍。或者我也这样想会议：如果我要召集一群人开会，我需要在会前，先投入这些人将会在会上花费的集体时间那么多的准备。

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. 所以，就保持思考锋利而言，我会自己先为那份文档写作，并确保我至少按我期望人们读它的集体时间，投入到写作和产出里。我也不太依赖模型来打磨我的 prose，我并不认为。它真的能做好这件事，尤其更不会用它来生成第一版。但我当然会在很多时候让模型帮我，比如 summarization，或者把内容从一种格式翻译成另一种，这些我一直在用。

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 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. 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. 主持人：所以我听到的是：那个 idea、那份 brief、那个 plan，你作为人自己写。自己写。不要从 AI 开始。甚至也不要用它去改进写作。让那全部保持 human。 Tara：是的。至少对我来说，我自己开始，也自己结束。中间我可能会用 AI 去研究某些具体元素，或者丢进一些数据，或者去拉一些数据，或者帮忙——主持人：对一些 ideas 做 push back。

Don't and and even don't use it to improve on the writing. Just keep that all human. 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 push back on some ideas. Yeah, push back on some ideas, but start yourself and yourself with a piece of writing and that doesn't deteriorate your thinking. Okay, one last uh question I want to ask about Setter Hill. Tara：对，对一些 ideas 做 push back，但用一篇写作时，自己开始、自己结束，这样就不会让你的思考退化。主持人：好。我想问的最后一个问题是关于 Sutter Hill。你有过一个非常少见的职业步骤。你是 PM、founder 那种人，然后就去做了 Sutter Hill Ventures 的 EIR，那是一家 iconic 的 VC。

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? 人们可以自己去查。很多非常出色的公司都出自 Sutter Hill。它接近 founding 的方式非常独特：基本上他们会孵化公司。 Snowflake 就是一个例子。那是怎么回事？你从那段经历里学到了什么？ Tara：Sutter Hill 是一家 iconic 的机构，而且有意非常 illegible。

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. 如果你去 Sutter Hill 的网站，网站上什么都看不到。这是一家不会大声运作的机构。它尽量在雷达之下运作，尽量谦逊，却又以某种方式对硅谷见过的一些最 iconic 的成功负有责任。

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. 他们有一种非常少见的孵化模型，是 Mike Speiser 开始的，他是那里非常出色的 partners 之一，并且一次又一次做出成功。

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. 我认为 Sutter Hill 对我来说最 iconic 的一点是：人们把找到 product-market fit 看成一门暗黑艺术，或者把做出一家数百亿美元的公司看成一门暗黑艺术，哦这是运气，哦这是偶然，哦必须有所有这些东西凑到一起。但 Mike Speiser 做过很多次。所以这里显然有办法去做，显然有一条让它成为可能的 roadmap，显然有一套人可以去做、并且可重复得到这个结果的事情。它不只是运气，不只是暗黑艺术。

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. 可以说有一份 playbook，而那份 playbook 活在 Sutter Hill 这家机构内部。他们已经搞清楚怎样在喊方向、下赌注上经常做对，也已经学会怎样在那些每天复利的事情上经常做对，去创造一家成功的公司：无论是你怎样搭建 enterprise sales 团队，怎样定位你的产品，怎样组建最初的 founding team。 Sutter Hill 的 recruiting 是一种无与伦比的 excellency。

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. 他们有一个秘密工具叫 Reticle，里面有一张地图：每一个他们互动过的人，以及那些人互动过的十个最优秀的人。

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. What'd you learn? 这帮助他们在这件事上极其、极其有效。所以我去 Sutter Hill，是因为某种程度上，我的职业生涯一直是：我怎样尽可能多次地去找 product-market fit，无论是作为 founder，还是在 Stripe 启动新产品，还是加入像 Watershed 这样的创业公司。而 Sutter Hill 是一个他们已经搞清楚怎样在 B2B 产品上找到 product-market fit 的地方。我想从他们那里学我能学到的东西。

What's one thing you took away from that experience other than they know how to do it? 主持人：你学到了什么？除了他们知道怎么做之外，你从那段经历里带走的一件事是什么？

