How to Reorg After AI Changes Everything | Block's Owen Jennings on the a16z Show

频道: a16z
视频: https://www.youtube.com/watch?v=krdrkl38nRw
原文语言: en
统计: 共 18 轮 · 主持人 2 · Owen Jennings 16

[0:00] 主持人

The biggest moat is going to be which companies understand something that's super hard for other people to understand. And if your answer to that is, "I don't know." then you maybe could get vibe code in the way. Block was one of the first to make a pretty drastic decision in cutting 40% of the workforce. What led up to that decision? There's been this correlation between the number of folks at a company and the output from the company for decades and decades. I think that basically broke and what we were seeing is that one or two engineers who is on the tools is able to be 10, 20, 100 X more productive. Over time it's like pretty obvious that these systems are just going to be so much better than like having a thousand humans who are doing that work. I I do believe that fundamentally for a given product or for a given road map, you're going to need fewer engineers, fewer designers, fewer PMs. I think that's like very, very clear. You show up on Monday, 40% of the company's gone. What's the most meaningful difference in how you're operating? I think the biggest thing is What does it actually look like for a large public company to restructure itself around AI? Owen Jennings is the business lead at Block where he oversees product, operations, and customer support across Square, Cash App, and Afterpay. Before this role, he was the CEO of of Cash App during its critical scaling period. And recently Block executed a roughly 40% reduction in force. And they've been pretty candid about AI being a critical component of that decision. Owen has gone through the AI transformation at scale across product lines and business units. And so we're going to dig into the that decision around the riff, how Block has adapted, the current and future state of the business.

未来最大的护城河，是那些能理解别人很难理解的东西的公司。如果你对这个问题的答案是"我不知道"，那你可能就有被 vibe coding 取代的风险。Block 是最早做出相当激进决定的公司之一，砍掉了 40% 的员工。是什么促成了这个决定？过去几十年里，公司的人数和产出之间一直存在某种相关性。我觉得这个关联现在基本上被打破了。我们看到的是，一两个真正上手用工具的工程师，生产力能提升 10 倍、20 倍、甚至 100 倍。长远看，很明显这些系统会比养一千个人去干同样的活强太多了。我确实相信，从根本上说，做同一个产品、推进同一个路线图，你需要的工程师、设计师、PM 都会更少。这一点我觉得已经非常非常清楚了。周一来上班，公司 40% 的人没了，你们运作方式上最大的变化是什么？我觉得最大的变化是——一家大型上市公司围绕 AI 重组自己，到底会是什么样子？Owen Jennings 是 Block 的业务负责人，主管 Square、Cash App 和 Afterpay 这几条线的产品、运营和客户支持。在这个岗位之前，他在 Cash App 关键的扩张期担任 CEO。最近 Block 执行了大约 40% 的裁员，他们也相当坦率地承认 AI 是这个决定的关键因素。Owen 经历了横跨多条产品线和业务单元、规模化的 AI 转型。所以我们今天要好好聊聊那次裁员的决策、Block 是怎么适应过来的，以及业务的现状和未来。

[1:39] 主持人

So thank you so much, Owen. Welcome to the stage. Awesome. Um so, you know, Jonathan I think did an amazing job kind of setting the stage, you know, for this conversation, uh you know, talking about how important it is to be founder-led. You know, Block was one of the first to make a pretty drastic decision in cutting 40% of the workforce. Um maybe walk us through kind of what led up to that decision and how you thought about it. Sure. I think I would probably I probably start two or three years ago. I think one thing about Jack is I find Jack to be generally right and generally early. Sometimes very early. Um and I think that's flowed through Twitter, Square, Cash App, Bitcoin, etc. And so we're pretty early on the agentic development side. We actually launched Goose, which was the first agent harness, at least that I know of, um in early 2024. And that started to augment how we approached software development, uh how we thought about internal tooling. And I would say that over the over that period, 24 and 25, it was like pretty meaningful progress. Um and then late November, first week of December, it was just there was a binary change. You basically have Opus 4.6, you have uh Codex 5.3, and essentially you get this shift where I think the the the tools and the foundational models were pretty good at writing code, especially for new ventures and kind of like green space. Um it became clear almost overnight, maybe in a couple of weeks, that now they're incredibly capable working with existing complex code bases. Um and so there was a massive paradigm shift where, at least from my perspective, there's there's been this correlation between the number of folks at a company and the output from the company uh for, you know, decades and decades. I

非常感谢你，Owen，欢迎上台。太好了。我觉得 Jonathan 刚才把这场对话的背景铺垫得特别好，讲了创始人亲自掌舵这件事有多重要。Block 是最早做出相当激进决定、砍掉 40% 员工的公司之一。能不能带我们梳理一下，是什么促成了这个决定，你们当时是怎么想的？当然。我可能得从两三年前讲起。关于 Jack 有一点我特别有体会：我觉得 Jack 大体上总是对的，而且总是很早，有时候是早得离谱。这一点从 Twitter、Square、Cash App、Bitcoin 一路都能看出来。所以我们在 agent 开发这块也算入场很早。我们其实在 2024 年初就推出了 Goose，据我所知那是第一个 agent harness。它开始改变我们做软件开发的方式，也改变了我们对内部工具的思路。我会说在 24 年和 25 年这段时间里，进展是相当可观的。然后到了 11 月底、12 月第一周，事情发生了一个非黑即白的突变。基本上就是 Opus 4.6 出来了，Codex 5.3 出来了，然后你能感觉到一个转折——我觉得在这之前，工具和基础模型已经挺擅长写代码了，尤其是对新项目、那种从零开始的场景。但几乎是一夜之间，可能就几周时间，突然变得很清楚：现在它们处理已有的复杂代码库的能力强得惊人。所以发生了一次巨大的范式转变。至少在我看来，过去几十年里，公司的人数和产出之间一直存在某种相关性。我

