探索潜在空间：微软的AI投资

我另外还主持两个播客。

I host two other podcasts.

其中一个叫《AI Hustle》。

One is called AI Hustle.

一个是讲怎么用AI工具把生意做大做强，另一个叫《AI Applied》，讲的是AI怎么助力你的职业发展。

It's about growing and scaling your business with AI tools, and one is called AI Applied, about using AI in your career.

偶尔我会在这档节目里放一段那两个播客的片段，让你感受一下它们的风格。

Every once in while, I play an excerpt of one of those podcasts on this show to give you an idea of what it's like.

接下来我要放一段今天《AI Applied》的节目片段。

I'm gonna play an excerpt from today's episode of AI Applied.

今天我们聊的是微软砸了25亿美元押注AI这件事。

We're talking about Microsoft's $2,500,000,000 AI bet.

希望你喜欢这段内容，如果觉得这期节目不错，不妨去各大播客平台听听《AI Applied》。

I hope you like it, and if you enjoy this episode, go check out the AI Applied podcast anywhere that you get your podcasts.

节目名字叫《AI Applied》。

It's AI Applied.

微软刚刚投入了25亿美元和6000名员工，成立了一个新的AI实施团队。

Microsoft has just committed $2,500,000,000 and 6,000 employees to a new AI implementation unit.

不过，这事儿其实并不新鲜。

Now, this is not new.

他们也不是第一个这么干的。

They're not the only ones that have done this.

之前OpenAI和Anthropic早就跟一些公司合作了，比如埃森哲和德勤，我记得是这样。其实早就有一大堆公司，还有不少私募基金，都在往这种AI实施团队里砸钱。

They're following what OpenAI and Anthropic both have, you know, made partnerships with different organizations, Accenture and Deloitte if I'm remembering correctly, and I mean there's a bunch of players that have been doing this, a bunch of private equity firms that have been kind of getting in on this and kind of investing money into these sort of AI implementation units.

最近我在领英上看到康纳对这事有个特别犀利的看法，我一看就愣住了，赶紧想跟他说：你这帖子火了，很多人看了都生气，但我觉得你说得真有道理。

Now, Connor has a spicy take on this that I was reading on LinkedIn and I was like, Connor, we gotta talk about what you've been saying because this post has been blowing up and I think it's making some people mad, but I see a lot of truth to this.

简单说，他的观点是，微软这种做法可能根本走错了路——这听着挺让人意外的，尤其是这25亿美元马上就要花出去了。

So, and and basically his take is that maybe what Microsoft is doing is not the right way to do this, which is, you know, shocker, especially when this is $2,500,000,000 that are about to be spent on this.

所以康纳，能不能请你解释一下，这些实施团队到底想达成什么目标？你觉得他们真能实现吗？普通人该怎么做？这整个事儿会不会就是一场20亿美元的豪赌？

So, Connor, I'd love for you to maybe explain a little bit about what these implementation units are hoping to achieve, what you think they will achieve, what you think people should do, and if this is all a giant $2,000,000,000 mistake.

这根本就是个百亿级别的错误，大家伙儿都别被忽悠了。

Total billion dollar mistake, everybody.

这个观点确实够劲爆，哥们儿。

Yeah, I love the hot take here, man.

顺便说一句，真有微软的人给我发消息，说其实没那么多钱，25亿这个数字没那么准确。

This is so by the way, I did have people from Microsoft like, you know, writing to me and being like, it's not really 2.5.

更准确地说，这笔钱是重新调配的，但核心意思没变。

It's sort of like, that's kind like reallocated, but the message is the same.

连微软内部的人也说，标题确实有点夸张，不过大体上没错，让我找找原文。

And even people inside Microsoft are like, yeah, you know, the headline don't really love the headline, but essentially like the, you know, the headline is essentially, let me grab it.

原始信息其实要付费获取，但花这钱值了。

It's from the information originally, if you don't know the information, but it's expensive to apply to subscribe to, but it's worth it.