Tara Sash 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. Tara：他们确实知道怎么做。我认为，我在那里学到、也非常让我意外的一件事是：product-market fit 当然重要，但我以前真的低估了 product-marketing fit。这个想法是：你谈论产品的方式、你营销它的方式，甚至可以先于真正把产品做出来。

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. 它大概应该来自把对技术的深入理解，和对 enterprise sales 过程的理解拉到一起。然后那种product-marketing fit，那个 narrative，那个 positioning，实际上甚至在你做出产品体验之前，就是该测试的正确事情。

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. 所以你应该去向 100 个人 pitch，尽可能把那套 pitch refine 清楚。把“为什么这件事是 transformative 的”营销叙事做对，然后、也只有到那时，才去承诺：好，这就是精确的产品形态。 Mike Speiser 在这门艺术上几乎无人能及。我以前一直有点低估PMM 工作。我会想：随便吧，它就是这些职能之间的胶水，还行。然后我意识到，把那项工作做到 excellently，对公司结果有多 transformative，事实上它可以成为让一家公司成功的那个元素。

Amazing. Uh I so agree with that positioning. We talk a lot about that on this podcast. Mhm. 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. Oh man. 主持人：太棒了。我非常同意 positioning。我们在这档播客里谈得很多。 Tara：嗯。主持人：好，我很快给你看一眼 sites 做出了什么。我们说话的时候它一直在跑。看看这个。 Tara：哦天。

主持人 As like as like make it more awesome and it made it more awesome. Multiroduct. Beautiful. Look at this. This is like legit design. Look at you got quotes. Big conviction. Small teams. Start with the buyer. How do you feel about this being your website? your new website. 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. Okay, good job. Looking good. 主持人：就像，让它更 awesome，它就变得更 awesome 了。多产品。好看。看看这个。这像是正经的设计。Tara：看，你还有 quotes。Big conviction. Small teams. Start with the buyer. 主持人：你觉得把它当成你的网站、你的新网站，感觉怎么样？Tara：我确实觉得最上面那张大概 19 岁的我的照片很好笑。但除此之外，我非常、非常喜欢这个 site。主持人：好，干得好。Tara：看起来不错。

Tara Sash I think that was that's my that was my badge photo from Stripe. 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? 主持人：我觉得那是我在 Stripe 的工牌照片。 Tara：哦哇。太棒了。我喜欢它做出来的东西。我已经取消分享了，但我喜欢它在你头周围做了一整圈小小的东西。好可爱。 Tara，你还有什么想分享的吗？在进入我们非常令人兴奋的 lightning round 之前，还有什么想触及的吗？

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. Tara：是的。我们在产品构建上想得很多的一件事，尤其是 ChatGPT Work 和这个新时代，是 knowledge work 和 coding 实际上从根本上不同。我们在这个过程中学到的一件意外的事是：coding 是如此 output oriented，当你让它做一项 coding 任务时，你可以通过 tests 验证它有没有做对、做得好不好。

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. 你可以试一下，看它能不能跑。有一种基于 output 去验证它的方式。但 knowledge work 不同：我不能只看最后那份 deck，看那些数字，哦，deck 里大概 90% 成功之类的，然后就真正相信那件事。我真正需要去想过程、inputs、reasoning，以及它一路是怎么走过来的。

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. 所以就这在产品里长什么样而言，我们已经做、也必须继续做的很多工作，就是继续让产品适配 knowledge work。这意味着要更聚焦于让 ChatGPT 成为你的 collaborator，让你能看到所有进行中的工作，看到它的 citations和 inputs，帮你和模型一起走完那段旅程，到达那个最终 output，好让你最后知道：哦。等等，这件事是对的，这件事是好的，这件事是有用的。

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. 这。当然会大量体现在产品的 UX 上，但也应该体现在 reasoning 和 chain of thought 这类事情上：比如，你是否应该沿途看到更多 citations，说明它是怎样到达那个最终状态、那份数据的？ thread 这种表面非常适合。 coding，但它是不是你在 knowledge work 里看到这一切的正确地方？

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. 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. 有非常多重大、重要的产品问题。所以当我们想到也许把人类协作者带进你的工作，我们也需要想：我们怎样能让模型在你们一起把事情做完时，更像你的 collaborator。主持人：这一点太好了。我在想象一场 exec meeting，你试着向 exec pitch：这就是计划，这就是我认为我们该做的事。

