Dispatch from the Future: building an AI-native Company – Dan Shipper, Every, AI & I

频道: AI Engineer
视频: https://www.youtube.com/watch?v=MGzymaYBiss
原文语言: en
统计: 共 29 轮

[0:13]

[music] I'm the last speaker of the day, so I'm just between you and dinner or drinks. So, I'm going to try to make this fun and hopefully a little bit short. So, first of all, I just want to say I'm very glad to see everybody and I'm actually kind of surprised to see so many people here. Um, because I've been I live here, but I've been traveling. I was in Portugal uh last week and I was on Twitter and someone said that everyone was moving to San Francisco.

[音乐] 我是今天最后一个上台的，所以站在我和大家的晚餐或者酒局之间的就是我了。那我尽量讲得有意思一点，也希望能讲得短一点。首先，我特别高兴能见到大家，说实话也挺意外现场来了这么多人。因为我虽然住在这儿，但最近一直在外面跑。上周我在葡萄牙，刷推特的时候看到有人说大家都搬去旧金山了。

[0:52]

Uh, but it's great to have everybody here instead because I [ __ ] love New York. >> [laughter] >> Come on. Come on. [applause] Um, so I'm supposed to talk uh today about uh how to build an a playbook for how to build an AI native company. And um I actually don't have one unfortunately. Um and that's because I think the playbook is actually being invented right now. So we're doing it at the company that I run every but all of you are doing it here today as well and and and so I don't want to do this talk from the perspective of I have all the answers and I'm going to tell you the framework and the playbook and all that kind of

不过反倒是大家都在这儿，太好了，因为我他妈太爱纽约了。>> [笑声] >> 来嘛，鼓个掌。[掌声] 那我今天本来是要讲怎么搭一套构建 AI-native 公司的打法。但很遗憾，我其实没有这么一套现成的打法。原因是我觉得这套打法现在正在被发明出来。我们在我经营的公司 Every 里就在摸索，今天在座的各位也都在做这件事。所以我不想站在那种「我手里握着所有答案，来给你们讲框架、讲方法论」的角度来做这个分享。

[1:35]

stuff. Um but um I do think it is helpful when we're in this beginning stage of uh learning how to use AI to do engineering to build companies uh to share like the the personal experiences that we're having inside of our companies um and uh and sort of collaboratively figure out the playbook together. So I think the best that I can offer is really just sort of dispatches from the future. Uh notes on what I've figured out um and the work that we've done inside of every um and I think the the first big thing the first the first big thing I really noticed is that there is definitely a huge there's a 10x

但我确实觉得，在我们刚开始学着用 AI 做工程、用 AI 建公司这个阶段，把各自公司内部的亲身经历拿出来分享、然后大家一起协作把这套打法摸索出来，是很有帮助的。所以我能提供的最好的东西，其实就是一些「来自未来的快讯」——我自己琢磨明白的一些笔记，还有我们在 Every 内部做的那些事。我注意到的第一件大事是：一家 90% 的工程师在用 AI 的公司，和一家 100% 的工程师都在用 AI 的公司之间，确实有一个巨大的、10 倍的差距。

[2:18]

difference between an org where 90% of the engineers are using AI versus an org where 100% of the engineers are using AI. It's it's it's totally different. Um, I think the I think the big thing is if even 10% of your company is uh is using a more traditional engineering method, you you sort of have to lean all the way back over into that world. Um, and so it it prevents you from doing some of the things that you might do if everyone was uh not typing into a code editor all the time. Um, and I know this because this is what we do at every um, which is the company that I run. And it has totally

这两者完全不一样。我觉得关键在于：哪怕你公司里只有 10% 的人还在用更传统的工程方式，你就不得不整个往那个旧世界靠回去。这就会拦住你，让你没法去做那些「如果所有人都不用一直盯着代码编辑器敲字」时本来可以做的事。我知道这一点，是因为这就是我们在 Every 的做法——Every 就是我经营的公司。这彻底改变了我们这样一家小公司能做到的事。

[2:58]

transformed what we are able to do as a small company. Um, and so I think of us as like a little bit of a lab for what's possible that I I'm excited to share with you. So for people who don't know, I run every um, inside of every we have six business units. We have four software products. We run four software products with just 15 people, which is kind of crazy. Um, and these software products are not toys. We've grown at every we've grown MR by double digits every month for the last 6 months. We have over 7,000 paying subscribers and over 100,000 free subscribers. Um, and we've done this in a very capital-like

