Please Stop the AI
Confidence Theater

AI headlines never disappoint.

AI 的新闻标题从不让人失望。

First, AI was killing education (oh the good ol’ days, I miss thee).

先是 AI 要搞垮教育(哦,那些美好的旧时光,我怀念你)。

Then we moved on to eliminating writers, engineers, designers, product managers, and sales jobs - I believe in that exact order.

然后我们又接着去消灭作家、工程师、设计师、产品经理和销售岗位——我记得顺序就是这个。

Marketing, Finance, and HR were spared though, which I find ironic.

不过市场、财务和 HR 被放过了,我觉得挺讽刺的。

Google, with its precious SEO, was on the chopping block because of AI.

Google 和它宝贝似的 SEO,也因为 AI 被推上了砧板。

Then we decided to collectively eliminate SaaS.

接着我们又集体决定要干掉 SaaS。

We didn’t, but the stock market believed it and lots of people lost $$$.

并没干掉,但股市信了,一堆人赔了大把钱。

Now we are in the middle of everyone and their mother needing an AI agent, because you are def missing out on a life changing experience if you don’t have one.

现在我们正处在‘人人都得有个 AI agent’的阶段,因为你要是没有,绝对就错过了一次改变人生的体验。

And yet… 99% of people don’t even know what an AI agent even does.

然而……99% 的人根本不知道 AI agent 到底能干嘛。

Meanwhile, I’m over here asking ChatGPT to rewrite the same paragraph for the third time because it keeps defaulting me into ‘LinkedIn wisdom post’ mode.

与此同时,我这边正第三次让 ChatGPT 重写同一段话,因为它老把我默认切进‘LinkedIn 金句体’模式。

GARH.

啊啊啊。

Look: I work at an AI company.

听着:我在一家 AI 公司工作。

I use AI all day.

我整天都在用 AI。

I strategize with it.

我用它做战略。

I build products with it.

我用它做产品。

I write with it.

我用它写作。

I analyze data with it.

我用它分析数据。

But even I feel like everyone else has cracked the AI code while I’m still using some basic tutorial version over here.

但即便是我,也觉得别人都破解了 AI 的通关密码,而我还在这儿用某个入门教程版。

So I started asking a simple question whenever someone told me AI had changed their life: ‘Cool. Show me.’

所以每当有人跟我说 AI 改变了他们的人生,我就开始问一个简单的问题:‘不错啊,给我看看。’

And most of the time I see some basic workflows.

而大多数时候,我看到的是一些很基础的工作流。

Summarizing Slack.

总结 Slack 消息。

Answering emails.

回邮件。

Doing scheduled scans.

做定时扫描。

Performing research and booking something.

做点调研、订个什么东西。

Sending emails out of Claude.

从 Claude 里把邮件发出去。

Okay…. it’s useful.

好吧……是挺有用。

But show me something that has become so critical in your day that if I took it away tomorrow, your work would actually fall apart.

但给我看样东西——关键到我明天要是把它拿走,你的工作就会当场散架。

Show me something truly life changing.

给我看点真正改变人生的东西。

It turns out that’s a super short list.

结果发现,这样的清单短得可怜。

But the noise continues on volume 11/10.

但外面的噪音还开在 11/10 档。

So this is my desperate plea... Can we PUHLEASE stop this AI Confidence Theater, people?

所以这是我绝望的恳求……各位,我们能不能拜托拜托,停下这场 AI 自信表演?

It’s doing more harm than good.

它弊大于利。

This fake AI hype is hurting all of us.

这种虚假的 AI 炒作正在伤害我们所有人。

This is not a victimless crime.

这不是一桩没有受害者的罪。

The AI headline chasers and fakers are robbing people of a real, cool Ah-ha moment with AI tools that could get them excited and bought-in.

那些追逐 AI 标题、弄虚作假的人,正在夺走人们本可以从 AI 工具里获得的、真实又酷的‘啊哈’时刻——那种能让人兴奋、真心买账的瞬间。

The problem is when you see someone talk about their ‘life-changing’ (it’s always ‘life-changing’) new AI-powered system but… it doesn’t actually work.