微软投入25亿美元，成立新的AI应用咨询团队。

Microsoft commits 2,500,000,000 to new applied AI consulting effort.

新团队的成立，正值大型企业纷纷跟进之际。

And then says the new unit comes as large companies.

这一点非常关键。

And this is important.

新成立的团队正是针对大公司长期以来的抱怨：把AI软件适配到自身需求太难，很难带来实际回报。

The new unit comes as large companies have groused that it can be tricky to configure AI software to their own needs and generate meaningful returns.

贾登，我来告诉你我为什么对这件事这么不满。

Jaden, I'll tell you why I am up in arms about this.

这让我想起，我们之前和一些大公司合作，帮助他们从行为层面推动AI转型，对吧？

So it reminds me, so we were working with the big, so AI mindset like works at big companies to sort of like transform from a behavioral standpoint, right?

真正实现AI的全面落地。

Organizations to really transform AI adoption.

我记得跟一家大型石油和能源公司合作，抱歉，是能源公司。

And I remember working with this huge, like oil and gas or energy, energy companies, sorry.

当时我们正在给他们高管团队做一场大型工作坊，大概三个半小时那么长。

And we were kind like talking about all this in this, doing this big senior leadership workshop, which we do there like, you know, three and a half hours long or something like that.

快结束的时候，他们聊起以前做SAP企业级转型的经历。

And at the end, these folks were talking about when they did like their SAP enterprise transformation thing.

他们说，对了，你还记得吗？那时候我们不断调整系统，因为员工就是不满意，诸如此类的问题。

They're like, yeah, and remember how we had to keep on tweaking it because people just weren't really satisfied with it and all that kind of stuff.

我当时打断了对话。

And I kind of paused the conversation.

我不想插嘴，因为那本来是他们之间的讨论。

I didn't really want get involved because it was a conversation kind of among them.

我只是想提一点意见，可以吗？

I was like, can I just point something out?

这种情况以前发生过吗？

Has this happened before?

他们说，经常发生，司空见惯了。

They're like, yeah, happens all the time.

我就说，这正是我们一直在思考的问题。

I'm like, this is what we think about all the time.

每次你们引入新系统，贾登，搞数字化转型的时候，比如现在要上线Salesforce了。

Every time you sort of like have a new system, Jayden, the digital transformation takes place, hey, we're now going use Salesforce.

然后呢？会发生什么？

What happens?

我跟你保证，人人都抱怨，因为大家就是喜欢老系统。

I promise you, everybody complains because people like the old system.

那他们怎么做呢？

So what do they do?

他们把责任推给系统，而不是反思自己的工作方式。

They blame the system instead of how they work.

微软看到这种情况，我跟你说，这不只是微软的问题。

And so when Microsoft sees this, and I'm telling you, this is what happens, it's not just Microsoft.

我是说，每个大型AI实验室都这样。

I mean, it's every big LAI lab.

谷歌、Anthropic、OpenAI，所有这些实验室都一样。

It's Google, it's Anthropic, it's OpenAI, it's all of these labs.

我跟你说，事情就是这么发生的。

And I'm telling you, this is what happens.

他们先在一家五千到五万人的公司里做个试点。

They put out a pilot of like, you know, 5,000 to a 50,000 person company.

他们说人人都会用，一用起来就像野火一样蔓延。

And what they say is everybody's going to use this and then it's going to catch like wildfire.

然后我们再把许可证卖给另外五万人。

And then we're going to sell our licenses to the other 50,000.

结果呢？

What happens?

只有很少一部分人真的在用。

A fraction of those people use it.

这都是实话。

It's just truth.

对吧？

Right?

关键是，他们现在开始收到反馈了，心里就在想：到底出了什么问题？

And the whole point is that they are now getting feedback because they're like, well what's happening?

为什么大家都不用呢？

Why aren't people using it?