所以我把我们当成一个有点像「探索可能性的实验室」，这些东西我很乐意分享给大家。给不了解的人介绍一下，我经营的是 Every。Every 内部有六个业务单元，我们运营着四款软件产品。我们就靠 15 个人运营四款软件产品，这其实挺疯狂的。而且这些产品不是玩具。Every 过去六个月每个月的 MR 都是两位数增长。我们有超过 7000 个付费订阅用户、超过 10 万个免费订阅用户。我们还是以一种非常省钱的方式做到的。

[3:39]

way. We've only raised about a million dollars in total. Um and very importantly for for this audience and for this discussion um 99% of our code is written by AI agents. Uh no one is handwriting code. No one is writing code at all. Um it's all done with cloud code, codec, Droid, what have you. Um uh coding agent of your of your choice. Um, and also really importantly for the size of team we are, each one of our apps is built by a single developer, which is crazy. And these are not like uh little apps. Uh, here here's an example. This is Kora, which is a um AI email management app. Um, it's sort of

我们总共只融了大概一百万美元。还有一点对在座各位、对今天这个话题特别重要：我们 99% 的代码是 AI agent 写的。没有人手写代码，根本没人在写代码。全都是用 Claude Code、Codex、Droid 这些工具做的，你喜欢哪个 coding agent 就用哪个。还有一点对我们这种规模的团队特别关键：我们每一款 app 都是由一个开发者单枪匹马做出来的，这很疯狂。而且这些可不是小打小闹的 app。举个例子，这是 Kora，一款 AI 邮件管理 app。它有点像……

[4:23]

an it's it is it's an assistant for your email. It on on the left over here, it summarizes all of your all of your emails that come in. So, you can kind of read your email that way. This is what my inbox looks like. on the right is a um email assistant that you can ask questions like I asked where's when's my AI engineer talk um today and it gave me just gave me the answer um and this is built primarily by one engineer um that he's got one or two contractors that have helped in in certain ways but like almost all of this is built by one guy same thing for um uh this app which is another one that we

它是你邮箱的一个助手。在左边这块，它会把所有进来的邮件都做个总结，你就可以用这种方式来读邮件。这就是我的收件箱长的样子。右边是一个邮件助手，你可以问它问题，比如我问它「我今天的 AI engineer 演讲是什么时候」，它就直接把答案给我了。这个产品主要是一个工程师做出来的，他有一两个外包帮着在某些地方搭了把手，但基本上几乎全是一个人做的。我们做的另一款 app 也是一样……

[4:58]

we make called monologue which is a speechtoext app It's sort of like Super Whisper or Whisper Flow if you know of those. Um, again, one guy, thousands of users. Um, I I love it. It's a it's a it's just a beautifully done app and it's not it's not simple. It's complicated. There's a lot of stuff to it. Same thing for this app called Spiral. You can see there's it's it's big. Um, and again, one engineer.

这款叫 Monologue，是一个语音转文字的 app。有点像 Super Whisper 或者 Whisper Flow，如果你听说过这俩的话。同样，一个人做的，几千个用户。我很喜欢它，是个做得特别漂亮的 app，而且它一点也不简单，挺复杂的，里面有很多东西。这款叫 Spiral 的 app 也一样，你能看到它体量很大。同样，就一个工程师。

[5:27]

So, obviously, this would not have been possible um a few years ago. it would not have been possible even a year ago. And I think the big change that happened that we're all starting to catch up to is um it started with cloud code this sort of like terminal UI that gets rid of the code editor really push pushed us into a place where um we are delegating tasks to these agents. We are and and that allows us to uh work in parallel and do much more than we would have ordinarily. Um, so some of the things that some of the things that I've noticed that we can do that I I assume people in this room are

很显然，这在几年前是不可能做到的，哪怕在一年前也不可能。我觉得发生的那个大变化——我们现在都还在追赶它——是从 Claude Code 开始的。这种终端式的 UI 把代码编辑器给干掉了，真正把我们推到了一个「我们在把任务委派给这些 agent」的状态。这样我们就能并行地干活，做到比平时多得多的事。我注意到我们现在能做的一些事情——我猜在座各位也开始看到了……

