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.

今年，在AI Ascent上，我们正在做一些不同的事情。其中之一是我们谈到的下一个部分，即这些具有远见的想法。另一个是索尼娅一直在谈论的现在是关于人们如何接受AI并将其实施的。作为其中的一部分，我们不仅有像Sam、Ann、Arthur和Daniella这样的令人惊奇的基础模型CEO。我们还引入了两位卓越的领导者，在将AI应用并使其具备规模化的企业就绪性上。其中之一是CJ。CJ在过去七年担任ServiceNow的总裁和首席运营官。此外，ServiceNow作为一家由Sequoia支持超过十年的公司，在业务上表现卓越。

It's the kind of business anyone in this room should aspire to be like. 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.

这是这个房间里任何人都应该渴望成为的一种企业。帕特，我相信，2012年开始运营这家企业。对吗？2009年。那时企业的规模是多少，帕特？20。什么？年收入（ARR）在2千万。好的。有人能猜到ServiceNow现在的ARR是多少吗？安妮，我觉得你知道。1.4。亿？再猜一次。20亿？好的。大致在这个范围内是正确的。因此，ServiceNow是世界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。目前它的ARR为97.5亿。令人惊讶的是，七年前你担任总裁和首席运营官时，它只有10亿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. 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.

这就是增长了10倍。市值已经达到130亿美元。从那时起，增长了12倍以上。每个季度增加6亿美元的ARR。所以让这成为一个值得追求的目标。我提到过它是世界第三大SaaS公司。第一名每年增长11％，第二名每年增长12％，而ServiceNow每年增长26％。所以我们都认为，在这种增长情况下，排名并不会持续很长时间。CJ告诉我，几乎所有这一切都是有机发展的。他们进行了一些收购，如Element AI。我们稍后会谈到这个。他们在人工智能方面处于领先地位。但实际上，这是有机的增长。

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%. 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.

这个公司叫做ServiceNow，但它并不是一个服务利润率很高的公司。它的毛利率达到了82%。自由现金流为30%，营业收入为27%。在“40条规则”的基础上，“56条规则”的操作。自07年被Pat引入IPO以来，不知道它的估值是多少。当时Pat，估值是多少？Moon对它投了多少？从2600万美元到1550亿美元的投资。自IPO以来，它增长了42倍，回报率为42倍。是一个非常出色的故事，我认为这对在座的每个人来说既是现实又是一个值得追求的目标。

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. 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.

我们之所以如此激动您前来，CJ，其中一个主要原因是ServiceNow在人工智能领域处于领先地位。我们第一次见面是在与NVIDIA的Jensen和团队讨论人工智能愿景的对话中。实际上，我们可能有一段视频，就在昨天的NVIDIA大会上，ServiceNow是一个主要特色，展示了在NVIDIA平台上的具体用例。在以往的会议上，ServiceNow也被提及为一个主要用户。我的第一个问题是，请告诉我们您如何在这个卓越的COO职位上发挥作用，您是如何进行大部分产品工作的。然后，请告诉我们您是如何将人工智能套件发展到今天的样子，并使其达到当前的水平。

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.

是的。首先，感谢你邀请我。他问了我一个有趣的事实，那就是我是一名失败的笑话演员。所以我经常在创作材料，试着表演一些非常自嘲的幽默，你会时不时看到。在最高水平上，我想说我们对红杉资本非常非常感激。

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. 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.

这里有一个简单的故事。故事是我们在2012年公开之前就已经公开了，市值只有39亿美元。好的，那就是我们在2012年公开的时候。那次IPO算是一般般。人们喜欢它。是的，Facebook那时还不错。当时叫Facebook。同一年，Workday也是一个。我们的IPO也算是一般般。但在那之前，VMware曾向ServiceNow提出了个一位数十亿美元的收购报价，低于五亿。道格·雷恩和红杉团队说服了管理团队，他们本来很乐意接受那个报价，因为他们觉得“哇，我们不用上市了，可以成为当时的VMware这样的伟大公司的一部分”。但道格·雷恩值得称赞的是，他不仅说服了董事会，也说服了管理团队，告诉他们你们可以变得很大。

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.