他们就说，哎呀，我不太清楚，就是觉得功能不太合心意之类的。

They're like, oh, I don't know, I just don't like the features or something.

然后他们还老抱怨这个，贾登，我这话可能说得都听腻了，但这就跟抱怨跑步机一样。

And they complain about the thing, which Jaden, I'm going to sound like a broken record here, but it's like complaining about the treadmill.

就像说，我不知道，反正就是觉得它在楼下，或者得去洗衣服，或者功能不喜欢——问题根本不在跑步机，问题在你自己，对吧？

It's like complaining like, know what, I don't know, it's just sort of like it's downstairs or like I have to do laundry or like the features, I don't want to The problem is not the treadmill, problem is you, Right?

那为什么呢？

And why?

因为我们讨厌改变。

Because we don't like change.

我们不喜欢新系统，诸如此类的东西。

We don't like new systems, all that kind of stuff.

所有坐在那儿听我说话、心里想着‘这话说得不对’的人。

And everybody who's sitting there listening to the sound of my voice and being like, That's not true.

AI真的很棒。

AI is great.

人们得更主动去探索，找到适合自己的用法。

It's just people have to be more curious and they have to just find their use cases.

我就想问，你试过吧？

I'm like, You've tried that, right?

有人对这个做出回应了吗？

Has anybody responded to that?

同样的，当你冲他们喊‘少吃多运动’的时候，有人听进去了吗？

In the same way, has anybody responded when you've shouted eat less and exercise to them?

事情不是这么简单就能解决的。

It doesn't work that way.

微软投入了这么多精力，我明白这里面有很多细节，不是说他们真拿了二十五亿美金和六千人就这么直接砸进去，但他们现在做的事，我真的特别欣赏微软，非常欣赏。

So when Microsoft is putting all of this effort, and I understand that there's nuances to this, it's not exactly like they took a pot of $2,500,000,000 and 6,000 people aren't putting into this, but what they're doing here and I love Microsoft, I really do.

我本人就是那种超级微软粉。

I'm actually one of these people that I'm a huge Microsoft fan.

但我一直跟他们说，你们才是这个房间里真正该负责的人。

But I keep telling them, you're the adult in the room here.

你掌控着企业。

You own enterprise.

为什么要把重点放在这儿，非要进来帮他们调整系统、优化功能呢？

Why focus on it like this, where you're like, yeah, let's come in and help you tweak the systems and work on the features.

这根本不是问题所在。

That's not the problem.

他们真正需要麦肯锡、波士顿咨询这些公司的地方，是帮他们推动员工改变工作方式。

The problem is that what they actually need the McKinsey's for and the BCG's and everybody else's is how to get people to sort of like transform how they work.

但就连这个也不管用，杰登，我保证说完这句就闭嘴。

But even that doesn't work, Jayden, I promise I'm going to shut up after this.

但就连这个也不管用，因为咨询行业的模式本身就失效了。

But even that doesn't work because the consulting model doesn't work.

为什么会这样？

Why is that?

因为当那些大型咨询公司——我说的是麦肯锡、波士顿咨询、贝恩、德勤这些公司——

Because when, when the big consulting firms, the Microsoft, I'm sorry, the McKinsey's, the BCG's, the Baines, the Deloitte's, etcetera.

他们一进去，擅长的就是观察你们的运作方式，比如你们销售是这么做的。

When they go in, what they are great at is they are great at looking at a system of like, Hey, you guys do sales this way.

然后说，我们见过上百万家公司的销售做法，最有效的是这样，你们也照着改。

Well, we know that from doing sales in a million other companies, the best way is to do this way, so do it like that.

或者你们运营是这么搞的，其实更好的方式应该是这样，你们得调整一下。

Or you do operations this way, the best way is to actually do it like this, so change what you do.

这没问题。

That's fine.

这很好。

That's great.

这叫咨询，但辅导完全是另一回事。

That's called consulting, but coaching is very different.

