人工智能盈利难题、硅谷长寿热潮、MeritFirst招聘策略 | 2025年10月8日

欢迎大家收看Informations TI TV。我是Akash Pesritcha。今天是10月8日星期三。我们为各位准备了精彩的节目。我们将与Coinbase的前首席产品官讨论他的新创公司。

Welcome everyone to the Informations TI TV. My name is Akash Pesritcha. It is Wednesday, October 8. We have got a great show planned for you today. We are talking with Coinbase's former chief product officer about his new startup.

我们还会带来下周在纳帕举行的聚焦长寿主题会议的最新消息。我们还将对硅谷创始人们当前在泡沫论持续讨论中的焦虑程度进行脉搏检测。最后但同样重要的是，有一家旨在让科技公司招聘更注重绩效的公司完成了新一轮融资。本期节目令人兴奋，但我想先谈谈AI盈利能力的问题。许多AI公司收入增长迅速，上周节目中我们讨论了这可能带来的一些负面影响。

We've also got the latest on a new longevity focused conference that is taking over Napa next week. We're also going to do a pulse check on how anxious founders across Silicon Valley right now are feeling right now as talks of a bubble persist. And last but not least, we've got a new funding round about a company that aims to make hiring at tech companies a much more merit focused process. It's an exciting episode, but I want to start with a discussion about AI profitability. For a lot of AI companies, revenue has grown quickly, and we talked last week on the show about some of the downsides that can come with that.

但当前许多初创公司必须考虑的另一个重要因素是盈利能力，这对其中许多公司来说更难实现。为此，我想请出我们的微软记者Aaron Holmes和风投基金SignalFire的合伙人兼首席技术官Ilya Kurnos。欢迎二位。很高兴你们能来。

But the other big factor that many startups have to think about right now is profitability, and that is harder to come by for many of these startups. And so to talk about this, I want to bring on Aaron Holmes, our Microsoft reporter, and Ilya Kurnos, partner and CTO at Venture Fund SignalFire. Welcome to you both. It's great to have you.

很荣幸来到这里。

Great to be here.

那么，Aaron，从你开始吧。我想谈谈AI领域的盈利能力问题，或者说在很多情况下是缺乏盈利能力的问题。我们看到这个挑战在技术栈的各个层面持续存在，云公司、基础设施公司，甚至是应用层公司。就你关注的初创公司以及你报道的微软等大公司而言，你是如何看待这一情况的？

So, Aaron, let's start with you. I want to talk about profitability, or in many cases, lack thereof in the AI sector. I mean, we are seeing this challenge persist at all layers of the stack, cloud companies, infrastructure companies, even the application layer companies. How are you seeing this play out in terms of the startups in your orbit and also the larger companies that you cover, the Microsofts and companies like that?

是的，我认为我们看到市场对各类AI应用确实有需求。但许多应用销售商面临的挑战是如何定价才能保证健康的利润率。比如，我们看到AI编程软件领域的挣扎，像Cursor和Replit这样的公司不得不彻底调整他们的...我的天啊。

Yeah, I mean, I think we've seen that there's definitely an appetite for, you know, AI applications across the board. But the challenge that a lot of these application sellers are running into is how to price them in a way that, know, have healthy margins. And so I think like, you know, we've seen struggles among the AI coding software where companies like Cursor and Replit have had to, you know, completely overhaul their their oh my god.

继续说吧。没关系的。没问题。

Keep it going. We're we're good. We're good.

这正是现场节目的魅力所在

That's completely the beauty of

做直播节目就是这样，各位，我们都在慢慢适应。但请继续。你刚才谈到那些编码公司、复制品、光标。我是说，没错，它们的成本确实很高。

doing a live show, folks, is that we're all getting used to it. But keep going. So you were talking about the coding companies, replicates, the cursors. Mean, yeah, their their costs are high.

确实如此。即使是微软的GitHub Copilot——它算是第一个广泛流行的AI编码工具或者说AI产品——大约一年前，它在每次查询上都是亏损运营的。之后我们听说他们改善了利润率。但我觉得问题在于，token的成本一直相对较高，这也与在GPU上运行这些应用的成本高昂有关。

They are. And even like Microsoft GitHub Copilot, which was kind of the first, you know, AI coding tool or AI product in general to take off broadly, you know, it was operating at a loss as of, you know, on each query as of roughly a year ago. And since then, you know, we've heard that they've improved their margins. But I think the issue here is just that, you know, the cost of tokens have been relatively high. And that also relates to that the cost of running these applications on GPUs being high.

不过，我们反复听到的说法是成本最终会下降，这将给利润率一些喘息空间。所以我认为很多公司仍在等待这一情况发生。

But, you know, the refrain that we're hearing is that costs will come down eventually, and that'll give margins some breathing room. So I think a lot of, you know, companies are still just waiting to see that happen.

对，没错。

Right. Right.

那么，Ilya，我想问问你。我们一直在听说成本会下降，但根据我们《The Information》的报道，成本下降的速度并没有一些人希望的那么快。在某些情况下，模型成本甚至已经趋于平稳。

Well, Ilya, I want to come to you. I mean, we've heard this talk about costs coming down. I mean, from what we've reported here at the information, they kind of are not coming down as quick as some people hope. And in some cases, I mean, model costs have kind of plateaued.

是的。我认为实际情况是能力在提升。如果你看老一代的模型，现在生成那些token确实便宜了不少。但问题是，对于很多应用来说，你需要使用前沿的尖端模型才能保持竞争力，因为你的竞争对手也在用这些模型。所以这有点像一场军备竞赛。

Yeah. Well, I think what's happening is the capabilities are increasing. So if you look at kind of an older generation model, it is true that generating those tokens is quite a bit cheaper now. But what's happening is, you know, for a lot of these applications, you want to be on the cutting edge on the frontier models to have competitive performance because your competition is on those models. So it's a bit of an arms race.

而且使用这些推理模型会消耗更多token，产生更多输出。所以现在有点像一场军备竞赛。在某些方面，是的，旧模型的token成本正在下降，但你用得越来越多，而且必须处于技术最前沿，这很昂贵。我认为许多公司的赌注是最终情况会放缓，他们能够利用硬件改进，真正具有竞争力的模型成本将会下降。这就是我们目前看到的情况。

And also you're using a lot more tokens with these reasoning models that produce a lot more tokens. And so it's a bit of an arms race right now. So, you know, in some ways, yes, older models, token costs are coming down, but you're using more and you're having to be on the bleeding edge, which is expensive. I think the bet for a lot of these companies is eventually kind of things slow down and they're able to sort of take advantage of the hardware improvements and sort of costs will come down for the models that are actually competitive. So that's what we're seeing right now.

Ilya，我昨天和另一位风险投资人聊天时，他们提到的一件事我想问你：他们说公司现在如此专注于推出产品、交付产品以保持竞争力，比如你有固定数量的工程师在负责这些工作。如果在交付产品和尝试让产品盈利、提高效率、优化后端之间做选择，现在的优先事项是交付。你投资组合中和接触的初创公司是这样吗？我是说，你是否看到初创公司说'我们现在甚至不关注盈利，只想先把东西做出来'？

Ilya, one of the things that I was talking to another venture capitalist yesterday, and one of the things they mentioned I wanted to ask you about is they said, you know, companies are so focused on getting products out the door right now and shipping products to stay competitive that you have a fixed number of engineers, for example, that are working on these. And if you have a choice between shipping product and then trying to make product profitable and more efficient and optimizing maybe some of the backend, the priority right now is on shipping. Is that the case for startups in your portfolio, in your orbit? I mean, you seeing startups say, Hey, we're not even focused on profitability right now. We just want to get stuff out the door.

我认为，单位经济效益和毛利率是有区别的，对吧？确实大多数初创公司都不盈利，你在积极投资于增长。但问题是，你是在用80美分还是14美分卖一美元？我觉得当前这个时间点，很多创始人都认为需要先抢占市场份额，之后再优化。

So I would say, you know, there's a difference between and unit economics gross margins, right? If, know, it's certainly true that most startups are not profitable, right? You're actively aggressively investing in growth. But the question is, you know, are you selling dollars for 80¢ or maybe 14¢ or whatever? And I do think right now kind of the moment in time is such that a lot of founders believe that they need to get out there, grab market share, and then optimize later.

