AI integration for enterprise ft. CJ Desai of ServiceNow - YouTube

This year, at AI Ascent, we are doing a few things differently. One of those things is the what's next section that we talked about, these visionary ideas. Another is the what's now that Sonya has been talking about, about how are people taking things in AI and implementing them. As part of this, we don't just have the amazing foundation model CEOs like Sam, Ann, Arthur, and Daniella. We've also brought in two exceptional leaders in the space of taking AI and making it enterprise-ready at scale. One of those is CJ. CJ has been the president and COO of ServiceNow for the past seven years. And in addition to ServiceNow being a Sequoia backed company for over a decade, ServiceNow is in an exceptional business. It's the kind of business anyone in this room should aspire to be like.

今年在AI Ascent大会上，我们做了一些不同的事情。其中之一是我们谈论过的“未来展望”部分，包括一些前瞻性的想法。另一个是索尼雅一直在谈的“现状”，即人们如何将AI技术应用于实践中。作为其中的一部分，我们不仅邀请了像Sam、Ann、Arthur和Daniella这样杰出的基础模型公司的CEO。我们还邀请了两位在将AI技术应用于企业规模上并使之就绪的卓越领导者。其中之一就是CJ。CJ在过去七年一直担任ServiceNow的总裁兼首席运营官。除了ServiceNow在过去十年中得到Sequoia的支持外，ServiceNow的业务也非常优秀。这是任何在座的人都应该向往的业务模式。

Pat, I believe, sourced the business in 2012. Is that right? 2009. And what was the scale of the business then, Pat? 20. What? Million of ARR. Okay. Anyone have a guess as to where ServiceNow is now in terms of ARR? Annie, I feel like you know this. 1.4. Billion? One more guess. 20 billion? Okay. Somewhere in that range is correct. So ServiceNow is the third largest software-to-service company in the world. It has a market cap of $155 billion. It is about to cross 10 billion of ARR. It's at 9.75 billion of ARR. Remarkably, when you took over as president and COO seven years ago, it was at a billion of ARR. So it's 10x growth. And it was 13 billion of market cap. So it's been a 12 plus x multiple from there. It's adding 600 million of ARR a quarter. So let that be something to aspire to.

帕特，我相信他在2012年找到了这个业务。是这样吗？2009年。那时这个业务规模如何，帕特？20。什么？年度重复收入（ARR）2000万。好的。有人猜测ServiceNow现在的年度重复收入是多少吗？安妮，我觉得你知道这个。1.4。十亿？再猜一次。200亿？好的。大约在这个范围内是正确的。所以ServiceNow是全球第三大软件服务公司。它的市值为1550亿美元。它即将突破100亿的ARR。它目前的ARR为97.5亿美元。令人惊讶的是，七年前你接任总裁和首席运营官时，它的ARR为10亿美元。所以增长了10倍。当时市值为130亿。所以它从那时起增加了12倍以上。它每个季度增加6亿的ARR。让我们把这作为一个值得努力追求的目标。

And I mentioned it's the third largest SaaS company in the world. Well, number one is growing at 11% a year. Number two is growing at 12% a year. And ServiceNow is growing at 26% a year. So we all argued at math that ranking doesn't last very long with that kind of growth. And CJ told me virtually all of this has been organic. They've made some acquisitions like Element AI. We'll talk about that in a little bit. They've been very ahead of the curve on AI. But really, it's been organic. It's called ServiceNow, but it does not have services margins. This is an 82% gross margin business. The free cash flow is 30%. Operating income 27%.

我提到它是世界第三大SaaS公司。第一名增长速度为11％，第二名增长速度为12％，而ServiceNow的增长速度为26％。所以我们都认为，在这种增长速度下，排名不会持续很长时间。CJ告诉我，几乎所有这一切都是自然发展的。他们进行了一些收购，比如Element AI，稍后我们会谈到这个。他们在AI领域走在了时代的前沿。但事实上，这是一种有机增长。虽然它被称为ServiceNow，但实际上并不具备服务利润率。这是一个毛利率为82％的生意。自由现金流为30％。营业收入为27％。

This is a rule of 56 business on the rule of 40 terms. And since IPO since Pat sourced it in 07, I don't know what kind of multiple it's had. What was the valuation then Pat? What did Moon me invest in? 260 million posts. That's pretty good from 260 million posts to 155 billion nicely done. Since IPO, it's been up 42 times, 42x returns. So an exceptional story and one that I think is both grounding and also aspirational for everyone in this room. One of the main reasons why we were so excited to have you come CJ is ServiceNow has been way ahead of the curve on AI.

这是56守则上的40守则业务。自07年帕特发现它以来，我不知道它经历了什么样的倍数。当时帕特，估值是多少？我在“月亮我”投资了什么？260亿个帖子。从260亿个帖子到1550亿美元，做得非常好。自IPO以来，它已经翻了42倍，42倍的回报。这是一个非常杰出的故事，我认为对在座的每个人来说既具有现实意义又具有憧憬意义。我们很兴奋你来CJ的主要原因之一是ServiceNow在人工智能方面走在时代的前沿。

We first met actually in a conversation where you were talking about the AI vision with NVIDIA, with Jensen and the NVIDIA team. And we might have a clip actually, but just yesterday at the NVIDIA conference, ServiceNow was a main feature, the specific use cases on the NVIDIA platform. And at the previous conference, it comes up as a main user. My first question for you CJ is, please tell us how you got here to this exceptional role as COO where you do much of the product work. And then please tell us how you've gotten the AI suite, what it is today and how you've gotten the AI suite to where it is.

我们实际上是在一次对话中首次相遇的，在那次对话中，您讨论了与NVIDIA、Jensen和NVIDIA团队相关的人工智能愿景。也许我们确实有一个片段，就在昨天在NVIDIA大会上，ServiceNow成为了一个主要亮点，在NVIDIA平台上具体使用案例。在先前的会议上，它作为一个主要用户出现。我的第一个问题是，请告诉我们，CJ，您是如何到达这个卓越的COO角色的，您在其中承担了很多产品工作。然后请告诉我们，您是如何将人工智能套件发展到今天的状态，以及您是如何将人工智能套件发展到当前的水平的。

Yeah. So first of all, thank you for inviting me. And he asked me a fun fact and the fun fact is that I'm a failed stand-up comedian. So I'm constantly working on the material to try something out, a very high self-deprecating humor that you will see from time to time. And at the highest level, I want to say that we are extremely, extremely grateful to Sequoia. And here is a simple story. The story is that before we were going public in 2012 is when we went public, with a modest market cap of $3.9 billion. Okay. That's when we went public in 2012. And it was a meh IPO.