[6:04]

starting to see but >> [snorts] >> um I think is sort of important to put put our finger on is uh the reason we can go much faster is we can work on multiple multiple features and bugs in parallel. And I think that there's a um there's like a little bit of a meme of the vibe coder on Twitter that is oh like they they have um they have four panes open but they're not actually doing any work. And I actually you can do it that way. And I think there are also definitely engineers and I know that they are because they work at every that are productively using four panes of agents at the same time. Um, and

但我觉得有必要点明一下：我们之所以能快很多，是因为我们可以并行地处理好几个功能和 bug。推特上有个关于 vibe coder 的小段子，说什么「他们开了四个窗格，但其实根本没在干活」。说实话你确实可以那么混。但我也知道确实有工程师——我很清楚，因为他们就在 Every 上班——是真的在同时高效地用着四个 agent 窗格干活。这很疯狂，而这一点很大程度上促成了一个开发者能独立构建并运营一款生产级应用。

[6:41]

that's that's crazy and that that contributes a lot to the um ability for a single developer to build and run a production application. Um, another like really important thing about this, a really big um, unlock is because code is cheap, you can prototype risky ideas and that allows you to do more experiments than you would ordinarily. And that lets you make way more progress because the starting energy to try something is so much lower because you just like say, "Oh, go do this. go do some research on this like big refactor I might want to do and then you go off and do something else. And that's a really big deal.

关于这件事还有一个特别重要的点、一个很大的解锁：因为代码很便宜，你可以拿那些有风险的点子去做原型，这就让你能做比平时多得多的实验。这又让你能取得多得多的进展，因为「试一下某件事」的启动成本低太多了——你只要说一句「去把这个做了，去给我想做的这个大重构做点调研」，然后你就可以去忙别的了。这是一件特别大的事。

[7:20]

Um, and another really interesting thing that I love about this stuff that I' I've noticed in inside of inside of our organization is we move we're moving a bit more toward a demo culture where um instead of you know previously if you wanted to make something you'd have to be like maybe write a memo or do a do a deck or um or you know convince a bunch of people that it was a good idea to spend time on because you can vibe code something uh in a couple hours that sort of shows the thing that you're uh that you want to make. It it allows you to show everybody and uh I think that being a being a sort of de democulture allows

还有一件我特别喜欢、在我们组织内部注意到的有意思的事：我们正在更多地转向一种 demo culture。以前你要是想做个什么东西，你可能得写一份 memo、做一个 deck，或者去说服一帮人「花时间在这上面是个好主意」。而现在因为你能在几个小时里 vibe code 出一个能大致展示你想做的东西的原型，它就让你可以直接展示给所有人看。我觉得变成一种 demo culture 之后……

[7:58]

you to do weirder things that you only get if you can feel it. Um which is I think really amazing and beyond just like sort of the basic productivity unlocks. um AI has and the way that we use it has caused us to sort of invent an entirely new set of engineering primitives and processes which I am sure that everybody in this room is starting to do already. I think everyone is sort of approaching the same things from different angles and a lot of them definitely do echo engineering processes from the past but I think it's really helpful to try to put our finger on okay what is the new way of programming if we're moving up a

它让你能去做一些更「怪」的东西——那种只有你能亲手感受到它的时候才会冒出来的点子。我觉得这真的很棒。而且不只是这种基础的生产力解锁，AI、以及我们使用它的方式，已经促使我们发明出了一整套全新的工程基本单元和流程。我敢肯定在座各位也都开始这么做了。我觉得大家其实是从不同角度逼近同一批东西，其中很多确实呼应了过去的工程流程，但我觉得点明这一点很有帮助：好，如果我们在技术栈上往上挪了一层，那么这种新的编程方式到底是什么？

[8:38]

level of the stack and and we're moving from you know Python and JavaScript and scripting languages up into um up into English and the uh the the name that we've given to this process is compounding engineering Um, and the way that I talk about compounding engineering is in traditional engineering, each feature makes the next feature harder to build. In compounding engineering, your goal is to make sure that each feature makes the next feature easier to build. Um, and we do that in this loop.

