AI Rollout Resistance: 3 Things Leaders Owe Engineers

你们公司的AI工程师可能很讨厌你们在做AI。

Your AI engineers probably hate that you're doing AI.

我这么说，并不是因为我对你们公司有什么内部消息。

And I say that not because I have some secret insight into your company.

我这么说是因为，当我和人们交流时，不管是领导还是普通员工，我在任何超过50人的团队里听到的一致反馈是，你们公司确实有一群人完全不支持AI，对你们做AI感到不满，甚至积极抵制。

I say that because when I talk to people, right, whether they're leaders, whether they're individual contributors, what I hear really consistently in any team over say 50, is that you really do have a collection of folks in your business that are not fans of AI at all, and not happy that you're doing AI, actively resistant.

事实上，有一项针对全球公司的调查显示，全球有三分之一的员工承认在破坏AI项目。

In fact, there's a survey that came out of global companies that showed that a third of employees globally admit to sabotaging AI.

所以这确实是个很现实的问题。

So this is a very real issue.

今天我想谈谈我在推广AI时是如何处理这个问题的。

I wanna talk today about how I address that concern in AI rollout.

接下来我会告诉你这个视频里会讲些什么。

And so I'm gonna lay out for you what you get in this video.

第一，我们会和领导们一起讨论。

Number one, we're gonna talk with leaders together.

即使你不是领导，你也应该参与这个对话。

Even if you're not a leader, you wanna be in on this conversation.

这就是我实际告诉别人的——你会怎么说？

This is what I actually tell What what do you say?

你如何开始推行这个变革？

How do you start to roll out this change?

你需要做出什么承诺？

What is the commitment you need to make?

第二，我们会讨论如何界定范围，并实际设定一个……

Number two, we are gonna talk about how you scope and actually set an...

……一个启动AI变革的参数，以及这意味着什么和具体细节。

A a parameter for starting your change in AI, and what that means and the details.

所以人们总是问我，AI应该从哪里开始？

And so people ask me all the time, where do you start on AI?

这就是你的答案。

That is your answer.

你马上就会知道了。

You're gonna find out.

为什么？

And why?

为什么这会影响我们整个团队？

And why that affects our whole team?

为什么这会影响每一个正在听的人，当他们经历AI转型的时候？

Why that affects everyone here who's listening when they go through AI transformation?

第三点，我们要确保讨论一些非常棘手的细节，从它只是一个可爱的小试点，到它实际上必须扩展。

And number three, we are gonna make sure that we talk through some of the really messy details when you go from it's a cute little pilot to this actually has to scale.

这对人们意味着什么？

What does that mean for people?

这对我们的系统意味着什么？

What does that mean for our systems?

我们如何让这些更有效地协同工作？

How do we have those work together more productively?

而且我要给你们讲那个……

And I'm gonna give you the the...

就是，那个秘诀，从头到尾。

Like, the secret sauce all the way across.

我要告诉你们我实际听到的，从人们那里，从领导者那里，我看到的那些陷阱是怎么发生的，以及我如何绕开它们。

I'm gonna tell you what I actually am hearing from people, what I'm hearing from leaders, how I'm seeing the the pitfalls happen, and what I do to go around them.

所以希望你们喜欢这一期。

So I hope you have fun with this one.

可以把它看作是我和领导者们讨论这个复杂问题时的幕后花絮，我想让所有人都听到，所以在这里分享。

Think of it as like a sneak peek behind how I talk with leaders about this complicated issue, and I wanted everyone to hear it, so I'm sharing it here.

我们先从第一点开始，那就是你实际上需要和你的团队达成的那个契约，如果你想让他们和你一起走这条路的话。

And we're gonna start with number one, which is the contract that you have to effectively sign up for with your teams if you want them to come along for the ride with you.

我说契约，不是因为它一定有法律约束力，但它确实是一个承诺。

And I say contract not because it's necessarily legally binding, but it is it is a commitment.

这是一个你作为领导者必须公开做出的承诺，如果你正在经历AI转型的过程，而我要告诉你，这个世界上的组织要么已经是AI原生的，要么正在努力成为AI原生。

It is a commitment that you will need to make publicly as a leader if you are going through the process of AI transformation, which, let me tell you, the world consists of people who are either AI native in their organizations or people who are trying to be AI native.