是的。首先，感谢邀请我。然后他问了我一个有趣的事实，那就是我曾经是一个失败的脱口秀演员。所以我一直在努力改进材料，尝试一些自嘲幽默，你们会不时看到的。在最高水平上，我想说我们对Sequoia非常非常感激。这里有一个简单的故事。故事是，我们在2012年上市之前，也就是2012年上市时，市值只有39亿美元。好吧，那就是我们在2012年上市的时候。那次IPO效果一般。

People like it. Yeah. Facebook was pretty good back there. It was called Facebook. Same year. And Workday was another one. And we had a meh IPO. But before that, VMware made an offer to service now for single-digit billions, single-digit billions below five. And Doug Leone and the Sequoia team convinced the management team, which would have been happy to take that offer because they're like, wow, we don't have to go public. We can be part of a great company like VMware at the time. And Doug Leone, to his credit, convinced not only the board, but also the management team that you can become big.

人们喜欢它。是的。当时Facebook很不错。它当时被称为Facebook。同一年，还有Workday。我们进行了一次不太成功的首次公开募股。但在那之前，VMware给ServiceNow提出了一个几十亿美元的收购报价，且不足五十亿美元。Doug Leone和Sequoia团队说服了管理团队，他们本来很乐意接受这个报价，因为想着，哇，我们不用上市，可以成为当时VMware这样伟大公司的一部分。Doug Leone真是很了不起，他不仅说服了董事会，还说服了管理团队，让他们相信可以走得更远。

So we are extremely grateful for Sequoia's coaching at that point in time. And for the $2 billion offer, which we could have taken, versus today's $155 billion in just a matter of 12 years, it's incredible. So thank you to Sequoia and the team for sourcing us and believing in us and allowing us to get here because it would have been a very easy thing for Doug to say who was on the board. And the return would have been amazing for Sequoia at that point in time. And we still walked away. CJ Taxon, to me before I said, excited to see you can't wait to be part of the cult that is Sequoia. Yeah. You're already in it now. I am. But I just wanted to be thankful and grateful. And you guys work with great people at Sequoia. And I never take that lightly. And on the path to our growth, we never forget our friends and supporters. So I just wanted to start there. Number two on the scale. So I joined the company. So Frank Slootman hired me. And Frank Slootman was also placed by Sequoia at ServiceNow. And Frank had two choices at the time, which is, I think, public knowledge. But Frank's data domain gets acquired. And then he decided, and I make fun of Jess all the time on this topic, but he decides that he's going to be a VC. And he joined Greylock. And if you have met Frank Slootman, which I'm sure some of you have, he is not a Sandhill guy.

所以我们非常感激 Sequoia 在那个时候的指导。而且对于当时我们可以接受的 20 亿美元的报价，相比于今天短短 12 年内就增长到 1550 亿美元，真是令人难以置信。所以感谢 Sequoia 团队为我们提供支持和信任，并让我们走到了今天这一步，因为对于当时董事会上的 Doug 来说，这本来是件很容易的事情。而 Sequoia 当时的回报将会非常可观。然而我们还是选择离开了。CJ Taxon 在我之前说过，很高兴看到你，迫不及待地成为 Sequoia 的一部分。是的，你现在已经是了。但我只是想表达我的感激之情。你们在 Sequoia 与伟大的人们合作。我永远不会轻视这一点。在我们的成长道路上，我们永远不会忘记我们的朋友和支持者。所以我想从这里开始。接下来是第二点。我加入了公司。Frank Slootman 招聘了我。而 Frank Slootman 也是 Sequoia 安置在 ServiceNow 的人选。当时 Frank 有两个选择，我认为这是公开的信息。但是 Frank 的 Data Domain 被收购了。然后他决定，我一直在拿 Jess 开玩笑，但他决定要成为一名风险投资人。于是他加入了 Greylock。如果你见过 Frank Slootman，我相信有些人见过，他不是一个 Sanhill 的人。

So he said, no, I need to go back to operational CEO job. And it was Sequoia that convinced him, Frank had two offers, Palo Alto Network CEO, or ServiceNow CEO. And he picked ServiceNow. At that point in time. And there was also Sequoia was behind it. So when Frank hired me, we were doing billion plus in ARR. And Frank said CJ, by 2020, if we can get to four billion of ARR, that would be a massive W. And let's go for it. And our founder who created the company close to at age of 50, Fred Luddy, who became bankrupt. So this is not a classic Stanford Harvard story, but it's like he went to Indiana University and it's originally from Indiana. And he said, I'm going to create a platform that can solve multiple use cases. And so we always knew that TAM was pretty much unlimited. And the platform provided everything you need to create a product or multiple products.

所以他说，不，我需要回到实际执行首席执行官的工作。是红杉资本说服了他，弗兰克有两个选择，帕洛阿尔托网络公司首席执行官，或者ServiceNow首席执行官。他选择了ServiceNow。在那个时候。红杉资本也支持着他。所以当弗兰克雇佣我时，我们的年度重复收入超过十亿美元。弗兰克说，CJ，到2020年，如果我们能达到四十亿美元的年度重复收入，那将是一个巨大的胜利。让我们为之努力。我们的创始人弗雷德·拉迪在五十岁左右创立了这家公司，后来破产了。所以这不是一个经典的斯坦福哈佛故事，而是他去了印第安纳大学并且原本来自印第安纳。他说，我要创建一个可以解决多个用例的平台。所以我们一直知道总地址可能是无限的。这个平台提供了你创建一个产品或多个产品所需的一切。

And so when I joined, we were one-ish billion. We had one large product and two or three small products. And since then, it has been brutal execution on which buyers we go out of. Like the simple question on when my product team comes and says, hey, we can create this great product. My first question is, who is the buyer? Do we have access to that buyer? Is that buyer next door or two doors down or five doors down? And will current buyer introduce us to that buyer or those two buyers don't talk to each other? Those kind of simple questions on who is the buyer? Who are we competing against? And even though this is very simple, the third one, what is the size of the price? That if we nail this use case, can we create a billion dollar ARR product? Again, another product. So we have been doing that level of precise execution. And that's what has helped us on organic innovation. We haven't bought revenue. We are the only SaaS company that has not bought revenue on our path to 10. And we always buy amazing companies, which has great people. And then we make them work on our platform. But that's how we have scaled now from 2016 billion plus to 2023.