我们正从 Python、JavaScript 这些脚本语言往上挪，挪到了英文这一层。我们给这个流程起的名字叫 Compounding Engineering。我是这么讲 Compounding Engineering 的：在传统工程里，每做一个功能，都会让下一个功能更难做。而在 Compounding Engineering 里，你的目标是确保每做一个功能，都让下一个功能更容易做。我们是在一个循环里做到这件事的。

[9:14]

Um, the loop has four steps. The first one is plan. And if you're you've been here today, you've been paying attention, you know how important it is when you're working with agents to make a really really detailed plan. So I think everyone is doing that. Second step is delegate. Just like go tell the agent to do it. Everyone's doing that too. Third step is assess. And we have tons and tons of ways to um assess whether the work that the agent did is any good. There's tests, there's trying it, there's having the agent uh figure it out. There's there's code review, there's agent code review, there's all

这个循环有四步。第一步是「规划（plan）」。如果你今天一直在场、一直在认真听，你就知道跟 agent 协作时，做一份非常非常详细的计划有多重要。所以我想大家都在做这件事。第二步是「委派（delegate）」，就是直接让 agent 去把它做了，这个大家也都在做。第三步是「评估（assess）」，我们有海量的办法去评估 agent 干的活到底好不好：有测试、有亲自试用、有让 agent 自己去搞清楚、有 code review、有 agent code review，各种各样的招数。

[9:42]

this types of stuff. And then the last step which is I think the most interesting one is codify. And this is kind of like the the money step which is where you compound everything that you've learned from the planning stage, the delegation stage, the assessment stage back into prompts that go into your, you know, your cloud MD file or your um your sub aents or your slash commands and you start to um basically create this library. You take all the tacet knowledge that you pick up um that all your engineers are picking up um as they find bugs, fix plans, um delegate work, and you um you make it

然后最后一步——我觉得是最有意思的一步——是「沉淀（codify）」。这有点像那个「最值钱的一步」：你把规划阶段、委派阶段、评估阶段里学到的一切，全都复利式地沉淀回 prompt 里，写进你的 Claude MD 文件、你的 sub-agent、你的 slash command 里，然后你就开始打造出这么一个库。你把你和你所有工程师在找 bug、修计划、委派工作的过程中积累下来的那些只可意会的隐性知识全都收集起来，把它……

[10:25]

into an explicit collection of prompts that you can spread for your entire organization. And um when you do that really well, there's a lot of like really interesting um second order effects that are are not I think that well understood or or that commonly talked about that I think would be interesting to to bring here because my guess is that um some people are already seeing this, but like maybe it needs to be pushed on a little bit more to like really be brought out and some people uh it might be an interesting way to get more of your organization to buy into using these tools. tools 100% of

……变成一套显式的 prompt 集合，可以铺给你整个组织用。当你把这件事做得特别好的时候，会出现很多特别有意思的二阶效应——我觉得这些效应还没被很好地理解、也没被经常拿出来谈，所以我觉得在这儿讲一讲会挺有意思。我猜有些人其实已经看到这些了，但可能还需要再往前推一把，才能真正把它显现出来。对另一些人来说，这或许是个有意思的切入点，能让你组织里更多人愿意去 100% ……

[11:00]

the time. Um, so the first thing that you notice if you sort of if you set up this process and you and you're like 100% bought in on something like compounding engineering um is that tacet code sharing becomes much easier. So uh we have we have multiple products at every a lot of a lot of products a lot of times need to implement similar things even if they use different technologies or imple implementing similar things like a team's feature or a certain type of ooth or whatever. Um previously in order to share code you'd have to like abstract out whatever you did into a library and then like allow

……地用上这些工具。第一件你会注意到的事是：如果你把这套流程搭起来、并且全身心地投入到像 Compounding Engineering 这样的东西里，那么隐性的代码共享会变得容易得多。我们在 Every 有好几款产品，很多产品很多时候需要实现一些相似的东西，哪怕它们用的技术不一样——比如说实现一个团队（teams）功能，或者某种 OAuth 之类的。以前你要想共享代码，你得先把你做的东西抽象成一个库，然后再让……

[11:36]

someone else to download it and it it'd be hard to do or you'd have to talk about it. with agents. Um you can just point your cloud code instance at um the repo from the developer sitting next to you and learn the process that they went through to build the feature that they that you need to reimplement and reimplement it yourself in your own tech stack in your own framework and in your own way. Um, and that's really really cool to kind of have this the more developers you have working on different things inside of the org, the more you can um share without any extra cost because AI can just go read all the code

……别人去下载它，这事做起来很费劲，要不然你就得当面聊。但有了 agent，你只要把你的 Claude Code 实例指向旁边那位开发者的 repo，就能学到他当初构建那个你现在需要重做的功能时走过的整个流程，然后用你自己的技术栈、你自己的框架、你自己的方式把它重新实现一遍。这真的特别酷——组织里在不同方向上干活的开发者越多，你能共享的东西就越多，而且几乎不增加任何额外成本，因为 AI 可以直接把所有代码读一遍……

[12:09]

and and um and use it. Um, another really cool thing that I've noticed is that new hires are productive on their first day because you've taken all of the things that you've learned about like, okay, how do I set up an environment and what does a good commit look like and all this kind of stuff and on the first day they have all that set up in their in their, you know, cloudmd files or their cursor files or uh codec files or whatever and um the agent just sets up their local environment and knows how to write a good PR. That's really cool. It also helps if you um want to hire like expert freelancers.