因此，我们对 Sequoia 在那时提供的辅导非常感激。对于那个时候我们可以接受的 20 亿美元的报价，与今天仅仅 12 年就达到的 1550 亿美元相比，这实在是令人难以置信。所以我要感谢 Sequoia 和团队为我们提供支持和信任，并让我们走到今天这一步，因为那时那个坐在董事会上的 Doug 可能轻而易举地说了不。那个时候，对 Sequoia 而言回报会很惊人。但是我们还是离开了。CJ Taxon 在我之前说过，很高兴看到你，迫不及待地想成为 Sequoia 的一部分。是的。你现在已经是其中的一部分了。但我只想表达我的感激之情。你们在 Sequoia 和优秀的人员合作。我从不轻视这一点。在我们成长的道路上，我们永远不会忘记我们的朋友和支持者。所以我就想从这里开始。

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 Slootman 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. 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.

在权重表上排名第二。所以我加入了这家公司。所以弗兰克·斯卢特曼雇了我。而弗兰克·斯卢特曼也是 Sequoia 在 ServiceNow 公司任命的。当时，弗兰克·斯卢特曼有两个选择，我认为这是公开的信息。但是弗兰克的数据领域被收购了。然后他决定，我总是拿杰斯开玩笑，但他决定要成为一名风投者。所以他加入了 Greylock。如果你们见过弗兰克·斯卢特曼，我相信有些人见过，他不是产自桑德希尔的人。所以他说，不，我需要回到运营首席执行官的工作岗位。Sequoia 说服了他，弗兰克获得了两个工作邀约：Palo Alto Network 首席执行官或 ServiceNow 首席执行官。他选择了 ServiceNow。当时，Sequoia 也在背后支持。

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.

所以当 Frank 雇佣我时，我们的年度重复销售额超过十亿美元。Frank 说，CJ，到2020年，如果我们能达到四十亿美元的年度重复销售额，那将是一个巨大的胜利。让我们努力实现这个目标。我们的创始人 Fred Luddy 在近50岁时创立了公司，曾经破产过。所以这不是一个经典的斯坦福哈佛故事，而是他毕业于印第安纳大学，原籍印第安纳。他说，我要创建一个可以解决多种用例的平台。因此，我们始终知道潜在市场规模几乎是无限的。这个平台提供了你创建一个或多个产品所需的一切。

And 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.

当我加入时，我们大约有十亿的规模。我们有一个大产品和两三个小产品。自那时起，我们一直在残酷地执行，决定要走向哪些买家。比如，当我的产品团队过来说，嘿，我们可以创造这个伟大的产品时，我的第一个问题是，谁是买家？我们有没有接触到那个买家？那个买家是在隔壁还是两扇门之外还是五扇门之外？当前的买家会不会把我们介绍给那个买家，或者那两个买家根本不会互相交谈？这些简单的问题是关于谁是买家？我们正在与谁竞争？即使这听起来非常简单，第三个问题是，价格有多大？如果我们精准地抓住这个使用案例，我们能否创造一个价值十亿美元的ARR产品？再次，又是另一个产品。

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. 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.

我们一直在进行精确执行。这是帮助我们实现有机创新的关键。我们没有购买收入。在达到10亿美元的路径上，我们是唯一一家没有购买过收入的SaaS公司。我们总是购买出色的公司，拥有优秀的员工。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张到2023年。当我们退出12月季度时，我们已经实现了100亿美元的ACV。当然，收入总是会滞后一点。我们预测2023年的年度收入将在107.5亿美元，并以21%的速度增长。这些只是一些数字，但这背后是一个基于云的底层平台。

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.

你们制造哪些产品？你们解决的问题是什么？谁是购买者？是的，对购买者的极端关注？我们能接触到购买者吗？价格规模是多大？没有这些，我和我的产品团队以及工程团队，并且我作为产品和工程主管加入了，Frank雇佣了我然后离开了。但这一直是关注的焦点。

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.