因此，当我加入公司时，我们规模大约是十亿美元。我们有一个大型产品和两三个小产品。从那时起，我们一直在残酷地执行，确定要进入哪些市场。比如，当我的产品团队来告诉我说，我们可以推出一个很棒的产品时，我的第一个问题是，谁是买家？我们是否可以接触到这个买家？这个买家是在隔壁还是两个街区以外或者五个街区以外？目前的买家是否会介绍我们给那个买家，或者这两个买家不会互相交流？这些简单的问题关于谁是买家？我们在和谁竞争？即使这些问题都很简单，第三个问题是，价格有多大？如果我们成功应用这个案例，我们能否创造一个每年十亿美元的产品ARR？再次，另一个产品。所以我们一直在进行精密执行。这就是帮助我们进行有机创新的关键。我们没有买来收入。我们是唯一一家在通往十亿美元之路上没有购买收入的SaaS公司。我们总是购买那些优秀公司，拥有优秀人才。然后让他们在我们的平台上工作。这就是我们如何从2016年的十亿美元以上扩展到2023年的方式。

When we exited the December quarter, we already reached 10 billion of ACV. And then of course the revenue trails a little bit. And we guided for 10.75 billion growing at 21%. I mean, these are some of the numbers, but it has been, hey, you have an underlying platform that's cloud based. What products do you create? What are you solving for? Who is the buyer? Right, that brutal focus on who is the buyer? Do we have access to the buyer? And what is the size of the price? And without that, with my product team and engineering team, and I joined as a head of products and engineering, Frank hired me and left after that. But that's been the focus.

当我们离开12月季度时，我们已经达到了100亿的ACV。当然，收入稍微滞后一点。我们预测10.75亿，增长21%。我是说，这些是一些数字，但事实上，你有一个基于云的基础平台。你创造什么产品？你解决了什么问题？谁是购买者？对，对购买者的残酷关注？我们是否有权访问购买者？价格是多大？没有这个，还有我的产品团队和工程团队，我作为产品和工程负责人加入，Frank雇了我后就离开了。但那一直是焦点。

And on AI, it's as simple as we had a fundamental belief from supervised machine learning and as AI evolved all the way to Gen AI today. We have been very focused on AI in service of our use cases. Because if we can infuse AI in our use cases, it's a very easy conversation with a JP Morgan Chase or a Citibank or United States Army that, hey, you are using service now for this use case. AI will help accelerate X or accelerate Y. And so we have been acquiring or gaining small teams that are AI experts at various stages all the way from 2016. 2017 was our first one. 2016, we started the journey.

在人工智能方面，我们坚信从监督式机器学习开始，随着人工智能发展到如今的Gen AI阶段，这一切都是很简单的。我们一直致力于人工智能为我们的使用案例提供服务。因为如果我们能够将人工智能融入我们的使用案例中，就会很容易与摩根大通银行、花旗银行或美国陆军等进行对话，告诉他们，你们正在为这个使用案例使用ServiceNow。人工智能将帮助加速X或加速Y。因此，我们一直在不同阶段收购或招揽小团队，这些团队都是人工智能专家，从2016年开始直至现在。2017年是我们的第一个团队，2016年我们开始这一旅程。

And then when we bought Element AI, they were trying to be the next Google of Canada. And they had somewhere between 170 to 180 engineers between PhDs, data scientists, and engineers. And they were in this amazing team. A lot of very well-known people, Yoshua Bengio, who won the Turing Award, was part of that team. There are people who have written some seminal paper on transformer model. That's the kind of team we got. And the call I got from Allen and Company was, hey, this is a great team. They have no revenue, zero. And they are trying to figure out what use case AI can be applied to.

当我们收购Element AI时，他们试图成为加拿大的下一个谷歌。他们拥有约170至180名工程师，包括博士、数据科学家和工程师。他们是一个令人惊叹的团队，有很多知名人士，比如获得图灵奖的Yoshua Bengio也是团队的一部分。还有一些人在转换器模型上写过一些具有开创性的论文。这就是我们得到的团队。艾伦公司打来电话说，“嘿，这是一个很棒的团队。他们没有任何收入，零。他们正在努力找出AI可以应用在哪些用例。”

And this was during pandemic. And I went to my boss, our CEO, and I said, hey, man, these people don't have any revenue, but it's a great talent. And we need to spend some money and to build credit. He said, absolutely, if you believe this is a great talent, let's take them. And that, they showed me chat GPT 1015, two-or-demos in 2020, late and early 2021. And then when this whole thing just blew up in 2022, we exactly knew where we could apply LLMs to our use cases. And again, I don't know if it's a term, but SLMs, we are very use case-specific LLMs that we apply in service now. And we started our monetization strategy in September. So that's the story. I know it was a simple question, but I had to give a pretty long answer, because there's a lot of history to it. Really incredible.

这发生在疫情期间。我去找我的老板，我们的首席执行官，我说，嘿，这些人没有任何收入，但是他们拥有很棒的才华。我们需要花一些钱来建立信誉。他说，绝对可以，如果你认为这是很棒的才华，那就招揽他们吧。那时，他们向我展示了2020年晚些时候和2021年初的Chat GPT 1015，还有演示。然后，当这整个事情在2022年爆发时，我们清楚地知道我们在哪里可以应用LLMs到我们的使用案例。再次强调，我不知道这是否是一个术语，但我们在服务现在非常使用案例特定的LLM，即SLMs。我们从9月开始了我们的货币化策略。这就是整个故事。我知道这是一个简单的问题，但我不得不给出一个相对较长的答案，因为这其中有很多历史。非常不可思议。

And I didn't realize, frankly, until this conversation that you guys are the only SaaS business ever to cross the 10 billion ARR plant fully organically. That's remarkable. And frankly, I've talked to a bunch of people at ServiceNow. You are so much of the product brain. It's such a pleasure to get to learn from you. This question is on-product. So you guys had a little bit of a head start a few years, because I know you and Bill had been talking about AI even ahead of the element acquisition.