So much of that is helping them see here's the work I did to get there. here's all the steps 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. 这里面很大一部分，是帮他们看到：这是我为了到达那里做过的工作，这是所有步骤。所以说得通，你需要 AI 向你展示它做过的同一种工作，本质上就是 proof of work。而工程则是：好，我不需要知道你做的每一个小小的架构决定，只要看它长什么样、它是不是通过了我们所有的 tests。所以这一点非常好：这两种模型有多么不同。而且还有 context：它有没有做成你想让它做的事所需的 context？它知不知道，它能不能看到你的 email，能不能看到你所有的 Notion Docs。 Tara：嗯。主持人：这一点太好了。所以我看到了你工作里的挑战。

Mhm. 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? Yeah. Let's jump into it. With that, we've reached our very exciting lightning round. I've got five questions for you. Are you ready? Yes. 我认为这些工作是同一个产品。很难，很难。太棒了。进入我们非常令人兴奋的 lightning round 之前，还有别的吗？ Tara：好。我们开始吧。主持人：这样，我们就到了非常令人兴奋的 lightning round。我有五个问题。你准备好了吗？ Tara：准备好了。

主持人 What are two or three books that you find yourself recommending most to other people? 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. 主持人：有哪两本或三本书，是你发现自己最常推荐给别人的？ Tara：我非常推荐给别人的一本书是 William Finnegan 的《Barbarian Days》。不知道你读过没有。它讲的是一个男人的一生，他是《New Yorker》记者，但他怎样爱上冲浪，把它当作自己的热情。我从这本书里带走的是：一个人可以深深热爱、深深投入，让某件事成为你的人生目的，即使你并不擅长它。

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 how I think one should continue 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. 它关于那种爱上冲浪的艺术，以及他在知道自己永远到不了那里的情况下，仍然追求卓越和完美。它对一个人该怎样继续过自己的生活，是一个如此有说服力、如此 transformative 的故事。我非常、非常喜欢那本书。另一本我可能会推荐、作为一本人们应该读的书，我非常喜欢《Anna Karenina》。

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. 我最近在重读经典。我喜欢《Anna Karenina》，因为它像一本有层次的书。我认为在这个新时代，我们将不得不做的很大一部分，是改造自己，或者带自己走一段旅程，去做和我们习惯的不同的事情。当我想到那本书，我会想到我 13 岁读它时，基本上只懂情节。大概 17 岁再读时，我懂了欧洲历史动态，以及阶级冲突。

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. 然后 30 岁再读时，我会想：哦，这是一个关于一个女人、关于人类的故事。它只是提醒我成长，以及随着你继续成长，你可以通过多种不同的透镜去看同一件事。我认为这也是我们所有人在考虑自己的职业生涯时，面前的那种挑战。主持人：有意思，这两本我都能接到我们现在所处的 AI 时代上。我也最近刚读了《Anna—— Tara：你觉得怎么样？

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 what did you think 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. 主持人：今年早些时候。太棒了。我以前从没读过。我在一份书单上看到它，像是世界上最聪明的人读过什么，整份书单，那本是我没读过的。所以我想我得读。对，太棒了。有人剧透了结尾，这让它没那么让人吃惊。我不想剧透。没有 spoilers。我也觉得它非常长。但现在我在读《The Power Broker》，它把“长”的新标准又立起来了。

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. I love the I love the Power Broker. 我读它已经读了半辈子。 Tara：我爱《The Power Broker》。另一件我非常推荐给人们的是：如果有人关注 Substack，像 Simon Haisell 的 Substack，他会慢读重要的书。

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. 他做过《War and Peace》，我想他正在做《Wolf Hall》，或者他做过《Wolf Hall》，那是 Hilary Mantel 的书。一章一章来。那几乎是读《The Power Broker》或《War and Peace》、甚至《Anna Karenina》的唯一办法：一章一章来。

