挑战 ServiceNow：Serval CEO Jake Stauch 谈企业编程智能体与权限治理

简要描述Brief Description

向 ServiceNow 发起挑战：与 Serval 联合创始人兼首席执行官 Jake Stauch 聊聊面向大众的编程智能体Taking on ServiceNow: Coding Agents for the Rest of Us with Serval Co-Founder and CEO Jake Stauch

目录Table of Contents

• 开场亮点
  Opening highlights
• 杰克·斯托奇简介及 Serval 的背景
  Jake Stauch Introduction and Serval’s Background
• 将编码代理的应用范围扩展到工程师之外
  Expanding Coding Agents Beyond Engineers
• 企业中个人代理的局限性
  Limitations with Personal Agents in Enterprise
• 在大型组织中有效部署 Serval
  Deploying Serval Effectively in Large Orgs
• 第 1 天：雄心壮志与攻克企业系统记录
  Day 1 Ambition and Attacking Enterprise Systems of Record
• 借助工作流自动化平台，迎战 ServiceNow
  Taking on ServiceNow with Workflow Automation Platform
• 看好编码智能体的演进，并在企业中构建防护机制
  Betting on the Evolution of Coding Agents and Building Guardrails in Enterprise
• Serval 和编码代理的重大风险、丰厚回报与大胆预测
  Big Risks, Big Rewards, and Big Predictions for Serval and Coding Agents
• 在企业层面采用不同的构建原则集
  Adopting Different Sets of Building Principles at an Enterprise Level
• 最大化 Token 使用、长期预算影响与投资回报率
  Token Maxing, Long-Term Budget Impacts, and ROI
• SaaS末日与SaaS对决AI
  The SaaS-pocalypse and SaaS vs. AI
• 在企业中向 IT 用户交付平台级能力的思维模型
  The Mental Model for Delivering Platform-Level Power to the IT User at Enterprise
• 使用 Catalyst 构建自动化并提升技术能力
  Building Automations with Catalyst and Raising Technical Competence
• 下一波浪潮：企业中的后台智能体与自主性
  The Next Wave: Background Agents and Autonomy in Enterprise
• Serval 的招聘速度与无限雄心
  Hiring Velocity and Unlimited Ambition at Serval
• 跟上客户步伐与产品功能的根本性转变
  Keeping Pace with Customers and Fundamental Shifts in Product Function
• 结论
  Conclusion

开场亮点Opening highlights

这是企业软件领域终极的登月式目标。这些智能体可以替你执行任务，神奇地发现并解决你所有的问题。我认为，目前还没有人真正摸索出如何把这件事做好。这有点像 OpenAI、Hugging Face 的那些事件，或其他类似情况：智能体接到任务后，做出了意料之外的事。智能体的能力会变得相当强。理论上，它们甚至可以开始编写代码，在你的系统上执行操作，而这会带来无边界的安全风险。我认为，短期内没人能承担这样的风险。一方面，你希望这些智能体高度自主，不需要有人一直盯着；另一方面，在企业环境中，自主性又非常令人担忧。Serval 就是这道边界。Serval 就是护栏。我们让有诸多规则、审批、流程和利益博弈的大型企业，能够安全、放心地大规模采用这些工具。This is the ultimate moonshot in enterprise software. These agents that go off and do work for you and magically discover all your problems and solve all your problems. And I think no one's really figured out how to do this well. This is kind of the OpenAI hugging face incidents or other things where agents are given a task and then they do something that's unexpected. The agent becomes pretty competent. They could theoretically just start writing code that could take action on your systems and that is an unbounded security risk that I don't think anyone's going to be able to take anytime soon. On the one hand, you want these to be very autonomous without somebody baby sitting them. On the other hand, autonomy is very scary in the enterprise. Serval is the boundary. Serval is the guardrails. We are the way that a large enterprise with a lot of rules and approvals and process and politics can adopt these tools safely and comfortably at scale.

杰克·斯托奇简介及 Serval 的背景Jake Stauch Introduction and Serval’s Background

主持人：听众朋友们，大家好。欢迎回到《No Priors》。今天，Alod 和我邀请到了 Serval 的联合创始人兼 CEO Jake Stauch。Serval 正以非洲野猫般的速度，尝试挑战 ServiceNow，并更广泛地将代码生成的力量带给 IT 和企业团队。欢迎你，Jake。Speaker: Hi listeners. Welcome back to No Priors. Today Alod and I are here with Jake Stauch, co-founder and CEO of Serval. Serval with all the speed of the African wildcat is trying to attack ServiceNow and more broadly bringing the power of code generation to IT and enterprise teams overall. Welcome, Jake.

主持人：杰克，感谢你今天做客《No Priors》。很高兴你能来。Speaker: Jake, thanks for joining us today on No Priors. Good to have you.

发言人：很高兴来到这里。Speaker: Great to be here.

发言人：现在，或许你可以多跟我们讲讲你的经历、你是如何创办 Serval 的，以及你最初想解决什么问题，或者说，你当初为什么开始做这件事？Speaker: Now, maybe you could tell us a little bit more about your history and how you started Serval and what is the problem that you started with or why did you start working on this to begin with?

发言者：是的，先介绍一下背景。Serval 做的是企业自动化和企业服务管理。我们的理念是，你可以在工作中提问并获得帮助，还能把很多你不喜欢做的工作自动化，而我们通过代码生成智能体来实现这一点。这就是我们公司的业务。我们的竞争对手包括 ServiceNow，它一直是这个领域的大型传统服务提供商。我是在上一家公司 Verkada 工作时发现这个领域的。当时我们向 IT 团队销售企业级实体安全产品。我花了很多年和 IT 团队交流，弄清楚该为他们开发什么产品。我很喜欢问这些团队一个问题：“你们花钱最多的是什么？最讨厌的又是什么？”ServiceNow 经常名列前茅。所以我一直对这个领域很感兴趣，觉得或许能找到更好的解决方案，但在我在那里工作的很长一段时间里，始终看不出要怎样才能打败 ServiceNow。Speaker: Yeah, so background, Serval is enterprise automation, enterprise service management. The idea is you can ask questions and get help at work and automate a lot of the parts of the job you don't enjoy and we do that through code gen agents. So, that's uh what the company does. We compete with companies like ServiceNow as historically the big legacy provider in the space. I discovered this category actually working at a previous company called Verkada uh where we sold enterprise physical security products to IT teams. Spent many many years talking to IT teams figuring out what to build for them. And one of the things I loved to do with these teams is ask them, "What do you spend the most money on? And what do you hate the most?" And ServiceNow would top a lot of those lists. And so, I was always interested in this category of maybe there's a better solution here, but it wasn't clear for most of my time there how you'd ever beat ServiceNow.

他们是一家很棒的公司。他们在很多方面都做得非常出色，你又凭什么能与他们竞争呢？They're a great company. They've done so much so well, and why would you be able to compete with them?

发言者：它让用户感到沮丧的地方是什么？Speaker: What was frustrating for users about it?

发言人：我觉得在这个平台上构建东西太难了。它是一个非常稳健、可定制且功能强大的平台，能够适配所有这些企业工作流。从根本上说，它是一个工作流自动化平台。因此，它能做的事情非常多，但每当你想到一个很酷的点子，想把它实现出来，就得亲自去开发，而且很多时候还得请顾问来实现。所以，它总是会比你的预期落后大约 6 到 12 个月。如果你要构建的是一个能持续 5 到 10 年的东西，比如一个大型入职流程，而且业务不会有什么变化，那么投入所有这些前期工作也没问题；部署之后，它也能正常运行一段时间。但如果只是想跟上你希望构建的各种自动化需求，ServiceNow 就跟不上了。Speaker: I think so hard to build in the platform. So, it's a very robust customizable, powerful platform that can map to all these enterprise workflows. Fundamentally, it's a workflow automation platform. And so, it can do so much, but every idea you have for doing something cool, you have to go and implement and a lot of times you're bringing consultants to implement it. So, it's it's always kind of running 6 to 12 months behind where you want it to be. And it's fine if you're building something that's going to last 5 10 years like a big onboarding flow and nothing about your business is going to change, so you can invest all that up-front effort, and then it gets deployed and it works for a while. But, for just trying to keep up with all the automation that you want to build, ServiceNow is not able to catch up.

然后它的成本非常高，而且随着时间推移还越来越贵。所以，真正让人感到沮丧的是，它跟不上我的业务发展目标，成本却还在不断增加。屡屡让人沮丧的主要原因就是这些。And then it's very expensive and it keeps getting more expensive over time. So, that frustration of it's not keeping up with where I want to go as a business and it keeps getting more expensive, that's what was driving a lot of the frustration.

让编码代理的应用范围超越工程师群体Expanding Coding Agents Beyond Engineers

发言人：我觉得你提到的关于你们所做的事情，有一点特别有意思：如果你看看 AI 的应用情况，早期采用者中有很多都在使用编程智能体。工程师们用它来为自己的企业、产品以及其他用途构建应用。而你们一直在做的事情，则是在开拓这一类别的应用范围：你们认为，应该让企业内部的任何人——比如 IT 人员等——都能构建可在整个企业范围内广泛使用的内部产品或工具。你们基本上是在提供类似于……的编程智能体。Speaker: I think one thing that you mentioned that's really interesting about what you do is if you look at the world of AI adoption, a lot of the really early adoption is coding agents. And that's engineers using it to build applications for their business, for products, other things. And what you folks have been doing is really pioneering expansion of the category in terms of saying we should let anybody internally an IT person, etc., build internal products or tools that can be used broadly across the enterprise. You're basically providing like coding agents for

发言者：那个，还有所有内部的东西。Speaker: the And all the internal stuff.