在人工智能方面，我们的信念非常简单，从监督式机器学习开始，一直演变到今天的通用人工智能。我们一直非常专注于将人工智能应用于我们的用例中。因为如果我们能够将人工智能融入我们的用例中，与摩根大通、花旗银行或美国陆军之类的机构进行对话会变得非常容易，告诉他们，你们正在为这个用例使用服务现在，人工智能将帮助加速X或加速Y。因此，我们从2016年开始一直在获得或组建小型团队，这些团队都是人工智能专家。

2017 was our first one. 2016, we started the journey. 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.

2017年是我们的第一年。2016年，我们开始了这段旅程。然后当我们收购了Element AI时，他们正在努力成为加拿大的下一个谷歌。他们拥有大约170到180名工程师，包括博士学位持有者、数据科学家和工程师。他们是一个令人惊叹的团队。很多知名人士，比如获得图灵奖的Yoshua Bengio，都是那个团队的一部分。团队中还有一些人写过一些关于转换器模型的开创性论文。这就是我们得到的团队。我从Allen and Company那里得到的信息是，嘿，这是一个超棒的团队。他们没有任何收入，零。

And they are trying to figure out what use case AI can be applied to. 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.

他们正在努力找出人工智能可以应用到哪些用例。 这发生在大流行期间。我去找我的老板，我们的CEO，对他说，嘿，这些人没有任何收入，但是有很强的才华。我们需要投入一些资金并建立信誉。他说，如果你觉得这是一种很棒的才华，那我们就接纳他们。他们给我展示了2020年末和2021年初的两个Chat GPT 1015演示。

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.

然后，当这整个事情在2022年爆发时，我们确切地知道在哪里可以应用LLMs到我们的用例中。而且，我不知道这是否是一个术语，但SLMs，我们非常具体的用例LLMs，我们现在应用于服务中。我们在九月开始了我们的货币化战略。这就是故事。我知道这是一个简单的问题，但我不得不给一个相当长的答案，因为有很多历史在其中。真的很不可思议。

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.

老实说，在这次对话之前我并没有意识到，你们是唯一一个完全靠自然增长超过100亿营收的SaaS公司。这真是非常了不起。而且说实话，我和ServiceNow的很多人交谈过，你是产品方面的天才。能够向你学习真是一种乐趣。这个问题是关于产品的。

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. 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.

所以你们几年前就有了一点优势，因为我知道你和比尔在元素收购之前就已经开始谈论人工智能。然后通过元素收购，你们开始考虑如何将其整合到你们的产品中。告诉我们你们是如何顺利上手的，现在人工智能如何在ServiceNow产品中运用的，也许举几个例子。是的。我就来举个最近的例子。

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. 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.

在人工智能领域，我们非常热爱开放源社区。即使在自然语言理解模型方面，我们曾与斯坦福合作，研究可以使用哪些库，这是四五年前的事了。我们真的很喜欢开放源社区。加拿大团队与拥抱面对面合作，找出了在ServiceNow中可以应用人工智能的使用案例。所以我们说，好的，现在听着，你们谈到了我们的毛利率。我们的毛利率是82%。而所有公司的盈利从毛利率水平开始。那是你们的第一步或阶梯，82。然后你添加研发成本、销售营销成本、DNA成本，然后才能实现盈利。

So we are world class in terms of our gross margin at scale. 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. 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.

因此，从规模上来看，我们在毛利方面是世界一流的。我没有这样的奢侈。这是一个受限制的优化问题，我没有奢侈地说，我要在我的农场、我们的云中到处运行open AI，因为我们是一个100%的云公司，目前拥有1700亿，谁知道现在是2万亿个参数，使用了4.0版本。我没有这种奢侈。因此，约束是，我能否为ServiceNow的用例运行更小、更快、延迟更低的模型。这是一个受限制的创新，我们与Hugging Face的科研团队合作。我们提出了第一个文字转代码的模型。我们并不试图像GitHub的合作伙伴那样用Java或其他任何语言进行文字转代码。

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.