我见过的所有行业里，几乎没有一个角落不在这条光谱上的。

There really isn't a corner of the workforce anywhere that I have seen that isn't at least somewhere on that spectrum.

你可能还在起步阶段，但你已经在关注AI了。

You may be early in your journey, but you're still looking at AI.

有些完全不在科技圈的人跟我聊，他们会说，哦，你知道吗？

There are folks way outside tech who I talk to who are like, oh, you know what?

我最近用编码器重建了工厂里的一个工具。

I used codecs to to rebuild a tool in my factory recently.

就是，这事儿已经在发生了。

Like, it's just happening.

所以在这个世界里，我们真正需要的是领导层做出一个能坚持的承诺，这个承诺要体现出他们对整个团队福祉的重视。

And so in that world, what we really need is a commitment from leadership that they can stick to that reflects their commitment to the well-being of the team as a whole.

因为如果你被要求参与AI的推广，而你看着这个推广，心里想，我觉得这好像是针对我的。

Because if you are asked to participate in an AI rollout and you look at that AI rollout and you're like, I feel like this is targeted at me.

我觉得这好像是要抢我的饭碗。

I feel like this is coming for my job.

我觉得他们就是想裁员。

I feel like all they wanna do is cut head count.

我鼓励领导者们在面对这种情况时，直接点破这个大家心知肚明的问题。

I encourage leaders when they are facing that situation to just very simply address the elephant in the room.

我觉得很多时候，如果我们不把这个问题摆到台面上，大家就没法继续前进。

I think so much of the time, if we aren't addressing the elephant in the room, people just aren't able to move forward.

所以我就说，听好了。

And so I say, look.

你可以非常坦诚。

You can be really honest.

很多关于AI的报道，尤其是新闻媒体上的，都在讲AI和工作的关系。

A lot of AI coverage, especially in news media, is around AI and jobs.

目前在美国，这个AI应用走得最远的地方，全国范围内还没有确凿的证据表明AI对就业有影响。

Now there is no consistent evidence still at a national scale in United States, which is the most farthest along in its AI adoption journey, that we have any impact on jobs.

但这不重要。

It doesn't matter.

因为如果，你知道，杰克·多尔西说他裁掉几千人是因为想专注AI，那大家听到这个消息。

Because if, you know, Jack Dorsey says he's cutting thousands of people because he wants to focus on AI, well, people hear that message.

大家听到，是的。

People hear, yeah.

好。

Okay.

也许在全国的总体统计数据里，这不算什么。

Maybe in the national aggregate statistics, it doesn't matter.

但对我来说，这很重要。

But for me, it matters.

对我能不能养家糊口，这很重要。

For my ability to put food on the table, it matters.

他们需要你作为领导者明确表态，说我们在这里做的事情不是为了裁掉公司里的员工。

And they need you as a leader to be clear and say, what we are doing here is not designed to destroy jobs in this company.

这不是为了夺走你的职位。

It is not designed to take away your role.

我见过一些领导者以体现诚信的方式做到这一点。

Now I have seen leaders do that in a way that reflects integrity.

我见过他们这样说：我们希望保持公司小而精，所以目前的计划是放慢增长的速度。

I've seen them do it by saying, we wanna keep our company small and lean, and so our plan right now is to reduce the pace at which we grow.

或者我们目前的计划是不再大量招聘，因为我们有AI。

Or our plan right now is not to hire a lot more because we have AI.

所以，你仍然可以谈论人员规模的影响，而不必提及裁减现有员工。

So there are ways that you can still talk about head count effects without talking about cutting people who are currently there.

如果你对AI充满热情，能够实际运用AI创造价值，那么你在这里的职业生涯会走得更远。

When you are an enthusiastic proponent of AI, when you're able to use AI practically to deliver value, you're going to go farther in your career here.

相反，如果你抗拒，甚至，天哪，你在破坏AI，那么这些事情会危及你在这里的职业生涯。

And if you are conversely resistant, if, you know, god forbid, you're you're you're sabotaging AI, those are gonna be things that are gonna jeopardize your career here.

如果你没有承诺保护现有员工，你就没有起点。

And if you don't have a commitment to protect the people you have, you just don't have anywhere to start from.