说话者：是的。Speaker: Yeah.

说话者：呃，对于那些通常不太擅长编程的人来说，你会多谈谈这方面吗？我觉得这特别有意思。Speaker: Uh for people who often aren't that adept at coding. So, do you talk more about that? I think it's like super fascinating.

发言者：是的，我们很喜欢这个“让所有人都能使用编程智能体”的想法。因为如果你想想，AI 在企业中的早期应用，很大一部分都来自工程团队。究其原因，显然有很多方面：他们是许多不同技术的早期采用者，而且他们能够构建和试验这些工具，因为他们有代码审查流程。即使是 19 岁的实习生，也可以构建功能强大的东西，再经过审查流程后投入生产，这非常安全。我们希望把同样的能力带给企业里的其他团队。因此，我们打造了一个平台，将编程智能体引入 IT 部门，再由 IT 部门将其推广到人力资源、财务、人事和法务团队。他们之所以能这样做，是因为底层采用了编程智能体，同时又提供了各种抽象层、安全防护机制和控制措施，让所有操作都经过审批、暂存与审批流程，并保留审计跟踪记录，等等。Speaker: Yeah, we love this idea of coding agents for the rest of us because if you think so much of the early enterprise adoption in AI has been engineering teams. And if you think about why that is, there's a lot of reasons, obviously early adopters in a lot of different technologies, but also they're able to build and experiment with these tools because they have this process of code review. It's very safe for even a 19-year-old intern to build something very powerful and then go through this process before it goes into production. We want to bring that same capability to the rest of the enterprise. So, we build a platform that brings coding agents to IT departments who then can bring it to HR and finance and people teams and legal teams. And they can do it because under the hood it's coding agents, but then you have all these abstractions and guardrails and controls, so things go through approval, they go through a staging and approval cycle and audit trail and all of that.

所以，问题是，如何构建一个系统，让每个人都能轻松成为构建者？这里的核心洞见是，IT 部门其实是想要构建东西的。对于世界上大多数公司来说，他们没有工程部门，只有 IT 部门。大多数公司都有 IT 部门，而不是软件工程师团队。所以，负责为公司构建和配置技术的是 IT 部门，而我们本质上是在为他们打造 AI 平台。And so it's how do you build a system that makes it easy for everyone to be a builder? And the core insight here was that IT actually wants to build stuff. And for most of the world, they don't have an engineering department, they have an IT department. Most companies have an IT department, not not a team of software engineers. And so IT is what's building and configuring technology for the company, and we're building essentially the AI platform for them.

企业中个人代理的局限性Limitations with Personal Agents in Enterprise

说话人：这会如何与正在开发的各种东西相互作用？比如那些更像劳动力智能体的东西，像 OpenAI 的 Dot，或者你知道的这些东西——你几乎可以把它们当作虚拟助手，让它们替你去做事。Speaker: How does How does that run into things like all the different more like workforce agents that are being developed? Like Dot from Open AI or, you know, some of these things where you almost have a virtual assistant that will go and do things for you.

说话人：是的，我觉得这些工具对消费者、中小企业，甚至很多中型企业来说确实很有效。但在大型企业里，事情太多了。我一开始其实都没意识到这一点：围绕审批、哪些事能做、哪些事不能做，有那么多流程；每个人的权限集都非常有限。所以，即使你获准把自己的智能体带到工作中——很多情况下其实是不允许的——它能做的事情也少得可怜。它甚至几乎连你的邮件都读不了。嗯，所以当你想到工作中需要做的所有事情、想要接触的所有系统，以及可以构建的各种有趣的自动化时，最终你个人的权限还是非常有限，这也让这些个人智能体变得极其……总之没那么有用。Speaker: Yeah, I think those really work well for consumers and SMB and even a lot of the mid-market organizations. In a large enterprise, there's so much, and I didn't even really appreciate this going in, there is so much process around approvals, around what you can and can't do, the permission sets of any individual are so limited that even if you were allowed to bring your agent to work, which a lot of cases you're not, what it can what it can do is so incredibly limited. It can It can barely even read your emails. Um and so when you think about all the stuff you need to do at work and all the systems you want to touch and all the interesting automations you could build, your personal permissions end up being so limited that these personal agents are also incredibly and all not all that useful.

所以，我们与这些 IT 团队合作，他们可以使用服务账户凭据和管理员级权限进行连接。我们可以据此构建一种机制，让人们能够获得更高权限，在工作中执行各种复杂操作，同时设置非常严格、可确定的审批周期和工作流，并保留审计记录，因为在底层，我们也是一个工单系统。比如你说：“好，我想让我的智能体去做 X、Y 和 Z。”大多数组织在大型企业规模下都会对此非常不放心；但通过 Serval，这会生成访问权限申请，并进入审批流程，整个过程都会被记录下来。之后，你就可以获得即时访问权限，运行一次这个确定性工作流，而整个过程也都会受到追踪。So what we can do because we work with these IT teams that can connect with, you know, service account credentials and admin level permissions, we can create a structure where people can access elevated permissions and do all these crazy things in the work, but with very, very strict deterministic approval cycles, workflows that are deterministic, um and an audit trail because under the hood we are also a ticketing system. So you say, "Okay, I want my agent to go do X, Y, and Z." Well, most organizations are going to be very uncomfortable with that at the large enterprise scale, but with Serval, that's going to create access requests that go through an approval process, and all of that's going to be documented logged, and then you can get just-in-time access to be able to run that deterministic workflow one time, and all that's going to be tracked.

没错，这确实比我们喜欢的 Instinct、Muse 以及所有这些工具所带来的神奇个人智能体体验要麻烦一点，但对于大型企业，尤其是受监管的企业来说，只有满足这些条件，才有可能采用这类技术。And yes, it's a little bit more annoying than the magical personal agent experience we love with Instinct and Muse and all these tools, but it's what has to be true for a large enterprise, especially regulated enterprise, to ever adopt these kinds of technologies.

在大型组织中有效部署 ServalDeploying Serval Effectively in Large Orgs

发言人：我想，这也涉及这项技术传统上的推广方式：咨询公司，比如埃森哲、德勤之类的公司，会参与其中，负责为客户实施。你们某种程度上是把这件事直接交到了 IT 部门手里。你们是否也在探索一种更像前线部署的模式？或者说，究竟怎样才能在企业内部真正落地这项技术，或者让它得到有效应用？Speaker: And this also, I guess, feeds into the traditional diffusion of this technology, which has been consulting firms, the Accentures and Deloittes and the like of the world kind of owning a piece of this, doing the implementation for people. You're kind of taking that and putting it in the hands directly of the IT department. Are you also exploring this more as we're sort of forward deployed motion, or how do you actually get this really built out in the enterprise or used effectively?

发言人：是的，当然。显然，差距就在于技术的普及应用。技术能做的事情非常多，而企业对其潜力的探索才刚刚起步。其中很大一部分工作，只是了解员工、流程、现有的工作流，以及未来希望这些工作流变成什么样。我们认为，这些事情仍然需要人来做。因此，我们会派遣一位部署策略师（我们这么称呼他们），以及一位软件工程师到客户现场，弄清楚该如何实施这项技术、如何解决企业面临的所有问题，并全程指导客户完成实施。不过，我们发现，很多时候，在完成实施和部署之后，客户还有一长串想要做的事情。正如我们在软件工程领域所发现的，待完成的工作需求实际上是无穷无尽的。Speaker: Yeah, absolutely. Diffusion is obviously the gap here. The technology can do so much, and enterprises have barely scratched the surface of what's possible. And a lot of that is just understanding the people, the process, what workflows actually exist, how do you want them to exist in the future, and we think that you still need people for that. So, we deploy both the a deployment strategist, we call them, and a deployed software engineer that go on site with customers, figure out how do we implement this, how do we solve all your problems as a business, and then walk you through the implementation. What we found though is that a lot of times after we've got this implemented and deployed, customers that have a long tail of more stuff they want. And as we've discovered with software engineering, there's actually unlimited demand for work.

我们已经开始组建一支团队，我们称之为 Pro Serval。嗯，自动化工程是这个领域的名称。我们引入这些自动化工程师，提供持续的支持和服务，因为他们有太多想要自动化的事情，也需要有人帮忙梳理哪些事情可以自动化、流程是什么样的、如何在我们的各个系统中操作，然后再借助 Serval 这样的产品将其投入生产。And we've started to build out a team, we call it Pro Serval, uh or automation engineering is the field, and we bring in these automation engineers to kind of do ongoing continued support and services because there's so much that they want to automate, and they need the help to be able to figure out what can be automated, what do the processes look like, how do we navigate all of our systems, and then put it into production with a product like Serval.

第 1 天：雄心壮志与攻克企业级记录系统Day 1 Ambition and Attacking Enterprise Systems of Record

发言人：这家公司今天成立多少年了？Speaker: How old is the company today?

发言者：两年半。Speaker: Two and a half years.

发言人：嗯，你知道，如果你只把 ServiceNow 当作一门生意来看，我觉得 Serval 是少数几家会直接出击、替换大型企业的核心记录系统的公司之一。嗯，一开始你就觉得自己会这么做吗？你是怎么……怎么啃下这头大象的？你知道，毕竟那套产品组合规模非常庞大。Speaker: And um, you know, if you just look at ServiceNow as a business, I feel like Serval's one of the only companies that is like, we are direct attack replacing enterprise systems of record including for large enterprises. Um at the beginning did you think you were going to do that? Like do you How do you eat the elephant? You know, just in terms of, you know, how big that product suite is.