我们的文本转代码工作特别针对ServiceNow代码，以及你如何配置ServiceNow。这是我们第一次与hugging face合作取得突破。然后我们做到了，你知道，你提到了Jensen，他是加拿大的忠实粉丝。所以当我们收购element AI时，加拿大。是的。所以当我们收购element AI时，他打的第一个电话就是告诉CJ，加拿大有才华，我们应该更多地合作。那是在2020年。因为他与你、多伦多、ImageNet等方面的历史。

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 cell, 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OpenAI小十分之一的模型。我告诉詹森，嘿伙计，你一直在不断推动下一轮的H类加加。我需要这些在A100上运行。因为我们是一家上市公司，所以我们将为此而努力。我们有1%的毛利率，D级销售，以及像你从风险投资人那里获得的那样多的问题，真的很不容易。所以，是的。我们基本上说我想要一个小型模型，可以在A100上运行。而且我可以在每个云端复制它。

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.

他还是一直试图推动我。他是个优秀的销售员，尽管他表现得好像不是。他总是试图要求H说H更快、更有效，这是正确的。但是我们想要运行在A上的东西。所以我们将用例用在更小的型号上。嗯，听说你们真的需要布莱克韦尔。是的，我知道。3万美元？没错。是的。对你来说算什么？太棒了。团队，我有一个问题要问CJ，我提前告诉你们这样你们可以脑海中想出一些问题。

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.

CJ，我们这里有一群建造者。 他们正在建造许多消费类公司，还有许多企业公司。老实说，对于这个房间里许多公司来说，你是一个梦想客户。 你能告诉这个房间里正在建造产品的人些什么，以帮助他们成为一个ServiceNow可能考虑合作并成为客户的出色AI构建者吗？是的。 所以我说有两个地方。 那么当你看着我时，请看我的额头，那是我在云端和软件上花费的十亿美元。 所以如果你想向我销售什么东西，那就快点吧，我会买的。

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. 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.

好的。但我每年在云和软件以及基础设施上花费十亿美元，毫不夸张，并且以25%的速度增长，与我们的收入保持一致。这就是我花了多少钱。因此，我可以成为你们的重要客户，或者至少是一个潜在客户。就有效性而言，如果你了解ServiceNow的话，你会知道我们的网站上并不能理解ServiceNow是做什么的。但如果你了解ServiceNow，我们基本上做的就是许多工作流，即在人与机器之间以特定顺序数字化协调的任务。这就是我们做的事情。

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. 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.

因为有人在一家大银行或客户告诉我，当他们订购东西时，他们可以更快地获得特斯拉，而不是从银行获取一台PC或Mac。这就是大型企业和政府的现实。所以当你在银行请求一台PC时，银行会尽力效率高，流程是需要经过两个级别的批准吗？有些银行需要四个级别的批准。然后一旦批准完成，它需要去发货部门。他们有库存吗？他们需要基于镜像，需要在上面放置安全卡。然后它会去，好的，是送到她的家里地址还是去？这就是工作流程。

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. 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.

这些是我们在幕后自动化的事情。所以你只需说，我想选择这台电脑。我想选择这台显示器。我希望明天早上通过联邦快递送达。这就是理念，对吧？但由于这些复杂的工作流程和银行希望加固他们为您提供的Mac的形象，尤其是在交易大厅使用时，这就是我们的工作。这就是ServiceNow的功能。我们将人工智能整合进来，让一切变得更简单更快速。所以对我们来说，如果你了解ServiceNow，并且能够说，嘿，CJ，针对你的应用案例，这是我们开发的优秀技术。你可以使用这项技术，无论是您的LLMs还是特定用例的人工智能，或者您所完成的某种类型的分析，无论是什么。

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. 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.