你不能光对人说：你们彼此要友善一点。

You can't just say to people, Hey, be nicer to each other.

或者：你们要换种思路，要更注重合作。

Or Hey, think differently or Hey, be more collaborative.

这并不是来自其他组织的最佳实践。

That doesn't come from best practices from other organizations.

你得让人改变他们的习惯和行为，方方面面都得改，所以抱歉，我又绕回来了，杰登，微软和那些大公司都在解决一个简单的问题，就是觉得‘咱们稍微调整一下系统就行’。

You have to get people to change their habits and behaviors and everything else, which is why, sorry, now I've brought it all the way back, Jayden, Microsoft is trying to solve the easy problem and Corporations are trying to solve the easy problem of like, Oh, well, let's just tweak the system.

问题根本不是跑步机本身，而是你根本不想踏上这台跑步机。

When the problem is not the treadmill, the problem is you just don't want to get on that treadmill.

我真希望微软能把25亿美元花在帮助人们重新思考工作方式和流程上。

That's where I wish Microsoft would put $2,500,000,000 on helping people to rethink how they work and rethink processes.

我觉得这真是个巨大的失误。

I just think it's a big miss.

完全同意。

A 100%.

如果你走进一家公司，跟大家说：‘嘿，你们得试试新的微软Copilot。’

I mean, if you're going into an organization and you're like, hey everyone, you've got to try the new Microsoft Copilot.

然后直接给每个人的电脑都装上。

We're signing it up on everyone's computers.

我们推荐的这十件事，每天早上都会开全员会，分享一个我们最爱的微软Copilot小技巧。

These are all the 10 things we recommend doing, we're gonna do an all hands every morning and share our favorite Microsoft Copilot like tip.

说实话，现实中根本不是这么推行的，但咱们不妨想象一下，对吧？

I mean, this is not how they're implementing this in reality, but like let's think about it, right?

或者我们让工程师们进来，仔细分析工作流程，想办法把微软Copilot工具真正融入到日常操作里。

Or we get the engineers in there and we're looking at the workflows and we're trying to like get the Microsoft work, you know, work copilot tools like embedded into the workflows and and everything.

但这根本不是推动重大变革的方式。

That's not how you that's not how you drive the big change.

真正的变革，来自个人突然被点燃的那一刻。

The big change comes from individual people getting a spark Yes.

然后他们意识到：天啊，这工具居然这么强大。

And realizing, oh my gosh, look how capable this is.

看看我能省下多少时间，用来做自己真正喜欢的工作，把那些重复枯燥的任务都自动化掉。

Look how much time I can buy back for myself personally to work on the parts of my job that I like doing, automate the repetitive mundane parts.

只要有人真正被触动了，根本不需要花25亿美元去说服他们使用。

Like as soon as someone gets that spark, you don't need to spend $2,500,000,000 to convince them to use it.

他们对这个着了迷。

They're obsessed with it.

我的意思是，听这个播客的大多数人，应该都处在这种状态吧？

I mean, most of you guys listening to this podcast are in that ballpark, right?

你一看到它能做些不可思议的事情，就忍不住想彻底深入，探索所有可能的用法。就连我，天天都跟AI打交道，每天也都能发现新花样。

Like, you see you see something incredible that it can do and you wanna go all in and figure out all of the ways, and even myself, who covers AI all day, every single day, there is so many ways that I discover every day.

天啊，我压根儿没想到还能这么用。

I'm like, oh my gosh, I never even thought of that.

太棒了，我得赶紧试试。

That's so cool, I wanna try it out.

你看，真正推动大家使用的，是那种发自内心的兴奋——当他们真的被点燃了，而不是简单地让大家去下载Copilot，然后命令他们去问它‘洋基队什么时候在XYZ比赛’这种小事。

Right, like this is what drives the adoption is people being genuinely excited because they they catch that spark, and you have to ignite that spark for people and you're not gonna do it by just going and telling everyone to go download Copilot onto your computer and make sure to go ask it, you know, what time the Yankees are playing at x y z, some simple little thing, right?