对很多公司来说这很有道理。如果你是家企业公司，销售10万美元以上的交易，我认为token成本不会影响未来能否建立一家优秀盈利的企业，因为模型成本可能只占总成本的一小部分。但如果你更像是消费者公司或专业消费者公司，比如Cursor向很多人每月收费20美元。有趣的是，我可能每月付20美元却大量使用Cursor。

And I would say for a lot of companies that makes a lot of sense. You know, if you're an enterprise company selling, you know, a 100 K plus deals, I don't think the token costs are going to be the thing that makes the difference between having a, you know, a great profitable business in the future, because the model costs are actually probably a small component of the overall cost. Right. But you know, if you're more of a consumer company or a prosumer company, like a cursor that's charging $20 a month to a lot of people. And what's funny there is, you know, I can be paying $20 a month and using a lot of cursor, right?

用得非常节省，但我们付的钱一样。我知道他们现在有分级套餐等。但我觉得很多也归结于定价策略，因为他们的底层成本是按token计算的，但向消费者收取的却是固定费用。

Using it very sparingly and yet we both pay the same amount. I know they have tiers now, etcetera. But I think a lot of it also comes down to pricing, you know, because their underlying costs are per token and yet they're kind of the price they're charging the consumer is a flat fee.

对，没错。

Right. Right.

我们看到的就是这种不匹配。我认为即使在更高套餐中，由于这种性质，可能也有使用速率限制和上限。我觉得他们最终可能会推出基于使用量的定价。

We're seeing is this mismatch. And I think they're also, even at the higher tiers, you probably have rate limits and caps to what you can use because of this nature. I think at some point, they probably introduced usage based pricing.

嗯。嗯。

Mhmm. Mhmm.

目前，他们追求定价的简洁性，因为这能赢得市场份额，而且坦白说，这也是人们已经习惯的方式。

Right now, they're going for simplicity in pricing because that's what gets market share, and that's what kind of people have been have become used to, frankly.

所以，我听到你的意思是，你更像是站在Greplit CEO的阵营里——他上过节目，谈了很多关于定价的问题。他说，成本可能不会像人们预期的那样下降。我们必须调整定价，以反映我们认为用户从服务中获取的价值，这也是长期实现盈利的一种方式。看来你属于那个阵营。

So what I hear you saying is you're kind of more in the camp of actually the CEO of Greplit who came on the show, he was talking about pricing a lot. He was saying, look, costs, I mean, they might not come down the way people expect. We have to adjust our pricing to reflect the value that we think people are getting out of our services. Then also a way to actually become profitable in the long run. It seems like that's sort of the camp that you're in.

是的，我认为这真的取决于具体应用。编程就是一个很好的例子，前沿模型的每一次改进都是开发者想要使用的，对吧？所以如果你是Replit，你必须使用最好、最智能的模型，否则就会失去开发者。而在其他应用中，比如为网站创建营销文案之类的，我认为你不需要追求最前沿的技术，可能更愿意在成本上进行优化。

Yeah, I would say it really depends on the application. I think coding is a good example of where every improvement to a frontier model is something developers want to use, right? So if you're a replet, you need to be on the best, smartest model. Otherwise you're going to lose developers. In another application, like let's say you're creating marketing copy for websites or something, I don't think that you need to be on the bleeding edge for those applications, and you're probably more willing to optimize for cost in that equation.

所以，我想说的是，这取决于领域。

So, it depends on the domain is what I would say.

没错。Aaron，我想再问你一下。关于收入质量的问题，上周我们在节目上讨论过，应用层公司与企业签订的很多交易，在某些情况下并不总是最稳定的收入。在你接触的公司中，这个问题有多受关注？

Right. Aaron, I want to come back to you. As it relates to quality of revenue, we had this discussion last week on the show about a lot of deals that application layer companies sign with enterprises. I mean, it's not always the stickiest revenue in some cases. How much of a concern is that among some of the companies that you're talking to?

是的。我认为，从这些公司听到的是，我们可以将部分成本转嫁给客户，因为他们通过使用我们的产品（比如自动化替代某些岗位）往往能节省更多开支。但同时，确实有很多AI初创公司报告的收入可能不如他们希望的那么具有复购性。所以问题在于这些应用的粘性如何？我认为这些公司面临的另一个大问题是，如果我的软件自动化替代了某些岗位，客户公司的员工数量会随时间减少，那么如何将这一点纳入定价模型？

Yeah. I mean, I think like the what we've heard from those companies is, you know, we we can pass on some of these costs to our customers, because they are getting even more savings from using our products often by like automating away roles. At the same time, yeah, there's a lot of AI startups that, know, have, you know, reported revenue that might not be as recurring as they would hope. And so I think like the question is how sticky these apps become? I think another big question that a lot of these companies are facing is, know, if my software automates away, certain roles and companies, the headcount of the customers goes down over time, you know, how do you price that into your model?

我认为这也是一个尚未经过验证的问题，目前许多初创公司都在努力探索这一点。

Which I think is also just kind of an untested question that a lot of a lot of these startups are trying to figure out right now.

没错。

Right.

太好了。感谢两位的到来。这个话题似乎在我们的节目中讨论得越来越多，我预计它会变得更加重要。Ilya和Aaron，感谢你们参加节目。这位是来自SignalFire的Ilya，以及我们的微软记者Aaron Holmes，他也是The Information报道企业软件相关新闻的记者。

Great. Well, I want to thank you both for coming on. It is a topic that we seem to talk about more and more on this show, and I anticipate it will get even more important. Ilya and Aaron, thank you for coming on the show. That is Ilya from SignalFire and Aaron Holmes, our Microsoft reporter, and also a reporter on all things enterprise software here at The Information.

谢谢。

Thank you.

担任像Coinbase这样大公司的首席产品官是硅谷许多人的梦想工作。但在2023年，我们的下一位嘉宾离开了那个职位，并迅速创办了一家专注于AI代理的公司。现在，我得说关于加密货币高管转向AI的笑话几乎不请自来，但我想请来AI代理公司Emma的创始人兼首席执行官Surajit Chatterjee。Emma，Emma，我们会向他确认一下这个名字的发音。这是他第一次参加我们的节目。

Being the Chief Product Officer for a company as big as Coinbase is the dream job for many people across the valley. But in 2023, our next guest left that role and quickly started a company focused on AI agents. Now, I will say the jokes about a crypto executive pivoting to AI basically write themselves, but I want to bring on Surajit Chatterjee, the founder and CEO of AI agents company, Emma. Emma, Emma, we're going to get clarification from him on how to pronounce that. He's coming on the show for his first time.

Suraj，欢迎来到节目。很高兴你能来。

Suraj, welcome to the show. It's great to have you.

谢谢。很兴奋能来到这里。

Thank you. Excited to be here.

是Emma吗？是Imaj吗？直接纠正它们吧。

Is it Emma? Is it Imaj? Just correct them.

它其实是一个缩写：Enterprise Machine Assistant，简称EMA。

It's actually an acronym. Enterprise Machine Assistant, EMA.

那它是什么呢？

And what was it?

企业机器助手，EMA。发音是Emma，不是Ima。

Enterprise machine assistant, EMA. It's pronounced as Emma, not Ima.

嗯，我，你知道，企业机器听起来对我来说像个智能体，对吧？我的意思是，在我看来这就是它的本质。简单快速地跟我讲讲EMA是做什么的，然后我们再更广泛地聊聊智能体。

Well, I, you know, enterprise machine sounds like an agent to me, right? I mean, that seems to me what it's all about. Very quickly, talk to me about what EMA does, and then we'll talk a little bit more about agents at large.

是的。所以我们叫它Emma，Emma。它是企业愿景助手，但发音是Emma。我们所做的，你知道，我们的目标是打造一个通用AI员工。我们认为我们已经构建了第一个通用AI员工。

Yeah. So we call Emma, Emma. So it's Enterprise Vision Assistant, but it's pronounced as Emma. What we do, you know, our goal was to build an universal AI employee. And we think we have built the first universal AI employee.