那么，如果我能让我们客户的使用情况更好，你就有我的关注，我会购买你的产品，让我们的速度更快，这样我们就能更好地为客户提供服务，对吧？我们只有8,000个客户，只有8,000个。如果你考虑一下8,000个客户，年度总收入达到100亿美元，你就能很快算出来。但我们只有8,000个客户。所以我着了迷，就像强迫症一样着了迷，如果你说，这就是它可以为你的使用情况做的事情，我每天都会关注你的页面。好吗？这是第一点。如果我们能更好地为客户服务，我有足够的资金可供支出。第二是我们拥有一个出色的营销团队。

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. 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.

除了我们的工程师、人工智能、科学和研究团队之外，我们还有一个出色的营销团队。如果您有东西要向旁边或再旁边的买家推销，并且想要利用，首席信息官是我们的主要买家。如果你想象一下，CIO在10年、15年、20年前，直到现在，CIO们一直在为其他高管服务。嘿，为了销售，我需要推广Salesforce。对于市场营销，我可能需要使用Adobe。对于财务，SAP，我需要为首席财务官提供支持。我们是第一个平台，我们说，这是CIO的平台。

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. 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?

所以如果你说CIO是你的买家，并且你想要接触CIO，那么没有比服务现在更好的合作伙伴了，对吧？真正擅长向CIO销售的两家公司是ServiceNow和微软。这两家公司销售得非常好。太棒了。我相信在座的很多人都对那10亿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。米歇尔，你好。谢谢，UJ。很多人都有实现第二幕的梦想。一些人可能已经在考虑第二幕的产品方面。在早期阶段，你对资源分配和围绕实验与有意识的押注的哲学有什么建议，以便开发第二幕的产品？

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.

没错。所以我将分享一个故事，我们的IPO之所以表现平平是因为人们说我们的TAM只有18亿美元。因此，一个行业分析师说，这些家伙不会做得很好，他们的TAM有限。很多公司都遇到过类似的情况，有人说，我不知道这个市场规模是否足够大。对于我们来说，这实际上在我们心头种下了一颗种子，因为我们相信ServiceNow的TAM比行业分析师社区所说的要大得多，他们的估计只有20亿以下。这是在2012年，不久前。所以其中一个要点是，核心至关重要，核心就是要真正了解TAM是什么，这是一门融合了艺术和科学的学问。在你开始说，我想要多产品，我想要针对不同的买家或同一个买家的多项产品策略之前，核心必须是核心。

The reason you exist is for something. You have tried to solve a problem. 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.

你存在的原因是为了某种事情。你试图解决一个问题。所以真正理解核心背后的TAM，然后在进入下一个行动之前弄清楚，你为什么真的要去追求下一个行动？因此，我们在实现10亿美元年收入之前不会追求下一个行动。然后一夜之间，我们转变策略，说我们要去追求安全、人力资源和客户服务这三个采购中心，除了信息技术之外。这就是市场推广策略，这就是买方，我们将依靠首席信息官向这些买家介绍，因为我们已经和首席信息官建立了良好的关系。

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. 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?

所以核心必须是核心。在你说“我现在接手了”之前，你真的必须了解TAM，因为很容易说“我会销售”，我经常听到创业者、CEO、像你这样聪明的人说的典型话语。我们有一个很棒的产品，但我没有一个很棒的销售团队。然后他们不断更换首席营收官，他们中的一些人可能会这样做。而我总是，在被征求建议时，尽管这种情况很少发生，但当我被征求建议时，我会说，你真正想要解决的问题是什么？是首席营收官，还是你真的不知道你正在构建什么产品？

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.

因此，那种对于主要事情的专注，那种像狂热般的专注于主要事情，以及在你改变方向之前或者进入第二幕之前真正的TAM是什么，这是我们要关注的。这就是我们学到的东西。我们说主要事情应该在达到十亿之前一直是主要事情，然后我们再去做其他的三件事情。我听说，任何一家红杉资本的公司在年收入达到十亿美元之后才会讨论第二幕。我认为，这是一个非常有力的洞察力，CJ，在我们准备下一个问题之前的问题是CIO的力量。我觉得很多人都忽视了HR和安全会去找他们。

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? 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.