说话者：我喜欢说，一切都完全按照我们那些极其不切实际的计划进行。我们从一开始就立志要成为史上最大的企业软件公司。我们确实列出了Speaker: I like to say everything has gone exactly according to our very delusional plans. So we set out from the beginning to be the largest enterprise software company of all time. We actually made a list of all the companies. We circled Service Now and we said we're going to beat them and we're going to build something much bigger. We said that on day one when it was two people in my co-founder Alex's living room and we just said we're going to do it. And so even though that was crazy, that was always the intention. We didn't grow into that ambition. We set out from the beginning and I think that actually

说话人：比如说，人们可能会先从工单系统上的自动化入手。Speaker: of people would have started with like, you know, automation on top of their ticketing system for example.

发言人：是的，没错。所以，通常你们进军大型企业市场的方式，至少是打造一个这样的层，或者转向中小企业市场。这算是两种常见的做法：打造一个小型层，与大型现有厂商友好共存，在他们现有的工作流程之上构建 AI 智能体。Speaker: Yes, exactly. So the way you typically go after these these large enterprise startups at least they build like the layer or they go down market. And those are kind of the two common approaches. Let's build a small layer, play nice with the big incumbents, AI agent on top of their existing work.

就像你知道的，这确实限制了……也许唯一成功的是 Vevo 之类的，对吧？因为他们一开始用的是 Salesforce，后来迁移到了自己的平台。所以他们是我能想到的唯一一家实现了反向整合的公司。Speaker: Which like you know, it's it really caps maybe the only one that worked is Vevo or something, right? Cuz they started off on Salesforce and then migrated to become their own platform. So they're they're the only one that I can think of that backwards integrated.

发言人：这确实很难。它就像给你设了个上限，除非你后来能找到某个细分领域，逐步拓展进去。嗯，另一种做法就是我们转向低端市场，你知道，去服务中小企业和中端市场。你会看到很多 Workday 和 Salesforce 的竞争对手都这么做。他们会说，我们要做同样的产品，只不过面向更低端的市场。Speaker: It's really tough. It like caps you unless you find some niche to kind of like expand into later on. Um the other approach is we just go down market, you know, go down market, service the SMB and mid-market. And you see that with a lot of, you know, competitors to Workday, competitors to Salesforce. They just say we're going to be that but for the lower end.

发言人：我们刚才看的就是 Rippling 或 HubSpot。Speaker: And we just looked at This is Rippling or HubSpot.

发言者：没错。Speaker: Exactly.

发言人：10年。Speaker: 10 years.

说话人：没错。我们看了看，就想，为什么不直接瞄准大客户呢？这确实难得多，但至少一旦成功，回报也相当丰厚。我认为这对我们来说非常重要，因为如果从第一天起就为大型企业开发产品，你最终会做出许多不同的决策。无论是产品决策、团队建设方式，还是对增长的思考，这些都和先服务一个市场、再希望日后拓展到其他市场有着根本性的不同。Speaker: Exactly. And we looked at that and we said why not just go after the big one? It's it's much harder but at least the prize is quite big if you win. And I think that was so important for us because you end up making so many different decisions if you're building for the large enterprise from day one. All the product decisions, how you build your team, how you think about growth, they're fundamentally different than if you go and you serve one market and then you hope to expand later on.

借助工作流自动化平台挑战 ServiceNowTaking on ServiceNow with Workflow Automation Platform

发言人：你是怎么在这个和 Salesforce Server 之间做选择的？你知道，不同领域还有几家其他堪称典型的巨头公司。Speaker: How'd you choose this versus Salesforce server? You know, there's a few other sort of canonical giant companies in different categories.

发言者：我觉得我们当时并没有真正弄清楚，要怎样才能打败其他公司、我们的优势是什么，以及 AI 带来了哪些他们无法追上的能力。基于我们在 IT 领域的经验，我们对 ServiceNow 的理解是，它从根本上说是一个工作流自动化平台。我和我的联合创始人都相信这一点，而我的联合创始人很早就有这样一个想法：代码才是表达企业自动化的正确方式。你应该把所有自动化都用代码来构建，而这些拖放式工作流构建器所提供的抽象层既让非技术用户觉得过于复杂，也让技术用户觉得抽象得令人恼火。代码是构建自动化的更好方式。显然，问题在于，能写代码、而且能足够快地写代码，让自动化变得切实可行的人并不多。Speaker: I think we didn't really understand how we'd beat the other companies and why we had an advantage and what AI unlocked that they couldn't catch up to. And what we understood about Service Now because of our experience with IT is that fundamentally it is a workflow automation platform. And our belief, me and my co-founder, and my co-founder really had this this idea early on that code was the right way to express automation in the enterprise. That you should just build all automation in code and these drag-and-drop workflow builders is a painful level of abstraction because it's too complex for non-technical users and it's annoyingly abstracted for technical users. Code is a better way of building automation. The problem obviously is not many people can write code and do it quickly enough for it to make sense for automation.

随着 AI 让这一切成为可能，我们俩都一下子意识到：如果代码是构建自动化的正确方式，而现在任何人都能写代码，那我们就能打造一个更好的自动化平台。什么是自动化平台？自动化平台最好的市场又是什么？其实就是挑战 ServiceNow 这样的庞大传统软件公司。And so as AI made this possible, that was what it clicked for both of us that actually if code is the right way to build automation and now anyone can write code, we can build a better automation platform. And what is an automation platform is actually what is the best market for an automation platform? It's actually taking on these massive legacy software companies like ServiceNow.

押注编码智能体的演进，并在企业中构建防护机制Betting on the Evolution of Coding Agents and Building Guardrails in Enterprise

说话者：我想，两年半前你刚开始的时候，大多数编码工作基本上还只是 Tab 补全。它并不好用。Speaker: I guess two and a half years ago when you got started though most of the coding stuff was sort of tab complete. It did not work.

发言者：是的，所以，嗯，不过实际上，当我们开始构建这个时……Speaker: Yeah, and so yeah, but in practice when we started building this

发言者：当时的假设是什么？是认为编程能力会大幅提升吗？还是说你们原本打算打造一些工具，后来发现事情进展得太顺利，就不需要了？我有点好奇这中间的转变。Speaker: What was the assumption? Was it that the coding would get much better? Was it that you'd build tooling and then you didn't need to because things got so good? I'm sort of curious of that transition.

发言人：我们的赌注是，编码智能体会变得非常出色。嗯，我们的理论是，这是一个可验证的领域，而且它应该能够很好地逐步提升。所以我们从根本上相信，编码智能体会变得很擅长——至少擅长这类事情。我没想到它们在通用软件开发方面会变得这么厉害，但对于重置密码、获取审批之类的确定性流程脚本，这些事情都有非常明确、可验证的定义，所以我们觉得它们会很擅长处理这些事情。因此，从工作流自动化的角度来看，我们认为它们最终能够做到。早期并非如此。所以我们在所有早期演示中最终采用的做法是，提示大语言模型并说：“嘿，下面是一种你可以考虑用来构建密码重置工作流的方案。”Speaker: The bet was that coding agents would be would get very good. Um and the theory there was it's a verifiable domain and it should actually hill climb fairly well. And so we believed fundamentally that coding agents would get good at least for these very I didn't expect them to get as good as they are for just general purpose software development, but for deterministic procedural scripts of reset password, get approval, like all of these things are just so defined and verifiable that we felt like it would get good at those things. And so from a workflow automation perspective, we thought it would get there. In the early days it did not. So what we ended up doing in all our early demos, we would prompt the LLM and say, "Hey, here's a suggested way you might want to build a password reset workflow."

所以我们会用大量示例来训练它，然后随着时间推移，不断扩充这个库。但后来模型变得非常强大，最终几乎很难让它出错。如果 API 存在，你很难给它一个它无法自动化的工作流程。And so we'd we'd seed it with like a lot of examples and then over time we'd make that library bigger and bigger, but then the models just got so good that eventually it became hard to break. It became hard for you to give it a workflow that it couldn't automate if the APIs existed.

说话者：是的。Speaker: Yeah.

说话人：当你想到如今编程智能体的发展状况，以及客户想要什么时，你和 Alex 对它们今后的进步感到兴奋吗？你们会紧张吗？你觉得这会对你们自己的产品产生怎样的影响？Speaker: When you think about where coding agents are today and what your customers want, like what are you Are you and Alex excited about them getting better from here? Are you nervous? Like what do you think it looks like in terms of impact on your own product?

发言人：我们非常期待它们变得更好，因为我认为这会解锁很多我们希望实现的功能，比如更好地使用浏览器和计算机，以及更好地采用后台智能体和个人智能体，让它们在企业环境中真正发挥作用。所以，我们对这一领域的发展感到兴奋。我们始终坚信，归根结底，我们并不是在自己构建大语言模型。我们构建的是护栏，是边界。对我们来说，边界就是产品，因为我们让拥有众多规则、审批、流程和复杂人际关系的大型企业能够安全、放心地大规模采用这些工具。因此，Serval 就是边界，就是护栏。智能水平不断提升，只会让我们的产品更强大，也会让客户更希望进一步收紧这些边界和护栏。Speaker: We're so excited for them to get better because I think it unlocks a lot of the things that we'd love to do around, you know, better browser use and computer use and more of a approach to background agents and personal agents that can be really useful in the enterprise. So, we're excited for the evolution of the category. We've always believed fundamentally that we are not building the LLMs ourselves. We are building the guardrails. We are building the boundaries. And the boundaries are the product for us because we are the way that a large enterprise with a lot of rules and approvals and process and politics can adopt these tools safely and comfortably at scale. And so, Serval is the boundary. Serval is the guardrails. The intelligence getting better just makes our product more powerful and also makes our customers want to actually clamp down even further on those boundaries, on those guardrails.