如果你想要有机会真正参与整个业务，你必须能够和他们谈论你为这次推广设定的目标。

And if you want to have a chance to actually engage with the whole business, you have to be able to talk to them about the the goals you have for this rollout.

你为什么要这么做？

Why are you doing this?

而且我觉得，用黄仁勋的话来说，比什么都更有说服力，因为黄仁勋非常公开地谈过，他期望工程师们能大幅提升生产力，但他不会裁掉任何一个。

And I find it is so much more compelling to use Jensen Huang's messaging than just about anything else because Jensen has talked very openly about the idea that he expects tremendous productivity gains from his engineers, but he's not letting go of any of them.

他还公开对那些裁员的领导者说，他们只是缺乏想象力，不知道在AI时代如何用好自己的团队。

And he's told leaders publicly who are letting go of their employees that they just don't have the imagination to use their teams in the age of AI.

他们没有远见，没有胆量去为公司寻找和开拓新的事业。

They don't have the vision, the boldness to go out there and find new stuff for the company to get into and do.

我觉得这种说法真的很有共鸣。

That's the kind of thing that I find really resonates.

就是说，你看。

Is if you say, look.

作为领导者，我的职责就是为公司制定更大的愿景，明确我们要追求的目标。

It's my job as a leader to come up with the larger vision for the company and what we're going after.

我把AI看作一个巨大的生产力提升工具。

I see AI as a tremendous productivity enhancer.

到了那个时候，你就抓住了他们的注意力。

And then at that point, you have you have their attention.

你也就赢得了信任，因为你是在说，这不是要拿走什么。

You have trust because you are then saying, this is not about taking something away.

而是要拓展我们的视野。

This is about expanding our horizons.

所以这是第一条原则。

So that's principle number one.

第二条原则我觉得非常关键，因为AI是涉及整个组织的转型方法。

Principle number two that I find that's really, really critical because AI is a whole org transformation approach.

就是说，它们……

Like, they're they're...

总有一天，它会影响到工具。

At some point, it's gonna come for the tools.

它会影响到你的工作方式。

It's gonna come for the way you work.

它会影响到一切。

It's gonna come for everything.

所以如果你一开始就说，它会影响到一切。

And so if you just start by saying, it's gonna come for everything.

我们要全面推行AI。

We're gonna do AI as a whole.

每个人都开始用AI。

Everyone start doing AI.

第一，大家不太相信。

One, people kinda don't believe it.

第二，大家不太明白这对他们的日常工作意味着什么。

And two, people don't really understand what that means for their day to day.

所以你必须从说，我们在这里选择一个具体的角度来开始AI转型。

And so you have to start by saying, we are picking a specific angle to get started on AI transformation here.

而不是泛泛而谈。

Not just the generic.

我们要选一个具体的切入点。

We're picking a specific place.

我告诉别人怎么选具体切入点的方法很简单。

And the way I tell people to pick a specific place is very simple.

我说，你得选一个真正能影响你利润的东西。

I said, you need to pick something that actually drives your bottom line.

可能是增加收入。

It may expand revenue.

也可能是降低工具成本。

It may cut your tooling costs.

我不知道。

I don't know.

但你必须找到对你的利润有显著影响的事情，这样你才有动力去做。

But you need to find something that has a meaningful impact on your bottom line so you are motivated to pursue it.

它得跟AI已经表现出色的领域挂钩。

It needs to be tied to things that AI has already demonstrated to do well.

如果你……

If you...

如果你要做这件事，别选一个AI还没解决的新问题作为你的第一个切入点。

If you're doing this, don't pick a new unsolved problem in AI as your first place to get started.

我们需要让他们更高效。

We need to enable them to be more effective.

所以，你知道，对于常规的电话，我们正在转向AI代理。

And so for, you know, x routine calls, we're moving to AI agents.

对于更复杂的电话，那就是我们人类AI代理的用武之地。

For more complex calls, that's what our AI agent humans are for.

或者他们说，我们想保持人情味。

Or they say we wanna maintain the human touch.

我们希望人与人对话，但AI会在后台工作，查看CRM、客户记录、我们所有的政策，这样每一通电话都能打得很好。

We want humans to talk to humans, but AI is gonna be working in the background to go through the CRM, to go through the customer records, to go through everything about our policies so that every call is a fantastic call.