所以它不仅仅是在企业内回答问题，它实际上会动态规划并采取行动，理解企业上下文，对各种结构化和非结构化数据进行推理，连接你所有的遗留系统，实现端到端的完整工作流自动化。这就是Emma所做的。我们预构建了用于客户支持、人力资源、销售等职能的AI员工，客户也可以利用这个框架和平台，构建他们自己的AI员工，这些本质上是多智能体工作流。所有这些，同时保持企业合规性、安全性、高标准的部署灵活性等等。

So it just doesn't answer questions in the enterprise, it actually takes actions dynamically plans, understands enterprise context, reasons over all kinds of structured and unstructured data, connects to all your legacy systems, take end to end kind of entire workflow automation. That's what Emma does. We have pre built AI employees for functions like customer support, HR, sales, customers can also take the framework, take the platform and build their own AI employees, which are essentially multi agent workflows. All of this, while maintaining enterprise compliance, security, high standards of deployment flexibility, so forth.

Brian，我们这周一直在讨论智能体，当然是因为周一OpenAI举办了开发者日。真正的问题是，随着像OpenAI这样的大型AI公司推出让用户更容易创建自己智能体的工具，像你们这样的初创公司以及其他推销智能体以帮助企业简化运营的公司会面临什么情况？你们正在构建的产品与OpenAI向客户宣传的‘你可以自己构建’的方案有何不同？

Brian, so we've been talking about agents this week, of course, with OpenAI's Dev Day that happened earlier on Monday. And the question really becomes, as these larger AI companies like OpenAI unveil tools that make it easier for people to create their own agents, what happens to startups like yours and other companies that are sort of pitching these agents to help companies streamline their operations. How is what you're building different than what OpenAI is pitching their own customers saying, Hey, you can build it yourself?

绝对如此。你看，OpenAI持续拓展着技术可能性的边界。但从那里到真正部署可用的企业软件、企业自动化软件，还有很长的路要走。我们所实现的是让企业自动化对我们的企业用户和领域专家变得非常简单，他们不需要拥有机器学习或工程学位，只需通过对话就能构建全新的复杂工作流、智能体工作流，这些工作流可以连接到他们所有的记录系统、数据集和数据库，并动态规划与执行操作。

Absolutely. So look, OpenAI continues to increase the overall overturn window of what's the art of the possible. But from there to actually getting a deployable enterprise software, enterprise automation software that works is a long path. What we have been able to achieve is, you know, actually making enterprise automation really simple for our enterprise users, subject matter experts, they don't need to have a degree in machine learning, engineer, they can just come and conversationally build brand new complex workflows, agentic workflows that can connect to their entire set of systems of records, their data sets, their databases, and dynamically plan and take actions.

那就是

That's the

区别所在——将可能的事情真正落实到企业级规模并使其运作起来。

difference where taking something that's possible to actually making it work at enterprise scale.

你们如何考虑定价策略，以确保业务的单位经济在长期内能够盈利？

How do you think about pricing to ensure that the unit economics of your business is gonna be profitable in the long run?

绝对如此。你看，我们所有的定价都基于使用量或结果，而不是基于席位，后者是SaaS应用常见的定价模式。事实上，我认为如今大多数SaaS应用或记录系统正因为这一点面临颠覆，因为每个许可证下大部分席位并未被使用，对吧？一切都基于结果、使用量以及我们为客户创造的价值。我们所做的一切都旨在实际提升投资回报率（ROI）。

Absolutely. Look, we price everything based on usage or outcome, not based on seat, which is like popular pricing scheme for SaaS applications. In fact, I think most SaaS applications today or systems of records are facing a disruption because of that, because most of the seats are unused under each line, right? Everything is based on outcome, based on usage, and based on the value we are creating for the customer. Everything we do is based on kind of actual improving the ROI.

我们的客户是大型企业，比如日立、毕马威，美国的福利管理公司等等。

And our customers are largest of enterprises, customers like Hitachi, customers like KPMG, benefit management company in The US and so on.

那么，通过这些你正在销售给代理商的大型合同，你的毛利率表现如何呢？

And so how have your gross margins fared then with these large contracts for these agents that you're selling them?

非常好。听着，我们不是——

Very well. Look, we are not-

我们说的是传统毛利率吗，你知道，比如80%左右的水平？或者，给我们一个大致的范围。

Are we talking like traditional gross margins, you know, 80% type of neighborhood? Or, you know, give us a ballpark here.

是传统毛利率，我们能够实现这一点是因为，你知道，我们并不从事构建大型基础模型的业务。我们构建的是较小的模型，并且利用所有模型。事实上，我们自主研发了一项技术，称之为MFusion，它是一个模型中的模型。这是一个元模型，位于所有现有模型之上，100个LMS动态优化每个企业任务及其执行方式。

It's traditional gross margins, and we are able to achieve that because, you know, we are not in the business of building large foundational models. We are building smaller models. We are leveraging all models. In fact, we had developed homegrown a technology that we call MFusion, which is a model of models. It's a meta model that sits on top of every model out there, 100 piece LMS dynamically optimizes every enterprise task and how it executes this task.

我们已经证明，对于典型的企业基准测试，成本降低了约20%，并且准确性高于大多数现有模型。它基本上利用了所有可用资源。

And we have proven that it's like onetwenty the cost for typical enterprise benchmarks, and with a higher accuracy than most models out there. It basically leverages everything out there.

所以，通过使用你们构建的这种模型中的模型技术，你们成功降低了成本基础？明白了。Surajit，这真是一个迷人的领域。我的意思是，智能体确实成了大家都热衷谈论的话题，感谢你坦诚地谈论盈利能力，因为这是我们节目真正想深入理解的问题。谢谢你的到来。

So you've been able to reduce your cost base by using this model of models sort of technology that you've built? Got it. Surajit, it is a fascinating space. I mean, agents have certainly become the thing that everyone loves talking about, and I appreciate you talking candidly about profitability because it is something that we are really trying to wrap our hands around on this show. Thank you for coming on.

这位是Surajit Chatterjee。他是Emma公司的CEO兼创始人，一家专注于智能体的新兴人工智能公司。谢谢。好的，我们昨天谈到了长寿和消费者健康如何成为科技界的最新热潮，下周在纳帕将有一个关于这一主题的大型会议，我们的下一位嘉宾正是这场会议的发起人。医生。

That is Surajit Chatterjee. He is the CEO and founder of Emma, a new agents focused AI company. Thank you, Okay. Well, we spoke yesterday about how longevity and consumer health is the latest craze in tech, and next week there is a big conference in Napa on this exact topic that our next guests are starting. Doctor.

Jordan Schlain是一位资深私人医生，也是Private Medical的创始人，而John Battelle则是一位资深媒体企业家。他们两人共同创办了DOC，也就是这次活动的名称，我想请他们来谈谈他们对长寿运动发展方向的看法。Jon和Jordan，很高兴你们能来。

Jordan Schlain is a longtime concierge doctor and the founder of Private Medical, and John Battelle is a longtime media entrepreneur. The two of them founded DOC, the name of the event, and I want to bring them on to talk more about where they see this longevity movement going. Jon and Jordan, it's great to have you.

很高兴来到这里。谢谢邀请

Good to be here. Thanks for having

嘿，怎么样

Hey, how

还好吗？

are doing?

我很好。嗯，我很期待这次有趣的对话。我想从这个问题开始：John，你是一位媒体企业家；Jordan，你一直是医生。你们最初是怎么认识的，又是如何决定创办这个项目的？

I'm doing great. Well, I'm excited for this fun conversation. Look, the place I want to start is, I mean, John, you're a media entrepreneur. Jordan, you've been a doctor. I mean, how did you guys even meet in the first place and decide to start this thing?

John？

John?

嗯，Jordan和我认识已经快二十五年了。事实上，我和他姐姐曾一起合作过Webbies奖项，你可能还记得最早互联网时代的事情。

Well, Jordan and I have known each other for almost twenty five years. As a matter of fact, I worked with his sister on, of all things, the Webbies, which you might remember back in the first.com.