而且我确实认为，企业中个人的访问权限会受到越来越严格的管控。随着访问管控变得更加严格，人们能做的事情越来越少，权限范围也越来越窄——我认为这种情况一定会发生，And I actually think access is going to get more and more controlled for individuals in the enterprise. And as access becomes stricter and you let people do less and less and your permissions get more and more narrow, which I think is going to happen,

发言者：为什么会发生这种事？Speaker: Why is it going to happen?

发言者：因为我觉得，如果你想想看，我可能会放心地给你比你需要的更多权限，因为我其实不觉得你会造成多大损害。但如果你能访问所有这些代理，那么只要权限稍微高于普通权限，你可能造成的损害范围就会扩大。我们现在在网络安全风险中就看到了这种情况。Speaker: Because I think if if you think about, you know, I might safely give you more permissions than you need because I don't actually think you're going to do all that much damage. But if you have access to all these agents, then the damage you can do with any kind of like slightly elevated beyond normal permissions expands. And then we're seeing this in cybersecurity risk right now.

发言人：当然。Speaker: Absolutely.

发言人：所以，如果我是大型企业，我真正想做的，就是把每个人的权限都收紧到严格遵循最小权限原则。也就是说，除非你确实需要为了工作这么做，否则你不能访问任何文档，也不能执行任何操作。但这样一来，你们就会不断遇到例外情况。我们提供的正是授予这些例外权限的这一层，并让你们能够围绕这些权限设置审批流程、保留审计跟踪记录，并关联相应的工单。因此，通过掌控企业中权限如何提升，我们实际上会变得更有影响力，也更加不可或缺——你们对终端用户权限的限制越严格，就越是如此。Speaker: And so, what I'm actually going to want to do if I'm a large enterprise is shrink everyone's permissions down to truly least privilege. Like you cannot access any document and you cannot take any action unless you absolutely need to do it for your job. But then you're going to have exceptions all the time. We are the layer that grants those exceptions and makes it possible for you to set up approval procedures around that, have an audit trail and a ticket associated with that. So, by owning how privileges get escalated in the enterprise, we actually become more powerful and more essential the more you clamp down on end user permissions.

关于 Serval 和编程智能体的重大风险、丰厚回报与大胆预测Big Risks, Big Rewards, and Big Predictions for Serval and Coding Agents

发言者：有没有什么故事或成功案例可以分享？你知道，人们选择你们来替换一个根深蒂固的现有供应商，肯定要冒很大的风险，对吧？我想，这也需要投入他们自己的时间。这就像是在承担个人风险。那他们为什么要这么做呢？或者说，有没有人已经走过这段路、成功转型的经历？Speaker: Is there um like a story or a win you can share as to, you know, people would be taking a big risk going with you to replace a very embedded incumbent, right? It's a investment of their own time, I assume. It's like personal risk. Like, why do that? Or is there a is there an experience where people have already gone through to the other side?

发言者：我认为，我们必须让自己和客户相信，Serval 是你在职场上获得晋升的途径。不能把它看成一种冒险：你只是希望冒险之后能有所收获。我们必须让客户相信，只要采用这种做法，你就能成就自己的事业。你不只是不会惹上麻烦，还真的能获得晋升。Speaker: I think we have to convince ourselves and our customers that Serval is the way you get promoted at work. It can't be the fact that Serval is a risk that you take to hopefully get something on the other side. We have to convince customers that you do this and you're going to make your career. You're not just going to not get in trouble, but you're actually going to get a promotion.

发言人：这是自上而下的，对吧？Speaker: And this is top-down, right?

发言人：自上而下。我们向高管层销售。在很多情况下，我们也向 IT 领导层销售，然后再推广到其他部门。我们传达的信息是：有人依托 ServiceNow 成就了自己的职业生涯，而你们将依托这一代新产品成就自己的职业生涯。我们也看到这一点正在成为现实。我们最大的客户之一是福克斯。嗯，福克斯公司在全公司范围内采用了 Serval，而在一线主导这次迁移的那个人，实际上获提名成为整个公司的 MVP。Speaker: Top-down. So, we sell into the C-suite. We sell into the IT leadership in many cases and then distribute into other departments. And that is the message is this is people built their career on ServiceNow. You're going to build your career on this next generation. And we're seeing this play out. So, one of our largest customers is Fox. Um Fox Corporation adopted Serval company-wide and the person who led that migration at the on the on the ground level actually got nominated to be the MVP of the entire company.

说话人：哇。Speaker: Wow.

发言人：他还因在那里所做的工作获得了奖项。我们真正关注的就是让客户相信，这不仅是证明你对组织有用的方式，更是证明你可能是公司里最不可或缺的人，因为你正在引领这场变革。而我们对AI转型的故事至关重要，所以我认为，这确实是我们可以很好地向客户推介的东西。Speaker: And got an award for his work there. And that is really what we're about is we're convincing our customers saying like this is the way to not just prove that your your useful to your organization, but to prove that you might be the most essential person in your company because you're leading this change. And we're so pivotable pivotal to the AI transformation story that I think it's a it's something we can sell really nicely to our customers.

发言人：你创办 Serval 的时候，我觉得你非常擅长未雨绸缪，对吧？所以你知道编程智能体会变得更好，或者说编程会变得更好。你知道转型会以什么方式发生。你也算是找准了值得切入的细分市场。你预测未来 2 到 3 年会发生什么？不仅是对你们公司而言，对更广泛的 AI 领域也是如此。你在前方看到了什么让你特别兴奋的趋势，或者你觉得即将到来的重大变革？Speaker: When you started Serval, I think you were very um adept at thinking ahead, right? So, you knew coding agents or coding would get better. You knew there's way of transformation. You kind of identified the good market segment to go after. What do you predict will happen in the next 2-3 years not only for your company, but for AI more broadly? Like, is else you're seeing on the horizon that you're very excited about or a big shift that you see coming?

发言人：我认为，消费领域往往能让我们窥见企业领域接下来会发生什么。嗯，这种情况并不总是一样，但我觉得这是一个很好的观察窗口。所以我非常看好个人代理在企业中的形态。我认为，就像电子邮件、Slack 及其他这些工具改变了我们在工作中的沟通方式一样，个人代理也会成为其中的重要组成部分。我觉得每个人都会有自己的个人代理，替自己处理任务，并把任务委派给其他个人代理。这样一来，你的代理就会和工作中的其他代理交流。我对此真的非常期待，但问题是，在网络安全风险不断上升、大型企业也越来越担心每个人的代理都在各自的电脑上执行操作、使用浏览器的情况下，我们该如何保障安全？Speaker: I think consumer often gives us a win-window into what's going to happen next in enterprise. Um and it all it doesn't always look the same, but I think it's it's a nice window. So I'm very bullish on what do personal agents look like in the enterprise? I think in the same way that email and Slack and these tools transform how we communicate at work, I think personal agents will also be a big part of that. I think everyone will have their personal agent that does tasks for them, that delegates to other personal agents. And so your agent will talk to other agents at work. So I'm really excited about that, but then how do we secure that in a world of increasing cybersecurity risk and increasing concerns at large enterprises around what's happening with everyone's agents taking action in all their computers and using their browsers.

因此，员工和消费者希望他们在工作中使用的个人智能体具备什么，与企业从治理角度需要什么之间的这种张力，我觉得非常有意思。我认为，这种张力中蕴藏着很多机会……And so that tension between what employees, consumers want out of their personal agents at work and what enterprises need from a governance perspective, I think is really interesting. And I think there's going to be a lot of opportunity in that in that tension of

发言人：你觉得会有单独的个人代理和工作代理吗？Speaker: think there'll be a separate personal and work agent?

说话者：我想是的。我想是的。Speaker: I think so. I think so.

说话者：是的。Speaker: Yeah.

说话人：我想是的。就像我有一个 Gmail 账号，也有一个公司邮箱。嗯，是的。Speaker: I think so. In the same way that I have a Gmail and I have a corporate email. Um yeah.

在企业层面采用不同的构建原则体系Adopting Different Sets of Building Principles at an Enterprise Level

发言者：如果说有个前提——这里其实有很多不同的想法——其中之一是，嗯，你知道，异常处理或访问控制会变得复杂，并且需要不同级别的规模，对吧？另一个想法是，自动化总体上会越来越多，因为人们，你知道，如果你让事情变得简单，人们就会在各种地方拓展应用。那么，除了“代码生成应该是你们今天在产品中采用的实际自动化形式”之外，你们还融入了哪些反映这些情况的核心设计原则吗？Speaker: If there's a premise that I mean there's a bunch of different ideas here, but one is that um uh you know, exceptions or access control is going to get complex and require different level of scale, right? Another is that you're just going to have more automations overall because people, you know, if you make it easy, people are going to extend in all different places. Are there like core design principles beyond uh code generation should be the actual form of automation that you have put into the product today that reflect that?

说话者：我觉得最重要的是软件开发生命周期。在工程领域，我们往往把一些事情视为理所当然：比如，实际上有开发环境，然后是预发布环境，再然后是生产环境，它们之间还有一些关卡；此外，可能还有供人们开发的分支，这样就不会影响其他系统。Speaker: I think the biggest one is the software development life cycle. Something that we take for granted in the engineering context of the hey, there's actually like a dev environment and then there's staging and then there's prod and there's like these gates between them and maybe you've got, you know, branches that people can develop on that they're not going to harm the other systems.

发言人：抱歉，我只是想澄清一下，今天的 IT 自动化并不是这样运作的。Speaker: And sorry, just to be clear, that's not how IT automation works today.