老实说，直到这次对话之前，我才意识到你们是唯一一个完全依靠自身努力实现了100亿美元的SaaS企业。这真是了不起。而且，坦率地说，我和ServiceNow的很多人都有过交流，你们在产品方面确实非常出色。能够从你们这里学到东西真是一种享受。这个问题是关于产品的。所以你们几年前就已经有一点优势了，因为我知道你和比尔在Element收购之前就已经开始讨论人工智能了。

But then with the element acquisition, you got to think about how you're going to integrate into your product. Tell us about how you got up the curve, and now how AI is in ServiceNow products, maybe a couple of examples. Yeah. So I'll just take the recent example. We are a big fan of open source community when it comes to AI. Even on the NLU models, we worked with Stanford to figure out which libraries we can use, which was four or five years ago. But we are a big fan of open source community.

但是随着元素的获得，你必须考虑如何将其整合进你的产品。告诉我们你是如何逐步提高技能水平的，以及现在怎样在ServiceNow产品中运用人工智能，也许可以举几个例子。是的。我只想拿最近的例子来说。在涉及人工智能时，我们很喜欢开源社区。即使在自然语言理解模型上，我们也是与斯坦福大学合作，找出可以使用的库，这是四五年前的事情。但我们非常喜欢开源社区。

And the team in Canada, working with hugging face, figured out for which use cases of ServiceNow you can apply AI. So then we said, okay, now listen, you talked about our gross margins. Our gross margins are 82%. And all of you run the companies, your profitability starts at your gross margin level. That's your first step or staircase, 82. Then you add R&D cost, sales and marketing cost, DNA cost, and then you get to profitability. So we are world class in terms of our gross margin at scale.

加拿大团队与Hugging Face合作，找出了ServiceNow可以应用人工智能的使用案例。然后我们说，好吧，现在听着，你们谈到了我们的毛利率。我们的毛利率是82%。你们所有人经营公司，你们的盈利从毛利率水平开始。这是你们的第一步或楼梯，82。然后加上研发成本、销售和营销成本、DNA成本，就能实现盈利。因此，从规模上看，我们在毛利率方面是世界一流的。

So I don't have the luxury. It's a constraint-driven optimization problem that I don't have the luxury to say, I'm going to run open AI everywhere in my farm, in our cloud, because we are 100% cloud company, with 170 billion, who knows 2 trillion parameters now, with 4.0. I don't have that luxury. So the constraint was, can I run smaller models faster with lower latency for ServiceNow use cases. And there was a constraint-driven innovation, and we partnered with hugging face our science and research team.

所以我没有这种奢侈。这是一个受限制的优化问题，我没有这种奢侈来说，我会在我的农场里的每个地方、在我们的云中无处不在地运行Open AI，因为我们是一个百分之百的云公司，有着 1700亿、谁知道现在是2万亿参数，使用着4.0版本。我没有这种奢侈。所以约束是，我能否为ServiceNow的用例快速地以更低的延迟运行更小的模型。这是一个受限制的创新，我们与 Hugging Face 我们的科学和研究团队合作。

And we came up with the first model on text to code. And we are not trying to do text to code like GitHub co-pilot with Java or anything. Our text to code was specifically ServiceNow code, how you configure ServiceNow. And there was our first breakthrough working with hugging face. And then once we do that, and you know, you talked about Jensen, he's a big fan of Canada. So when we acquired element AI. Canada. Yes. So when we acquired element AI, it was the first phone call he made and said, CJ, loudly Canadian talent, we should do more together. And that was in 2020. Because his history with you, Toronto, and ImageNet and all of those things.

我们提出了第一个文本转代码的模型。我们并不像GitHub合伙人一样尝试用Java或其他语言进行文本到代码的转换。我们的文本到代码针对的是ServiceNow的代码，也就是如何配置ServiceNow。这是我们与hugging face合作的第一个突破。之后，你知道，你提到了詹森，他是加拿大的超级粉丝。所以当我们收购了元素AI公司。加拿大。是的。所以当我们收购了元素AI公司，他第一个打电话给我，大声表示我们应该更多的合作，因为加拿大有很多才华。这是在2020年。因为他和多伦多，ImageNet等方面有历史渊源。

So what we did is that Canada team, working with hugging face, we figured out smaller models, one tenth the size of open AI. And I told Jensen, hey man, dude, you are constantly pushing the next round H class, plus plus. I need these to run on A100. And that's what we'll work for because we are a public company. So you have 1% gross margin, D sell, and the number of questions I get from investors, like you get from VCs all the time, are not fun. So, yes. We basically said I want smaller model that can run on A100. And I can replicate that in every cloud.

所以我们做的是，加拿大团队与Hugging Face合作，我们找出了比Open AI小十分之一的模型。我告诉Jensen，哥们儿，你不断地推动下一轮H类，再加加。我需要这些在A100上运行。因为我们是一家上市公司，所以我们会努力达成这个目标。所以你只有1%的毛利，D销售，以及投资者问我的问题数量，就像你经常从风投那里得到的一样，都不好玩。所以，是的。我们基本上说我想要能在A100上运行的更小的模型。我可以在每个云中复制这一点。

He's still always trying to push me. He's a great salesman, even though he acts like he isn't. He's always trying to push for H to say H is faster, more efficient, which is right. But we wanted something to run on A. So the smaller model, smaller models is where we are going with use cases. Well, I hear you're really going to need Blackwell. Yes, I know. 30,000 dollars? Exactly. Yeah. What's that to you? Fabulous. Team, I have one more question for CJ, and I'm giving you that heads up so that you come up with a couple of questions top of mind.

他仍然总是试图推动我。他是一个很棒的销售员，虽然他行事并不像是。他总是试图让H说H更快，更有效率，这是正确的。但我们希望有一些适用于A的东西。所以我们打算用小型模型，小型模型是我们要使用用例。嗯，我听说你确实需要布莱克韦尔。是的，我知道。3万美元？对，就是这个数。嗯。这对你来说算什么？棒极了。团队，我还有一个问题要问CJ，我提前告诉你们这个消息，所以你们可以先想出一些问题。

CJ, we've got a room of builders here. And they're building many consumer companies, but also many enterprise companies. Frankly, you're a dream customer for a lot of the companies in this room. What can you tell people building products in this room to help guide them towards being a great AI builder that ServiceNow might consider partnering with and being a customer of? Yeah. So I said there are two places. So just when you look at me, look at my forehead, and it's a one billion dollar spend I have in my cloud and software. So if you want to sell something to me, make it quick, and I'll buy. Okay. But I spent one billion dollars, no jokes, on cloud and software and on the infrastructure a year and growing at 25% in line with our revenue. So that's how much I spent. So I can be a great customer of yours, or at least a prospect.

