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ClickUp 用裁员押注 AI 原生组织,但“100x 组织”更像激进管理宣言而非已被证明的定律

这篇文章最有价值的判断是“AI 正在重写组织瓶颈而不只是提升个人效率”,但作者把这一点直接推演成裁员 22% 与“100x 组织”必然正确,论证明显过度,且带强烈 PR 包装。
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2026-05-22 原文链接 ↗
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核心观点

  • AI 不是平均提效,而是放大分化 作者最强的判断是,AI 不会让所有人同步变强,反而会把价值集中到少数能定义问题、编排 agent、评审结果的人身上,这一点比“人人效率提升”的陈词滥调更接近现实。
  • 组织瓶颈正在从生产转向统筹与评审 他认为代码生成、研究执行、设计迭代等环节的稀缺性下降,真正稀缺的变成架构判断、系统设计、结果验收与客户上下文,这个判断站得住,但“其他一切都不重要”的说法过头了。
  • 裁员被包装成组织重构,而非成本动作 作者坚持说这不是为了省钱,而是为了重建岗位与流程,并把节省回流给高杠杆人才;这个说法在激励逻辑上自洽,但本质上仍是用战略叙事为裁员正当化,不能因为叙事高级就忽略其残酷性。
  • “100x 工程师/PM/Agent Manager”是新组织原型 文章最可迁移的部分不是百万年薪,而是角色重组逻辑:工程师更像 agent 指挥官,PM 与设计边界收缩,自动化高手升级为系统 owner,前线客户角色反而更需要保留人味。
  • 从岗位定价转向杠杆定价是可能趋势 百万美元年薪档并非噱头本身,而是一个信号:若 AI 真把产出集中到少数高判断力节点,薪酬结构就会被重写;但“几乎每个人都有机会到这个水平”显然更像文化动员口号,而不是大概率现实。

跟我们的关联

  • 对 ATou 意味着什么 ATou 不该把 AI 先理解成“省人工具”,而该先找“谁在定义任务、谁在卡评审、谁在拖慢最好的人”;下一步可以直接盘一次团队流程,判断哪些 AI 产出在制造审查垃圾,哪些环节真的释放了核心人才带宽。
  • 对 Neta 意味着什么 Neta 如果做 agent 或 AI workflow,不该只盯生成能力,而要盯“是否减少高阶判断者的上下文负担”;下一步可以把产品指标从生成量改成评审时间、返工率、客户结果是否同步改善。
  • 对 Uota 意味着什么 Uota 可以把这篇文章当作“AI 时代组织叙事模板”来拆,而不是当结论来信;下一步适合追问每一个宏大判断背后的数据基线:哪些岗位真被替代,哪些岗位只是换了名字继续存在。
  • 对三者共同的用法 这篇文章最值得复用的是“按瓶颈而非按职能看组织”的方法;下一步可以用三问筛流程:这个岗位是在生产价值、管理系统,还是维护客户信任,AI 应自动化的是岗位本身还是围绕岗位的杂务。

讨论引子

1. 如果 AI 时代真正稀缺的是统筹与评审能力,那么企业最该裁掉的是低杠杆岗位,还是最该重训的是中层协作岗位? 2. “让最强的人带 agent”到底是在释放生产力,还是在进一步制造超级明星依赖与组织脆弱性? 3. 当公司用“AI 原生转型”解释裁员时,我们该看哪些硬指标,才能区分真重构和高级 PR?