你得真正让他们自己体会到那种被点燃的感觉。

Like, you really gotta get them to actually get a spark with it.

所以，这是第一点。

So, that's one thing.

另一点我觉得是，这么多钱其实可以花在其他很多地方。

And the other thing that I think for me is just, I mean, like, it's just so much money that could be spent in so many other places.

我知道你说微软那边的意思是，其实没真花25亿，可能只是发布会这么说的，但我总觉得还有更多别的办法。

I know you said Microsoft was like, oh, it's not really 2,500,000,000, I mean, it's just kind of the way the the presser goes out or whatever, but I just think that there's a lot of ways.

康纳，你觉得呢？从你给很多公司做咨询的经验来看，怎么才能帮别人在组织里点燃这种兴趣呢？

In your opinion, Connor, and from a lot of the consulting that you've done with organizations, what's the, what's the best way for people to help others in the organization catch that spark?

是的，我很喜欢你用‘火花’这个词。

Yeah, I, it's, I love that you call it the spark.

我们在这过程中发现，之所以不教具体用例，而是教流程，是因为用例只是表面鼓励。

So the thing that we figured out, I think in this whole thing is the reason why we don't teach use cases and we teach process instead is that use cases just encouragement.

光说‘大家快去找用例吧’，没用。

Come on guys, find your use cases.

这就像在说：‘你们难道不想感觉更好一点吗？’

It's again, it's sort of like, come on guys, don't you want to feel better?

就像喊人‘出去跑步吧’一样，空洞无力。

Like get out there and run.

这种做法行不通。

Like that doesn't work.

你得建立一套流程。

You have to put processes in place.

对有些人来说，我们通过行为引导这种方式来做，这其实能激发很多人的兴趣，因为他们会说：‘哦，我从来没这么想过。’

So for some people, you know, we do it through this whole behavioral thing, which actually drives a lot of spark because people are like, Oh, I didn't think of it like that.

事情其实是这样的，而不是那样。

It's actually like this and not like that.

这样能点燃不少人内心的火花，但不可能让每个人都被触动。

So that gets a lot of people kind of like with that spark, but we can't get everybody.

真的做不到。

We just can't.

所以对那些没被触动的人，我们就得靠流程来推动。

So then the people that we don't get, we have to put a process in place.

对吧？

Right?

那我来分别说说这两方面。

So the two, let me attack those two sides.

对吧？

Right?

首先，简，我完全同意关于火花的说法。

So first of all, Jane, I totally agree on the spark.

推动人工智能应用的唯一动力，首先得从个人层面入手，除非你谈的是内置AI的产品，对吧？

The only thing that drives AI adoption, it's one, first of all, it has to be driven at the individual level, unless you're talking about AI in a product, right?

就像金的AI盒子那样。

Like, Jin's AI Box, right?

那种产品会因为AI而不断变得越来越好。

Like that's, your product keeps getting better and better and better because of AI.

对吧？

Right?

这确实很棒。

Like, I mean, and that's, that's awesome.

但对于公司里的员工来说，要想创造价值，必须从个人层面入手，毕竟公司付钱给员工，就是希望他们带来价值。

But for individuals at a company, when you're trying to drive value, it has to happen at the individual level because you're paying people to drive value for your company.

你不可能只靠一部分人和一部分机器人，归根结底，都是人在做事。

You don't have like some people and some robots, it's all people.

那在这种情况下，你该怎么做呢？

So what do you do in that case?

你得让每个人都找到自己的那种动力。

You want to have everybody have their spark.

但问题是，这种动力往往发生在工作范围之外。

And the problem with the spark is that it often happens outside the scope of work.

在听的各位，你们是不是也都有过那种瞬间的灵感，就像你刚才说的？

Anybody listening, you always had that spark as you said, right?

我想知道，你们有多少人是通过生活中的事找到这种动力的，而不是在工作中？

I want to know like how many of you have found that spark in a personal thing versus a work thing.