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. 说到这个，有人告诉过我，我忘了是谁，99% Invisible 有一个 Power Broker book club breakdown，13 集，每集一两个小时，一次讲书里的几章，讨论它，还有特邀嘉宾，比如 Pete Buttigieg 和 AOC，以及住在那个地区的人，他们会谈每一个，你知道，那个故事。一边读一边听他们的分析，非常有趣，然后他们还请 Robert Caro 来过几次。 Tara：那太棒了。主持人：是的。热 tip。好，我们继续非常闪电的 lightning round。

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. 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. 最近有没有你真正喜欢的电影或电视剧，如果你有时间看任何东西的话。 Tara：当然，我看了《The Odyssey》。我觉得它是一部极其、极其出色的电影。它是关于 AI 的，或者我的 hot take 是它关于 AI。或者说Christopher Nolan 对 AI 如何改变社会的看法。

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. 我很喜欢，也非常推荐去看《The Odyssey》。他就是那样一位极其出色的导演，把 artistry 和商业成功桥接在一起的方式，我认为没有其他当代导演做到过。

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. 我最近还看了电影《Rashomon》，Akira Kurosawa 的那部。它第一次用了那种技巧：通过多个人的视角讲一个故事，而你到最后永远不知道什么是真的。电影里的那种技巧是 Kurosawa 开创的。它提醒我，人在约束下能做出什么。那部电影大概拍于五十年代，是黑白的，你知道，有一个人举着摄像机，它却如此完美，是如此有品位、创新、惊人的创造力的例子。

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? 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. Kevin Clark got us tickets at 10 PM at the Metreion earlier this week. 看那部电影时我被提醒的是：我在 iPhone 里拥有的力量和工具，是他拍那部电影时的一百倍。那我有什么借口不去拉高自己的野心、做出更好的东西？主持人：一切又回到 ambition。关于《The Odyssey》，我还在试着抢票。太难了。我睡过头了，现在大概一个月都不可能。哪里都没有座位。 Tara：Kevin Clark 这周早些时候给我们搞到了晚上 10 点 Metreon 的票。

It was so good. Next time, call me. I'm in. 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 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. 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. 太好看了。主持人：下次打电话给我。我加入。 Tara：哦天，我像是有 bots 在跑，有一个人在帮我搞，还有一个朋友。我们都在试着找——Tara：太棒了。你会喜欢的，我迫不及待想听你看完之后怎么想。如果你同不同意我：它是关于 AI，以及道德的崩塌。主持人：好，没有 spoilers。希望这期出来时我已经看过了。如果没有，谁有门路请告诉我。

And I'm trying to do like the IMAX full power matron sort of thing. 我在试着搞那种 IMAX 全功率、Metreon 那种。

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. 对。好。下一个问题。你最近发现的最喜欢、或者有意思的 AI 产品，理想情况下不是 OpenAI 的产品，但你知道，你想说那边也可以。 Tara：哦。我的意思是，当然，我最喜欢的 AI 产品是 ChatGPT，以及在 Codex 里用很酷的 sites 和 visualize，那很棒。但在 OpenAI 产品之外，我最喜欢的 AI 产品，是朋友为我做的产品，因为现在人们真的能做到这一点。

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. 我觉得这太酷了。我是 cozy software 运动的超级粉丝：你为五个朋友做软件工具，然后你们一起用。所以我有一个朋友叫 Sebastian，做了一个非常酷的 AI app，能把任何东西变成播客，再放进一个小小的播客 app 里给你。他还为我们的朋友做了一个非常好的私人社交网络，叫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. 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 learn the most interesting things on that product. It's like a WhatsApp, but not Yes. Exactly. Exactly. 它正是我认为未来该有的样子：人们应该做出精确满足自己和朋友需求的软件。主持人：GATS 代表什么？是某种内部笑话吗？ Tara：不是。或者至少如果它是内部笑话，我也不知道。但它就是我待的那个地方。它有点像给一小群朋友用的私人 Twitter。我在那个产品上学到最有意思的事情。主持人：有点像 WhatsApp，但又不是。 Tara：对。就是这样。就是这样。

Tara Sash 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. It's a It drops it in your Apple podcast feeder. You watch. Amazing. I want this. It's great. How do I help me? Help me subscribe to this. For sure. Okay. Amazing. Okay. Two more questions. 主持人：那个播客 app 很有意思，但我感觉我会喜欢的版本是：它就是你播客 feed 里真正的播客，然后你想读的东西之类的，会作为新一集加进去。 Tara：对，它就是这样做的。主持人：它会丢进你的 Apple Podcasts feed 里。你看着。 Tara：太棒了。我想要这个。太好了。我怎么订阅这个，帮帮我。主持人：一定。好。太棒了。