发言者：嗯，有些情况下确实如此，但我认为大多数新的 AI 产品并没有采纳这种做法。它们基本上是在说：“嘿，我们来打造这些很酷的智能体，然后直接上线。”但是，像“嘿，如果你是一家大型企业或大型金融机构，就必须遵循 SDLC 流程”这样的理念，并不会让人不经审查和用户验收测试等流程，就直接推出新的智能体功能……Speaker: Uh it does in some cases, but I think most new AI products are not embracing that. They're basically saying, "Hey, let's build these cool agents and ship to production." But, this idea of, "Hey, you have to actually follow an SDLC process if you're a large enterprise, a large financial institution, is not just going to ship new agent capabilities uh without a review and user acceptance testing and all of these

发言者：合规检查。Speaker: Compliance checks.

发言者：没错。所以我认为，我们经常思考的一件事是，什么才能说服世界上最大的公司采用这项技术，而不只是关注它有多强大、多酷，以及我们多么期待把它交到客户手中。Speaker: Exactly. And so, I think that's something we think about a lot is what is going to convince the largest companies in the world to adopt this technology, not just what is powerful and cool and something we're excited to get in the hands of customers.

发言人：许多 AI 公司，尤其是那些专注于垂直领域的公司，往往要花一两年，甚至更久，才能弄明白这一点。有趣的是，如今整个行业都在采用前线部署模式，并开始全面考虑软件开发生命周期、合规性以及企业的其他方面，而这些过去几乎都被忽视了。Speaker: it takes a lot of AI companies, particularly if they're vertically centric, a year or two to figure this out, sometimes longer. And it's interesting to watch the whole industry now adopting both the forward deployed motion, starting to think through uh software development life cycle, compliance, other aspects of the enterprise in a way that was almost missing.

发言人：我觉得有些情况下，他们永远也走不到那一步。比如，有些公司会看看企业软件需要做些什么，然后决定：“我们其实不想做这个。”你知道，看看我们之前提到的许多转向下沉市场的公司，它们的发展历程就能发现这一点。我觉得有时候，他们确实会考虑进军企业市场，但这需要一套完全不同的构建原则，也需要打造完全不同的产品，而有些公司就是不愿意这么做。他们眼看着其他公司在这片领域站稳脚跟。而我们选择说：“嘿，把你们最棘手的问题交给我，我们会解决它们，让 AI 转型成为可能——就在这个疯狂的世界里，在这个充满风险与治理顾虑的世界里。”Speaker: I think in some cases they never get there. Like, some companies just they look at what enterprise software takes, and they decide, "We don't really want to build that." And it takes, you know, you look at the story of a lot of these companies that we mentioned earlier that have gone down market. I think sometimes they do look at the opportunity to go and build for the enterprise, and it requires a whole different set of building principles and products that you have to build, and some just don't choose to do it. And they see that ground other companies. And we've chosen to say like, "Hey, give me your your gnarliest problems, and we're going to solve them and make AI um transformations possible in this this crazy world, in this world of risk and governance concerns."

发言人：当你们部署时，会有一些关键客户环境工程师、持续自动化专家，以及核心平台。你们如何决定哪些内容应该纳入核心平台，哪些内容应该保留在每位客户各自的环境中？Speaker: When you um have your, you know, deployment, you have sort of key customer environment engineers, and then ongoing automation specialists, and then you have the core platform. How do you decide what is actually brought into the core platform or, you know, in every individual customer's environment?

发言人：是的。所以，在部署软件时，我认为真正重要的是，我们实际上从不开发定制功能，也不打造专属的产品能力。幸运的是，就我们这个类别而言，没有人要求我们这么做。大家提出的需求，迟早都会是其他客户也想要的。它们或许会影响优先级，但始终都是我们原本就希望纳入平台的功能。另一方面，由于底层采用的是 CodeGen 平台，在 Serval 上构建的东西会非常、非常独特。因此，一家公司的密码重置工作流，和另一家公司的密码重置流程会截然不同，甚至让人惊讶。入职、离职以及各种内部自动化也是如此：它们看起来都大不相同，但这些差异本来就融入了平台的核心基础组件之中。Speaker: Yeah. So, when we deploy the software, I think what's really important is we actually never build custom features. We don't build bespoke product capabilities. And luckily for our category, no one asked us to. Everything that people ask for is something that every other customer is going to want at some point. Maybe they impact the prioritization, but it's still something we always wanted in the platform. Now, because it is a CodeGen platform under the hood, what you build in Serval is very, very unique. So, the password reset workflow for one company is going to be very different, shockingly, than the password reset for another. Um, same with onboarding and offboarding and all these different automations internally, they look very different, but that's just baked into the core primitives of the platform.

Serval 几乎就成了 IT 部门和其他部门用来构建自动化流程并大规模管理它们的 IDE，对吧？所以，我们确实会做的是：如果我们发现同一个客户一遍又一遍地构建相同的自动化流程，还得以同样的方式在产品中定制和搭建它们，我们就会开始考虑：“嘿，这是不是应该成为产品中的一项一等功能？”举个例子，我们发现很多客户都在构建工作流，用来检测知识库文章之间是否存在冲突，或者内容是否已经过时。于是我们就说：“嘿，我们应该直接自动完成这件事。”还有些客户会设置自动化流程，回收闲置许可证。也就是说，对于那些你付费购买、但没人使用的软件许可证，我们可以自动取消相应的订阅。Serval almost becomes the IDE, right, for the IT department and other departments to build their automations and manage them at scale. So, what we do do is if we look and we see the same customer building the same automations over and over and over again, and having to customize them and build them in the product in the same way, we start to consider, "Hey, should that be a first-class feature in the product?" So, one example is we saw a lot of customers building workflows to detect knowledge base articles that were out uh conflicting or out of date. And so, we said, "Hey, we should just do that automatically." And we had customers that, you know, would would set up automations to reclaim old licenses. So, licenses for software you're paying for that no one is using, let's automatically cancel those subscriptions.

嗯，我们刚刚决定在平台中构建这个功能。所以，这能让我们试探一下，哪些功能应该成为 Serval 中的一等功能，哪些则应该继续作为自动化流程。Well, we just decided to build that in the platform. So, it is a way for us to kind of test the waters of what should be really first-class features versus what should stay as automations uh in Serval.

Token 最大化、长期预算影响与投资回报率Token Maxing, Long-Term Budget Impacts, and ROI

发言人：就软件团队在代码生成方面的一般支出而言，我们的企业客户今年经历了一段过程，对吧？他们一开始会说：“呃，我们先让大家试试。然后我们会把 token 上限设好，再限制一下，看看谁真正有效地在用这个产品。”嗯，你觉得这对你的业务有什么影响？你又是如何看待实际的智能成本的？Speaker: Our enterprise customers, as it relates to just general spend on code generation for software teams, have come through a journey this year, right? They're like, "Uh, we're going to let people try it. Then we're going to token max and we're going to like restrict that and figure out who's actually doing this productively." Um, how do you think that reflects for your your business and how do you think about um the sort of actual intelligence cost?

发言者：是的，我觉得我们还在关注这一点。我确实看到，我们的 CIO 客户正试图从最初那种不计代价地消耗 token 的阶段收手，但我也认为，我们还处在采用曲线的早期阶段，所以总体上不会出现收紧开支的情况。实际上，采用规模还会继续大幅增长，因为大多数公司都还在第一次摸索如何使用这项技术。他们都会经历这样一个周期：早期快速采用，随后在一定程度上缩减支出，并尝试衡量和计算投资回报率（ROI）。不过，我一直从客户那里听到的，并不是他们真的担心长期预算会受到什么影响。他们意识到短期内会有所收缩，但仍计划增加支出。不过，他们需要更多投资回报的证据。我认为，这正是行业即将发生的转变：人们会开始寻求证明，自己投入的这笔钱究竟能带来什么。Speaker: Yeah, I think we're still watching this. I do see our CIO customers trying to pull back from that initial token maxing era, but I also think we're so early in the adoption curve that it's not going to be a clamp down in aggregate. It's actually going to continue to be a pretty dramatic rise because most companies are still figuring this out for the first time. And they're they're all going to go through this cycle of rapid early adoption and then kind of a pull back of spend and trying to measure and calculate ROI. Um, but what I hear from our our customers all the time is not really a concern about the uh long-term budget impacts. They realize that there's going to be a short-term pullback, but they're still planning on increasing spend. What they need though is more proof of ROI. And that I think is what's going to transform in the industry is people looking for how can I prove that this spend is giving me something?

而这很难。我不知道是否有人真正弄清楚了，如何衡量你从购买的 token 中获得了什么，但我认为，这将是一个巨大的机会，让我们展示正在完成的工作，并尝试将其与在其他平台上、采用其他成本模式或由人工完成的工作进行对比。因此，我们的客户提出的要求是：帮我证明这笔投入是值得的。这就是我们的任务，也是我们必须做到的事。我们试着按运行的工作流来定价，因为我认为这比只看 token 更能反映实际完成的工作；单看 token 数量，更像是在衡量冗长和低效。不过，我想我们最终都会找到不同的方式，来证明我们所做的事是合理的。And that is hard. I don't know that anyone's really figured out how to measure what you're getting from the tokens that you're buying, but that I think is going to be a huge opportunity for us to show the work that's being done and try to equate it to work that would have been done in other platforms or with other cost models or by labor. And so that's what our customer asked for is help me prove that this was worth it. And that's what the assignment is. That's what we have to do. We try to price on workflows run because I think it's a better reflection of actual work being done versus just tokens, which is more like verbosity and inefficiency, but I think we're all going to figure out different models of proving that what we're doing makes sense.