因为我发现，很多时候这种灵感其实来自生活。

Cause I find it's often in personal.

对吧？

Right?

你突然发现咖啡洒了，正着急呢，结果ChatGPT一下帮你解决了难题。

You're like, oh my gosh, I spilled, know, coffee on this and I don't and all of sudden ChatGPT gets you out a bind.

你简直惊呆了。

You're like, oh my gosh.

这种灵感通常不是来自有人发现怎么更快地写邮件。

Like it doesn't usually come because somebody discovered how to write an email faster.

那种感觉，就像 genie 从瓶子里跑出来了，对吧？

That who's that who's that like being like, the genie has come out of the bottle, right?

不，那根本没意思。

No, it's like, it's not exciting.

它不会让你兴奋得想通宵跟AI打交道。

It doesn't get you sort of like wanting to stay up all night, like just working with AI.

它不会带来那种感觉。

It doesn't get those things.

那如果大家根本找不到那种感觉，你该怎么推动呢？

So then how do you drive that if you, if, if you sort of like, if people just aren't finding that spark, right?

我们在培训中会接触到很多人，但不可能覆盖所有人。

So again, like in our, in our training, like we get a lot of people, but we don't get everybody.

那些没接触到的人，就得靠他们所在团队的管理者来建立流程、安排会议，把AI融入日常工作中。我们有具体的做法，但关键是，AI必须成为你一天结束前绕不开的环节，不然就变成强迫了。

So the people we don't get, we have to have like the people leaders in those organizations put processes in place, meetings, things like that, AI is integrated and we have specific ways of doing this, but like where AI, you can't get to the end of the day without going through AI in some way, because then it's sort of like forcing people.

这就像是说，嘿，各位，从今天起，咱们公司每天早上都得去散个两英里步，之类的。

It's almost like, Hey, listen guys, to start the day at this company, we're all going to go out on a two mile walk or whatever.

总有一天，会越来越多的人开始想：其实吧……

At some point you're going get more and more people who are like, you know what?

我挺庆幸自己在做这件事的。

I actually like, I'm really glad I'm doing this.

你懂我的意思吧？

You know what I mean?

你得先用这种方式推一把，让他们在过程中慢慢找到自己的动力。

Like you force it in that kind of way, a forcing mechanism because then they will find their spark through that.

所以我们不搞具体案例。

But that's why we don't do use cases.

因为案例就是那种：大家自己去找感觉吧。

Cause use cases are just like, come on everybody, just find your thing.

你其实是在鼓励某种行为。

And you're kind of encouraging X.

所以我们主张从鼓励转向强制使用。

So we say moving from encouragement to expectation of use.

强制使用就是说：听好了，我们所有会议都在三楼，电梯早就不能用了。

Expectation of use is, listen, all our meetings are on the 3rd Floor and the elevator doesn't work anymore.

这才是让人变得更健康的方式。

That's how you get people healthier.

你明白我的意思吧？

Do what I mean?

就是说，大家必须经过这个流程。

Like you're just saying like people have to go through a process.

所以我们在这方面才取得了成功。

So that's how we've had success on that.

我只想再对微软的朋友们说一句，你们才是房间里最靠谱的。

And I just wish, again, to my friends at Microsoft, you are the adult in the room here.

你们真的能做到这一点。

Like you are able to do this.

你们掌握着企业市场。

Like you own enterprise.

当然，IBM、谷歌、SAP、Salesforce这些公司也一样。

I mean, obviously so does IBM, so does Google, so does SAP, so does Salesforce.

很多公司其实都具备这个能力。

A lot of these places do.

所以我这话也是说给他们听的。

So I'm kind of speaking to them as well.

但如果你关注的是怎么让人改变工作流程，而不是盯着工具本身，那他们就会大规模采购你的产品，因为会真正被点燃。

But if you focus on how you get people to change their processes rather than the tool itself, then they're going to buy your product at scale, like, because they'll have that spark.