五个字的获奖感言，对吧？

Five word acceptance speeches, right?

是的。没错。

Yes. Right.

对。那是那是乔丹的妹妹蒂芙尼。但乔丹和我已经是多年的朋友了。在我搬到东海岸之前，他当了我十年或十五年的医生，后来我在纽约联系上了他的一位医生同事。但我们一直互相交流笔记，并就一些问题进行了多次白板会议讨论。

Right. That was that was Tiffany, Jordan's sister. But Jordan and I have been friends a long time. He was my doctor for ten or fifteen years till I moved to the East Coast, and I I hooked up with one of his doctors out in New York. But he and I have always traded notes and done a bunch of whiteboard sessions on problems.

我当时在创业，而他则在扩展他的私人医疗业务时遇到了一些问题。大约两年前，我们最终意识到我们想一起做点什么，那就是Dah。

I was at starting companies and problems he was having with his business scaling his private medical business. And that ended up about two years ago with us realizing we wanted to do something together, and that was Dah.

就是这样。

There you go.

这一切始于我在拉斯维加斯参加一个活动时，与一位资深企业家凯文·瑞安在一起。我们当时在感叹这些医疗保健会议是多么商业化，多么缺乏证据，以至于它们并不是真正的医疗保健活动。它们更像是，你知道的，那种表演性的商业活动。而现在如果你去参加学术活动，它们又那么晦涩难懂，所以人们不去参加那些。

And it started with me as I was at a event in Las Vegas with a longtime entrepreneur, Kevin Ryan. And we were lamenting how these healthcare conferences were just so commercial and so lacking in evidence that they weren't really healthcare events. They were more, you know, kind of performative commercial events. And now if you go to an academic event, you know, they're so inscrutable and hard to understand. So people don't go to those.

但当你去参加这些大型商业活动时，你并没有真正学到任何关于医疗保健的东西。就像是，你能做什么？所以凯文挑战我说，嘿，乔丹，如果你能凭空创造点什么，你会想去参加什么样的活动？我说，我不知道，让我想想。然后我就打电话给了约翰。

But when you go to these big commercial events, you're not really learning anything about healthcare. It's like, what can And you so Kevin challenged me and said, Hey, Jordan, if you could invent something out of whole cloth, like what event would you go to? And I said, I don't know. Let me think about that. And kind of then I called John.

我在想，我们能不能就这个想法稍微白板讨论一下：如何构建一个既具有学术性，又便于人们理解、专注于长寿领域，并且真正反映当前创新进展的内容。现在市场上噪音太多了。

I'm like, Can we whiteboard a little bit on this idea of how do we put something together that's both academic, but it's also ready made for people to understand, focuses on longevity, and really addresses the innovations that are happening right now. There's so much noise in the market.

我确实想谈谈这些噪音，并且希望重点听你的见解，因为你是我们三人中的医生，或许你能给出一些明示。过去两三年里，关于长寿的讨论特别多。现在有手环、戒指，还有纪录片不断推出。我的问题是：这是过去三年里某项特定科学或医学突破的结果，还是说它只是恰好抓住了当下的时代精神，让人们纷纷追随

And I do want to talk about that noise because, and I want to stick with you because you're the doctor out of the three of us, so maybe you can shed some light here. There's been so much conversation around longevity in the last two to three years specifically. And we've got the bands, we've got the rings, we've got the documentaries now that are coming out. And the question I have for you is, is this the result of any particular scientific or medical breakthroughs that we've had in the last three years, or is it really just the thing that has captured the zeitgeist right now that people are kind of rallying

很好的问题。我认为有很多因素共同作用。其一，我们以COVID为例简单说明。

Great question. I think there's a lot of factors that kind of all come into it. One is, let's take COVID just for a quick example.

没错。

Right.

在COVID的某个阶段，所有人——无论是否意识到——都曾想过我们或认识的人可能会死亡。我们一度直面死亡或死亡的阴影，时间或长或短。因此我们也意识到，那些在疫情期间保持健康的人才是最终存活下来且未受重创的群体。

At one point in COVID, all, I mean, whether we recognized or not thought maybe we were going to die or somebody we knew was going to die. So we all confronted mortality, or the specter of mortality for a minute or maybe longer. So we also appreciated that those who were healthy during that COVID episode were the ones who actually made it out alive and didn't get that sick.

所以说

So there

长寿运动中有这样一个层面：第一，我们开始思考如何更健康长寿；第二，经过长期投入的数十亿美元研究终于结出硕果，无论是CRISPR、蛋白质组学还是代谢组学等生物医学领域，我们对生物学的理解正在深化；第三是计算技术的崛起。但这也带来问题：大家都觉得这不像工程学那样直观。

is this piece of the longevity movement that like we are now thinking about living healthier and longer, number one. Number two is there's like billions of dollars of research over very long periods of time that are finally coming fruition in terms of the biomedical research on whether it's CRISPR or proteomics or metabolomics. We're starting to understand biology more. And that leads into the third thing with this technology, which is the ability for compute to come into the fore. And so, but that's part of the problem too, is like everybody thinks this isn't engineering.

长寿是一个工程问题。我认为现在技术已经超越了生物医学行业，成为最热门的话题，这理所应当。

Like longevity is an engineering problem. And I would say that the technology is like eclipsed the biomedical industry as the sexy hot thing right now, which is as it should be.

没错。因为生物技术的一切都需要很长时间，对吧？长寿问题，我现在就能在这里掌控。所以我完全理解为什么它会流行起来。你刚才想说什么来着。

Well, right. Because I mean, everything biotech takes so much time, right? I mean, longevity is, I can control this here and now. And so I certainly see why it's caught on. You were going to say something.

我正要问你呢，约翰，你刚才想说什么？是的，我正想说

I'm coming back to you, John, but what were you going to say? Yeah, I was just going say

长寿不是技术问题，而是人类问题。你需要的是技术、科学家和医生共同协作。这不像召集一群工程师就能解决长寿问题。对吧。

that longevity isn't a technology problem. It's a human problem. And what you need is you need technology and scientists and physicians to all come together. And this is not like bring a bunch of engineers and solve the longevity problem. Right.

我认为DOC正在努力做的就是汇聚技术、医学、科学、媒体等各界人士，真正尝试如何让科学重新获得我们所有人的尊重？因为如果有人反对科学或怀疑科学，我就会说，那你手上的手机呢？你喜欢手机吗？那就是科学。对吧？

And I think that what we're trying to do at DOC is to bring together a community of technology, medicine, science, media, and really try to like, how do we bring science back into something that we all respect? Because if people are anti science or science skeptics, I just say, How about that cell phone? You like that cell phone? That's science. Right?

我是说，你的汽车呢？那也是科学。

I mean, your car? That's science.

没错。

Right.

我们怎么可能反对科学呢？

How can we be anti science?

约翰，你们这次会议的主题确实围绕这个问题展开：人工智能何时（如果可能的话）会取代医生？这是网站上提出的问题。我们应该向医生们提出这些问题，但约翰，我想先听听你的看法。你认为人工智能何时会取代医生？

So John, the headline of the conference that you guys are putting on, it really surrounds this question, When, if ever, will AI replace doctors? And it's the question that's on the website. And so we should be asking the doctor these questions, but John, I'll come to you. What do you think? I mean, when, if ever, will AI replace doctors?

我们将在周日晚上以这个问题开启会议，届时将由医生们进行辩论，乔丹是辩论的主持人，技术专家们也会参与，包括里德·霍夫曼和迈克·克鲁格，Instagram的联合创始人兼Anthropic的产品官，可能全场观众都对这两个名字很熟悉。这是一种强制并构建关于技术在医学和医疗保健中作用的对话的方式。我不想在辩论开始前就下结论，但这将是一场非常有趣的讨论。它将为接下来几天的议题设定框架，我们会讨论技术如何影响医学的诸多问题。

We're opening the conference on Sunday night with that question that is going to be debated both by physicians, and Jordan is the moderator of that debate, and by technologists, including Reid Hoffman and Mike Krueger, who's the co founder of Instagram and the product officer at Anthropic is probably the whole audience knows both those names well. It is a way of forcing and framing a conversation about the role of technology in medicine and healthcare. Right. And I don't wanna, you know, call the debate before it had happens, but it's gonna be a really interesting conversation. It'll frame the next couple of days where we talk about a lot of the issues of how technology impacts medicine.