CJ，我们这里有一群建设者。 他们正在建设许多消费者公司，也有很多企业公司。 老实说，对于这个房间里的很多公司来说，你是一个梦想的客户。 你能告诉这个房间里正在开发产品的人们，以帮助他们成为 ServiceNow 可能考虑合作的出色人工智能构建者和客户吗？ 是的。 所以我说有两个地方。 当你看着我的时候，看着我的额头，我在云和软件上有十亿美元的花销。 所以如果你想向我出售什么，就赶快，我会买。 好了。 但我一年在云和软件以及基础设施上花了十亿美元，不是开玩笑，并且按照我们的收入以 25% 的速度增长。 这就是我花了多少钱。 所以我可以是你们的一个好客户，或者至少是一个潜在客户。

In terms of what works is, if you understand ServiceNow, which if you go to our website, you will not understand what ServiceNow does. But if you understand ServiceNow, we do basically a lot of workflows as in tasks that get orchestrated, digitally, in a certain sequence between human and machines. That's what we do. Because people at a large bank or a customer tell me that they can get a Tesla faster than getting a PC from the bank or a Mac from the bank when they order something. That's the reality of large corporations, large governments, and so on.

就业方面而言，如果您了解ServiceNow，就会知道我们主要是进行许多工作流程，即在人与机器之间以特定顺序进行数字编排的任务。这就是我们所做的。因为许多大银行或客户告诉我，他们可以更快地得到一辆特斯拉，而不是在从银行订购PC或Mac时。这就是大型企业、政府等的现实。

So when you request a PC at a bank, say, and banks try to be very efficient, the process is that it goes through, does it require two levels of approval? Some banks have four Mac four levels of approval. Then once those approvals are done, it needs to go to shipping department. Do they have inventory? They need to base image it. They need to put security crowds on it. And then it goes to, okay, what is going to her home address or is going to? These are the workflows. And these are the things that we automate behind the scene. So all you say is, I want to pick this PC. I want to pick this monitor. I want it to be delivered via FedEx tomorrow morning. That's the idea, right? But because of these complex workflows and the banks want to harden the image of the Mac that they give you if you're doing on a trading floor, that's where it takes us.

所以当你在银行或其他地方请求一台电脑时，银行会尽力提高效率。流程是这样的：需要经过两级批准吗？有些银行甚至需要四级批准。一旦批准完成，需要将电脑送到发货部门。他们有库存吗？他们需要给电脑安装基本镜像，加上安全设置。然后电脑就会寄到目的地，可能是你的家或其他地方。这些就是工作流程，我们在幕后会自动化处理这些问题。所以你只需说一声，我想要这台电脑，我想要这台显示器，明天早上通过FedEx寄送过来。这就是我们的理念。但是由于这些复杂的工作流程以及银行想要加强他们提供的Mac电脑的系统镜像，这就是我们要面对的挑战。

So that's what ServiceNow does. And then we infuse AI in making it simpler and faster. So for us, if you understand ServiceNow, and you can say, hey, CJ, for your use cases, here is the great technology that we have built. And you can consume this technology, whether it's your LLMs or whether it's a use case specific AI that you have done or some kind of analytics, whatever it is. Then you have my attention that if I can make the use cases for our customers better, I have your attention and I'll buy your product to make us go faster so we can deliver for our customers, right? We have only 8,000 customers, only 8,000. And if you think about 8,000 customers, 10 billion ARR, you can do the math pretty fast.

这就是ServiceNow的功能。然后我们加入人工智能，使其更简单更快速。对我们来说，如果你理解ServiceNow，你可以说：“嘿，CJ，针对你的使用情况，我们建立了很棒的技术。”你可以使用这项技术，无论是你的LLMs，还是你已经开发的特定用例的人工智能，又或者是某种类型的分析，不管是什么。那么，如果我可以让我们的客户使用情况更好，我会吸引你，我会购买你的产品，以加快我们为客户提供服务的速度，对吧？我们仅有8,000个客户，仅有8,000个。想想8,000个客户、100亿ARR，你可以很快做出计算。

But we have only 8,000 customers. And so I'm obsessed, like OCD level obsessed, that if you come in and say, here is what it can do for your use cases, I will listen to your page every day. Okay? So that's one. And I have enough money to spend if we can serve our customers better. And number two is we have a great go-to market team. So besides our engineering, AI, science, research team, we have a great go-to market team. And if you have something coming back to the buyer next door down person or two doors down person, and you want to leverage, CIO is our prime buyer.

但是我们只有8,000个客户。所以我很着迷，像强迫症一样着迷，如果你来了并说，这个产品对你的使用情况有什么好处，我会每天听你说。好吗？这是第一个。我有足够的钱可以花费，如果我们能更好地为我们的客户提供服务。第二是我们有一个很棒的市场团队。除了我们的工程、人工智能、科学、研究团队之外，我们还有一个很棒的市场团队。如果你有什么回馈给我们的买家或者两层楼下的人，而且你想利用，CIO是我们的主要买家。

If you think about CIOs, 10, 15, 20 years ago, till service now came, CIOs were serving other C-suite. Hey, for sales, I need to put sales force in. For marketing, I may need to put Adobe in. For finance, SAP, I need to put for the CFO. We were the first platform we said, this is the CIOs platform. So if you say that CIO is your buyer and you want access to the CIO, there is no better company to partner with than service now, right? The two companies that really sell to CIO well is ServiceNow and Microsoft. These are the two companies that sell really well. Brilliant. I'm sure quite a few people in this room are interested in that $1 billion of cloud span. All right, we've got time for, let's say, three to four questions.

如果你想到CIOs，10、15、20年前，直到ServiceNow出现之前，CIOs一直在为其他C级管理人员提供服务。嘿，为了销售，我需要加入销售团队。对于市场营销，我可能需要加入Adobe。对于财务，SAP，我需要为CFO加入。我们是第一个平台，我们说，这是CIO的平台。所以如果你说CIO是你的买家，你想要接触CIO，没有比与ServiceNow合作的更好的公司了，对吧？真正向CIO出售的两家公司是ServiceNow和Microsoft。这两家公司真的卖得很好。太棒了。我相信这个房间里有相当多的人对那100亿美元的云业务感兴趣。好的，我们有时间，让我们说，三到四个问题。

Michelle, hello. Thanks, UJ. Many of us have dreams of an act two. Some of us might already be thinking about act two in terms of a product. Any advice in the early days of how you think about resourcing and philosophy around experimentation versus intentional bets around act two's product development? Correct. So I will share a story that the reason our IPO was very mid is because people said that our TAM was only 1.8 billion. So one of the industry analysts said, these guys are not going to do well and their TAM is limited. Same thing happened to many, many companies where people say, I don't know if the TAM is there. So for us, that actually created a chip on our shoulder because we believed that the TAM for ServiceNow was a lot bigger than what the industry analyst community said it was, which was sub 2 billion. And this was in 2012, not too long ago. So one thing is on your core, core being core, you really, really have to understand what is the TAM, which is an art combined with science. Before you start saying, I want to go multi-product, I want to go now to different buyers or the same buyer, but multi-para-arex, whatever the strategy you want to go after with the buyer access, but the core has to be core. The reason you exist is for something. You have tried to solve a problem.