查理，我有一个问题，就是现在服务是一个功能广泛的平台，具有许多功能。您有其他与客户互动的方式，比如客户支持。您是如何考虑要将人工智能集成到哪里的优先级？有一件事情很困难，就是弄清楚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，因为这仍然是一个非常尖端的技术。在买方方面，如果你在与一家大银行谈话，如果你在与一家大政府谈话，我会分享一个故事。

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.

因此，美国的公共部门，包括联邦、州和地方政府，在您的产品获得认证时，您必须在美国的公共部门进行大量投资。云计算领域，微软在IL-5、IL-6都有区域。所以我们的首席营收官来找我，说我们想在美国的公共部门全力以赴。我说，好，我们必须在我们真正开始在美国的公共部门赚钱之前投资1亿美元以上的基础设施。现在，无论是美国陆军、美国海军、空军还是所有公共部门机构，甚至是民用部门，现在都是为了所有客户提供服务。

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.

回到这个问题，我们总是试图找到痛点，看看人工智能能否以积极的方式干扰这种用例，使客户从现在的服务中获得更高的价值。所以，如果我在一个用例中注入人工智能，因为并非所有用例都是平等的，对吧？您为多个用例提供产品。并非所有用例都是平等的，但哪个用例能真正提供更高的价值，因为当客户为您消费时，他们只关心的是我在这次投资中能获得多少价值。

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.

这款软件的投资回报率（ROIC），包括人工智能ROIC，是困难的。就像现在，我们正在努力告诉每个人，好吧，我们在服务产品中注入了Gen AI。首要问题是，这将花费多少？我能得到多少回报？如果你不是基于结果的销售，那么就好像你又是另一个人在那里向客户推销人工智能。事实是，没人关心。我是说，他们并不关心，因为你必须非常明确并具体地说明在这里你将获得ROIC。

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.

所以无论最高ROIC在哪里，我们优先考虑的是客户可以说，好的，我能看到如果CJ为这家大银行提升了1000万美元的生产力，很可能是因为CJ的费用将是300万美元，但300万美元仍然比零要好。是的，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? 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.

你需要开始逐渐了解CIO想要的东西。是的。除了人力资源支持服务，安全性IT。是的。CIO对什么服务现在目前正在开发之外的下一批用例感到非常兴奋？是的，我想说，如果你考虑一下，你们所有人都应该知道，这是我在服务现在的七年里学到的一件事，他们不断告诉我CIO是最无关紧要的官员，好的。他们说，所有的权力都掌握在开发人员和CJ手中，你正在向错误的人出售，你需要向其他人学习，向开发人员出售。

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，开发商会购买XYZ，一切都很好。但是CIO的无关性已经被夸大了。而现在，在您的潜在买家中，CIO是大多数大公司C级高管中最了解技术的人，对吧？您可能会有一位首席技术官，负责产品的人，对吧？产品技术人员可能会专注于创新，而不是关于他们将从您那里购买什么。

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.

因此，回到首席信息官（CIO），人们一直年复一年地夸大和过度夸大CIO的无关紧要。现在，我们主要销售给财富500强企业。在财富500强企业中，首席执行官们只会向首席信息官询问，给我们提供人工智能路线图，给我们提供这个，给我们提供那个等等。因此，首席信息官依然非常重要和相关，这是第一点。并不是说开发人员不重要。

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. That's a hard thing to sell. 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.

但是如果你在跟开发人员打交道、做销售，我是说，他们是非常善变的人，对吧？他们频繁地变化和出售东西，有一天他们喜欢这个，我在 Reddit 上读到了这个，现在我喜欢这个。这是一个难以销售的事情。 CIO 现在在面对当今经济形势时，专注于两个主要方面。第一，我能从哪里节省成本，通过技术在整个企业范围内。所以我能从哪里节省成本呢？第二，我如何能在增收之路上提供帮助？如果我能在增收之路上提供帮助，无论是从代码到现金，还是销售的任何部分，CIO 都是不变的。

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.