Do you have a favorite life motto that you find yourself coming back to often in work or in life? 好。还有两个问题。你有没有一句喜欢的人生 motto，是你在工作或生活里经常会回到的？

主持人 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. Amazing. 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. Tara：我在工作里一直会回到的人生 motto，其实是 Toni Morrison 关于工作的三点。让我很快把它找出来。主持人：太棒了。Tara：好，是四件事。出自她的随笔《The Work You Do, the Person You Are》。第一件：无论工作是什么，都要把它做好。不是为了老板，而是为了你自己。第二件：是你造就这份工作，不是工作造就你。第三件：你真正的生活是和家人在一起。

And the fourth is you are not the work you do, you are the person that you are. I got tingles. 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. So cool. Okay. Uh maybe we'll show that on the screen as you're talking about that. I love that. 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. 第四件：你不是你做的工作，你是你这个人。主持人：我起鸡皮疙瘩了。哇。太好了。我想这就是你 pinned 在 Twitter profile 上的那句话。对，因为我记得见过。 Tara：太酷了。好。也许你讲的时候我们会把它放到屏幕上。我喜欢这个。主持人：我喜欢，这是记住某件事的好办法。就把它钉在 Twitter 顶上，因为我每次去 Twitter：哦，它又在那里。 Tara：嗯。主持人：好。

Mhm. Uh okay. Final question. Uh you were a Theel fellow back in the day. Teal fellow. Teal or Theel? Teal. Teal. Yeah. What an alumni group. Holy moly. Just like so. 最后一个问题。你以前是Thiel Fellow。 Thiel Fellow。 Teal 还是 Thiel？ Thiel。 Thiel。

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 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 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. 对。主持人：那是怎样一个校友群体。天哪。就是，那么。这是一个非常棒的 idea 和项目。那段时间有没有什么也许有趣的故事可以分享，让人觉得：哦哇，那太疯狂了。 Tara：我不知道，有没有其他让你感到骄傲的 Thiel Fellow，或者其他。面试是什么样的？沿着这些方向，我什么都可以。 Tara：是的。 Thiel Fellowship 是我人生中的一个拐点。没有它，我不会走到现在。也许可以接到那个点：有一些关键时刻，你可以告诉人们把野心拉高，他们真的会这样做，而这会改变他们。

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. 那就是这样一个时刻：有人走到我面前，把我的野心拉高，说不，你可以做这个，你不必走你当时正在走的那条路。我真的永远感激他们能那样做。我现在一直能一起工作的 Thiel Fellows 之一是 Ari Weinstein，他创办了一家叫 Sky 的公司，后来被 OpenAI 收购。在此之前，他创办过公司，也在 Apple 工作过一段时间，因为他们收购了他之前的公司。 Ari 就是我见过的最有创造性的思考者之一，也真正是 Mac 上所有酷事能做什么的专家。

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 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. 所以 Ari 在 OpenAI 负责我们很多 computer use 的事情，他也已经 ship 出一堆很棒的computer use 功能。但他的创造力，他对自己所做之事的喜悦，以及他对 craft 的爱，真的很启发我。 Ari 是个很酷的人。但我在想，那段时间有没有一个感觉合适的好故事——主持人：你想的时候，我给不知道这件事的人解释一下 Thiel Fellowship，如果我讲错了你纠正我。

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? 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. And how many years did it go on for? 基本上，Peter Thiel 会说：嘿，人们不该去上大学。相反，他们应该去试着构建自己想做的东西，然后你拿到 10 万美元，不去上大学，而是去追随你的野心。大概是这样吗？ Tara：对，就是这样。而且当时你和另外 19 个人在一起。那是每年大约 20 个人，因为是 20 under 20。

Is it still 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. 主持人：然后——它办了多少年？现在还在办吗？ Tara：我想还在办，但前四五年左右，人数大概就卡在 20 这个数字上。