……然后拿来用。我注意到的另一件特别酷的事是：新员工第一天就能产出。因为你已经把那些你摸索出来的东西——比如「怎么搭开发环境」「一个好的 commit 长什么样」之类的——全都攒下来了，新人第一天来，这些就已经在他们的 Claude MD 文件、Cursor 文件、Codex 文件之类的里面配好了，agent 直接就把他们的本地环境搭好，还知道怎么写一个好的 PR。这真的很酷。如果你想雇那种专家级的自由职业者，这一点也很有帮助。

[12:49]

Like there's some there's one guy there's one person who just is really good at this one specific thing. You can have them come in for a day and like do that thing. It's I think of it a little bit like um like a DJ or whatever can like go in on like a couple bars of a song. Like you can just sort of drop in and that's really helpful. it's it would ordinarily be like too hard to collaborate because the the startup cost is too high, but you can do that a lot better now.

比如说，总有那么一个人，特别擅长某一件具体的事。你可以请他来一天，专门把那件事搞定。我觉得这有点像一个 DJ 之类的，能上来给一首歌加几个小节——你可以随时插进来帮一手，特别管用。换作以前，这种协作基本搞不起来，因为启动成本太高了，但现在做这种事容易多了。

[13:16]

Um, another thing that I've noticed which is really cool too is um developers inside of every commit to um other products. So, uh you know we have four products that run internally. Everybody uses all the products. If someone uh runs into a bug or a paper cutter, like a little minor quality of life thing that they want, they will um often just um they will often just uh just submit a poll request for it to other GM of the app um because it's very easy for them to go download the repo and figure out uh or have really have Claude or Codeex figure out, okay, this is how we fix the bug or this is how we

还有一件我觉得特别酷的事：Every 内部的开发者会给别的产品提交代码。我们内部跑着四款产品，每个人都在用所有这些产品。如果有人碰到一个 bug，或者一个小到让人膈应、想顺手改掉的体验问题，他们往往就直接给那个产品的负责人提一个 PR。因为现在对他们来说太简单了——把代码仓库拉下来，自己琢磨，或者干脆让 Claude 或 Codex 去搞清楚，好，这个 bug 该这么修，或者这个该……

[13:55]

fix the paper cut. Um and that's really really cool because you have this much um much easier way of collaborating across apps that I I think over the next couple years I imagine that you will also be able to let customers do this to some extent like if you run into a bug um this is you know speculative but if you run into a bug you can have your little agent fix it um and submit it as a pull request it's a weird open source thing but um yeah this is really really cool and and definitely is happening a lot inside of our company [snorts] Um, another really cool thing is um, we we have not this may get different as we

……这个小毛病该这么修。这真的特别酷，因为你跨产品协作的方式一下子变得轻松太多了。我估计接下来这几年，你甚至能在一定程度上让用户也这么干——比如你碰到一个 bug，这当然还只是设想，但你可以让你自己的小 agent 把它修好，然后以 PR 的形式提交上来。这是一种很奇特的开源玩法，但是，对，真的特别酷，而且在我们公司内部确实经常发生。[笑声] 还有一件特别酷的事是，我们——这一点等我们规模扩大可能会变——但我们到现在……

[14:36]

as we scale, but um, we have not yet had to standardize onto a particular stack or language. We instead let everyone who's building different products like pick the thing that they like best and the reason is because it makes it AI makes it much easier to translate between them. Um, and it makes it much easier to to jump into any language and framework and environment and be productive. And so it we don't uh it's easier for us to let people just do the thing that that they like and let AI kind of like handle the translation in between.