对。另外，回到乔丹的观点，我们如何能够支持一种以科学和证据为真正导向的叙事，而不是基于声称和营销，这正是我们在医学领域看到的一个炒作周期，感觉非常类似于我们在技术领域都熟悉的炒作周期。但这里我们谈论的是人们的生命，所以我认为我们需要更认真地对待它。

Right. And also, back to Jordan's point, how we can get a narrative supported that is about a true north of science and evidence as opposed to claims and marketing, is what, we're seeing a hype cycle in medicine that feels very similar to the hype cycles we're all familiar with in technology. But we're talking about people's lives here, so I think we need to take it more seriously.

没错。乔丹，DOC的目标是提供以长寿为重点的疗法吗？从长远来看，你如何看待这个业务的发展？

Right. Jordan, is the goal with DOC to offer longevity focused therapies? The long run, where do you see this business going?

长期目标是展示，就像我之前说的，约翰也提到，外面有太多噪音。一个播客主持人、一位名人健康播客主持人对人们健康的影响力，比开发和提供这些解决方案的科学家还要大。所以我们试图突出什么是真实的、什么是有效的、什么是现在可行的，并尝试创建一个理解并推广这些事物的社区。因为正如约翰提到的，这次活动的一个前提是，糟糕科学基础上的出色营销总是会击败优秀科学基础上的糟糕营销。所以在约翰的帮助和他对媒体的理解下，我们试图做的一部分是，如何以优秀科学的方式营销科学。

The long term goal is to showcase, like I said, John said, there's so much noise out there. A podcaster, a celebrity healthcare podcaster has more influence over people's health than the scientist that's developing and delivering these solutions. So we're trying to highlight what's real, what works, what's here now, and try to create a community that will understand those things and promote those. Because as John mentioned and kind of one of the premises for this event is great marketing on top of shitty science will always beat, you know, shitty marketing on top of great science. So part of what we're trying to do with John's help and his understanding of media is how do we how do we market science in a way great science.

没错。

Right.

因为大多数科学家并不追求名声。他们只想攻克难题，花费毕生精力试图解决一个问题。如果有医生或科学家这样做，那对所有人都有益，但他们却被肽类、肽类闹剧所淹没，那么我们就输了。所以我们想尝试提升科学家地位，让他们再次成为酷炫的人物。

Because most scientists don't want fame. They just want to tackle a hard problem and they spend their whole life trying to solve one thing. And if some doctor does that or some scientist does that, that benefits everybody, but they're drowned out because of peptides, the peptide circus, then you know, then we lose. And so we want to try to like elevate and make scientists the cool cats again.

那么，约翰，让我们回到你这里。你创办了这么多媒体公司。DOC在未来三到五年内让这些科学家成为城里酷孩子的商业计划是什么？

And so, I mean, John, let's come back to you. You've started so many media companies. What is the business plan here for three to five years for DOC in making these scientists the cool kids in town?

嗯，未来几年DOC肯定会推出更丰富的媒体内容，但我们的野心不止于此。作为创办过一堆媒体公司的人，我知道很少有公司能达到信息传播的那种高度。

Well, will definitely be more robust media coming from DOC over the next few years, but we have greater ambitions than that. As someone who started a bunch of media companies, very few get to the point where the information has gotten.

这

It's

并不容易。而且我们知道还有其他方式来执行支持伟大科学的使命。所以我们肯定会制作关于伟大科学的媒体内容，但我们还将创建一个平台。今年晚些时候我们会对此发布一些公告，敬请关注。

not easy. And we know that there are other ways to do you know, to execute the mission of supporting great science. So we'll definitely be doing media about great science, but we're going to be also creating a platform. We'll be making some announcements about that later in the year, so stay tuned.

格雷格，等你们今年晚些时候发布那些公告时，我们得请你们两位再来节目。祝下周会议顺利。这是个激动人心的话题，我很期待看到这些对话的成果，尤其是周日晚上的那场辩论。你们两位一定要回来告诉我们结果。乔丹，你好像有话要说。

Greg, well, we'll have to have you both on later in the year when you make those announcements. Best of luck with the conference next week. It's a it's an exciting topic, and I'm excited to see what the output of those conversations are, not the least of which is that debate on Sunday night. You both got to come back on and tell us what yep. Jordan, you're about to say something.

最后说一句，算是剧透预警，其实也不完全是——在我们的辩论中，我们将让克劳德和克劳迪娜登上辩论舞台。

One last thing, is spoiler alert, kind of not really, is at our debate, we are going to have Claude and Claudine on the debate stage.

好的。那么我们将要

Okay. So we are going to

让AI参与这场辩论。

have AI participate in this debate.

好的。就这样吧。嗯，那就给我们发些片段吧。我们会把片段放到节目里的，老兄。我觉得这这让我很兴奋，而且，你知道，如果有直播的话我一定会收看。

Okay. There you go. Well, send us some clips then. We'll put the clips on the show, man. I think that's that's I'm I'm excited, and and, you know, I will have to tune into the livestream if there is one.

我知道门票可能相当昂贵，所以你们可能还没这么做，但再次感谢你们两位的到来。他们是John和Jordan，DOC的联合创始人，这是一个下周将在纳帕掀起热潮的新会议。好的。毫无疑问，过去几周开始让人觉得科技行业的情况变得非常泡沫化。而在八月份，我们在The Information发表了一篇精彩报道，讲述了这种情况实际上给创始人和初创公司带来了很多焦虑，因为他们面临着比以往更激烈的竞争。

I know that tickets are probably pretty expensive, so you're probably not doing that just yet, but thank you again to the both of you for coming on. That is John and Jordan, the co founders of DOC, the new conference that is sweeping through Napa next week. Okay. Well, there is no question that the past few weeks have started to feel like that things are getting very frothy in the technology sector. And back in August, we published a great story in The Information about how that has actually caused a lot of anxiety for founders and startups as they grapple with more competition than ever.

我想请上Todd Olson，Pendo的创始人兼CEO，这是一家他于2014年创立的数据分析公司。他一直在密切关注这一动态的发展，我想请他上节目来谈谈这个问题。Todd，很高兴再次见到你。

I want to bring on Todd Olson, the founder and CEO of Pendo, a data analytics company he started back in 2014. He has been watching this exact dynamic play out very closely, and I want to bring him on to the show to talk about it. Todd, it's great to see you again.

嗯，谢谢邀请。很高兴来到这里，Akash。

Well, thanks for having me. It's great to be here, Akash.

嗯，应该说这个环节的起因是昨晚我和你在纽约证券交易所的First Mark Capital创始人晚宴上相遇，我们聊得很投机，谈到了当前创始人和初创公司的处境。我昨晚问你的问题是，最近怎么样？氛围如何？这个问题其实源于我们发表的那篇报道，即考虑到技术创新的风险和速度，人们现在非常焦虑。我觉得你的回答很有见地。

Well, I should say the genesis of this segment was you and I met last night at the First Mark Capital Founders Dinner at the New York Stock Exchange, and we sort of hit it off talking about the current moment for founders and startups. The question I asked you last night was, said, How's it going? What's the vibe? That question really came out of the story that we published, which is that people are so anxious right now, just given the stakes and the pace of technological innovation. I found your answer pretty insightful.

我要再问你一次，现在的氛围怎么样？你周围的世界里人们感觉如何？

I'm going to ask you again, what's the vibe? How are people feeling around you in your world right now?

是的，我的意思是，这很紧张。这是一个非常、非常不同的时期。我想我们谈过焦虑这个词，毫无疑问。这是我在这家公司历史上感受到的最焦虑的时期之一，当然也是近年来最焦虑的。回顾过去几年，2021年显然是一个高峰时刻，科技IPO达到顶峰，资金充裕，一轮又一轮的融资。

Yeah, I mean, it's intense. I mean, it's a really, really different time. I think we talked about the word anxiety or anxious, and there's zero question. It's one of the most anxious times I've felt in the company's history, and certainly in recent history. If you look back across the last few years, you had obviously 2021, which you had this peak moment within peak tech IPOs, you had significant funding, you had one round after another.