[3:45] Owen Jennings

think that basically broke the first week of December. And what we're seeing is that one or two engineers or a designer and an engineer who was on the tools, quote on quote, as we say, is able to be 10, 20, 100 x more productive. And so that's really what led us to make the the decision a few weeks ago. We spent Q1 discussing like what does this mean? Fundamentally, what does this mean in terms of how we're going to build products, how we're going to build software for customers, and then also how we're going to run a company. What is it going to mean to actually run a company? And we spent Q1 as an executive team Jack working through that. And ultimately, that's what led us to this place where where we we did a reduction in force that was, you know, slightly greater than than 40% and that wasn't even, you know, to the to the conversation we were just having. The tools are flowing through really meaningfully on the development side and so the cuts were way larger on the development side. If you think of something as outbound sales or account management, the cuts were, you know, fairly de minimis. And so that was really what we were reacting to. Can I push you a bit on this little bit? I mean, Alex, when you kind of introduced the, you know, the conference just, you know, an hour ago, talked about the surf period. You know, how much of the riff was sort of overhang from 2021 kind of over hiring versus AI and and kind of like the product actual productivity gains going to be in the business? Like if you look at where we were from a from a gross profit per full-time employee basis from like 2019 through 2024, we're basically like right in the middle of the pack with all of the with all of the competitors. If you look at last year, I think we

觉得这个关联在 12 月第一周基本上就被打破了。我们看到的是，一两个工程师，或者一个设计师加一个工程师，用我们的说法是真正"上手用工具"的那种，生产力能提升 10 倍、20 倍、100 倍。这才是几周前促成我们做这个决定的根本原因。我们整个 Q1 都在讨论：这到底意味着什么？从根本上说，这对我们怎么做产品、怎么为客户写软件意味着什么，进而对我们怎么经营一家公司意味着什么？真正经营一家公司又意味着什么？我们整个 Q1，连同 Jack 在内的高管团队都在琢磨这件事。最终就走到了这一步——我们做了一次略超过 40% 的裁员。而且，回到我们刚才聊的那个话题，工具在开发侧的渗透特别明显，所以开发侧砍得幅度大得多。像 outbound 销售或者客户管理这类岗位，砍的就非常少。这就是我们当时在回应的东西。我能不能在这一点上多追问几句？Alex 大约一个小时前在介绍这场会议时，提到了那段裁员潮。这次裁员里，有多少是 2021 年招人过度遗留下来的包袱，又有多少是 AI、是业务里实打实的生产力提升带来的？如果你看我们 2019 年到 2024 年人均（按全职员工算）毛利润的水平，我们基本上就处在所有竞争对手的正中间。但如果看去年，我觉得我们

[5:25] Owen Jennings

were kind of, I don't know, second quintile or something like that. I think it's basically like Nvidia and Meta that are ahead of us. And then when you look at the composition of what we did, if you thought it was like cruft and bloat and so on and so forth, then like this riff would have accrued to the operational teams and that like that sort of stuff. So really, really meaningful cuts on the development side. You don't make really, really significant cuts on the development side if you're not seeing a technology and a tool that's just fundamentally changed how we build. I mean, we're we're like we're not writing code by hand anymore. That's over. That's done. Um and so so anyway, everyone has their narrative. Um it's largely not true. Um so maybe just walk through like tactically, how did you actually execute, you know, this this transition, you know, culturally, you know, operationally in the business? So I think so we were um the the the nice part about this riff uh relative to some other, you know, things that have happened at Block or at other companies is we're coming from a position of strength on a on a profitability and operating income side. And so sometimes when it's really financially motivated, you know, the CFO or the CEO says, "Okay, we need to do a 16% riff in order to like hit this hit this target." And um that wasn't the case at all. We said, "What should the org look like given how these AI tools are flowing through now and what we expect to happen in the in the coming months and quarters?" We had some core principles. Um the first one was reliability. When you do something this size, worst case scenario is you have an outage or you go down. So that's like P00, not acceptable at all. Obviously, you know, things have

大概排到了第二个五分位还是哪儿。基本上就 Nvidia 和 Meta 在我们前面。再看我们这次裁员的构成——如果真的是因为冗余、臃肿之类的问题，那这次裁员就该落在运营团队这类岗位上。但实际上是开发侧砍得非常非常狠。如果你没有看到一项技术、一个工具从根本上改变了你的构建方式，你是不会在开发侧下这么大刀的。我是说，我们已经不再手写代码了。那个时代结束了，过去了。所以呢，每个人都有自己的叙事版本，但那些说法大多不是真的。那要不你具体讲讲，在战术层面你们到底是怎么执行这次转型的——在文化上、在运营上是怎么落地的？这次裁员相比 Block 或者其他公司发生过的一些情况，有个好处是：我们是在利润和营业收入都很强势的位置上动手的。有时候裁员是纯财务驱动的，CFO 或 CEO 说"好，我们得裁 16% 才能达到这个目标"。我们完全不是这种情况。我们问的是：考虑到这些 AI 工具现在的渗透程度，以及我们预期未来几个月、几个季度会发生的事，这个组织该长成什么样？我们有几条核心原则。第一条是可靠性。你做这么大规模的动作，最糟糕的情况就是出故障、系统宕机。所以这是 P00，绝对不能接受。当然，过去几周一切都