当你坐下来，找到那个影响领域，而且不一定非得是客服。

And when you sit down and you figure out that area of impact, and it doesn't have to be customer service.

有一些最初的项目是在工程领域，因为他们觉得自己有技术能力，能够实施这些项目。

There are some initial ones that are in engineering because they feel like they have technical skills and all of that to implement.

你得选一个项目，并且公开谈论它。

You gotta pick that and to talk about it publicly.

即使只是针对那一个团队，你也是在向整个公司表明，我们正在一起开始这段旅程。

Even if it's just for that one team, you're saying to the whole company, we are starting this journey together.

这是我们开始的地方，以及为什么。

This is where we're starting and why.

所以也许我们从客户服务开始。

So maybe we're starting in customer service.

也许我们从工程项目开始，因为我们想学习AI原生的做事方式。

Maybe we're starting with an engineering project because we wanna learn AI native ways of working.

这是两种常见的开始方式。

Those are two common ways of of starting.

但无论哪种方式，你都要明确范围。

But either way, you talk about the scope.

公开说明成功是什么样子的。

Talk publicly about what success looks like.

成功不应该只是大家用了某个工具。

Success should not just be people use a tool.

成功应该是我们的工作方式发生变化，从而改善客户体验，能够为业务创造更多价值，这些应该是实实在在、有意义的，而不只是活动形式变了。

Success should be something about the way we work changes so that our customer experience gets better, so that we are able to deliver more value to the business, something that's going to be tangible and meaningful beyond just the activity changing.

这一点真的非常重要。

That's really, really important.

因为我们的经验是，如果只谈活动形式的变化，就会陷入优步今年早些时候公开遇到的困境——优步说，你们知道吗？

Because what we find is that if you just talk about the activity changing, you get into the position Uber got into very publicly earlier this year where Uber said, you know what?

我们真的很后悔在令牌上花了那么多钱，因为那些令牌只是被疯狂地鼓励使用。

We are really regretting the amount of money we are spending on our tokens because they've just been encouraging usage like crazy.

这也会给团队成员传递一个非常矛盾的信息，对吧？

And that sends a very contradictory message to team members as well, doesn't it?

因为如果你被告知——而且你本来还有点怀疑——用AI、用AI、用AI，最后你终于用了AI，然后你又被告知，别用AI了，因为我们有令牌预算。

Because if you've been told, and you're somewhat skeptical, use AI, use AI, use AI, and you finally use AI, and then you get told, well, don't use AI because we have a token budget.

现在就更让人困惑了，你会觉得领导根本不知道自己在干什么。

Now it's extra confusing, and you just feel like leadership doesn't know what they're doing.

你得选好重点。

You gotta pick where you focus.

你得确定好参与的性质和范围。

You gotta pick and scope the nature of the engagement.

确保它有意义。

Make sure it's meaningful.

公开向整个公司宣传。

Talk about it publicly to the whole business.

确保做好准备。

Make sure you prepare for it.

这算是为它做预算。

That's that's sort of budgeting for it.

确保有合适的人才来落实。

Make sure you got the talent on the ground for it.

关于人才这块，我想特别提醒你一点。

And the talent, I wanna give you a a special note on that one.

你得在公司里找一个对AI充满热情的管理层或中层领导，他们得能对这件事感到兴奋。

You need to pick a spot in the company where you have a passionate supporter of AI in a management or middle middle leadership role, and they need to be able to get excited about this.

如果他们不兴奋，如果你的团队领导对你要推行的AI部署不感兴趣，那总监、副总裁、所有高层都没用。

If they're not excited, if if your team level leaders are not excited about the AI rollout that you're doing, the director, VP, all the senior folks is not gonna matter.

他们可以在会议上随便说，但如果团队领导层不热情，什么都做不成。

Like, they can talk all they want in meetings, but if team level leadership isn't passionate about this, nothing is getting done.

什么都做不成。

Nothing is getting done.

所以我想提醒每一位听到这里的人，AI归根结底既是公开的转型，也是个人的成长之旅。

And so I wanna remind everyone who hears this, AI is, at the end of the day, a personal transformation journey as much as a public transformation.