嗨，米歇尔。谢谢，UJ。我们很多人都对一个“第二幕”有梦想。有些人可能已经在考虑产品方面的“第二幕”。您在早期阶段如何考虑资源和实验与有意的投注在产品开发上的哲学方面有什么建议？正确。所以我将分享一个故事，我们的IPO很成功的原因是因为有人说我们的TAM只有18亿。所以其中一位行业分析师说，这些家伙不会做得太好，他们的TAM有限。很多公司也遇到了同样的情况，人们说，我不知道TAM是否存在。对我们来说，这实际上激起了我们的兴趣，因为我们相信ServiceNow的TAM比行业分析师社区所说的要大得多，他们说的是低于20亿。这是在2012年，不久之前。所以首先要关注你的核心，非常重要的是要真正了解TAM，这是一门融合了艺术和科学的学问。在你开始说我要推出多个产品，我要发展不同的买家或同一个买家但是多种产品线，无论你想要追求的策略是什么，但核心始终要保持原有的核心。你存在的理由是为了解决问题。

So really understand the TAM behind that core and then figure out before you go into the next act, why are you really going after that next act? So we prevented going after the next act till we hit 1 billion in ARR. And then overnight we flipped it and we said we are going to go after these three buying centers, security, HR and customer service, in addition to IT. And here is the go to market for it, here is the buyer for it, and we are going to rely on the CIO to make introduction to those buyers because we nailed the CIO. So core has to be core. And you really have to understand the TAM before you say, I'm now taking because it's so easy to say, I'll sales, typical thing I hear from entrepreneurs, CEOs, smart people like yourself, we have a great product, but I don't have a great sales team.

因此，真正了解核心背后的TAM，然后在进入下一个阶段之前弄清楚，为什么你真的要追求下一个阶段？因此，我们在ARR达到10亿美元之前防止追求下一个阶段。然后一夜之间，我们改变了策略，我们说我们要同时针对安全、人力资源和客户服务这三个购买中心，除了IT之外。在这里是市场策略，这里是买家，我们将依靠CIO向这些买家介绍，因为我们已经掌握了CIO。因此核心必须是核心。在你宣布“我现在要采取行动”之前，你真的必须了解TAM，因为很容易说出这种话。来自企业家、CEO、像你这样聪明的人经常听到的话，我们有一个很棒的产品，但我们没有一个很棒的销售团队。

And then they flip constantly chief revenue officer, they do some of you probably do. And I always, when I'm asked for advice, which rarely happens, but when I'm asked for advice, I say, what problem you are really trying to solve? Is it the chief revenue officer or you really don't know what product you are building? So that focus, that like maniacal focus on main thing being the main thing and what is the TAM really in there before you pivot or before you go to second act is something that we look out for. So that's what we learned. We said main thing should be the main thing till it hits billion before we go to the three other things. Any Sequoia company can discuss act two after a billion of ARR is what I'm hearing. And I think a very powerful insight there, CJ, will we get the next question set up is just the power of the CIO? I think a lot of people overlook that that HR and security would look to them. Charlie. I have a question which is just service now as a broad platform with many capabilities. You have other ways you interface with customers like customer support. How do you think about prioritizing where you want to integrate AI?

然后他们不停地翻来覆去，首席营收官，他们做的一些事情你们可能也在做。我总是在被问起建议时，很少发生，但当我被问起建议时，我会问，你真正想解决的问题是什么？是首席营收官还是你真的不知道你在建立什么产品？所以那个专注，那种疯狂地将主要事物作为主要事物的专注，以及在摇摆或者在进行第二次行动之前真正的TAM 是什么，是我们要关注的事情。所以这就是我们学到的。我们说主要事物应该成为主要事物，直到它达到十亿，然后我们再去做其他三件事。任何 Sequoia 公司在达到十亿 ARR之后可以讨论第二幕是我听到的。我认为 CJ，我们开始设置下一个问题之前有一个非常强大的洞察，那就是 CIO 的力量？我认为很多人忽视了 HR 和安全会寻求他们的帮助。查理。我有一个问题，就是作为一个拥有多种能力的广泛平台的服务现在，你还有其他方式与客户接触，比如客户支持。你如何考虑优先集成人工智能？

So one of the things, it has been hard in figuring out where AI could truly disrupt a use case. Right? Because that's always the hardest thing because it's still very bleeding edge. And on the buyer side, if you're talking to a large bank, if you're talking to a large government, and I'll share one story on this. So US public sector, which is federal, state and local, you have to invest a lot in US public sector for certification of your product, the cloud, Microsoft has regions for IL-5, IL-6. So our chief revenue officer came to me and said, we want to go all in on US public sector. And I said, okay, what, and we had to invest 100 million plus in Infra before we can start really making money in US public sector. And now, whether it's US Army, US Navy, Air Force, to all public sector institutions, even on civilian side, are all service now, all to all customers. And coming back to the question, we always try to figure out the pain point and can AI really disrupt that use case in a positive way that customers gets higher value from service now. So if I infuse AI in a use case, because not all use cases are created equal, right? You have a product for multiple use cases. Not all use cases are created equal, but which use case will really provide higher value because when customers spend money on you, all they are looking for is how much value I'm going to get out of this investment. And that software ROIC, including AI ROIC, is hard. Like right now, we are trying to tell everybody that, okay, we have Gen AI infused in service now products. Number one question is, how much will it cost? And what's the return I'm going to get? And if you're not doing outcome based selling, so if you're not doing outcome based selling, it's like you are another guy coming in there and giving the AI pitch to the customer. And truth is, nobody gives a shit. I mean, they don't because you have to be very, very clear and specific on here is where you will get the ROIC on that. So wherever the highest ROIC is, that's what we prioritize that customers can say, okay, I could see if CJ is saying $10 million productivity for this large bank, most likely because it's CJ is going to be $3 million, but $3 million is still better than zero. Yeah. Andy. You're going to have to start to close understanding what the CIO wants. Yeah. Beyond HR support services, security IT. Yeah. What's the next set of use cases that the CIO is super excited about beyond what service now is currently harvesting?