……随着规模扩大可能会变，但我们到现在都还没被迫统一到某一套技术栈或某一种语言上。我们反而是让每个做不同产品的人自己挑最顺手的，原因是 AI 让这些东西之间的转译变得容易多了。它也让你跳进任何一种语言、框架和环境都能很快产出。所以我们不用统一，对我们来说，让大家就用自己喜欢的那套、剩下的转译交给 AI 去处理，反而更省事。

[15:06]

Um and the last thing which is my favorite but like is also the horror I think of of some developers and to some degree maybe the horror of my team um is that managers can commit code. um if you're technical uh even the CEO and um for for me like I have no business committing code because we've got four products we've got 15 people we're growing really fast um I'm doing tons and tons of other things but I can and I I have like committed production code over the last couple months and the reason for that is AI allows um engineers to work with fractured attention so previously you might have needed like a 3 or 4 hour block of focus

最后一点是我最喜欢的，但我觉得它同时也是某些开发者的噩梦，某种程度上可能也是我们团队的噩梦——那就是管理者也能提交代码。只要你懂技术，哪怕是 CEO 也行。对我来说，我本来是没什么理由去提交代码的，我们有四款产品、15 个人、增长又特别快，我手上还有一堆别的事要忙；但我确实可以，而且过去这几个月我真的往生产环境提交过代码。原因是 AI 让工程师能在注意力被打碎的状态下工作。以前你可能需要一整块三四个小时的专注……

[15:45]

time in order to like get anything done. Um, but with cloud code, you can kind of like get out of meeting and say, "Hey, like I want you to investigate this bug." And then go do something else and then come back and you have like a a plan or like a um root cause fix and then you can submit a PR. And it's not easy. It's not magic, but it is actually possible. And I think that's a that's just a totally new way of thinking how thinking of thinking about how managers interact with the products that they make.

……才能做成点什么。但有了 Claude Code，你可以刚开完会就说：「嘿，我想让你去查一下这个 bug。」然后就去忙别的，回来时手上已经有了一个方案，或者一个找到根因的修复，接着你就能提一个 PR。这并不轻松，也不是什么魔法，但它确实是可行的。我觉得这是一种全新的思路——管理者该如何与他们亲手做的产品打交道。

[16:17]

So, um, just to just to summarize, um, there's a I really think there's a 10x difference in how things work when you hit 100% AI adoption. I think, um, from what we've seen, a single engineer should be able to build and maintain a complex production product. what we call compounding engineering, but I think what all of us are are sort of pointing to um is I I think really works to make each feature easier to build and then creates all of these sort of nonobvious second order effects that makes it easier for the entire organization to collaborate together.

所以，简单总结一下：我真心觉得，当你把 AI 采用率拉到 100% 时，做事的方式会有 10 倍的差别。从我们目前看到的情况，单个工程师应该就能构建并维护一款复杂的生产级产品。这就是我们说的 Compounding Engineering（复利式工程），但我觉得我们大家其实都在指向同一件事：它真正起作用的地方，是让每一个功能都更容易做出来，进而催生出一堆并不那么显而易见的二阶效应，让整个组织协作起来都更顺畅。

[16:54]

And very importantly, many people in San Francisco don't know this yet. Um so you're you're the first to hear it. Um so that is my talk. So, if you're interested in um in what we do, uh I run every uh Every is the only subscription you need to stay at the edge of AI. You can find us at every.to. Um we uh we have a daily newsletter about AI. So, we do ideas, apps, and training. We have a on the ideas side, we have a daily newsletter. We review all the new models when they come out and all the new products when they come out. the apps.

而且很重要的一点是，旧金山很多人还不知道这件事，所以你们是第一批听到的。好，这就是我的演讲。如果你对我们做的事感兴趣，我经营的是 Every——Every 是你站在 AI 最前沿所需要的唯一一份订阅。你可以在 every.to 找到我们。我们有一份关于 AI 的日报。我们做三件事：ideas（思想）、apps（产品）和 training（培训）。在 ideas 这边，我们有一份日报，每当有新模型发布我们都会评测，每当有新产品发布我们也都会评测。还有 apps（产品）。

[17:26]

You already saw we've a bundle of all these apps and then we do training and consulting with big companies to help them use AI and it's all bundled into one subscription so you get everything for one price and that's it. Thank you very much. [music]

你们刚才已经看到了，我们把这一整套 app 打包在一起；然后我们还为大公司做培训和咨询，帮他们用好 AI——这一切全部打包进一份订阅里，所以你一个价格就能拿到全部。就这些。非常感谢大家。[音乐]