Tara Sash 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. Tara：对。我想我那一年发生的一件非常疯狂的事是：我是第二个——Fellowship 每年都会决定把它全程拍成 CNBC 的纪录片。所以我们整个，我为 Fellowship 做的 pitch，走上舞台去讲我打算做的 idea，所有这些不幸都还在 YouTube 上。所以如果你真的想看 19 岁的我做一件尴尬的事，它就在那里。

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. Amazing. Yeah, it's interesting that Dylan's like the guy I think everyone thinks of when they think of Teal Fillers. Yeah. Yeah. What a what a brand. Okay, Tara, this was incredible. 当然，从那一届Fellowship 走出来、最惊人也最成功的人之一是 Dylan Field。他不仅才华惊人，人也非常善良。能和那些人一起工作，我觉得非常幸运。主持人：太棒了。有意思的是，Dylan 就像人们想到 Thiel Fellows 时会想到的那个人。 Tara：对。对。主持人：那是怎样一个 brand。好，Tara，这期太精彩了。你有什么想 plug 的吗？

Uh, is there anything you want to plug? Anything you want to point people to? And how can listeners be useful to you? 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. 有什么想让人们去看的吗？听众可以怎样对你有用？ Tara：我想 plug、想让人们去看的？也许他们该用 ChatGPT desktop app。他们该在 web 上用 ChatGPT，并试试 work。不幸的是它是一个小小的 toggle。他们可以 toggle 过去，试试 work。让它做一件酷的事。让它做一个关于你的 site。

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. 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. Great. That will that will work. Solve all the problems. Okay. I interrupted you. 也许从这里开始，或者让它做一个小小的 visualize block，展示你的 ChatGPT usage。这是一种非常酷的方式，开始非常切身地体验这些东西的力量。他们从那里能做的 use cases 列表，你知道，是无限的。我很乐意。主持人：这有一个更好的主意。这有一个更好的主意。让它做一个 site，告诉你可以用 work 做什么。 Tara：太好了。主持人：那会有用。

I apologize. Uh what else were you gonna add or say? 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. 把所有问题都解决了。好。我打断你了，抱歉。你本来还要补充或说什么？ Tara：是的，我主要的 plug 就是：对，去下载ChatGPT app。去 web 上用。更 transformative 的是，去 mobile 上试。然后坐一趟很长的地铁，或者一趟 Muni。当你没有信号、再出来时，事情已经给你做完了。那一部分感觉超级、超级神奇。你不用一直开着笔记本电脑走来走去。

You've finally got these things running in the cloud doing real work. 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. No, it's everywhere. 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. 你终于让这些东西在云端跑着，做真正的工作。主持人：是的，最后那一块我本来也想提，但我认为那是今天这个产品在mobile 上一个被低估的元素，而且那只是 mobile only 的功能。云那一块。 Tara：不，它到处都有。主持人：到处都有。好。太棒了。所以在你的 mobile app 上，你可以去 ChatGPT，toggle 到 work，让它做一些工作，你并不需要它真的在本地跑。

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? No, that's it. Okay. Thanks,this was awesome. Thank you so much for doing this. Such a pleasure. Uh what a journey since the fellowship back in back in the day. I'll talk about that more in the intro. Yeah. Uh, all right. Well, thanks for being here. 它在云端跑。它会一直做，直到做完，然后你可以和它 chat。所以那感觉非常简单，但那是极其强大的一件事。好。 Tara，在让你走之前，还有别的吗？ Tara：没有了，就这些。主持人：好。谢谢。这太棒了。非常感谢你做这期。 Tara：非常愉快。主持人：从当年的 Fellowship 到现在，怎样一段旅程。我会在 intro 里再多讲一点。 Tara：好。主持人：好。谢谢你来。 Tara：谢谢你。

Thank you. Bye, everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennispodcast.com. See you in the next episode. 主持人：大家再见。非常感谢收听。如果你觉得这期有价值，可以在 Apple Podcasts、Spotify，或你喜欢的播客 app 上订阅这档节目。也请考虑给我们评分或留下评论，因为这真的能帮其他听众找到这档播客。你可以在 lennyspodcast.com 找到所有过往集数，或了解更多关于这档节目的信息。我们下期见。