今天,我们将员工人数缩减了 22%。与此同时,公司的业务状态比以往任何时候都更强。所以,我觉得有必要直接说明我看到了什么,以及原因是什么。

第一,这个决定是我做出的,由我负责。我之所以这么做,是因为以最高生产力水平运作的方式正在改变,而如果 ClickUp 想赢得未来,就必须随之改变。

第二,这不是为了削减成本。这次调整带来的大部分节省,都会直接回流到留下来的人身上。我们将推出百万美元年薪档。如果你借助 AI 创造了远超常规的影响力,你的薪酬将不再受传统薪酬带限制。

最重要的是,我对受影响的同事怀有最深的感激。我们是在业务强劲的情况下做这件事,正是为了能够妥善照顾大家。每一位受影响的人都会获得一份方案,既是对他们贡献的尊重,也能帮助他们顺利过渡。

在我看来,只有两个选择。要么等着这件事在市场中慢慢发生,要么坦诚面对我所看到的变化,主动采取行动。

THE 100X ORGANIZATION 最主要的变化,是我们正在围绕我所说的 100x 组织进行重组。目标是实现 100 倍产出。要以最高水平完成建设,如今所需要的岗位,本质上已经和一年前不同了。

对现有系统做渐进式改良,无法带我们到达那里。我们需要新的系统。这意味着必须制造足够大的扰动,用重建取代在已经坏掉的东西上继续修补。

一种常见说法是,AI 会让每个人都更高效。事实并非如此。今天的许多工作流,如果不改变,反而会在 AI 系统中制造瓶颈。

这些岗位会演变。但如果等它自然发生,就意味着现在就会落后。

100x 组织其实高度依赖人,依赖程度比今天高得多,几乎无法相比。只有那些已经接受并采用新工作方式的 10x 人才,才能让这一切成为可能。

THE BUILDERS, AGENT MANAGERS, AND FRONT-LINERS

— THE BUILDERS: 10X ENGINEERS 我认为,大多数公司都还没有真正理解 AI 在工程领域到底带来了什么变化。常见叙事是,AI 会让所有工程师都更高效。单独看某个人,也许是这样。但从组织层面看,现实恰恰完全不是这么回事。

这是 ClickUp 最近验证出来的结果。那些真正优秀的工程师,也就是能够统筹、架构和评审的人,正在变成 100x 工程师。他们不再亲自写代码,而是在指挥会写代码的 agent。真正重要的能力,是判断力。

AI 会让最优秀的工程师效率暴涨,而其他人使用 AI,反而会拖慢这些工程师。 想一想就明白了。瓶颈在于两件事,第一是统筹,也就是告诉 AI 该做什么,第二是评审,也就是检查 AI 做了什么。其他一切都被跨过去了,不再重要。 所以,你希望由谁来统筹和评审代码?

你又希望公司里最好的工程师,把时间花在哪里?

如果你最好的工程师把时间花在审查别人的代码上,这本身就是一种低效的瓶颈。与审查人写的代码相比,他们审查自己 agent 写出来的代码会快得多。

新世界的关键,是让你的 10x 工程师进化成 100x。

错误的策略,是推动每个工程师都去无限制地使用 token。采用这种做法的公司,会为 pull request 增长 500% 而欢呼。但客户获得的结果,并不会随着代码产量一起增长。

我把这叫作 AI 编程的大清算。每家公司很快都会面对这个问题,如果现在还没遇到的话。

更多代码,只会成为最优秀工程师的另一个瓶颈,最终也会成为公司影响力的瓶颈。

— THE BUILDERS: 10X PRODUCT MANAGERS 产品管理和设计岗位正在合并。

那些真正关注客户的设计师,会越来越像产品经理。

而那些对 UX 有直觉的产品经理,也会越来越像设计师。

用户研究这个瓶颈已经消失了。现在只需要提一句 agent,我们就能立刻启动研究并分析结果。

产品和设计之间反复迭代的瓶颈也消失了。产品建设者会自己完成迭代,同时借助 agent 和技能,确保结果与质量和战略保持一致。

还有一个今天听上去会有争议的观点。我认为,让 PM 去交付生产代码,是错误策略,因为这只会再引入一个瓶颈,浪费最优秀工程师的时间。

说清楚一点,PM 应该会写代码,但应该是在试验场里写,用来迭代、验证和界定范围。这些代码不应该进入生产环境。

除了管理系统、统筹 AI、评审输出之外,其他事情都会变成瓶颈。 这也是为什么,除了这些岗位之外,另外几个关键角色是系统管理者,他们负责减少瓶颈;以及一个你无法替代的瓶颈,那就是与客户见面的时间。