然后到了2022年，发生了很多变化，很多变化。显然，市场进行了调整，很多估值倍数被压缩，它们下降了。我想当时，我们都调整了。对吧。我们都调整了，然后我们说，是的，看看明年会怎么样。

Then '22, there's a lot of change, a lot of change. Obviously, the market corrected, a lot of valuationsmultiple compressed, they came down. I think at the time, look, we all adjusted. Right. We all adjusted and we're like, Yeah, we'll see how next year goes.

明年，我确信情况会好一点。然后你到了下一年，2022年，你会说，下一年会好一点。快进到现在，我们到了2025年，市场又变得泡沫化了。你可以说它甚至比2021年更泡沫化，但不同的是，它基本上是由人工智能驱动的。所以它和2021年不同。

Next year, I'm sure this thing will be a little bit better. Then you get to next year, 2022, you're like, The next year will be a little better. Fast forward, now we're in 2025, and the market is frothy again. You could argue it's even frothier than it was in say 2021, but it's different because it's basically driven by AI. So it's different than it was in 2021.

所以如果你是一家在2021年很火的公司，你可能会想

So if you were a company that was hot in 2021, you're kind

我该怎么加入那个行列？

of like, How do I get on that?

一种思考方式是，我们都在跑自己的比赛，我们可以在自己的比赛中做得很好，但然后我们看到隔壁有另一场比赛在进行，我们就会想，我想参加那场比赛。我想很多人都在寻找重新创业的时刻。你听到过这样的术语。

One way of thinking, we're all running races and we can be doing really well in our race, but then we see another race going on next door and we're like, I want to be in that race. I think a lot of folks are looking at refounding moments. You hear terms like that.

重新定义他们是我公司的AI角度吗？我的问题是，正如你刚才所说，你在跑自己的比赛，也在关注其他公司在进行的其他比赛。我的意思是，在某些情况下，作为初创公司，我们是不是有点忘记了如何正确构建业务的基本原理？因为，从根本上说，你必须解决一个问题，对吧？我们在节目中讨论过，这么多企业软件业务，尤其是那些大公司，对吧？

Reinventing their is the AI angle to my company? My question for you is, as you just said, you're running your race, you're paying attention to the other races that other companies are running. I mean, have we sort of forgot about the fundamentals of how to build a business properly in some cases as startups? Because, I mean, at the core of it, you got to be solving a problem, right? And we talk about it on the show, so many of these enterprise software businesses, especially the big ones, right?

他们的产品有点趋同。我的意思是，每个人都有一个代理，它基本上会做同样的事情或某种变体。我认为我们已经迷失了要解决的问题是什么。

Their products are kind of converging. Mean, everybody has an agent that is going to do pretty much the same thing or some variation of the same thing. I think we've lost sight of what the problem is we're trying to solve.

是的。听着，我确实认为最终都会回归基本面：你是否在解决一个难题？你做得好吗？质量高吗？我认为，仅仅因为你能在两周内快速编码出一个解决方案，并不意味着它真的能满足需求。

Yeah. Look, I I do think it's all going to come down to fundamentals, are you solving a hard problem? Are you doing it well? Is there high quality? I think just because you can vibe code a solution in two weeks doesn't mean it's actually going to meet needs.

然后，即使你回顾本周早些时候，OpenAI的公告，台上有人被问及存在哪些机会，我认为答案是关于那些无聊的企业事务。事实是，很多像我们这样的公司已经建设了十多年。我们已经构建了大部分无聊的企业事务。猜猜怎么着？当你与大型企业交谈时，是的，虽然人们正在试验AI，他们正在使用它，成熟度各不相同，但他们仍然需要一个懂得如何与大型企业合作的公司。

Then even if you go back to earlier this week, the OpenAI announcement, folks were asked on stage around what opportunities exist, and I think the answer was something around boring enterprise stuff. The truth is, a lot of companies like us have been building for over ten years. We've built most of the boring enterprise stuff. Guess what? When you talk to large enterprises, yes, while people are experimenting with AI, they're using it, there's different levels of maturity, and they still need a company that understands how to work with large businesses.

我认为最终市场上仍然有大量的机会。我认为肯定会出现一些现有的大型 incumbent 公司和一些这些泡沫般的新初创公司的融合，因为这可能是并购，也可能是创新，但我确实认为让人焦虑的原因是，我们都觉得我们应该做得更多一点。就像我们可以做得非常好。老实说，我觉得我们做得相当不错。第三方告诉我我们做得很好，但然后我会在新闻上看到一些东西，再次，他们又回到了开幕公告——

I think ultimately, there's still tons of opportunity in the market. I think there's definitely going to be probably a convergence of some of the large existing incumbents out there and some of these frothy new startups because that could either be M and A, it could innovation, but I do think that the reason it's anxious is that we all feel like we should be doing a little bit more. It's like we could be doing really well. I feel like we're doing pretty well, to be quite honest. I'm told by third parties we're doing well, but then I'll see something on the news where, again, they go back to the opening announcement-

Anthropic与IBM或与德勤达成了大交易。就像是——是的。

Anthropic does this big deal with IBM or with Deloitte. It's like- Yeah.

是的。甚至对于成功的企业来说，也更容易产生冒名顶替综合症，因为你有什么用？我们是一家成功的企业，有近100名员工，我们有真实的收入和真实的客户。我认为这就是当前世界的状态。正如我告诉我的团队，我宁愿焦虑和紧张，也不愿只是放松和悠闲，然后有一天醒来发现整个世界在我们脚下改变了。

Yeah. It's easy to have even more imposter syndrome than And even for successful businesses, because what good are you? We're a successful business, there were nearly 100 employees, we have real revenue and we have real customers. I think that's the state of the world right now. As I tell my team, I'd rather be anxious and intense than just chilling and relaxing and then wake up one day and have the whole world change out from underneath of us.

好的。我想快速问你一个关于你业务的问题。Pendo从事数据分析业务，你们某种程度上帮助公司研究其内部各种软件的使用情况。这让你们对过去几年人工智能如何改变软件使用情况有了一个有趣的视角。你有没有注意到这样一种理论，即人们将开始自己编写代码制作软件，他们会减少购买企业软件，使用量会下降。

Right. I want to ask you one question quickly about your business. Pendo is in the business of data analytics, and you sort of help companies study how various different softwares are being used across their company. That gives you kind of an interesting perspective as to how usage of software has been changing over the past few years with AI. Have you noticed anything about this theory around, hey, people are going to start to vibe code their own software, they're going to start to buy enterprise software less, usage is going go down.

我的意思是，你们研究这个，这就是你们业务的核心。在人工智能时代，你们看到软件使用量下降了吗？

I mean, you studied this, That is the name of your business. Are you seeing software use come down in the era of AI?

没有。到目前为止没有。我们每天测量超过十亿人使用软件的情况，不，软件使用量并没有下降。实际上，数字还在持续上升。

No. So far, no. We do measure over a billion people using software on daily basis, and no, software usage is not down. Actually, numbers continue to go up.

那么，你认为这是为什么呢？

Now, I Why do you think that is?

因为我认为人们部署人工智能主要是为了提高现有员工的生产力和效率。虽然确实有关于裁员之类的报道，但我认为大规模的人员替换还没有发生。所以我觉得它更像是一个助手或副驾驶，而不是真正自主地取代人类活动。我要说的是增长速度没有那么快了，更重要的是，我们的客户对未来增长的预测没有以前那么乐观。比如2020、2021年的时候，人们预测未来会有显著增长。

Because I think people are deploying AI predominantly to get more productivity and efficiency out of existing employees. And while, yeah, you read about layoffs and other things, I don't think mass people have been replaced quite yet. So I think it's more been an assistantco pilot than it has been truly autonomously replacing activities. I will say it's not quite growing at the pace, and more importantly, our customers are not forecasting as much growth that they would have in the future. Say take 2020, 2021, people were forecasting significant growth out of ahead.