这大概就是让我特别兴奋的原因，你也看出来了，但我就是这么看的。

That's what gets me probably over, as you could see, overly excited, but that's how we think about it.

对，我想最后再说一点，很多公司其实自己也没做够，就像你提到的，那种推动力特别关键，因为我觉得企业本身根本没怎么去鼓励或推动员工。

Yeah, and I mean, the last thing that I'll say is, there also is an issue in a lot of organizations where I feel like the companies themselves are not doing enough, and like you mentioned, that forcing function is so important because I feel like the companies themselves are not doing enough to encourage or push people.

也许他们早期直接禁止用AI，也许根本没鼓励过，甚至从来没奖励过使用的人。

Maybe they had early like bans on AI, maybe they just never encouraged it, maybe they never rewarded it.

有些奖励机制简直荒唐，比如谁用的token最多就给奖。

I mean there's all sorts of absolutely ridiculous reward systems like who's using the most tokens.

这种做法根本没法真正让人用上这些工具。

Okay, But terrible like genuinely getting people to leverage these tools.

因为我看到几种不同的情况。

Because the things, I'm seeing a couple different things.

第一，我用的那些软件公司，还有比较灵活、聪明的初创企业，每两周就推出新功能，因为他们做得到。

Number one, a lot of the software companies I use and the scrappier, savvier startups, they are churning out new features every two weeks because they just can.

这真让我大开眼界。

And it's like, it's actually blowing my mind.

我长期关注的一些公司，它们推出新功能或彻底重构平台的速度，真的让我特别佩服。

There's a bunch of companies I've followed for a long time and the rate that they're able to just put out these incredible features or rebuild their entire platform is so impressive to me.

我理解为什么会这样，因为我自己也在用同样的方式更新所有软件和工具，但并不是所有公司都这样。

And I understand why because I'm doing the same thing with all my software and platforms and tools, but I'm not seeing it from all companies.

而那些没在这么做的人，说实话，你会发现我们其实活在一个信息茧房里。

And the companies that I'm not seeing it from, for example, I mean, there's just so many people where you realize that we are sort of in a bubble.

有些人充分利用了这些工具，也有些人完全没动起来。

There's some people that are really taking advantage and there's some that are just not.

我最近跟一个人聊天，他是家大型游戏公司的开发者，我一听说他是前端工程师，简直惊呆了。

I was recently talking to someone and he's a developer at like a big gaming studio and he said, I'm like, I'm like, oh my gosh, like he's a front end developer.

我心想，你肯定天天拿Clyde当宝贝吧？

I'm like, you must just like, Clyde must be your best friend, right?

这太棒了，因为我自己每天都在干这个。

It's like so awesome cause I'm doing this all day.

对吧？

Right?

他说实话，我都不确定自己有没有试过Claude。

And he's like, to be honest like, I don't know if I've tried the Claude one yet.

我记得我们之前用过一个GitHub的，但后来就不用了，最近我才开始偶尔用一用，不过真的让我大开眼界。

Like I think I we had like a GitHub one, but then it's we don't have it anymore, and like, I've started using it a little bit lately, but anyways, it just blew my mind Yeah.

他居然几乎没怎么用，我就想，如果公司不把这当回事，员工自然也不会当回事。

How much he didn't use it, and I'm like, if it's not a priority in your company, it's not a priority for your employees.

如果员工都不当回事，那你们怎么可能每两周就推出新更新呢？明明有这个能力啊。

And if it's not a priority for your employees, you're not shipping new updates every two weeks because you can.

你们根本不可能靠AI把产出提升十倍，因为根本没把这个当回事。

You're not 10 x ing your output because you like you can with AI.

当然，有些行业还是老样子，公司稳稳当当，按部就班也过得去，但如果你真想保持竞争力，就必须把这当成头等大事。

And so, yes, there's like business as usual, and some companies are like in these industries where you're kind of entrenched, you kind of have a good thing going, and business as usual works pretty good, but I mean, if you really wanna stay competitive, you have to make this a priority.