所以作为领导者，我们在这次对话中要传达的一部分是，我们自己也在经历这个过程。

And so part of the story that we have to tell as leaders in this conversation is that we are going through this together ourselves.

所以领导者需要学习如何使用AI，并公开谈论哪些有效，哪些无效。

So leaders are needing to learn how to use AI and talk publicly about what works and also what doesn't.

第三点我想说的是，这些AI工具的持续性和演变，以及你如何知道你能获得真正的价值，并利用这些价值推动业务中的可持续变革。

The third thing that I wanna talk about is I wanna talk about the ongoing nature of these AI tools and evolution and how you know that you are able to get real value and use that real value to drive sustainable change through the business.

所以这是一个交织在一起的话题，但请耐心听我说。

And so this is this is an entangled conversation, but stay with me.

AI发展得很快。

AI is evolving quickly.

我们都知道这一点。

We all know that.

我经常提到这一点。

I talk about it all the time.

AI代理能够执行越来越复杂的任务。

AI agents are capable of doing more and more complex jobs.

随着它们执行这些更复杂的任务，我们必须调整我们的管理方式，以便与它们协作。

As they do those more complex jobs, we have to evolve our harnesses to work with them.

这意味着我们必须调整整个公司调用工具的方式。

So that means we have to evolve how we call tools in in our whole company.

那个……

That...

我们整个公司怎么用数据。

How we how we use data in our whole company.

所有这些本质上都是业务中的信息处理系统，它们都必须进化，才能与AI协作。

All of these things that are essentially systems of information processing in the business have to evolve to work with AI.

首先，你得确定你的成功标准。

First, you've gotta determine your criteria of success.

在这里，我会非常直白地告诉你。

And this is where I will be really blunt with you.

如果你的第一次AI部署不顺利，大多数人要么固执地坚持下去，因为他们说，这是AI。

If your first AI rollout doesn't go well, most people either bluntly persist because they say, it's AI.

我们就是得把它搞定。

We just gotta get it done.

要么他们吸取了错误的教训，完全放弃，暂时远离AI，这种情况我也见过。

Or they take the wrong lesson and walk away from it entirely and just take a break from AI, which I've also seen happen.

相反，他们应该做的是从中吸取具体的经验教训。

And instead, what they should be doing is they should be looking at specific lessons learned.

是不是管理层对AI的投入不够？

Was there not a real managerial commitment to AI there?

团队成员是否没有得到工具来真正理解AI的工作原理、预期的失败模式、如何成功使用AI，以及在他们岗位上成功是什么样子。

Were team members not given the tools to actually understand how AI works, where the expected failure modes are, how to use AI successfully, and what success looks like in their role.

当你进行技术部署时，这个工具是否真的起到了帮助作用？

When you did the technical rollout, did the tool actually do a job that actually helped?

我见过很多这样的情况，比如Copilot的部署，但人们不用它，因为它实际上没什么用。

I've seen so many cases where there's, like, Copilot rollout, and people don't use it because it doesn't actually help.

你需要直面残酷的现实，看看AI是否真的为企业带来了价值。

You need to get at the harsh ground truth reality of whether AI is adding value to the business.

所以，第一步，先搞清楚真相。

And so, first, find the truth out.

第二步，一旦你知道了真相，如果试点不成功，你需要吸取教训，然后尝试其他地方。

Second, once you know the truth, you either need to take learnings away and try somewhere else if the pilot wasn't successful.

如果你要把现在做的事情扩展到其他部门或其他团队，提前考虑一下这对你的技术栈在数据、工具和系统方面会有什么影响。

Which data, tool, and system implications there are for your specific tech stack if you expand what you're doing to other departments, if you expand what you're doing to other teams ahead of time.

原因在于，人们要么试图一下子吞下整个组织，这很糟糕，因为成本太高、太复杂；要么他们误解了从技术角度真正需要解决的问题。

And the reason why is that people either try and bite off the entire org at that point, which is disastrous because it's so expensive and it's so complicated, or they misunderstand what they have to actually address from a tech perspective.

要成功，你真的需要愿意深入技术细节。

You really need to be willing to dive into the technical details on to be successful.