— THE SYSTEM MANAGERS 有点讽刺的是,那些用 AI 自动化自己工作的人,反而永远都会有工作。他们会成为 AI 系统的拥有者,也就是 agent 管理者。ClickUp 里已经有很多这样的人。

我们所依赖的底层系统,必须做对,这一点至关重要。我觉得,大多数公司如果以为可以在现有系统上继续迭代,然后在这个新世界里竞争,那就是在自欺欺人。

你必须制造足够大的扰动,让旧系统被彻底淘汰。如果 AI native 这个词还有定义,那它就是这个意思。

— THE FRONT-LINERS 在一个会被 AI 沟通淹没的世界里,对客户来说,最重要的会是人的触感。

这是一个不该被替代的瓶颈,即使有一天 agent 的质量已经高到足以参加视频会议。

和客户一对一交流的时间,不应该被自动化。应该被自动化的,是围绕会议的各种系统。这样一来,前线人员几乎 100% 的时间都能花在客户身上。

REWARDING 100X IMPACT 当公司能够用更少的人做更多的事,多出来的钱会流向哪里? 至少在我们这里,这种新运营模式带来的很大一部分节省,会直接回流给那些促成这一切的人。

创造生产力的人,必须得到与之相匹配的回报。这样双方的激励才是一致的。更何况,在一个顶尖人才能创造 100 倍影响力的世界里,你根本承受不起失去他们的代价。

你的目标,应该是把这些员工留住几十年。他们所掌握的背景信息,以及他们高效统筹和评审的能力,几乎不可能被替代。

今天的薪酬带应该被彻底丢掉。我们将推出每年 100 万美元现金年薪档,而且公司里几乎每个人都有机会达到这个水平,只要他们通过创建或管理 AI 系统,真正做出了 100 倍影响力。

THE FUTURE 几乎每一家公司都会做出类似的改变。那些主动去做的公司,会定义接下来会发生什么。

未来不是更少的人,而是不同的工作、新的岗位,以及给那些拥抱变化的人更好的回报。我们已经看到全新的岗位开始出现,比如一年前还根本不存在的 Agent Managers。

ClickUp 正在为领导这场转变做准备,不只是对内,也包括对客户。我从未像现在这样笃定,我们正朝着正确的方向前进。

Today we reduced headcount by 22%. The business is the strongest it's ever been. So I think it's important to be direct about what I'm seeing and why.

今天,我们将员工人数缩减了 22%。与此同时,公司的业务状态比以往任何时候都更强。所以,我觉得有必要直接说明我看到了什么,以及原因是什么。

First, I made this decision and I own it. I did it because the way to operate at the highest level of productivity is changing, and to win the future, ClickUp needs to change with it.

第一,这个决定是我做出的,由我负责。我之所以这么做,是因为以最高生产力水平运作的方式正在改变,而如果 ClickUp 想赢得未来,就必须随之改变。

Second, this wasn't about cutting costs. Most savings from this change will flow directly back into the people who stay. We'll be introducing million-dollar salary bands. If you create outsized impact using AI, you'll be paid outside of traditional bands.

第二,这不是为了削减成本。这次调整带来的大部分节省,都会直接回流到留下来的人身上。我们将推出百万美元年薪档。如果你借助 AI 创造了远超常规的影响力,你的薪酬将不再受传统薪酬带限制。

Most importantly, I have the deepest gratitude for those affected. We're doing this from a position of strength specifically so we can take care of people properly. Everyone affected receives a package aimed at honoring their contributions and easing the transition.

最重要的是,我对受影响的同事怀有最深的感激。我们是在业务强劲的情况下做这件事,正是为了能够妥善照顾大家。每一位受影响的人都会获得一份方案,既是对他们贡献的尊重,也能帮助他们顺利过渡。

I only see two options: wait for this to play out gradually in the market or be honest about what I'm seeing and act proactively.