我知道在这儿说这些像是对牛弹琴，但真让我惊讶，几乎每周我都会遇到有人跟我说，他们根本没用AI。

I I know I'm speaking to the choir here, but it it blows my mind because this probably happens at least once a week where I talk to someone and they're like not using AI

这就是我们所处的这个信息茧房。

or Jin, this is this is the bubble we live in.

这就是我们所处的环境。

It's the bubble we live in.

最后再提醒大家两点。

Just to close that out, just remember guys that like two things.

首先，我们生活在一个信息茧房里。

First of all, we live in a bubble.

所有听这个节目的人，都活在这个茧房里。

The anybody listening to this show lives in the bubble.

很多人其实根本没怎么用人工智能。

A lot of people are not, like, sue me, using AI.

我这不是在情绪化。

I'm not getting emotional.

我只是喝口水。

I'm just gonna take a sip of water.

康纳对这一点特别激动，但很多人根本没怎么用人工智能。

Connor is incredibly emotional about this point, and people just aren't using AI enough to

人工智能。

the AI.

前几天我看英格兰对墨西哥的比赛，哈里·凯恩嗓子哑了。

I was watching England Mexico Mexico the the other other night, night, and and Harry Harry Cain Kane lost his voice.

这得多尴尬啊？

I'm like, how embarrassing is that?

他观众那么多，相比之下我觉得我还行。

And he had a much bigger audience, so I think I'm okay.

杰登，关键是这事得从领导层开始。

Jayden, the thing is like, this has to start with leadership.

得从领导层入手，然后自上而下推行，就像你说的那样。

It has to sort of like start with leadership and work its way down, just as you're saying.

如果领导层不问责，公司根本没法让其他人承担责任。

There's literally no way for a company to sort of like hold people accountable unless leadership is holding people accountable.

这事就得从这儿开始。

That's where that has to start.

但话说回来，光靠喊口号让人去用，根本没用。

But again, we have to understand that like just telling people to use it is just never going to work.

各位，我再不抓紧说，嗓子又要哑了——要是你们看过英格兰对墨西哥那场，肯定知道，哈里·凯恩那个采访简直太精彩了。

Guys, before I lose my voice again, like again, if anybody saw Mexico, England, they know this, the Harry Kane interview was glorious.

他当时嗓子完全哑了。

He'd lost his voice.

说话跟凯文·克莱恩的青蛙一样。

He sounded like Kermit the Frog.

好在，我总算把自己救回来了。

Luckily, think I've rescued myself.

但重点是，各位。

But here is the thing guys.

如果你真想逼自己一把，琢磨怎么更好地用上这工具，我强烈推荐 jaidensaibox.ai。

If you are sort of like trying to push yourself and trying to sort of like see how you can use this better, I cannot recommend more highly jaidensaibox.ai.

这东西是我最爱用的，因为我总在 Claw、Gemini 和 OpenAI 这三个主力工具之间来回切换。

This is my absolute favorite thing to use because when I'm bouncing between Claw, Gemini, OpenAI, those are my kind of like big three.

每个月还不到十美元，你就能享受这些功能。

This allows you to do that for less than $10 a month.

简直让人难以置信。

It's absolutely unbelievable.

用这些模型来对比分析，真的特别有帮助。

Use all these models help, you know, compare things.

我现在就是这样做的，每个月花几百美元。

This is what I'm doing and spending hundreds of dollars a month.

如果你还没试过，一定要去看看，绝对物超所值。

Check this out if you haven't already, it is unbelievably worth it.

你用了绝对不会后悔。

You won't regret it.

别忘了给个评分和评价。

And don't forget to leave a rating and review.

非常感谢大家参与这些对话，我们下一期再见。

We are so grateful for these conversations with you all and we will see you in the next episode.