有一件事情，很难确定人工智能真正可以颠覆一个使用案例。对吧？因为这总是最困难的事情，因为它仍然是非常尖端的。在买家这边，如果你在和一家大银行交谈，如果你在和一个大政府交谈，我会分享一个故事。美国公共部门，包括联邦、州和地方，在美国公共部门需要为产品进行认证投入大量资金，云端，微软有IL-5、IL-6的区域。因此，我们的首席营收官来找我说，我们想全力发展美国公共部门。我说，好的，我们必须在美国公共部门投入1亿以上的基础设施，在这之前我们才能真正开始在美国公共部门赚钱。现在，不管是美国陆军、美国海军、空军，所有公共部门的机构，甚至在民用方面，现在全都是服务现在，为所有客户提供服务。又回到问题上，我们总是试图找出痛点，AI是否真的可以以积极的方式颠覆那个使用案例，让客户从服务现在中获得更高的价值。因此，如果我在一个使用案例中注入AI，因为并非所有使用案例都是平等的，对吧？一个产品有多个使用案例。并非所有使用案例都是平等的，但哪个使用案例才能真正提供更高的价值，因为当客户花钱在你身上时，他们都在寻找的是我将从这项投资中获得多少价值。软件ROIC，包括AI ROIC，是困难的。目前我们正在告诉所有人，好的，我们在服务现在产品中融合了Gen AI。第一个问题是，这将花费多少？以及我将获得什么回报？如果你不是基于结果的销售，那么如果你不是基于结果的销售，那就像你是另一个人对客户进行AI推介。事实是，没有人会在意。我的意思是，他们不会因为你必须非常明确和具体，告诉他们在哪里能够获得ROIC。因此，我们将优先考虑哪里获得最高的ROIC，这样客户就可以说，好的，我能看到如果CJ说给这家大银行创造了1000万美元的生产力可能因为是CJ，所以最终只会是300万美元，但300万美元仍然比零好。Andy，你必须开始着手了解首席信息官想要什么。超出人力资源支持服务、安全IT的范围。下一组使用案例是什么，让首席信息官比服务现在目前正在挖掘的更加兴奋？

Yeah, I would say if you think, and one thing you all should know, this is what I learned is in my seven years that service now, they constantly told me about CIO being chief irrelevant officer, okay. And they said, all the power is with developers and CJ, you are selling to the wrong door, you need to be like other people and sell to developers. Yes, developers will buy XYZ, all that is fine. But the irrelevancy of CIO has been exaggerated. And right now, CIO is the most technical person on a C suite at most of the large companies which are your buyers, right? You may have a CTO, the product person, right? Product tech person and you have the CIO, but product tech person is focused on innovation, not about what they will buy from you.

是的，我想说，如果你考虑一下，你们大家都应该知道，这是我在服务现在的七年中学到的，他们经常告诉我CIO是首席无关紧要官员，好吧。他们说，所有的权力都掌握在开发者和CJ手中，你正销售到错误的门户，你需要像其他人一样销售给开发者。是的，开发者会购买XYZ，这一切都挺好的。但是CIO的无关紧要性被夸大了。而现在，CIO是大多数大公司中属于你的买家的C套房中最技术水平最高的人。你可能有一个CTO，产品人员，对吧？产品技术人员和你有CIO，但产品技术人员专注于创新，而不是关于他们会从你这里购买什么。

So coming back to CIO, CIO's irrelevance has been exaggerated and over exaggerated year after year. And now, you know, we mainly sell to Fortune 500. In Fortune 500, the CEOs are only asking CIOs, give us the AI roadmap, give us this, give us that and so on. So that's number one that CIO is still very relevant and very important, okay. It's not that developers are not. But if you're telling, if you're selling to developers, I mean, I was one, very fickle people, right? They churn and sell thing and someday they like this and I read this on freaking Reddit and now I like this.

因此，回到CIO，CIO的无关紧要性被夸大了，年复一年。现在，我们主要是销售给财富500强公司。在财富500强公司，CEO只是在要求CIO们，给我们提供人工智能路线图，给我们这个，给我们那个，等等。所以首先，CIO仍然非常重要和关键，好吧。并不是说开发人员不重要。但如果你在向开发人员销售，我是一个开发人员，他们是非常靠谱的人，对吧？他们循环研究和销售产品，有一天他们喜欢这个，我在Reddit上读到这个，现在我喜欢这个。

That's a hard thing to sell. So CIO is right now with the state of economy today or focused on two main things. One, where can I take out the cost, just enterprise-wide using technology. So where can I take out the cost? And second, how can I help in the path to revenue? If I can help on the path to revenue, whether it's code to cash or whether it's any part of the sales front end or front office, CIO is constant. Like today, I'll tell you our service now. It still takes us a time when we propose a bill of material to our customer and customer says, well, I want to change quantity here, quantity there. Then we have to respin the order form, make sure it's in SAP, make sure it's in our CPQ system. That process is still three, four hours sometimes. And at the end of quarter, three, four hours feels like eternity. So how can we do that fast? But CIOs right now are the two. The CFO and CRO are their biggest stakeholders. And if your product is in path to that, you'll always get that CIO meeting. But you have to make it like really quick. Because I talked to seven, eight CIOs a day. And that's what I constantly see on the pattern matching. Excellent.