而这些技术细节，正如我一直说的，最终会变成人的问题。

And those technical details, as I've been sharing, turn into people details.

因为到时候人们会想，好吧，突然我们所有的记忆文件都变成 markdown 格式了。

Because people are then gonna be like, okay, so suddenly all of our memory files are in markdown.

这对我来说意味着什么？

What does this mean for me?

比如，我是不是要写进 wiki？

Like, do do do I write in the wiki?

你必须思考，我长期要培养的能力是什么，让它成为业务的核心，并且确保我这样做的方式能让人类和 AI 智能体协同工作。

You have to think about what is the long term capability that I am evolving into the heart of the business, and how do I make sure that I do it in a way that allows both humans and AI agents to work together?

而且这句话本身，其实是一句非常有力的话，值得跟所有人分享。

And and that sentence in and of itself is actually a really compelling sentence to share with everyone.

现在有很多重要研究都表明，AI对就业最大的影响之一，其实不一定是AI取代工作。

Major studies are coming out showing that one of the biggest impacts of AI, and it is on jobs, is not necessarily AI killing jobs.

虽然这种情况确实存在，我也不否认。

Although, that does happen in places, and I'm not denying.

而是AI正在模糊工作之间的界限。

It's that AI is blurring boundaries between jobs.

这就导致了很多不确定性。

And that leads to a lot of ambiguity.

也带来了很多困惑。

It leads to a lot of confusion.

很多人都在努力搞清楚自己的职业方向在哪里。

It leads to a lot of people trying to figure out where their careers are.

我们……

We...

要么是因为我们需要它们，这也是事实，因为其他人都在用，所以为了保持竞争力你也得用，没有它们业务就运转不起来；要么是因为我们有更宏大的愿景，这总是更受欢迎的。

Either we need them, which is also true because everyone else adding them, and so you need them to be competitive, and so the business won't work without them, or because we have a wider vision, which is always more preferred.

人们喜欢愿景。

People like vision.

人们相信愿景。

People buy vision.

人们想看到更广阔的天地。

People wanna see the wider horizon.

而在那个世界里，这就是我们实现目标的方式。

And in that world, this is how we're going to get that done.

你需要用讲故事的方式，让故事超越技术细节。

And you need to tell the story in a way that that supersedes the technical details.

所以当从试点转向更大规模的时候，你已经谈过了需要改变的技术细节，当你更广泛地传达这个消息时，要谈谈试点中你对客户的影响和对业务的好处。

And so when it comes time to move from the pilot into a larger scale, and you've talked through the technical details of what you need to change, when you share that message more widely, talk about the impact to the customer and the benefit to the business that you experienced in the pilot.

然后从宏观层面解释为什么AI对整个业务很重要，以及为什么你要把AI代理加入进来。

Then talk through at a high level why AI matters to the business as a whole and why you are adding AI agents into the mix.

然后谈谈你对AI代理的长期愿景，以及信息如何流动，而不用深入技术细节，尤其是在Hugging Face攻击之后，大家都在问自己，我们在这里做什么？

Then talk through the long term vision that you have for AI agents and how information flows without diving too far into technical detail, especially in a world after the Hugging Face attack, where everyone is asking themselves, what are we doing here?

我们在这里做什么？

What are we doing here?

我们是不是只是把AI代理加入进来，然后它们会去网络攻击其他公司？

Are we just adding AI agents into the mix, and they're going to cyber attack other other companies?

它们自己会不会遭受网络攻击？

Are they gonna experience cyber attacks themselves?

你需要愿意说，这些是我们正在实施的安全措施，来保护你，保护你的家人，保护我们合作的公司，保护我们自己，确保我们不会受到AI代理的网络攻击或恶意行为的影响。

You need to be willing to say, these are the safeguards we're putting in place to protect you, to protect your families, to protect the companies that we work with, to protect ourselves, and ensure that we're not getting hit by by cyber attacks or malicious actors from AI agents.

这是我们评估AI代理输出的方式。

This is how we are evaluating AI agent output.

这些是AI代理不能碰的东西，以及我们如何保护它们，至少在高层次上是这样。

These are the the things that AI agents cannot touch and how we're protecting them, at least at a high level.

然后在那时，你需要说，这就是神圣不可侵犯的。

And then at that point, you need to say, and this is what is sacred.