[6:59] Owen Jennings

been great over the past several weeks, which is fantastic. Second is building trust with customers and um compliance and navigating the regulatory environment. We all operate in a super complex, nuanced regulatory environment. That's a non-negotiable. We have to make sure that we're that we're doing we're doing right there. For instance, like we we basically did not touch our our compliance team and our compliance technology team. Even if the tools are there, it's like let's not take any risks. And then third was let's continue to drive durable growth. So there's things that are on the road map that we already know that we're building. We need to continue to do that. We know that it might be a squad of three people instead of a feature team of 14 who's building that. We're going to make sure we're continuing to build those features and that we're continuing to make longer-term bets. And then we built up the org from scratch and in some areas like the regulatory council team or the SDR BDR team, the org looked pretty similar to how it looked in January. On the development side, it looks completely completely different. And then, you know, from a from an execution perspective, you know, we thought very deliberately. Obviously, I've been in the company 12 years. A number of folks who we parted ways with are friends and colleagues for for you know, more than a decade. We were in a position where we were able to be generous in terms of, you know, the the severance packages that we gave. We didn't cut people's technology access instantly, which can suck. We chose to have an all-hands with everybody at the company. So Jack and the executive team were you know, looking each other in the eyes and explaining this decision and explaining the the drivers behind it. And

运转得很好，这很棒。第二条是建立客户信任、做好合规、应对好监管环境。我们都在一个极其复杂、极其微妙的监管环境里运作，这是不可谈判的，我们必须确保在这块做对。比如说，我们基本上没动我们的合规团队和合规技术团队。哪怕工具已经到位了，我们也想着——这块不要冒任何风险。第三条是继续推动可持续的增长。路线图上有些东西是我们已经明确要做的，那就得继续做下去。我们知道现在可能是一个三人小队，而不是过去那种 14 人的功能团队来做这件事，但我们要确保那些功能继续做出来，也要确保我们继续下一些更长期的赌注。然后我们是从零开始重新搭建这个组织的。在某些领域，比如监管法务团队、SDR/BDR 团队，重组后的样子跟一月份其实差不多。但在开发侧，完全完全不一样了。从执行的角度，我们想得非常审慎。毕竟我在公司待了 12 年，我们这次告别的不少人都是相处了十几年的朋友和同事。我们当时处在一个还算宽裕的位置，所以在遣散方案上能做得比较慷慨。我们没有立刻切断离开的人的技术权限——那种做法挺糟心的。我们选择开一场全员大会，让 Jack 和高管团队直视着大家的眼睛，把这个决定、以及背后的驱动因素讲清楚。

[8:36] Owen Jennings

I I think that that it was on a Thursday. I think like the Friday, Saturday, Sunday, there's a lot of shock, dealing with ambiguity. And then what we've been doing is uh we massively reduced the number of meetings we have, probably like 70 or 80%. So I now have time to like build and work and it's not back-to-back meetings. We're also meeting with the company every week. So we have like a one or two hour all-hands with Jack every every Monday. It just feels like we're we're smaller, we're leaner, we have fewer layers, we have larger spans, and it's it's been back to building. So you show up on Monday 40% of the of the company's gone. Like what how is what's the most meaningful difference in how you're operating? I don't know, maybe it's in the EPD org or elsewhere. I think that there's a there's a there's a few different components to this. I think the biggest thing is it so one concern that I have with like how some of these org changes might flow through the tech industry is that and then it gets back to the to the founder led point. If you're not founder led and you don't have the the ability to be bold, then you're going to probably take a more incremental approach. And so, the way that that's going to feel is like you do a 15% riff and it's like, "Oh, it's fine." And then you do another 15% riff. And then culturally, that's just like devastating for your team cuz there's always this like pending riff looming looming over your over your shoulder. Um this was obviously a decision to go in a different direction. I think one of the benefits that we got from this is like we were already seeing a a very meaningful increase in AI tool usage, especially on the development side. This is just a massive forcing function. Like if we're building

我记得那是个周四。然后周五、周六、周日，大家有很多震惊的情绪，要消化各种不确定性。之后我们做的事情是——大幅减少了会议数量，大概砍掉了 70% 到 80%。所以我现在有时间真正去构建、去干活，不再是背靠背一个接一个的会。我们也保持每周和全公司见面，每周一都有一两个小时、Jack 在场的全员大会。整个感觉就是我们更小了、更精干了、层级更少、管理幅度更大，又回到了埋头构建的状态。所以周一来上班，40% 的人没了，运作方式上最大的不同是什么？不管是 EPD（工程/产品/设计）这块还是别的地方。我觉得这里面有好几个不同的层面。我觉得最大的一件事是——我对这些组织变革在整个科技行业里会怎么扩散，有一点担忧，这又回到了创始人掌舵那个点上。如果你不是创始人掌舵、没有那种敢于大刀阔斧的底气，那你大概率会采取一种更渐进的做法。那种做法给人的感觉就是：你裁了 15%，大家说"哦，还好"；然后你再裁 15%。久而久之，这对团队来说简直是毁灭性的，因为头上总悬着一把随时会落下的裁员之剑。我们这次显然是选择了完全不同的方向。我觉得这次还带来一个好处：我们本来就已经看到 AI 工具使用量在大幅上升，尤其是开发侧。这次裁员就是一个巨大的倒逼机制。比如说我们要做