现在每个人都对未来的增长预测有点紧张和不确定。我们看到了这种变化。这更多是对未来的预测，而不是现状的反映。所以不，我认为我们没有看到太多变化。现在，人们使用软件的方式正在改变。我认为人们显然更喜欢对话式的方式，要求软件去做事情。

Now everyone's a little bit nervous and uncertain of how much growth can we forecast out in the future. We are seeing that change. That's more of a prediction of the future than it is a reflection So of no, I don't think we're seeing a lot of change. Now, how people software is changing. I think people obviously are enjoying a more conversational way, asking the software to do things.

我认为他们在软件中做的事情正在改变，但这对我来说只是创造了新的机会来真正做得更好。

I think what they're doing in software is changing, but that to me just creates new opportunities to really make that better.

重要的是，你在这里说的是，关于‘我将增加席位数量’或‘我将购买更多软件’的预测，这种增长率已经开始有所下降或开始减速。这就是

Importantly, so you're saying here that the forecasting of, Hey, I'm going to increase my seat count, or I'm going to buy more software, that growth rate has started to decline a bit or started to decelerate. That's

我们所看到的情况。我想说，我们看到人们在规划上变得更加保守，而过去他们更为激进。我们并不按席位收费，但我们的许多客户是这样做的。我们更关注的是行业层面的趋势，而不是

what we're seeing. I'd say we're seeing people being much more conservative in their planning, where in the past they were more aggressive. And we don't charge on seats, but a lot of our customers do. We're looking more at the industry approach than it

确实如此。但我想问你的一个问题是，人们已经讨论了这背后的核心原因。这是我们整个行业普遍听到的说法。这是因为人员编制增长不再那么快了吗？

is. Right. But one of the questions I want to ask you then is, people have talked about the core reason behind that. That's something we've heard from the industry at large. Is that because head counts are not growing as quickly?

是因为CEO们作为软件采购的负责人，不再像以前那样花那么多时间在这些传统软件上，而是更关注AI吗？你认为核心原因是什么？

Is that because CEOs are just not people in charge of buying the software, they're not spending as much time with these old school softwares, they're looking more at AI. What are the core reasons for that, do you think?

好的。我确实认为总体上，人们对人员编制增长更加保守。人们会反复问：既然有了AI，我们真的需要增加人手吗？这又归结到一些焦虑。我们看到其他公司在做某些事情，为什么我得不到那样的回报？

Okay. I definitely think that in general, people are more conservative on headcount growth. People are double asking, Do we really need this additional head when we have AI? Again, it's come down to some of the anxiety. We see other companies doing something, Why can't I get those returns?

我回过头去找那些认为需要为某些问题增加人手的领导。我说：嘿，我刚读到OpenAI在做这个。为什么我们不能做？他们会说：嗯，他们的架构不同。不，再去查查看。

I go back to my leaders who think they need heads for certain problems. I'm like, Hey, I just read that OpenAI is doing this. Why can't we do this? They'll say, Well, they're architected different. No, go check again.

那么，这是否意味着我们最终不会招聘那个人？我们可能会。非常有可能。我只是想说，现在的门槛比历史上任何时候都要高得多。但是的，看看事情如何发展会很有趣。

Now, does that mean we won't eventually hire that head? We may. We very well may. I'm just going to say that bar is a much higher bar than it's ever been before in history. But yeah, it'll be interesting to see where it plays out.

我认为我们正处于一个充满变动的时期，变化太多了。人们正采取一种更为观望的态度。很好。

I think we're in this period of flux where there's just so much change. People are taking a little more of a wait and see approach. Great.

好的，托德，非常感谢你来到节目。昨晚见到你很高兴，今天在节目上见到你也很棒。这位是Pendo的创始人兼CEO托德·奥尔森，做客TITB。好了，在我们最后一个环节，如今招聘优秀人才变得有点混乱，因为AI职位发布和AI简历已经席卷了招聘领域。我们的下一位嘉宾表示，他们有一个解决方案，可以更可靠地找到更好的人才。

Well, Todd, thank you so much for coming on the show. Was great seeing you last night and great seeing you on the show today. That is Todd Olson, the founder and CEO of Pendo here on TITB. Okay, well, for our final segment, hiring good talent has become a bit of a mess these days as AI job postings and AI resumes have swept through the recruiting landscape. Our next guest says that they have a solution to finding better talent more reliably.

MeritFirst是一家专注于招聘的初创公司，今天已在种子轮融资中筹集了超过600万美元。公司的联合创始人兼CEO扎克将在这里谈谈他们的方法。扎克，很高兴见到你。欢迎来到TI TV。

MeritFirst is a hiring focused startup that has raised more than $6,000,000 today in a seed funding round. Here to talk about their approach is Zach, the co founder and CEO of the company. Zach, it's great to see you. Welcome to TI TV.

嘿，非常感谢邀请我上节目。

Hey, thanks so much for having me on.

我已经念错了另一个上我们节目的初创公司的名字，所以我不想冒险念错你的姓氏。你的姓氏是什么？怎么念？

I already mispronounced the name of another startup that we had on the show, and so I wasn't about to take a chance on mispronouncing your last name. What is your last name? How do you say it?

是Gagne。

It's Gagne.

Gagne。好的。这就对了。嗯，我从No那里可猜不出来。

Gagne. Okay. There you go. Well, I wouldn't have guessed that from No

一个就搞定你了，所以。

one gets you right, so.

Merit First是做什么的？给我们概述一下。

Does Merit First do? Give us overview.

是的，我的意思是，我觉得你一开始就说得很好，现在的招聘流程确实问题很多，双方都感到非常沮丧。公司对他们招的人没有太多信心。你知道，他们因为依赖这些相当糟糕和过时的评估人才的标准而错过了优秀人才，比如简历和证书。另一方面，我们看到求职者普遍感到疲惫，就像在简历堆里迷失了方向。

Yeah, I mean, think you hit on it well upfront that the hiring process is pretty busted today, where you're seeing a lot of frustration on both ends. Companies don't have a ton of conviction in the hires that they're making. You know, they're missing out on great talent because they're relying on these, you know, pretty poor and outdated proxies for evaluating talent. You know, that's resumes and credentials. You know, the flip side of that, we're seeing candidates get fatigued across the board, just kind of getting lost in the resume shuffle.

我们所做的是采取一种几乎独特的方法——其实这不应该算独特，但可以说是退一步说，嘿，正确的招聘方式实际上是亲自验证某人能否完成他们声称能做的工作。而正确的方法是通过某种形式的评估，无论是标准化评估、带回家的测试，还是让人们完成实际的工作产出，这样你就能看到他们能做的工作。

What we're doing is taking, you know, almost a unique approach. It really shouldn't be a unique approach, but kind of taking a step back and saying, Hey, the right way to hire is actually validating for yourself that someone can do the work that they say they can do. And the right way to do that is through, you know, some form of assessment. So whether that's a standardized assessment, a take home assessment, getting folks doing actual real work product so you can can see the work that they can do.

明白了。那你们已经有客户在使用这个进行招聘了吗？

Got it. And and do you guys have customers yet that are that are using this for their hiring?

是的，我们现在有几个客户。从早期初创公司到目前正在使用我们产品的一家殡仪馆都有。公司对优秀人才的需求并不局限于硅谷。我们看到各行各业的企业都有兴趣。

Yeah. We we have several customers now. Anything from early stage startups to we have a funeral home using the product right now. The need for strong talent in your company isn't something that's siloed in Silicon Valley. We see interest from companies across the board.

那你们实际上如何评估公司招聘的候选人是个好候选人呢？按理说，必须有某种系统来跟踪该员工后续的生产力，比如做调查来回馈说，嘿，这个结果好吗？我们的系统是否比使用LinkedIn带来了更好的结果？你们如何跟踪这一点？

And how do you actually assess that the candidate that a company has hired is a good candidate, conceivably, there has to be some system of tracking that employee's productivity down the line, doing surveys for you to say, Hey, did this work out? Did our system lead to a better outcome than if you had used LinkedIn? How do you track that?