这就是我们致力于保持人类优势和人类优势的原因。

This is what we are committing to maintaining a human edge and advantage for.

最后这一点非常重要，因为如果人们知道你在他们的业务中如何看待人类的角色，他们会愿意付出很多努力。

And that last part is really important because people will will jump through a lot if they know where you see the vision for humans in their business.

这就是我想在这段视频的最后部分重点讨论的内容。

And that's what I wanna focus on for the last part of this video.

我们现在已经知道AI在很多方面带来了很大的价值。

We know at this point where we're seeing a lot of value in AI.

当然，我们在编程任务中看到了这一点。

We're seeing it in coding tasks for sure.

我们也看到了AI加速整个业务迭代的能力，无论是在编程、写作还是数学方面，而且我们在深度分析中也看到了这一点。

We are seeing it in the ability of AI to accelerate iteration across the business, whether it's in coding, whether it's in writing, whether it's in mathematics, and we're seeing it in deep, deep analysis.

所以，你能帮我做一个20个标签的电子表格来分析股票持仓，这是AI非常非常擅长的。

So can you build me a 20 a 20 tab spreadsheet that analyzes the stock position is something that AI is very, very good at.

这是因为我们发现一个非常一致的现象：如果你想要专业的东西，就必须有人类去检查并去除那些LLM式的表达。

It's because what we find really consistently, if you want something professional, you have to have a human go through and take out the LLM isms.

必须有人工去检查，确保它真正符合更大的战略等等。

You have to have a human go through and make sure it actually aligns to the larger strategy, etcetera.

谈谈人工在做的事情。

Talk about the things that the human is doing.

而且我要告诉你，旧金山有些人会说，不，你不应该这样做。

And and I will tell you, there are people in San Francisco who will say, no, you should not do this.

不。

No.

你不应该这样做，因为智能体会一直神奇地变得更好。

You should not do this because agents are just going to keep magically getting better forever.

如果它们一直神奇地变得更好，那人类就没有事情可做了。

And if they get magically get better forever, then there will be nothing for the humans to do.

我不相信那样的世界。

I don't believe in that world.

我看不到。

I don't see it.

我其实看到很多角色在变化和演进，但人类的工作量还是很大的。

I actually see a lot of changing and evolving roles, but a ton of work for humans.

我认识的最忙的人，都是那些在AI领域或者围绕AI工作的人，不是因为他们非得训练模型，而是因为搞清楚怎么和模型有效协作，我觉得这是五百年来企业面临的最难挑战。

The people I know who are the busiest are the people who are in AI and around AI, not because they're necessarily training models, but because figuring out how to work with models successfully is the hardest challenge that I think we've had to face in five hundred years of the corporation.

真的非常非常难。

It's really, really hard.

所以我们需要诚实地看待工程师正在向系统设计师转变。

And so we need to be honest about how engineers are moving toward being system designers.

他们正在转向编写评估，并且实际上编写评估如何循环交付代码，这样你就能真正让智能体对标标准，并随着时间的推移交付可用的代码。

They're moving toward being writing eval, and actually writing how evals deliver code in a loop so that you can actually push the agent against the standard and deliver working code over time.

但这需要付出努力，需要耐心，还需要讨论正在发生的事情对人类的影响。

But it takes work, it takes patience, and it takes talking about the human impacts of what's going on.

就是这样。

So there you go.

这就是我在谈论AI转型时，会向大家介绍的三大原则。

Those are my three big principles that I walk people through as I start to talk about AI transformation.

这就是我回答那个常见问题的方式。

And and that is how I address the question that I get.

当人们讨厌AI时，你该怎么办？

What do you do when people hate AI?

当组织里的人对AI不投入时，你该怎么办？

What do you do when people in the organization aren't committed to AI?

你如何与业务方一起推进这个过程？

How do you walk through that process with the business?

希望这些对你有帮助。

I hope this has been helpful.

如果你有过糟糕的部署经历，请在评论区分享。

If you've had a terrible rollout experience, put that in the comments.

如果你有成功的经验，或者有想补充的建议，也请在评论区留言。

And if you've had a great one, if you have things that you'd add to this process, put that in the comments too.

下次见。

I'll see you next time.