SaaS末日与SaaS对决AIThe SaaS-pocalypse and SaaS vs. AI

发言人：人们一直在讨论的一件事，是所谓的“SaaS 末日论”：也就是说，人们会直接构建内部 SaaS 软件，而所有这些类别的软件都会消失。正如你刚才提到的，很多人正在尝试厘清，以 token 计算投资回报率，重建这些系统是否值得？而且，这真的能有效实现吗？你怎么看所谓的“SaaS 末日论”，或者说 SaaS 与 AI 之间的这种转变？Speaker: One of the things people have been talking about is the sort of SaaS-pocalypse, where the idea is, you know, people will just build their internal SaaS software and all these categories will go away. And a lot of people, to your point on calculating the ROI in tokens, are kind of trying to sort is it worth rebuilding these systems? And can you actually do that effectively? What is your view on the SaaS-pocalypse or this sort of shift in SaaS versus AI?

发言人：我认为，我接触过的所有尝试自行编写代码、开发这些工具的公司，尤其是开发核心系统记录工具的公司——不是那些点解决方案，而是核心系统记录工具——都发现构建和维护企业软件的成本相当高。即使做得到，在很多情况下也不符合经济效益，除非你的需求非常定制化、独特。所以，对于非核心竞争力相关的事务，购买现成产品，我认为始终都是“自建还是购买”的问题。如今这个问题依然如此，和以往任何时候都一样。嗯，因为构建企业软件仍然很难。很多很多公司都在发现这一点，或者重新认识到这一点：企业软件确实很复杂，而且需要有人来维护。Speaker: I think all the companies I've talked to that tried to buy code these tools internally, especially the main system record tools, not the kind of point solutions, but the main system record tools, have discovered that it's quite expensive to build and maintain enterprise software. Even if you can do it, it doesn't make economic sense in many cases to do it unless your needs are very bespoke and unique in some way. And so buying off-the-shelf for things that are not your core competency, I think has always been the build versus buy argument. I think that is true now as it is as it as it's ever been. Um because it still is hard to build enterprise software. A lot A lot of companies are discovering this or relearning this that actually enterprise software is complex and you need people to maintain

发言者：有哪些使用场景和边缘情况？Speaker: What are use cases and edge cases?

说话人：边缘情况，呃，那些会出故障、需要有人更新的东西。这样一来，你就得给团队配人，然后为这些人力买单；而且很多情况下，根本没人愿意去内部工具团队工作。所以，做这件事会遇到这些问题。我确实能看到它在一些单点解决方案领域发挥作用，很多公司都有成百上千个 SaaS 应用。它们可能需要几十种工具。所以我确实认为，各种单点解决方案会逐渐减少，它们会被核心记录系统和核心平台所取代。Speaker: Edge cases, uh thing things that um break down and people need to update it, so then you have to staff the team and then you're paying for that labor and then no one really wants to work on the internal tools team in many cases. So, you have all these problems with doing that. Where I do see it is in kind of the point solutions where a lot of companies have hundreds and hundreds of SaaS applications. They probably need a couple dozen tool. And so, I do think you're going to have a shrinking of the sprawl of different point solutions and they're going to be eaten by the core systems of record and the core platforms.

发言人：我觉得中间件也会逐渐消失。Speaker: middleware, too, I think is just going to go away.

发言者：没错，没错。所以我认为行业会出现整合。嗯，SaaS 确实会迎来一场末日，但这主要会影响那些提供单点解决方案、市值较小的公司。我不认为核心记录系统会就此消失，比如 ERP、HRIS、ITSM 和 CRM。我觉得这些系统会继续存在。它们可能会转型，而我们从 Serval 身上看到的是，我们正在取代这些工具。嗯，所以我认为会出现新一代的行业巨头，但我不觉得这些类别会就此消失。Speaker: Exactly. Exactly. So, I think there is going to be consolidation. Um and so, this there will be a SaaS apocalypse, but in that kind of point solution um smaller market cap type companies. I don't think that you're going to truly get away from the core systems of record, the ERP, the HRIS, the ITSM, the CRM. I think those are going to stick around. They might transform and what we're seeing with Serval is we are displacing the those tools. Um so, I think there will be a new generation of incumbents. Um but I don't see those categories just disappearing.

向企业 IT 用户交付平台级能力的思维模型The Mental Model for Delivering Platform-Level Power to the IT User at Enterprise

发言者：呃，我很好奇，你对 IT 用户有什么样的心智模型，呃，或者说心智理论？你知道，他们不是软件工程师，但他们了解自己的业务，也清楚自己想要自动化什么。你知道，聊到氛围编程（vibe coding）时，我就会想：“好吧，但你了解安全架构吗？你明白这要如何与治理体系集成吗？”你知道，我们该如何看待代码生成和氛围编程，以及其中的挑战，同时又要实现构建稳健的 IT 系统这一目标？Speaker: Uh I'm curious as to what mental model uh what or what theory of mind do you have for the IT user um given, you know, they're not software engineers, but they understand their business, they understand what they're trying to go automate. Is it, you know, when you talk about vibe coding, I'm like, "Okay, but do you understand like security architecture? Like, do you understand how this is going to integrate with governance?" Like, how do you square, you know, code generation and how we think about vibe coding and what the challenges are with that with, you know, we want to build robust IT systems?

说话人：是的，当然。我觉得 IT 非常有意思，因为他们其实比很多人认为的更接近软件工程师。呃，尤其是在大型企业里，很多情况下，IT 部门就是工程团队。他们没有软件工程团队，所以 IT 部门负责运行所有这些系统，而且 IT 人员经常会编写代码、管理系统。因此，我认为我们应该把他们当作成年人来对待，给他们提供我们会给软件工程师的工具。当然，我们会抽象掉其中一些复杂性，在某些方面让工具更容易使用；我们不会只是把云代码扔给他们，然后祝他们好运。实际上，我们会搭建一个专门针对他们使用场景的平台。我们不一定指望他们能写代码，或者理解所编写的内容，但我们仍然会让他们访问底层的代码。Speaker: Yeah, absolutely. I think IT is really interesting because they're they're closer to a software engineer that I think a lot of people give them credit for. Uh especially in large enterprises, the IT department is the engineering team in a lot of cases. They don't have the software engineering team, so IT runs all these systems and IT often does write code and manage the systems. And so, I think we treat them as adults. We give them the tools that we would give software engineers. Now, we abstract away some of that complexity. Uh we make it easier to use in some regards and we don't just kind of hand them cloud code and tell them good luck. We actually we build a platform that's dedicated to their use case. And we don't expect them to be able to necessarily write code or understand what's being written, um but we still give them access to it under hood.

所以，你始终可以看到代码，也可以始终按照完整的软件开发生命周期来处理，但也不一定非得这样做。因此，很多产品原则都在于设想几种不同的用户角色：比如一位确实能够并且会从头到尾编写代码的 IT 工程师；再比如市场部或人力资源团队的人，他们完全不想看到代码，但仍希望底层能灵活地生成代码，因为他们要构建复杂的工作流，不想靠拖放操作来实现。我认为，这在很大程度上就是要在脑海中考虑多种用户角色，同时也要把 IT 当成成熟的专业人士来对待。我觉得，市面上很多产品对 IT 的态度其实有点说教，仿佛在说：“哦，你其实不懂这些，所以你需要一个功能精简得多、预设更多、也更简单的版本。”So, you can always see the code, and you can always treat this through a full software development life cycle, but you also don't have to. And so, a lot of the product principles is thinking with a few different personas in mind, you know, an IT engineer who actually can and does write code all the way through someone maybe in the marketing department and the people team that doesn't want to see code ever, but still wants to have that flexibility of code gen under the hood because they've got a complex workflow that they want to build that they don't want to drag and drop their way to. So, I think a lot of it just comes to having multiple personas in your head, and also treating IT like an adult. I think a lot of the products that have been out there have actually kind of been pedantic to IT of like, "Oh, you don't actually understand this stuff, so you need this very stripped-down, more opinionated, simpler version."

实际上，IT 部门了解这些平台的复杂性，也认可它们的强大功能。我们希望将这些优势带给他们。Actually, IT appreciates the complexity and appreciates the power of these platforms. We want to deliver that to them.

使用 Catalyst 构建自动化并提升技术能力Building Automations with Catalyst and Raising Technical Competence

发言者：你们构建了一个帮助你们构建自动化流程的智能体。能解释一下它是如何工作的吗？Speaker: You guys built an agent that helps you build automations. Can you explain how that works?

说话人：是的，我觉得各家公司在打造第一代这类 AI 工具时，都发现了一个问题：你可以构建非常出色、非常复杂的系统，但随后还得培训大家，让他们理解产品的各种基本构件，以及这些系统如何协同运作。因此，第一代产品的做法是，我们派出所有这些全职员工向客户解释：“好，这就是如何在这个平台上构建东西。其实，还是让我直接替你搭建吧。”后来我们意识到，如果客户只需和一个了解他们需求的智能体对话，再由它把需求转化为产品的基本构件，那就方便多了。于是，我们打造了一个名为 Catalyst 的智能体，专门完成这件事。它是一个用于管理平台的智能体，管理员可以用它搭建所有底层自动化流程，还可以配置审批规则、权限检查，制定各种策略，更新这些不同的系统，并了解整个部署情况。Speaker: Yeah, so one of the things I think every company discovered this as they were building kind of the first generation of these these AI tools is that you could build such amazing complicated systems, but then you had to train people to understand all of your product primitives and how these systems fit together. And so, the first generation of this is we deployed all these FTEs to explain to customers, "Okay, here's here's how to build on the platform. Actually, let me just build it for you." And then we realized it would be really nice if customers could just talk to an agent that understood their requirements and then translated that into the product primitives. And so, we built this agent called Catalyst that does exactly that. It's an agent for managing the platform. So, it's an agent for admins to build out all those underlying automations, but also configure the rules around approvals, um permission checks, um build out different policies, update all these different systems, understand the entire deployment.