在我看来,只有两个选择。要么等着这件事在市场中慢慢发生,要么坦诚面对我所看到的变化,主动采取行动。

THE 100X ORGANIZATION The primary change is that we're restructuring around what I call 100x org. The goal is 100x output. The roles required to build at the highest level are fundamentally different than they were a year ago.

THE 100X ORGANIZATION 最主要的变化,是我们正在围绕我所说的 100x 组织进行重组。目标是实现 100 倍产出。要以最高水平完成建设,如今所需要的岗位,本质上已经和一年前不同了。

Incremental improvements to existing systems won't get us there. We need new ones. That means creating enough disruption to rebuild rather than iterate on what's already broken.

对现有系统做渐进式改良,无法带我们到达那里。我们需要新的系统。这意味着必须制造足够大的扰动,用重建取代在已经坏掉的东西上继续修补。

The common narrative is that AI makes everyone more productive. It doesn't. Many of the workflows of today, if left unchanged, create bottlenecks in AI systems.

一种常见说法是,AI 会让每个人都更高效。事实并非如此。今天的许多工作流,如果不改变,反而会在 AI 系统中制造瓶颈。

These roles will evolve. But waiting for that to happen naturally means falling behind now.

这些岗位会演变。但如果等它自然发生,就意味着现在就会落后。

The 100x org is actually heavily dependent on people - infinitely more than today. This is only possible with 10x people that have embraced and adopted new ways of working.

100x 组织其实高度依赖人,依赖程度比今天高得多,几乎无法相比。只有那些已经接受并采用新工作方式的 10x 人才,才能让这一切成为可能。

THE BUILDERS, AGENT MANAGERS, AND FRONT-LINERS

THE BUILDERS, AGENT MANAGERS, AND FRONT-LINERS

— THE BUILDERS: 10X ENGINEERS I don't think most companies have internalized what's actually happening with AI in engineering. The common narrative is that AI makes all engineers more productive. That may be true in isolation, but at an organization level - that is the farthest thing from reality.

— THE BUILDERS: 10X ENGINEERS 我认为,大多数公司都还没有真正理解 AI 在工程领域到底带来了什么变化。常见叙事是,AI 会让所有工程师都更高效。单独看某个人,也许是这样。但从组织层面看,现实恰恰完全不是这么回事。

Here's what we've validated recently at ClickUp: the great engineers, the ones who can orchestrate, architect, and review, are becoming 100x engineers. They're not writing code. They're directing agents that write code. The skill is judgment.

这是 ClickUp 最近验证出来的结果。那些真正优秀的工程师,也就是能够统筹、架构和评审的人,正在变成 100x 工程师。他们不再亲自写代码,而是在指挥会写代码的 agent。真正重要的能力,是判断力。

AI makes the best engineers wildly more productive, and everyone else using AI slows these engineers down. Think about it - the bottlenecks are (1) orchestration - telling AI what to do, and (2) reviewing - what AI did. Everything is leapfrogged and no longer needed. So who do you want orchestrating and reviewing code?

AI 会让最优秀的工程师效率暴涨,而其他人使用 AI,反而会拖慢这些工程师。 想一想就明白了。瓶颈在于两件事,第一是统筹,也就是告诉 AI 该做什么,第二是评审,也就是检查 AI 做了什么。其他一切都被跨过去了,不再重要。 所以,你希望由谁来统筹和评审代码?

And how do you want your best engineers to spend their time?

你又希望公司里最好的工程师,把时间花在哪里?

If your best engineers are spending time reviewing other people's code, then this is inherently an inefficient bottleneck. These engineers can review their agent's code much faster than reviewing human code.

如果你最好的工程师把时间花在审查别人的代码上,这本身就是一种低效的瓶颈。与审查人写的代码相比,他们审查自己 agent 写出来的代码会快得多。

The new world is about enabling your 10x engineers to become 100x.

新世界的关键,是让你的 10x 工程师进化成 100x。

The wrong strategy is to push every engineer to use infinite tokens. Companies doing this are celebrating 500% more pull requests. But customer outcomes don't match the volume of code being generated.