[10:11] Owen Jennings

Okay, we're we're building money bot and we want to roll money bot out to 50% and there used to be a team of 15 people working on it and now there's a team of four people plus $2,000 on the tokens. That This is like un- unlimited access to tokens and you can use fast mode on Claude code. Um so, now you have four people plus the tools. It's like, "Okay, well, you need to have eight instances of goose up and you need to shift your workflow from sequentially working through a PR, submitting it, getting a review, making the change to I have 14 agents who are building PRs on my behalf right now and I'm going to context switch between all of those. And it's not just uh on the software development side. It's for PMs, too. It's for growth marketers, too. The biggest shift Myself included. I I have you know, countless agents running right now that I have to go I have to go check on. Uh it's it's not um it's less of a linear workflow and it's more of like in the background, there's 10 or 20 agents who are doing a whole bunch of stuff and then I have to check in on the work and nudge it and change it and what have you and then I can commit it to GitHub and I can I can get the markdown file. We can put it in the source of truth and we can move on. So, we have a lot of, you know, public companies in the audience. We have a lot of founder-led businesses in the audience. Do you expect other companies to kind of follow a similar path? And and I guess what conditions need to be in place for that to be successful? I don't I don't I don't I don't necessarily want to Like I I talked at the beginning about um um the groundwork that happened in '23, '24, and '25. Like we built this agent substrate goose, and then we built a lot of tooling at the company on top of it.

好，我们在做 money bot，想把 money bot 推到 50% 的用户，以前是一个 15 人的团队在做，现在是 4 个人加上 2000 美元的 token 预算。这就相当于无限量的 token，你还能在 Claude code 上用 fast mode。所以现在你是 4 个人加上一整套工具。于是就变成——"好，你得同时开 8 个 goose 实例，你得把工作方式从'顺序处理一个 PR、提交、等 review、再改'，切换成'此刻有 14 个 agent 在替我写 PR，我要在它们之间来回切换上下文'。" 而且这不只是软件开发侧的事，PM 也一样，增长营销人员也一样。最大的转变包括我自己在内——我现在有数不清的 agent 在跑，我得一个个去查看。它不再是一种线性的工作流，更像是在后台有 10 个、20 个 agent 在干一大堆事，然后我去检查这些活、推它一把、改一改、做点调整，之后我就能把它提交到 GitHub，拿到 markdown 文件，放进唯一可信源，然后继续往下走。台下有不少上市公司，也有很多创始人掌舵的企业。你觉得其他公司会走类似的路吗？要让这条路走得通，需要具备哪些条件？我不太想……我在开头讲过 23、24、25 年我们打下的那些底子。我们搭了 goose 这个 agent 底座，然后在它之上为公司建了一大堆工具。

[11:46] Owen Jennings

We have a agentic operating system internal only called G2, where anyone can automate any deterministic workflow. So, anyway, there there I think there's work to do to to be successful. I would expect many companies are doing that work. Some some of them are incredibly um far ahead than than others. Um and so I I I don't know what to expect. What I will say is like to the extent that I I do believe that fundamentally for like a given product or for a given road map, you're going to need fewer engineers, fewer designers, fewer PMs. I think that's like very very clear based after like December. Um that doesn't necessarily mean that there's going to be fewer engineers, designers, and PMs in the world. Um it's like the classic Jevons paradox thing, where I I think that there's probably now just a super set of things that that can be built. Um so, I don't know you know, a given tech company might be might be way smaller, but there might be 50 or 100 more tech companies, or you're going to start getting this development working in in sectors and and areas where that hasn't historically been the case. Um but I I'm not here to to predict the future. I'm focused on Block. Uh fair. You you talked a bit about kind of some of the AI infrastructure build. Maybe you can get go in a bit more depth, uh you know, both in how it's impacting the kind of technology org. I'm also curious about, you know, how are you using AI in in other parts of the business? You oversee ops, customer support. Yeah. Um so, I got to ask that at a investor conference uh last week, like how is AI like flowing through Block? And then to me that's like asking um how are computers flowing through Block? Uh like I it's it's a uh fundamental inbuilt thing that has changed in like a

我们有一个仅供内部使用的 agent 操作系统，叫 G2，任何人都可以用它把任何确定性的工作流自动化掉。所以总之，我觉得想做成这件事是有功课要补的。我估计很多公司都在补这个功课，有些公司比另一些遥遥领先。所以我也不知道该期待什么。我能说的是——我确实相信，从根本上说，对一个特定产品、一条特定路线图来说，你需要的工程师、设计师、PM 会更少。经过 12 月那一波之后，我觉得这一点已经非常非常清楚了。但这不一定意味着世界上的工程师、设计师、PM 总数会变少。这就像经典的杰文斯悖论：我觉得现在能被构建出来的东西，是一个更大的超集了。所以呢，某一家科技公司可能规模会小很多，但可能会冒出 50 家、100 家新的科技公司；又或者，软件开发会开始渗透到一些历史上从没这么干过的行业和领域。不过我不是来预测未来的，我专注的是 Block。有道理。你刚才聊了一些 AI 基础设施的搭建。能不能再深入讲讲，一方面是它怎么影响技术组织的；我也很好奇，你们在业务的其他部分是怎么用 AI 的？你管着运营、客户支持这些。是的。上周在一个投资者大会上有人问我，AI 是怎么在 Block 里渗透的？对我来说，这就好比在问"计算机是怎么在 Block 里渗透的"。它是一个根植于底层、已经在过去 18 个月里以一种非黑即白的方式被改变的东西，