这是一件难以销售的事。因此，首席信息官目前关注经济状况，主要集中在两个方面。首先，我可以在哪里削减成本，只需利用技术即可实现企业范围内的成本削减。那我在哪里可以降低成本呢？第二，我如何能够在增收的道路上发挥作用？如果我能够在增收的过程中发挥作用，无论是编码到现金，还是销售前端或前台的任何部分，首席信息官都是不断变化的。就像今天，我告诉你我们的服务现在依然需要花费时间，当我们向客户提出一个材料清单时，客户说，我想在这里改变数量，那里的数量。然后我们必须重新整理订单表格，确保它在SAP中，确保它在我们的CPQ系统中。这个过程有时仍需要花费三到四个小时。在季度末，三四个小时就感觉像是永恒。那么我们该如何加快这个过程呢？但首席信息官目前面对的两个最大的利益相关者分别是首席财务官和首席收入官。如果你的产品正在朝着这条道路走，你将永远获得与首席信息官的会面。但你必须让它非常快速。因为我每天都要与七八位首席信息官交谈。这就是我不断看到的模式匹配。绝妙。

We have time for one more question. Peter. You talked a lot about use cases. I'm curious if you have any stories of use cases with AI that worked really well and use cases with AI that really did not work at all. Yeah. So one of the things I would say, trying to read documents and understand documents, which is a consumable invoices and this and that, it is still very hard for AI to crack that. And we have tried multiple different ways. And people talk about OCR and this and that. And there is a junkyard of technologies that we have tried and not been able to crack through. Because if you can automate the paperwork in voice matching and other things, there is still a lot of dollars to be had on productivity, on booking the revenue and so on.

我们还有时间再提一个问题，彼得。你提到了很多用例。我很好奇是否你有任何关于AI的使用案例的故事，有的运作得非常成功，有的则完全没有效果。是的。我想说的是，尝试阅读文件并理解文件，比如消费票据等等，对AI来说仍然非常困难。我们尝试了多种不同的方式。人们谈论OCR和其他技术。我们尝试了一大堆技术，但仍然没有突破。因为如果能自动化文件匹配等工作，仍然可以在提高生产力、确认收入等方面获得很多收益。

Where we have seen the most is simple things like predicting X for our use cases, specifically for our use cases. So for example, say a large bank, their policy is that if you use your computer, every three years, you can refresh your computer, say your Mac. We can do that now with AI and we can say, hey, Julie, you're four months away from your entitled computer refresh. And we have already notified IT and you will get your new computer on that third, so the depreciation and all the schedules work. And say yes, if you agree, because we still want human in the loop, because nobody likes so far companies don't like it, we just make the decision.

我们看到的最常见的情况是像为我们的用例预测X这样的简单事情，特别是针对我们的用例。所以举个例子，比如说一个大银行，他们的政策是，如果你使用你的电脑，每三年，你可以更换你的电脑，比如说你的Mac。我们现在可以通过AI做到这一点，我们可以说，嘿，朱莉，你离你应得的电脑更换还有四个月。我们已经通知了IT部门，你将在第三天得到你的新电脑，所以折旧和所有的计划都能顺利进行。如果你同意，请点击“是”，因为我们仍然希望人为其中一环，因为迄今为止，没有公司喜欢那样，我们只是做出决定。

That's where we see that when we see the pattern matching and can we predict better and make it easy is where we are seeing the highest leverage on even generative AI. Amazing. CJ, this is fabulous. I want to tie together some findings here. Really, this is unique in that we had two separate areas. First is application layer. We've been talking about this throughout the day and here's someone who has done it incredibly successfully at massive scale. You talked about who's the buyer, what is the size of the prize and who are you competing against? And also the overlooked customer. In this case, the chief irrelevant officer, you said that really actually is incredibly powerful.

这就是我们看到的地方，当我们看到模式匹配并能更好地进行预测，使事情变得更容易时，我们就能看到生成式人工智能的最高杠杆作用。太神奇了。CJ，这太棒了。我想在这里联系一些发现。实际上，这是独一无二的，因为我们有两个不同的领域。第一个是应用层。我们全天都在谈论这个，这里有人以巨大规模极其成功地做到了。你谈到了谁是买家，奖金规模是多少，你在与谁竞争？还有被忽视的客户。在这种情况下，你说实际上是非常强大的不相关主管。

I'll tell a quick story, which is I dinner with you and Bill from ServiceNow a little while ago, you guys said to me, hey, you get to a building, you go to the elevator, what floor do you go to? So I don't know what floor. The top. Okay, great. You get off at the top floor, where do you go from there? Bathroom? No, the corner. That's the person who's the buyer and that seems like it permeates your mentality. And two, actually focusing on the customer, each of you in this room, if you succeed, we'll try to sell to the likes of ServiceNow, a billion dollar cloud spend business. And you give us a great guide here with AI. For you, you're looking at small language models, not just the biggest ones. You're looking at cost, you're looking at open source. 1% gross margin matters to you.

我来讲一个简短的故事。一段时间前，我和ServiceNow的比尔一起吃晚饭，你们问我：“当你到达一栋大楼，进入电梯，你会去哪个楼层？”我不知道，可能是顶楼吧。好的，你到达顶楼，接下来会去哪里？洗手间？不，去找那个角落。那个人就是买家，似乎这种思维贯穿其间。并且，专注客户，这个房间里的每个人，如果你们成功了，我们将尝试向ServiceNow之类的企业销售十亿美元的云支出业务。你们为我们提供了很好的AI指导。对于你，你关注小型语言模型，而不仅仅关注最大的模型。你关注成本，关注开源。对你来说，1%的毛利率很重要。

That's how you build an 82% gross margin, 160 billion dollar business and actually understand the customer. Don't just go to the marketing website and try to guess what ServiceNow does, talk to people of built in. This is fabulous. CJ, any parting words for the team? Nothing. It was a pleasure. And I'm always around if you want any words of wisdom. I made a lot of mistakes as well, too many in terms of scaling ServiceNow from a product perspective, engineering perspective, which use cases you prioritize, which you don't. How do you ring fence the team when you go for the second act and really, really get focused. So lots of mistakes as well. But we are constantly learning.

这就是如何打造一家拥有82%毛利率、市值1600亿美元的企业并真正了解客户的方法。不要只是去营销网站上猜测ServiceNow做什么，与内部人员交谈。这太棒了。CJ，团队有什么告别的话吗？没有。很荣幸。如果你需要任何智慧之言，我一直在这里。我也犯过很多错误，尤其是在推动ServiceNow产品、工程、优先考虑哪些使用案例以及如何在进行第二幕时如何保护团队方面。我们也犯过很多错误。但我们不断学习。

So, I'll be able to see one last question for you. Will you do stand up for us later tonight? No, I will not do stand up today. It's my stand up when I used to do it. Nowadays, I'll get canceled very fast and Bill will not appreciate that. So, I will not do that. There we go. That was all for now. Thank you. Thank you.

所以，我最后可以给你们看一个问题。今晚你会给我们表演脱口秀吗？不，我今天不会表演脱口秀。那是我以前做的事情。现在，我会很快被取消，比尔也不会欣赏。所以，我不会这样做。这就是全部了。谢谢你们。谢谢。