所以，由于 Servaless 在底层完成了所有代码生成，在它之上配备一个代理来帮你管理整个系统，就显得非常合理，而且功能强大。这样一来，你就不必专门学习如何使用 Servaless 了。你只需与一个真正了解如何使用 Servo、如何基于它进行构建的代理对话，而它就是你与产品交互的主要入口。And so, because Servaless all code gen under the hood, having the agent on top of that to help you manage the system just made a ton of sense and is so powerful. Because now I don't need you to train yourself on how to use Servaless. You can just talk to an agent that actually understands how to use Servo and how to build on it and that is your primary interface into the product.

发言者：我觉得有一点常常被低估，而且我觉得挺酷的，那就是不同产品中的智能体体验，实际上还有代码生成智能体，能够在用户打造产品、实现方案或其他东西的过程中一路陪伴他们，这确实是在提升大量用户的技术素养和能力，实际上也让更多人变成了工程师。Speaker: I think one thing that's under appreciated and I think is cool is that uh the experiences for agents in different products and actually in you know code generation agents as well being able to bring a user along as they are building a product or an implementation or something is actually like raising the technical competence and ability of a huge number of users and turning people into more you know engineers actually.

发言人：当然。老一代自动化工具面临一个从零开始的问题：我到底该从哪里着手？我知道自己想把工作中的这些环节都自动化，但该从哪里开始？像我们这样的产品会问你：“你想从哪里开始？”然后就可以开始提出建议，你可以和它们反复迭代，也可以说：“其实我不太明白。你想表达什么？能给我解释一下吗？”“好，我想做这件事。那我该怎么做呢？”它们可以为你提供信息、查找信息，也可以向你解释各种概念。这样一来，它就成了你的构建伙伴；你能做到的远不止是提示一个智能体去构建某样东西——它还能带你一步步走过整个过程，帮助你探索那些你原本根本不会想到的新机会。Speaker: Absolutely. You have this blank slate problem in the old generation of automations of where where do I even begin? I know I want to automate all these parts of my job but where do I begin? Products like ours say, where do you want to begin? And just can start making suggestions and you can iterate with them and you can say I actually don't understand that. What are you trying to say? Can you explain this to me? Okay, I'm trying to do this. How would I even go about doing this? And they can give you that information, they can fetch the information, they can explain concepts to you. And so it does become a build partner and you can achieve so much more than just prompting an agent to go and build something and it can actually walk you through the process and help you explore new opportunities that you wouldn't even have thought of.

新浪潮：企业中的后台智能体与自主性The Next Wave: Background Agents and Autonomy in Enterprise

不过，目前似乎有一件事讨论得不够多，那就是后台智能体。呃，你能多谈谈你对此的看法，以及你觉得接下来这一波会带来什么吗？But so one thing that seems a little bit under discussed right now is background agents. Uh could you tell us more how you think about that and what you think is coming in terms of this next wave?

发言者：是的，我总是这样向公司描述后台智能体：这是企业软件领域最具雄心的终极目标。让这些智能体自行开展工作，神奇地发现并解决你所有的问题。如果我们能部署它们，让它们真正发挥作用，而且遵循我们的权限设置，那就太棒了。我觉得还没有人真正摸索出如何把这件事做好，因为一方面，你希望它们足够自主，能够自行摸索并解决问题，而不需要有人时刻盯着它们；另一方面，在企业环境中，自主性又很让人担忧。所以，你确实会想知道它们究竟能读取哪些内容。这有点像……Speaker: Yeah, I always describe background agents to the companies like this is the ultimate moonshot in enterprise software. Just these agents that go off and do work for you and magically discover all your problems and solve all your problems. And it would be amazing if we could get that deployed and it could work and it could follow our permissions. And I think no one's really figured out how to do this well because on the one hand you want these to be very autonomous to go off and figure stuff out and then solve problems without somebody babysitting them. On the other hand, autonomy is very scary in the enterprise. And so you do want to see what exactly can they read. This is kind of

发言人：OpenAI、Hugging Face 的事件，或者其他类似情况：智能体被分配了一项任务后，为了完成任务却做出了意料之外的行为。那么，你可以设置哪些防护措施？Speaker: OpenAI hugging face incidents or other things where agents were given a task and then they do something that's unexpected in order to accomplish that task and so what are the guardrails you can put in place?

发言者：没错。对于我最优秀的员工，你会怎么做？你会告诉他们：“这是总体上的高层次使命，放手去做吧，别来找我，直接去完成它；等你回来时，你已经做出了了不起的成果。”我希望也能信任智能体为我做同样的事：我给它们一个高层次的任务，它们就能着手解决问题，然后回来向我汇报。我觉得我们还没找到一种让人觉得安全的方式来做到这一点。Speaker: Exactly. Because my best employees, what do you do with them? You say, here's the general high-level mission, go off, don't talk to me and go do it and you'll come back and you'll have done amazing things. I want to be able to trust agents to do the same thing for me where I can give them this high-level task and they can come back and solve this problem and come back to me. I don't think we've figured out how to do that in a way that is feels safe

嗯。Speaker: Mhm.

说话人：在企业中。Speaker: in the enterprise.

发言者：你觉得有什么办法能让它变得安全？我是说，人们一直以来尝试过各种不同的方法，从宪法式 AI 到某些形式的强化学习。我只是有点好奇，你心里有没有什么解决方案，还是说……Speaker: What do you think is a way to make it safe? Is that I mean people have experimented with different things over time, everything from constitutional AI to certain forms of RL. I'm just sort of curious if you have a solution in mind or is it just

发言者：在大型企业中，我们对这件事的看法是，它并不完美，但能力会逐步提升。你让它去做这些事，然后它回来告诉你：“嘿，我希望能做这些事，这样会有助于我完成工作。”然后你批准它们。而这些都是确定性的工作流。比如：“我想调用这个工具。我想运行这个能完成 X、Y 和 Z 的脚本。我可以这么做吗？”然后你只需给它们设置好特定权限和防护措施，再逐一批准，说：“好，这个可以。这个也可以。这个也行。”随着时间推移，智能体会变得相当胜任，因为它拥有足够丰富的工具集，可以解决大多数问题。嗯，这并不完美，因为你得一直盯着这个过程，挺烦人的。但我认为这是不得不做的，否则它理论上可能会开始编写代码，在你的系统上执行操作，而这会带来无法设限的安全风险。我认为目前没人敢贸然承担这种风险。Speaker: We think of it in the large enterprise, it's not perfect, but it's a it's kind of an incremental escalation of capabilities. So you go off and you do these things and it comes back and says, "Hey, I would like to be able to do all this stuff. This would help me do my job." And you approve them. And all this stuff are deterministic workflows. I want to call this tool. I want to run this script that does X, Y, and Z. Can I do that? And you just kind of approve these with certain permissions and guardrails around them and you say, "Okay, yeah, that's okay. That's okay. That's okay." And over time the agent becomes pretty competent because it has a big enough toolkit that it can solve most problems. Um and it's not perfect because it's annoying to have to babysit that process, but I think it's what you have to do because otherwise it could theoretically just start writing code that could take action on your systems and that is an unbounded security risk that I don't think anyone's going to be able to take anytime soon.

发言者：你觉得，关于你刚才提到的兴奋之处，或者你和 Alex 对未来能力感到兴奋这件事，我们现在是不是还缺少某些模型能力？我这么问是因为，你知道，要主动采取行动，并预测某个人——比如作为 CEO 的 Jake、作为投资人的我，或者作为一个普通人的我——会怎么想，而且还要预测准确，这仍然非常难，对吧？你需要大量偏好数据。想想为你工作的员工会怎么想：“好吧，Jake 真正优先考虑的是什么？他给我这个高层次的使命时，到底是什么意思？”你觉得这是模型的问题，还是说如今完全是护栏和支撑框架的问题？Speaker: Do Do you think to your point of being excited, or you and Alex being excited about future capability, um like we're we're still missing some model capability here? The reason I ask is uh you know, the ability to be proactive and then predict what an individual, Jake as CEO, me as an investor, um or me as a human being, you know, and get it right is still very hard, right? You need a lot of preference data. Think about employee working for you like, "Okay, what are Jake's actual priorities? When he's gives me this high-level mission, what does he mean?" Do you think that's a model problem or is it entirely like a guardrail and harness problem today?

说话人：我觉得说实话，两方面都有。我觉得记忆显然需要越来越好，因为你得了解我的偏好。你需要拥有大得惊人的上下文，因为我不想和你开一堆不同的聊天。我想要一个贯穿始终的聊天，从我们第一次对话开始，你还能记住其中相关的要点。嗯，然后我觉得权限问题始终会是最大的难题，因为即使我觉得你是一个非常非常有价值、很聪明的智能体，而且你能为我做很多事情，但我到底能有多信任你，让你放手去做，而不必时刻盯着你的行动呢？Speaker: I think it's um it's both, honestly. I think memory obviously has to be better and better because you want to understand the preferences. You want the context to be insanely large because I don't want to have a bunch of different chats with you. I want to have kind of one single chat that goes back all the way to our very first conversation and you remember the key points of that are relevant. Um, and then I think the permissions problem will always remain the biggest thing because even if I feel like you are a very, very valuable, smart agent and I you can do all these things for me, how much do I trust you to just run wild and not have to babysit your actions?