就像今天这样，我将告诉您我们的服务现在是什么情况。当我们向客户提出一个物料清单时，客户还需要花一些时间，客户可能会说，我想在这里修改数量，那里修改数量。然后我们必须重新整理订单表格，确保它在SAP系统中，确保它在我们的CPQ系统中。这个过程有时候仍然需要三四个小时。而且在季度末，三四个小时感觉像是永恒。那么我们如何做才能更快呢？但现在CIO们是两座大山。CFO和CRO是他们最重要的利益相关者。如果您的产品符合这一标准，您总会得到CIO的会议机会。但您必须让这一切变得真的很快。因为我每天都要和七八位CIO交谈。这正是我不断看到的模式匹配情况。太好了。

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.

我们还有时间再问一个问题。彼得，你谈了很多关于使用案例的内容。我很好奇你有没有关于AI使用案例成功的故事，以及完全失败的AI使用案例的故事。是的。我想说的是，尝试阅读文档并理解文档，比如消费发票之类的内容，对于AI来说仍然非常困难。我们尝试了多种不同的方式。人们谈论过OCR等技术，但我们尝试过的技术却并未取得成功。因为如果你能够自动化文书工作和发票配对等工作，那么在提高生产效率、预订收入等方面还有很大的潜力。

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. 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.

我们看到最多的是简单的事情，比如为我们的用例预测X，特别是为我们的用例。因此，举个例子，比如一个大银行，他们的政策是，如果你使用你的计算机，每三年，你就可以更新你的计算机，比如你的Mac。现在我们可以用人工智能做到这一点，我们可以说，嘿，朱莉，你距离你有权更新计算机还有四个月。我们已经通知了IT部门，你将在第三天拿到你的新计算机，所以折旧和所有的计划都可以按计划进行。如果你同意，请说是，因为我们仍然希望有人在其中，因为到目前为止没有公司喜欢，我们只是做出决定。我们看到的情况是，当我们看到模式匹配并且能否更好地预测并使其变得容易的时候，甚至生成式人工智能也能发挥出最大的作用。太棒了。

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. 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. 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，这太棒了。我想在这里总结一些发现。实际上，这个情况很独特，因为我们有两个完全不同的领域。首先是应用层。我们整天都在谈论这个，在这里有人在大规模上做得非常成功。你谈到了谁是买家，奖金有多大，你竞争对手是谁？还有被忽视的客户。在这种情况下，无关紧要的主管，你说这实际上非常强大。我来讲个简短的故事，有一段时间前我和你以及ServiceNow的比尔吃过晚餐，你问我，你到了建筑物，去了电梯，你去哪一层？我不知道，顶层。好的，你到了顶层后，接下来去哪里？洗手间？不，去拐角。那个人就是买家，而且这似乎贯穿了你们的思维方式。其次，专注于客户，如果在座的每个人都成功了，我们会努力去卖给ServiceNow这样的、价值十亿美元的云计算企业。您在这里为我们提供了很好的指导，涉及到人工智能。对你来说，你不只是看最大的语言模型，你还要看成本，你还要看开源。1%的毛利对你很重要。这就是你建立82%毛利、1600亿美元企业并真正了解客户的方式。不要只看营销网站，试图猜测ServiceNow做什么，要和真正参与过的人交流。这太棒了。

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. 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.

CJ，对于团队有什么告别的话吗？没有了，很高兴能和大家共事。如果你们需要任何智慧之言，我随时在这里。我在许多方面犯过很多错误，包括从产品角度、工程角度来看，确定优先处理哪些用例，哪些不需要处理。在迈向第二步时，如何给团队一个明确的目标。所以，我也犯了很多错误。但我们在不断学习。所以，我最后想问你一个问题。晚上你会为我们表演单口相声吗？不，今天我不会表演单口相声。那是我以前的表演。如今，我会很快就被取消，而且比尔也不会欣赏。所以我不会这样做。好了，就这样了。谢谢。谢谢。