错误的策略,是推动每个工程师都去无限制地使用 token。采用这种做法的公司,会为 pull request 增长 500% 而欢呼。但客户获得的结果,并不会随着代码产量一起增长。

I call this the great reckoning of AI coding, and every company will face this soon if not already.

我把这叫作 AI 编程的大清算。每家公司很快都会面对这个问题,如果现在还没遇到的话。

More code is just another bottleneck to the best engineers, and ultimately to your company's impact as well.

更多代码,只会成为最优秀工程师的另一个瓶颈,最终也会成为公司影响力的瓶颈。

— THE BUILDERS: 10X PRODUCT MANAGERS Product management and design roles are merging.

— THE BUILDERS: 10X PRODUCT MANAGERS 产品管理和设计岗位正在合并。

Designers that have customer focus, become more like product managers.

那些真正关注客户的设计师,会越来越像产品经理。

And product managers that have intuition for UX become more like designers.

而那些对 UX 有直觉的产品经理,也会越来越像设计师。

The bottleneck of user research is gone. It takes us just one mention of an agent to kickoff research and analyze results.

用户研究这个瓶颈已经消失了。现在只需要提一句 agent,我们就能立刻启动研究并分析结果。

The bottleneck of product <> design iteration is also gone. The product builder iterates on their own, along with agents and skills that ensure alignment with quality and strategy.

产品和设计之间反复迭代的瓶颈也消失了。产品建设者会自己完成迭代,同时借助 agent 和技能,确保结果与质量和战略保持一致。

Also controversial today - I believe that the wrong strategy is to have your PMs shipping code - that just introduces another bottleneck that the best engineers will waste their time on.

还有一个今天听上去会有争议的观点。我认为,让 PM 去交付生产代码,是错误策略,因为这只会再引入一个瓶颈,浪费最优秀工程师的时间。

To be clear, PMs should be coding but they should do this in a playground to iterate, validate, and scope. That code should not go to production.

说清楚一点,PM 应该会写代码,但应该是在试验场里写,用来迭代、验证和界定范围。这些代码不应该进入生产环境。

Everything outside of managing systems, orchestrating AI, and reviewing output becomes a bottleneck. That's why the other roles that are critical along with these are the systems managers (to reduce bottlenecks) along with a bottleneck you can't replace - customer meeting time.

除了管理系统、统筹 AI、评审输出之外,其他事情都会变成瓶颈。 这也是为什么,除了这些岗位之外,另外几个关键角色是系统管理者,他们负责减少瓶颈;以及一个你无法替代的瓶颈,那就是与客户见面的时间。

— THE SYSTEM MANAGERS Ironically, the people that automate their jobs with AI will always have a job. They become owners of the AI systems - agent managers. We have many examples of these people at ClickUp.

— THE SYSTEM MANAGERS 有点讽刺的是,那些用 AI 自动化自己工作的人,反而永远都会有工作。他们会成为 AI 系统的拥有者,也就是 agent 管理者。ClickUp 里已经有很多这样的人。

The underlying systems in which we operate are absolutely critical to get right. I think most companies are delusional to think they can iterate on existing systems and compete in this new world.

我们所依赖的底层系统,必须做对,这一点至关重要。我觉得,大多数公司如果以为可以在现有系统上继续迭代,然后在这个新世界里竞争,那就是在自欺欺人。

You must create enough disruption so that old systems are deprecated entirely. If there's any definition for 'AI native' that's what it is.

你必须制造足够大的扰动,让旧系统被彻底淘汰。如果 AI native 这个词还有定义,那它就是这个意思。

— THE FRONT-LINERS In a world that will become saturated with AI communication, the human touch will matter more than anything to customers.

— THE FRONT-LINERS 在一个会被 AI 沟通淹没的世界里,对客户来说,最重要的会是人的触感。

This is a bottleneck that you shouldn't replace - even when agents are high enough quality to do video meetings.