[13:30] Owen Jennings

binary way over the past 18 months and then feels like it changed all over again in the past 4 months. Um so I'll break it down into internal and then external and how we're thinking about our products, what we're putting in customers' hands. And then I can talk a little bit about the the future and where we think things are going. So on the internal side, I think the biggest difference is the shape of the of the org. So we used to have kind of like a classic hierarchical uh structure. It was functional, um which was great, but it was like fairly standard if you like averaged through a bunch of medium-sized tech companies. Um And so you would have kind of eight server engineers, four client engineers, a PM, a designer, and you would work linearly through your road map. Now we have um small squads. So squads of like one to six people. Um so meaning meaningfully smaller than the other teams would be. And we have way more flexibility and and fluidity where a given squad can work a few cycles on this product, get it live, and then a cycle on this other product. Um which is different than how things worked a year or two ago where it's like, "I'm on the banking team. I'm going to be on the banking team forever." We also have way fewer layers. So on the development side, I think we probably cut our layers by I don't know, 50 or 60%. Like on the product side, I only have I think two layers, maybe three layers in a in a couple of places. And so information is flowing um way more freely. I think that then in terms of how we actually build on the development side, things have changed. I think everyone's probably seen, you know, every every CEO out there is going on Twitter and showing their like green dot on on uh on GitHub. Um but that's real. Like all of

而且感觉过去这 4 个月里又彻底变了一遍。我把它拆成内部和外部两块来讲：我们怎么看自己的产品、要交到客户手里的是什么，然后我再聊一点未来、我们觉得事情会往哪儿走。先说内部，我觉得最大的不同是组织的形态。我们过去是那种很经典的层级化结构，按职能划分，挺好的，但也就是相当标准——如果你把一堆中型科技公司平均一下，大概就是那个样子。你会有 8 个服务端工程师、4 个客户端工程师、一个 PM、一个设计师，然后线性地推进你的路线图。现在我们是小分队，一个 squad 大概 1 到 6 个人，比以前的团队小得多。我们也有了大得多的灵活性和流动性——一个 squad 可以花几个周期做这个产品、把它上线，然后再花一个周期去做另一个产品。这跟一两年前很不一样，那时候是"我在银行团队，我就永远待在银行团队"。我们的层级也少了很多。开发侧的层级，我觉得大概砍掉了 50% 到 60%。产品侧我觉得只有两层，个别地方可能三层。所以信息流动顺畅多了。然后在我们实际怎么做开发这块，也变了。我觉得大家可能都见过了，现在每个 CEO 都跑去 Twitter 上晒自己 GitHub 上的绿点。但那是真的，我们所有的

[15:15] Owen Jennings

our designers are are shipping PRs. All of our product managers are shipping PRs. That's not that interesting anymore. I think more interesting is that we have uh internal tools that are similar to Claude code, but they're like more plugged into our infrastructure. So, we have a tool called Builder Bot. Builder Bot is just autonomously merging PRs and actually like building features to 100%. We've had some fairly complex features that are built to 100%. More often than not, it's building them to like 85 or 90% and then a human who who has a lot of context understands does like the final the final 10%. So, that feels really really different. The ability to go from um to go from idea to like this is in the hands of 100,000 or a million customers has been compressed massively since since December. Outside of development, I would say most of what we're seeing is like anytime there's a deterministic workflow, we're we're able to automate that. And so, generally at a at scale tech company, you have individuals who are working queues. Um a lot of that is just being completely automated away. Like from a customer support perspective, this is not new, but you know, our chatbots and and AI phone support and and whatnot are automating a a majority of inquiries that we get. And then it gets into like um product operations and risk operations and compliance operations and any sort of decisioning like generally um generally the the the models and the agents are going to do a better job than humans. Right now, I think it's critical that we have a human in the loop. Uh that's like the key kind of buzzword uh when you talk to talk to partners and regulators and and what have you. Um but over time, it's like pretty obvious that these systems are just going to be

设计师都在提 PR，所有的产品经理都在提 PR。这事现在已经不新鲜了。我觉得更有意思的是，我们有一些类似 Claude code 的内部工具，但它们更深地接进了我们的基础设施。我们有个工具叫 Builder Bot，它会自主地合并 PR，甚至真的能把功能做到 100% 完成度。我们有些相当复杂的功能就是被它做到 100% 的。不过更多时候，它会做到 85% 或 90%，然后由一个掌握大量上下文的人来收尾最后那 10%。这个感觉真的非常非常不一样。从一个想法，到"这东西已经在 10 万、100 万客户手里了"，这中间的时间从 12 月以来被极大地压缩了。在开发之外，我会说我们看到的大部分情况是——只要有一个确定性的工作流，我们就能把它自动化掉。在一家规模化的科技公司里，通常会有人专门处理各种工单队列，这些活现在很多都被彻底自动化了。从客户支持的角度看，这其实不算新鲜事，但我们的聊天机器人、AI 电话支持之类的，正在自动处理掉我们收到的大部分咨询。再往下，就进入到产品运营、风险运营、合规运营，以及任何涉及决策判断的环节——总的来说，模型和 agent 会比人做得更好。不过现在我觉得保留一个 human in the loop（人在回路中）是至关重要的，这是你跟合作方、监管机构这些人打交道时的关键热词。但长远看，很明显这些系统终将

[16:58] Owen Jennings

so much better than like having a thousand humans who are who are doing that work. So, that's on the internal side. Um on the on the product side, I think that And and maybe just catch people up on kind of the shape of the business. Obviously, you have Square, you have Cash App, you you made a big acquisition in Afterpay. Sure. What do those businesses look like? And then yeah, how are they kind of changing with that? AI? Sure. So, um so we used to operate in a business unit structure. So, Square used to be kind of its own business unit with its own CEO, Cash App was its own business unit with its own CEO. Um that wasn't leading to the right outcome. So, about 18 months ago, we functionalized the company just meaning that all of engineering rolls up to our head of engineering, all of design to our head of design, all of product to me. So, we have a financial platform team that spans the entirety of Block. We have a business platform team that's doing a lot of this automation that spans the the entirety of of Block. And then increasingly we're building features and products that actually connect the Square side, the Cash App side, and the Afterpay side. And so, naturally you're you're building technology and you're building infrastructure that is not um brand specific. And that's actually like kind of central to our our overall strategy and and and overall thesis. Um But yeah, I mean Cash Cash App went from when I joined Cash App in 2016, uh we had just just started to to figure out how to monetize and had our first dollars of gross profit. And now I think Cash App's probably like, I don't know, 60-ish percent of like overall gross profit at the at the company. So, overall been been growing at a healthy clip over the past decade. Um but uh