对人也要这么做，对吧？我的意思是，任何为你工作的人都得回来跟你确认一下，看看是不是你想要的，然后给你三个选项。所以我觉得这就是个很正常的流程，对吧？是啊。Speaker: to do that with people, too, right? I mean, anybody who works for you has to come back and check in and is what you wanted and here's three options. And so, I think it's a very normal just process, right? Yeah.

说话人：是的。Speaker: Yeah.

Serval 的招聘速度与无限雄心Hiring Velocity and Unlimited Ambition at Serval

发言者：这家公司成立大约两年半了。呃，你们很快就打造出了至少达到成熟企业级水平的产品。现在团队有多大？Speaker: The company is about two and a half years old. Uh, you have gone very quickly to at least an enterprise mature product. How big is the team today?

发言者：今天我们有200人。Speaker: We are 200 people today.

发言者：200 人。Speaker: 200 people.

发言人：从一月开始，所以这一年开局非常出色。Speaker: in January, so it's been an incredible ramp year.

发言人：这一年可真是不得了。首先，我想问，你们预计还会继续这么快地招聘吗？你显然是个坚定的 AI 信仰者，为什么呢？其次，你和你的团队之前都参与过初创公司。过去两年，你们的运营方式与之前十年相比，有哪些很不一样的地方？Speaker: That's quite a year. One, I guess, do you expect to continue hiring so fast and as somebody who clearly believes in AI, like why? And then two, just, you know, you've been part uh, you and your team have been part of startups before, like what are you operating, how are you operating very differently, you know, the last two years than the previous 10?

发言者：是的，我认为招聘速度会继续加快，甚至超过我们目前的水平。嗯，我们相信工作需求是无限的，竞争是无限的，雄心也是无限的。因此，尽管每位员工现在完成的工作都比一年前多得多，但我们对他们能够做到的事情也抱有更大的期待。所以我认为，正因为每位员工的效率都提高了很多，我们实际上想要更多员工，而不是更少。Speaker: Yeah, the hiring velocity I think will will increase even from where we're at today. Um, we believe that there is unlimited demand for work and there's unlimited competition and there's unlimited ambition. And so, even though every single employee does so much more than what they could do a year ago, we have even bigger ambitions for what they could do. And so, I think because every employee is so much more productive, we actually want more of them, not less of them.

发言人：考虑到你之前在 Verkada 工作过，你觉得过去两年里的工作方式与此前十年相比，有哪些不同？Speaker: Given your, you know, time at Verkada before, uh, how are you operating differently over the last two years than the previous 10?

发言人：我认为 Verkada、我们所在的品类以及我们所处的时机之所以如此独特，是因为我们的总潜在市场（TAM）没有边界。所以，真正可触达的市场规模，更多取决于我们的雄心有多大，而非这项业务在规模上存在什么根本性限制。因为我们实际上是在为全球每一位员工自动化各种工作，所以 TAM 有多大，完全取决于我们的目标有多大。嗯，关键在于我们能以多快的速度增长、我们的雄心是什么，以及如何据此做决策，而不是说，好吧，这是市场的现状，这是我们认为自己实际能做到的事。这带来了一系列不同的挑战。这并不一定更好，因为现在还有那么多未开发的空间，我们也需要做出更多决策，决定自己究竟要专注于什么。Speaker: I think what's so unique about Verkada and the category we're in and the moment we're in is the TAM is unbounded. So, it feels like the dressable market is really more about the size of our ambition than it is about fundamental limitations on how big this business can get. Because we are automating essentially all kinds of work for every single employee in the world, the TAM is as big as we want it to be. Uh, and it's really how fast can we grow and what is our ambition and making decisions based on that versus, okay, here's here's what the market looks like. Here's what we think we can actually do. And that's a different set of challenges. It's not it's not strictly better because now there's so much open space and there's so many more decisions we have to make about what we actually want to focus on.

嗯，不过不受市场所允许的范围限制，真的很有意思。Um but it is really fun to not be constrained and hemmed in by what the market allows for.

紧跟客户步伐，适应产品功能的根本性转变Keeping Pace with Customers and Fundamental Shifts in Product Function

发言人：鉴于工作范围很广，你们是如何组织团队的工作节奏，或者说 EPD 团队的运作方式的？Speaker: How given that scope is very broad, how do you organize like the cadence or the you know, um the EPD team?

发言人：我们与客户密切合作。因此，即使是没有直接派驻客户现场的工程师，也都在客户的 Slack 频道里。我们不停地讨论客户，也每天都能听到客户的反馈。大多数工程师每周至少会参加一次客户电话会议。我觉得他们中大多数人其实每天至少都会参加一次。这个过程就像沉浸在一个国家里学习外语。你会深入融入买家和客户的思维方式，了解他们想要什么、如何看待问题，并实时适应他们偏好的变化。随着他们顺应市场变化，开始谈论正在尝试的不同产品以及令他们兴奋的事情，我们的工程师始终密切关注这一切，并能迅速做出调整。Speaker: We are embedded with customers. So even the engineers that are not necessarily deployed, they are in the customer Slack channels. We are talking about customers non-stop. They're hearing from customers every single day. Most engineers are on at at least one customer call a week. I think most of them are actually on at least a customer call a day. And so what this is, it's it's like immersion in a country to learn a foreign language. You become so immersed in your buyer and your customers' mindset that you understand what they want, you understand how they're thinking about things, and you are adapting to their preference changes in real time. So as they're moving with the market and they're starting to talk about different products that they're trying out and things that they're excited about, our engineers are constantly aware of all of this and able to adapt very quickly.

所以，我们实际上把产品开发权下放给了工程团队。我们没有专门的产品职能，因为工程师每天都在与客户交流，能够迅速根据客户今天和本周的反馈做出调整，而不是还照着一个月前的反馈行事。So we've decentralized product development really to the engineering team. We don't have a product function because they're the ones talking to customers every day and they're able to rapidly adapt to whatever customers are saying today and this week versus what they're saying a month ago.

发言人：听起来，这确实是个很自然的方式，能跟上快速变化的市场，以及客户不断变化的优先事项。那你、Alex 和管理层又是怎么理清这些事情的呢？比如说，在传统企业软件公司里，通常会有架构评审……Speaker: That sounds like a really like natural way to keep pace with um a like a ripping market and changing priorities for your customers. How do you and Alex and leadership then make sense of it? Like you know, in a traditional enterprise software company, you'd have like architectural review

发言人：是的，你们有季度路线图，会确定路线图的优先级，而且你知道，还会培训所有客户了解新推出的产品。Speaker: Yeah, you have a quarterly road map and you prioritize the road map and you know, train all your customers on the new launches.

演讲者：你也会告诉客户，变化会来得太快，因为他们吸收信息的速度也有限。Speaker: And you'd communicate with your customers that like things are going to change too fast because they can only absorb it so fast, too.

发言者：是的，这是个很大的挑战。我们的产品发布和迭代往往快得多，很多时候谁都跟不上，包括我自己。嗯，我们只是尽量确保，第一，我们招聘的工程师都真正以产品为导向。我们做出的一个改变是，他们必须真正了解我们的客户，而且我们希望让他们直接面对客户，因为他们必须在一线做出很多决策，不可能每次都把每一个产品决策层层上报给领导层。这是一项根本性的改变：你必须愿意把很多产品决策权下放，也必须愿意快速行动；如果方向错了，就撤销、回退，并放弃自己钟爱的想法。你还必须愿意改变那些你原以为对产品至关重要的事情；当工程师告诉你：“嘿，客户现在是这么看待问题的，我们应该换种方式做。”你就得愿意转换方向。Speaker: Yeah, it's a big challenge. Our product fat ships and changes faster a lot of times than anyone can keep up, including myself. Um we just try to make sure that one, the engineers that we hire are really product oriented. That's one change we made is they have to really understand our customers and we want to put them in front of our customers because they're going to be have to make so many decisions at the edge and not every single product decision can be bubbled up to leadership every single time. That is a fundamental change is you have to be willing to push a lot of the product decision-making down below and you have to be willing to move fast and also undo and revert if you go in the wrong direction and kill your darlings. You have to be willing to get, you know, change course on things that you thought were fundamental to the product and switch gears when your engineers bring you something that, "Hey, this is how the customer sees things now and this is what we should do differently."

在 Serval，我最引以为豪的事情之一，就是我们曾多次决定，放下过去那些我们曾全力投入的事情，并直截了当地说：“你知道吗？市场变了，客户也变了。我们要彻底换一种做法。”我认为，正是这种能力和意愿，让我们能够跟上变化，一次又一次地重塑自己。And one of the things I'm proudest of at Serval is how many times we've decided to erase things we've done in the past that were very committed to and just say, "You know what? The market's changed, the customer's changed. We're going to do things entirely different." And I think that is what's enabled us to keep up is that ability and willingness to reinvent ourselves over and over again.

发言人：这个时代最经久不衰的一些事物。谢谢你，杰克。Speaker: Some of the most durable things in this era. Thanks, Jake.

发言人：感谢邀请我们。Speaker: Thanks for having us.

结论Conclusion

主持人：欢迎在 Twitter 上关注我们，账号是 No Priors Pods。如果想看看我们的样子，可以订阅我们的 YouTube 频道。在 Apple Podcasts、Spotify 或你收听节目的平台关注本节目。这样你每周都能收到新一期节目。还可以订阅邮件，或在 no-priors.com 查阅每期节目的文字稿。Speaker: Find us on Twitter at No Priors Pods. Subscribe to our YouTube channel if you want to see our faces. Follow the show on Apple Podcasts, Spotify, or wherever you listen. That way you get a new episode every week. And sign up for emails or find transcripts for every episode at no-priors.com.