这是一个不该被替代的瓶颈,即使有一天 agent 的质量已经高到足以参加视频会议。

One-on-one meeting time with customers is something that shouldn't be automated. The systems around the meetings should be - so that front-liners spend nearly 100% of their time with customers.

和客户一对一交流的时间,不应该被自动化。应该被自动化的,是围绕会议的各种系统。这样一来,前线人员几乎 100% 的时间都能花在客户身上。

REWARDING 100X IMPACT In a world where companies are able to do so much more with less, where does that excess money go? In our case, much of the savings in this new operating model will flow directly back to those that enabled it.

REWARDING 100X IMPACT 当公司能够用更少的人做更多的事,多出来的钱会流向哪里? 至少在我们这里,这种新运营模式带来的很大一部分节省,会直接回流给那些促成这一切的人。

We must reward people that create productivity accordingly. This aligns incentives on both sides. Plus, in a world where your best people create 100x impact, you can't afford to lose them.

创造生产力的人,必须得到与之相匹配的回报。这样双方的激励才是一致的。更何况,在一个顶尖人才能创造 100 倍影响力的世界里,你根本承受不起失去他们的代价。

You should aim to retain these employees for decades. The context they have and their ability to efficiently orchestrate and review will be nearly impossible to replace.

你的目标,应该是把这些员工留住几十年。他们所掌握的背景信息,以及他们高效统筹和评审的能力,几乎不可能被替代。

Compensation bands of today should be thrown out the door. We're introducing $1 million cash/year salary bands with a path available to nearly everyone in the company if they produce 100x impact by creating or managing AI systems.

今天的薪酬带应该被彻底丢掉。我们将推出每年 100 万美元现金年薪档,而且公司里几乎每个人都有机会达到这个水平,只要他们通过创建或管理 AI 系统,真正做出了 100 倍影响力。

THE FUTURE Nearly every company will make changes like these. The ones that do it proactively will define what comes next.

THE FUTURE 几乎每一家公司都会做出类似的改变。那些主动去做的公司,会定义接下来会发生什么。

The future is not fewer people. It's different work, new roles, and better rewards for those who embrace it. We're already seeing entirely new roles emerge, like Agent Managers, that didn't exist a year ago.

未来不是更少的人,而是不同的工作、新的岗位,以及给那些拥抱变化的人更好的回报。我们已经看到全新的岗位开始出现,比如一年前还根本不存在的 Agent Managers。

ClickUp is positioning to lead this shift, not just internally, but for our customers too. I've never been more certain about where we're headed.

ClickUp 正在为领导这场转变做准备,不只是对内,也包括对客户。我从未像现在这样笃定,我们正朝着正确的方向前进。

Today we reduced headcount by 22%. The business is the strongest it's ever been. So I think it's important to be direct about what I'm seeing and why.

First, I made this decision and I own it. I did it because the way to operate at the highest level of productivity is changing, and to win the future, ClickUp needs to change with it.

Second, this wasn't about cutting costs. Most savings from this change will flow directly back into the people who stay. We'll be introducing million-dollar salary bands. If you create outsized impact using AI, you'll be paid outside of traditional bands.

Most importantly, I have the deepest gratitude for those affected. We're doing this from a position of strength specifically so we can take care of people properly. Everyone affected receives a package aimed at honoring their contributions and easing the transition.

I only see two options: wait for this to play out gradually in the market or be honest about what I'm seeing and act proactively.

THE 100X ORGANIZATION The primary change is that we're restructuring around what I call 100x org. The goal is 100x output. The roles required to build at the highest level are fundamentally different than they were a year ago.

Incremental improvements to existing systems won't get us there. We need new ones. That means creating enough disruption to rebuild rather than iterate on what's already broken.

The common narrative is that AI makes everyone more productive. It doesn't. Many of the workflows of today, if left unchanged, create bottlenecks in AI systems.

These roles will evolve. But waiting for that to happen naturally means falling behind now.

The 100x org is actually heavily dependent on people - infinitely more than today. This is only possible with 10x people that have embraced and adopted new ways of working.