比起雇一千个人去干这活儿，要好太多了。这是内部这一块。至于产品这一侧，我觉得——也许先帮大家梳理一下业务的大致结构。显然你们有 Square，有 Cash App，还在 Afterpay 上做了一笔很大的收购。这些业务大概长什么样？它们又是怎么随着 AI 在改变的？好的。我们以前是按事业部（business unit）结构来运作的，Square 是一个独立的事业部，有自己的 CEO，Cash App 也是一个独立事业部，有自己的 CEO。但这没带来理想的结果。所以大概 18 个月前，我们把公司做了职能化改造，意思就是所有工程团队都向我们的工程负责人汇报，所有设计向设计负责人汇报，所有产品向我汇报。于是我们有了一个横跨整个 Block 的金融平台团队，有一个横跨整个 Block、在做大量自动化的业务平台团队。而且我们越来越多地在打造真正能把 Square 这一侧、Cash App 这一侧和 Afterpay 这一侧连起来的功能和产品。很自然地，你做出来的技术、搭起来的基础设施就不再是某个品牌专属的了。这其实可以说是我们整体战略和整体判断的核心。Cash App 呢，我 2016 年加入 Cash App 的时候，我们才刚刚开始摸索怎么变现，赚到了第一笔毛利。而现在 Cash App 大概占了公司整体毛利的、我说不准，差不多 60% 左右。所以整体上过去这十年一直在以一个健康的速度增长，不过——

[18:33] Owen Jennings

Cash App and Afterpay have definitely been growing um more quickly. But increasingly we're trying to think about things from an ecosystem perspective. And and that's maybe where like Goose as a platform comes in, which is we boot we built Goose internally. The way to think about Goose is um it's a nod to uh Top Gun or whatever, the co-pilot thing. But way to think about Goose is it's a it's a agent harness and it's model agnostic. So, I can run Goose on an Anthropic model, on a on a on a OpenAI model, on an open-source model. There's probably like 120 models that we have. And depending on what I'm trying to do, I'll kind of swap out the swap out the models. And then that was useful for a human to use, but we've built like the agentic layer on top. And so, now a lot of the automations at at Block are actually routing through the Goose agent harness. And um we've been able to leverage this across the products that we're building. So, Money Bot, which we'd like to think of as like a CFO in your pocket, but it's essentially like a proactive um uh uh a proactive uh chatbot that can take actions on your behalf within Cash App. That is built on top of Goose. Manager Bot, which is roughly a similar thing on the Square side. That's built on top of Goose. So, it's a lot of this foundational work on agentic systems and then like the the triggers and the underlying data and events that you need to power them. That's working across the uh the entirety of the of the company. So, on the on the product side, um I think that the the biggest shift has really been like we're going from a world where uh for the past 10 or 15 years, everyone's used to a static UI, a rigid UI. You tap through the UI. Everyone has the same Everyone's Uber or Lyft or Cash App or whatever it looks

Cash App 和 Afterpay 确实增长得更快一些。但我们越来越多地在从生态的角度去思考问题。这可能也正是 Goose 这个平台登场的地方——Goose 是我们内部自研的。可以这样理解 Goose：这个名字其实是在致敬《壮志凌云》（Top Gun），就是那个僚机搭档的梗。但本质上 Goose 是一个 agent harness（智能体运行框架），而且它跟模型无关。我可以在 Anthropic 的模型上跑 Goose，可以在 OpenAI 的模型上跑，也可以在开源模型上跑。我们大概接了有 120 个模型吧。根据我要做的事情不同，我会随时换掉底层用的模型。这一层本来是给人用的，但我们又在上面搭了一层 agentic（智能体化）的能力。所以现在 Block 的很多自动化其实都是经由 Goose 这个 agent harness 来路由的。而且我们能把它复用到我们正在做的各个产品上。比如 Money Bot，我们喜欢把它想成「装在你口袋里的 CFO」，但它本质上是一个能主动出击的聊天机器人，能在 Cash App 里代你执行操作。它就是搭在 Goose 之上的。还有 Manager Bot，在 Square 那一侧大致是类似的东西，也是搭在 Goose 之上的。所以这是一大堆关于 agentic 系统的底层基础工作，再加上你需要的那些触发器、底层数据和事件来驱动它们。这套东西是贯穿整个公司在跑的。所以在产品这一侧，我觉得最大的转变其实是——我们正在从一个这样的世界走出来：过去 10 到 15 年里，大家都习惯了一个静态的 UI、一个死板的 UI，你一层层点过去，每个人看到的都一样。每个人的 Uber、Lyft 或者 Cash App，长得都是——

[20:17] Owen Jennings

the same. That's going to fundamentally change in the next like 6 months. Um generated generative UI is is is here. We're seeing it with Money Bot. We're seeing it with Manager Bot. As the models get better,

都一模一样。这在未来大概 6 个月里会发生根本性的改变。生成式 UI（generative UI）已经来了。我们在 Money Bot 上看到了，在 Manager Bot 上也看到了。随着模型越来越强，