是的，我认为这意味着要真正贴近我们的客户，了解这些招聘结果在后续的表现，就像你说的，三十天、六十天、九十天。我们通过保持与客户的紧密联系，向他们询问对所招人员的反馈来实现这一点。我们流程的独特之处在于，我们尽可能避免使用代理指标。我认为这意味着要尽可能接近某人实际在岗时会做的真实工作。因此，我们平台上看到的大多数评估都是某种形式的实际练习，是那个人在岗位上可能遇到的情况。

Yeah, I think that what that looks like is really staying close to our customers, getting an understanding of how these hires turned out down the line, like you said, thirty, sixty, ninety days. And we do that by just doing just that staying close to them and you know, asking for feedback on the hires that they make. You know, what's unique about our processes, you know, we are trying to steer away from proxies as much as we can. And I think what that looks like is getting as close to the real work that someone would actually do if they're in the seat. And so most of the assessments that we see on our platform are some form of actual exercise that that person could encounter in the seat.

所以，这在某种程度上仍然是一个代理指标，但比仅仅看简历和某种程度的资历筛选要接近得多。

And so that's, you know, still a proxy to some extent, but much closer than just, you know, the resume and kind of credential screen.

那你们运行的一个示例评估是什么？

And what's a sample assessment that you run?

是的，我的意思是，一个示例问题可能是这样的：你为一个劳动力市场平台工作，要开设一个新的垂直领域，去找水管工来配备人员，你的假设是什么？你会运行哪些实验？你在什么时候决定继续还是放弃？这样你就能真正深入挖掘解决问题的能力，以及他们如何做决策。而且是在这种开放式的、模糊的环境中，对吧？

Yeah, mean, you know, an example question could be something like, you work for a labor marketplace, you're going to set up a new vertical, you're going to go find plumbers to staff, what's your hypothesis? What are the experiments you run? At what point do you decide go and no go? And so you're really trying to dig into kind of problem solving ability, how they make decisions. And in this kind of open ended ambiguous environment, right?

因为在现实世界中，你所做的大部分工作都没有对错答案。只是需要在模糊中导航，朝着正确的方向推进，然后必须在何时决定加倍投入和何时决定后退之间做出权衡。

Because so much of the work that you do in the real world, there's no right or wrong answer. It's just navigating ambiguity and and kind of pushing in the right direction and then having to make those trade offs on when you decide to to double down and and back off.

所以，这就像是针对一个以策略为重点的角色。那么对于一个工程角色，你们基于实力帮助寻找候选人，你们会要求他们实际交付，你们会说，嘿，把这个做出来，基本上是这样。

So so that would be like a like a strategy focused And role, I so for an engineering role that you're helping to find a candidate based on merit, you would ask them to actually deliver on you would say, hey, build this, essentially.

是的，没错。我们在很多带回家的任务中看到的就是这样，你知道，这是一个项目。去实际构建这个项目，并且，你知道，我们让它保持开放性，人们实际上必须做出假设，做出决定。然后你才能真正理解某人的思维过程，他们优先考虑项目的哪些要素？他们认为什么是最重要的？

Yeah, exactly. That's what we see in a lot of the take homes is, you know, here's a project. Go off and actually build this and, you know, we, you know, kind of keep it open to them where people actually have to make assumptions, make decisions. And then you can really understand someone's thought process, what are the kind of elements of the project that they prioritize? What do they find most important?

这样你就能更近距离地观察这个人会如何在这个职位上开展工作。

And you're really getting a closer look at how this person would operate in the seat.

明白了。那么公司是根据成功录用情况支付费用，还是只要运行招聘流程就会付费？

Right. And they they the company pays you based on successful hires or just for running the hiring process at all?

目前我们的定价模式只收取平台费用。就像您支付给ATS合作伙伴的费用一样，我们将其视为软件产品。随着业务规模扩大，我们将能够根据企业需要的职位，为我们拥有的候选人进行匹配。

Right now, just a platform fee is our pricing model. So similar to what you pay your kind of ATS partners, we view this as a software product. And then as we continue to scale the business, we'll be able to make, you know, matches for companies based on the roles that they're looking for and just to know candidates that we have.

让我们把视角放宽一些。您如何看待未来企业招聘的发展方向？我看到有人从大学辍学却成为非常成功的企业家，也有人质疑：我真的需要上大学才能获得职位吗？

So let's zoom out here a little bit. What is sort of the future that you envision here for companies hiring for roles? I mean, I look at people dropping out of college, becoming very successful entrepreneurs. I look at people questioning, Hey, do I even need to go to college to get a role? Right?

这个理念是要取代高等教育作为培训人才的途径？还是与高等教育结合，教人们如何更好地构建事物？这是针对职业后期的招聘吗？您怎么看待这个问题？

Is idea here to replace higher education as vehicle for training people to do things? Is it it sort of integrating with higher education and teaching people how to build things more? Is this for later career hires? How do you think about that?

这是个很好的问题。我们不认为自己在取代高等教育。随着互联网发展，尤其是AI技术的进步，现在有更多途径可以掌握特定技能。我们的理想结果是：企业不再根据 arbitrary 的公司logo或工作年限筛选候选人，而是大幅开放人才漏斗，给所有想展示能力的人公平机会，最终不论背景如何都能让最合适的人选上岗。

Yeah, it's a really good question. I don't think we see ourselves as replacing higher education. I think with the internet, and now even more so with AI, there are more than there, you know, there are many ways to kind of figure out how to, you know, learn a certain skill set. And so the, you know, fast forward, the ideal outcome for us is companies are no longer, you know, screening candidates based on arbitrary, you know, logos or years experience, you can actually open up the funnel super wide, give them a fair shot who wants to show what they can do, and then ultimately get the best person in the seat, irrespective of background.

最后一个问题：AI对招聘来说是福还是祸？

Last question for you. Has AI been a blessing or a curse for hiring?

这是个好问题。我觉得，你知道，

It's a good question. I think, you know,

你得选一个。就这样吧，我们得在这里结束了。

You gotta pick one. That's that's we gotta end it on this.

我的意思是，我认为这是一种福气。人们想要高绩效的人才，他们能够快速行动并在整个组织中推动变革。总的来说，这是一种福气。只是在评估这类人才时，你需要仔细甄别其中的细微差别。

I mean, I think it's been a blessing. I think people, you know, you want people that are high performers, and they can, you know, you know, move quickly and affect change throughout the organization. Overall, it's a blessing. There's just nuance that you got to sort through when you're evaluating that talent.

但Merit First正试图解决其中的诅咒部分。

But Merit First is trying to tackle the curse part of it.

没错，完全正确。

Exactly, exactly.

好吧。也许你更倾向于认为它是一种诅咒，但我明白你的意思。我不会替你说话。这真是个非常有趣的业务。非常感谢你，Zach，来参加我们的节目。

Okay. Well, I would say maybe you think of it more as a curse, but I hear you. I'm not going to put words in your mouth. It's a really fascinating business. Thank you so much, Zach, for coming on the show.

我期待看到它的发展，以及你最终还会与谁签约和测试。天哪，我真想看到更多这样的交付成果。也许我们可以请几位候选人上节目聊聊他们构建的东西。这位是Merit First的创始人、联合创始人兼CEO Zach Jannier，在TI TV做客。今天的节目就到这里。

I look forward to seeing how it evolves and who else you end up signing on with and testing. Gosh, I want to see more of these deliverables. Maybe we'll maybe we can have a couple of the candidates on the show to talk about what they've built. That is Zach Jannier, the founder and co founder and CEO of Merit First here on TI TV. That does it for today's show.

提醒一下，我们每周一至周五太平洋时间上午10点，东部时间下午1点在这个直播频道播出。我要感谢亚马逊网络服务，他们是本次节目的主要赞助商，同时也要感谢大家的收看。我们非常珍视您的观看。我已经对明天的节目充满期待了。那么，下次再见，感谢您的观看。

A reminder, we are on this stream Monday through Friday at 10AM Pacific, 1PM Eastern. I want to thank Amazon Web Services, who was our presenting sponsor for this production, and I want to thank you for tuning in. We really do appreciate your viewership. I am already excited for our next show tomorrow. And so until then, thanks for tuning in.

暂时先再见啦。

Bye bye for now.