THE BUILDERS, AGENT MANAGERS, AND FRONT-LINERS

— THE BUILDERS: 10X ENGINEERS I don't think most companies have internalized what's actually happening with AI in engineering. The common narrative is that AI makes all engineers more productive. That may be true in isolation, but at an organization level - that is the farthest thing from reality.

Here's what we've validated recently at ClickUp: the great engineers, the ones who can orchestrate, architect, and review, are becoming 100x engineers. They're not writing code. They're directing agents that write code. The skill is judgment.

AI makes the best engineers wildly more productive, and everyone else using AI slows these engineers down. Think about it - the bottlenecks are (1) orchestration - telling AI what to do, and (2) reviewing - what AI did. Everything is leapfrogged and no longer needed. So who do you want orchestrating and reviewing code?

And how do you want your best engineers to spend their time?

If your best engineers are spending time reviewing other people's code, then this is inherently an inefficient bottleneck. These engineers can review their agent's code much faster than reviewing human code.

The new world is about enabling your 10x engineers to become 100x.

The wrong strategy is to push every engineer to use infinite tokens. Companies doing this are celebrating 500% more pull requests. But customer outcomes don't match the volume of code being generated.

I call this the great reckoning of AI coding, and every company will face this soon if not already.

More code is just another bottleneck to the best engineers, and ultimately to your company's impact as well.

— THE BUILDERS: 10X PRODUCT MANAGERS Product management and design roles are merging.

Designers that have customer focus, become more like product managers.

And product managers that have intuition for UX become more like designers.

The bottleneck of user research is gone. It takes us just one mention of an agent to kickoff research and analyze results.

The bottleneck of product <> design iteration is also gone. The product builder iterates on their own, along with agents and skills that ensure alignment with quality and strategy.

Also controversial today - I believe that the wrong strategy is to have your PMs shipping code - that just introduces another bottleneck that the best engineers will waste their time on.

To be clear, PMs should be coding but they should do this in a playground to iterate, validate, and scope. That code should not go to production.

Everything outside of managing systems, orchestrating AI, and reviewing output becomes a bottleneck. That's why the other roles that are critical along with these are the systems managers (to reduce bottlenecks) along with a bottleneck you can't replace - customer meeting time.

— THE SYSTEM MANAGERS Ironically, the people that automate their jobs with AI will always have a job. They become owners of the AI systems - agent managers. We have many examples of these people at ClickUp.

The underlying systems in which we operate are absolutely critical to get right. I think most companies are delusional to think they can iterate on existing systems and compete in this new world.

You must create enough disruption so that old systems are deprecated entirely. If there's any definition for 'AI native' that's what it is.

— THE FRONT-LINERS In a world that will become saturated with AI communication, the human touch will matter more than anything to customers.

This is a bottleneck that you shouldn't replace - even when agents are high enough quality to do video meetings.

One-on-one meeting time with customers is something that shouldn't be automated. The systems around the meetings should be - so that front-liners spend nearly 100% of their time with customers.

REWARDING 100X IMPACT In a world where companies are able to do so much more with less, where does that excess money go? In our case, much of the savings in this new operating model will flow directly back to those that enabled it.

We must reward people that create productivity accordingly. This aligns incentives on both sides. Plus, in a world where your best people create 100x impact, you can't afford to lose them.

You should aim to retain these employees for decades. The context they have and their ability to efficiently orchestrate and review will be nearly impossible to replace.

Compensation bands of today should be thrown out the door. We're introducing $1 million cash/year salary bands with a path available to nearly everyone in the company if they produce 100x impact by creating or managing AI systems.

THE FUTURE Nearly every company will make changes like these. The ones that do it proactively will define what comes next.

The future is not fewer people. It's different work, new roles, and better rewards for those who embrace it. We're already seeing entirely new roles emerge, like Agent Managers, that didn't exist a year ago.

ClickUp is positioning to lead this shift, not just internally, but for our customers too. I've never been more certain about where we're headed.

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