[20:28] Owen Jennings

What it What is that going to look like kind of in practice? I'm curious. I think I mean, in the simplest terms, it's like your Cash App should look really different from mine. And the reason why it's like, "Okay, well, I get my paycheck in the Cash App and I'm super into Bitcoin. Let's say like you don't and you use Afterpay all the time." Great. When we open up our apps, that should be totally different. That you could probably achieve that just through personalization. That's not that interesting. What we're actually seeing and Anthropic had some releases this week that are that are incredible. What we're actually seeing is like I can go into Money Bot and say, "How have I been spending my money?" And it'll show me a bunch of charts and uh and visua- visualizations where it is actually like on the fly generati- generating that visualization. It's not actually in the code itself. So, that's really cool. It's also potentially a nightmare from like a QA perspective. And so, we need to figure out how you're going to QA all of these like non-deterministic outputs for for tens of millions of customers. But, um a great example on the on the Square side is with Manager Bot, maybe charts aren't that impressive to you. But, with Manager Bot, let's say you're a you're a uh you own a a multi-location quick-serve restaurant. You say like, "Hey, can you build me an app where I can uh manage scheduling for these two locations and like automatically fire off texts via, you know, WhatsApp or or Signal or whatever to my um to my employees. It's actually going to like create that app for you. And the the way that that app looks and feels is not in the source code of the actual application that we push to the to the App Store. And so, I think it's um it

那这在实践中大概会是什么样子？我挺好奇的。我想——用最简单的话说，就是你的 Cash App 应该看起来跟我的很不一样。原因在于：「好，比如我的工资是打进 Cash App 的，而且我超级痴迷比特币。再比如你不是这样，你天天用 Afterpay。」太好了。那当我们各自打开 App 的时候，界面就应该完全不同。这一点你可能光靠个性化就能做到，那没什么意思。我们真正看到的——而且 Anthropic 这周发布了一些非常惊人的东西——我们真正看到的是，我可以走进 Money Bot 然后说：「我最近钱都花哪儿了？」它会给我展示一堆图表和可视化，而这些可视化是它真正在实时、即兴生成出来的，并不是写死在代码里的。所以这真的很酷。但从 QA（质量保证）的角度看，这也可能是个噩梦。我们得想清楚，对几千万的客户，你要怎么去 QA 所有这些非确定性的输出。不过呢，在 Square 那一侧有一个很好的例子，就是 Manager Bot——也许图表对你来说没那么惊艳。但有了 Manager Bot，假设你经营一家多门店的快餐店，你可以说：「嘿，帮我做一个 App，让我能管理这两家门店的排班，并且自动通过 WhatsApp 或 Signal 之类的给我的员工发短信。」它真的会帮你把那个 App 生成出来。而那个 App 长什么样、用起来什么感觉，并不在我们推到 App Store 的那个实际应用的源代码里。所以我觉得，这——

[21:56] Owen Jennings

gives folks way more control. It's way more personalized. And uh and ultimately, I think it'll lead to higher engagement. Um I think it'll lead to uh better product discovery. And and really, I think the key thing I I I don't think that if we ask customers to to like prompt these tools themselves, they're going to necessarily know the right prompts and come up with the right answers. So, we've invested massively on the proactive intelligence side where what we've found, especially as it relates to money, is like we need to be prompting our customers with things that we think make sense for them. And that's where we're creating a lot of the the value. So, I I mean, I think we're all incredibly bullish on on kind of the impact of AI, you know, in the kind of in the way that all these businesses run and the products you can create. How does that flow back to your stock price? You know, the the business is the stock has been roughly flat for, I don't know, six or seven years.

这给了用户多得多的掌控权，个性化程度也高得多。而且我觉得，最终它会带来更高的参与度，会带来更好的产品发现。说到根上，我觉得关键的一点是——我并不认为，如果我们让客户自己去给这些工具写 prompt，他们一定就知道该写什么样的 prompt、能想出对的答案。所以我们在「主动智能」这一侧投入了巨大的精力，我们发现，尤其是在跟钱相关的事情上，我们需要主动用一些我们认为对客户有意义的东西去提示他们。这正是我们在创造大量价值的地方。所以我是说，我觉得我们都对 AI 的影响极度看好——就是说它会怎样改变这些业务的运作方式、会催生出什么样的产品。那这些怎么反映回你们的股价上呢？你们这业务的股价，我说不准，大概有六七年了基本是平的。

[22:48] Owen Jennings

Thanks for reminding me. But, the the business has grown a lot, you know, to your point. The gross profit per employee has grown, you know, massively. Like, how do you sort of reconcile the that that dimension? Yeah, I think um so So, I think, you know, markets are markets are cyclical and there's all sorts of things that are happening. I remember uh in 2021 when our stock price was like, I don't know, 260 bucks. And I was like, that was a little bit irrational. Um you can take a a kind of longer-term mature view and say, you know, markets are voting machines in the near term, but they're weighing machines in the long term. Just like focus on building. I you know, David and Jonathan earlier talked a bit about kind of defensibility. How do you think about your own moats at Square I mean at Block, excuse me. You you know, you talked a bit about the ecosystem. You guys obviously have, you know, regulatory infrastructure. Um you know, how do you think about, you know, that the business overall in that context? Yeah, I think in the I think in the near term and the medium term, um there's a bunch of there's a bunch of moats that exist for for Block and and we can talk about the industry more broadly. I think I think distribution and network effects are are one of them. I I agree on the the Citrine piece and and DoorDash. I don't think anyone's vibe coding DoorDash in the next uh couple of weeks here. Uh I like to say like any of us can can create a peer-to-peer app in probably a week. Uh no one's going to vibe code, you know, 50 or 60 million monthly actives who are actually using that. So, I think that that's true. Uh I think um you know, licenses and and regulatory posture um definitely exist. I think hardware right now it's like harder to imagine how some

谢谢你提醒我啊。不过正如你说的，业务本身增长了很多。每名员工创造的毛利已经增长了非常非常多。你怎么看待并调和这中间的落差？是啊，我觉得——市场是有周期性的，各种各样的事情都在发生。我记得 2021 年我们股价大概是、我说不准，260 块吧，我当时就觉得那有点不理性。你可以用一个更长期、更成熟的视角去看，就是那句话——市场短期是投票机，长期是称重机。专注做事就好。David 和 Jonathan 早些时候聊了一些关于防御性（defensibility）的话题。你怎么看 Square——抱歉，是 Block——自己的护城河？你刚才聊了一点生态。你们显然也有，比如，监管层面的基础设施。你整体上是怎么在这个语境下看待这门生意的？是的，我觉得在近期和中期，Block 有一堆护城河存在，我们也可以更宽泛地聊聊整个行业。我觉得分发渠道和网络效应是其中之一。关于 Citrine 那块还有 DoorDash，我是认同的——我不觉得未来这一两周里会有人用 vibe coding 搞出一个 DoorDash。我喜欢这么说：我们这些人里随便谁，大概一周就能做出一个点对点（P2P）的 App。但没人能 vibe code 出五六千万真正在用它的月活。所以我觉得这一点是成立的。我还觉得，牌照和监管姿态这些护城河肯定是存在的。我觉得硬件这块，现在还比较难想象那些

[24:22] Owen Jennings

of the AI tools flow through to the to the hardware side. Like you can't vibe code a piece of Square hardware. Um but I I think longer term, if we continue like if we look at the rate of the change and and the change in the change, I think longer term, the key thing that's going to make uh a company defensible is um the extent to which the company understands something that is pretty hard for other companies to understand. And so, we're increasingly building toward a world and talking about block as an intelligent system itself. So basic like the the the the the way that I see this going if we can if you extrapolate forward the past several months is that ultimately a company is sitting on top of some sort of signal, some sort of like rich data and and and deep insight. Um for us it's like how sellers and buyers participate in the economy. Um and and most companies I think have this thing that they understand deeply. And then the question is going to be how quickly can you iterate to improve that understanding over time. And so we're building world models internally and externally of like understanding who our customers are but then also understanding how Block operates. Like you can imagine you can imagine for any company just like a markdown file of like who you are. And then you need the feedback loop with two things. You need the feedback loop with the signal which is like what do you what do you deeply understand that's hard for others to understand. And then you need a tool like Builder Bot or Claude Coder or what have you. And then you can just iterate through that loop over and over and again. It's like this is this is what I'm seeing, this is what's happening. Great, this is our markdown file for for Block. These are our values, this is the metrics

AI 工具怎么传导到硬件那一侧。比如你没法 vibe code 出一块 Square 的硬件。但我觉得从更长期看，如果我们持续观察——变化的速率，以及变化本身的变化——我觉得长期来看，真正能让一家公司有防御力的关键，是这家公司在多大程度上理解某种别的公司很难理解的东西。所以我们越来越多地在朝这样一个世界去建设，并且开始把 Block 本身当作一个智能系统来谈。基本上，我看到的这个走向是这样的：如果你把过去这几个月的趋势往前外推，最终一家公司是坐在某种信号之上的——某种丰富的数据、某种深刻的洞察。对我们来说，就是卖家和买家是如何参与经济活动的。我觉得大多数公司都有这么一样它们理解得很深的东西。那接下来的问题就是：你能多快地迭代，去随时间不断提升这种理解。所以我们在内部和外部都在构建「世界模型」（world models）——理解我们的客户是谁，同时也理解 Block 自己是怎么运转的。你可以想象，对任何一家公司来说，就像一个描述「你是谁」的 markdown 文件。然后你需要两样东西构成的反馈闭环。你需要跟信号之间的反馈闭环——就是你到底深刻理解了什么别人很难理解的东西。然后你需要一个工具，比如 Builder Bot 或者 Claude Coder 之类的。这样你就能在这个闭环里一遍又一遍地迭代。就是：这是我看到的，这是正在发生的。很好，这是我们 Block 的 markdown 文件，这是我们的价值观，这是我们

[26:14] Owen Jennings

we're trying to optimize for. Um this is what we care about, this is what we don't care about. And then you have agentic systems you can just build stuff. And right now you basically you've taken that humans used to do that and it used to take a couple months to build a feature. Um now it takes maybe a week or two and there's still humans involved. Pretty clear that in the future you'll be able to run that loop like I don't know, hundreds, thousands of times a day and maybe there's some humans involved, maybe not, maybe the humans are more like editors. And so I think the the biggest moat is going to be like which companies understand something that's super hard for other people to understand. And if your answer to that is is um I don't know, then uh then you maybe could get vibe coded away. This has been an amazing conversation. Thank you uh thank you so much for for joining us. Appreciate it. Thanks so much. Awesome.

正在努力优化的指标。这是我们在意的，这是我们不在意的。然后你有了 agentic 系统，就可以直接造东西了。而现在你基本上已经接管了过去由人来做的那部分——以前做一个功能要花上几个月，现在可能一两周就够了，而且其中还是有人参与的。但很清楚的是，未来你将能把这个闭环一天跑上、我说不准、几百次、几千次，也许还有人参与，也许没有，也许人更像是编辑（editor）的角色。所以我觉得最大的护城河会是——哪些公司理解了某种别人极难理解的东西。如果你对这个问题的答案是「我也不知道」，那你大概就有被 vibe code 掉的风险了。这真是一场精彩的对话。非常非常感谢你来参加。太感激了。也特别感谢你们。棒极了。