问题在于:当你看到有人大谈他们‘改变人生’的(永远是‘改变人生’)全新 AI 系统,可它……其实根本不好使。

So you just assume that all of the AI stuff is BS and keep your head in the sand.

于是你干脆认定所有 AI 玩意儿都是扯淡,把头埋进沙子里不管了。

And instead of celebrating the saved time and reduced annoyance that AI actually can do right now, people are out here promising employee-replacing super agents… despite the fact that their agents only trigger 50% of the time and only deliver decent outputs if hand-fed very specific context (and get shit wrong most of the time)

而人们非但不去庆祝 AI 当下真能带来的省时和少烦心,反倒在这儿承诺什么能取代员工的超级 agent……哪怕这些 agent 只有 50% 的概率会被触发,还得有人手把手喂进非常具体的上下文才能给出像样的结果(而且多数时候还会搞砸)。

I didn’t have ‘Kind of misses toxic hustle culture’ on my 2026 bingo card and yet, here we are.

‘竟有点怀念有毒的奋斗文化’这一条,我 2026 年的预测卡上可没写,然而……我们就是走到了这一步。

Because now we have an even more toxic environment.

因为现在的环境更有毒了。

Five years ago, people wanted you to think they worked harder than everyone else.

五年前,人们想让你以为他们比谁都拼。

Today they want you to think AI does it all.

今天,他们想让你以为一切都是 AI 干的。

Five years ago, people shared and bragged about big outcomes: revenue, user milestones, fundraising, headcount.

五年前,人们晒的、吹的是大成果:营收、用户里程碑、融资、团队规模。

Today people are just highlighting how many tokens they’re burning.

今天,人们只顾着炫耀自己烧了多少 tokens。

Everyone wants you to believe they have an invisible team of AI employees running their business while they think big thoughts.

每个人都想让你相信,他们有一支看不见的 AI 员工团队在打理生意,而他们只负责思考宏大命题。

But where are those business outcomes, tho?!?

可那些实打实的业务成果呢?!?

Five years ago, people bragged about waking up at 5am, doing cold plunges, having inbox zero, and working while endlessly Peletoning.

五年前,人们吹的是清晨五点起床、冲冷水浴、做到 inbox zero、一边没完没了地蹬 Peloton 一边工作。

Now it’s all about having 17 agents, not opening email, and AI running your business.

现在,一切都变成了拥有 17 个 agent、从不打开邮箱、让 AI 打理生意。

It’s the exact same performance, just with different props.

这是一模一样的表演,只是换了道具。

This has also blown up the hiring process.

这也把招聘流程搅得一团乱。

AI has made average intelligence incredibly cheap and it has given everyone the vocabulary of expertise.

AI 让中等水平的智力变得极其廉价,还给了每个人一套‘专家词汇’。

It used to be that if someone started talking about vector databases, MCP, agents, memory, or RAG you assumed they knew what they were doing.

过去,要是有人张口就聊 vector database、MCP、agent、memory 或 RAG,你会默认他懂行。

Today, everyone knows the words.

今天,人人都会这些词。

AI regurgitates some smart one-liner for them and 3 hot takes.

AI 帮他们吐出几句漂亮的金句、外加三条犀利观点。

Everyone sounds like they have an experience.

每个人听上去都像很有经验。

But sounding competent and being competent are completely different things.

但‘听起来能干’和‘真的能干’是完全两码事。

So how do you hire in the middle of that?

那在这种局面下,你要怎么招人?

Not that the old interview and hiring process was so great - I’ve been frustrated with it for years.

倒不是说过去那套面试和招聘流程有多好——我已经被它折磨好多年了。

But verbal interviews for real don’t work anymore.

但纯靠嘴的面试,是真的不管用了。

Just because you can ‘confidently’ explain MCP doesn’t mean you can build one or you’ve built a single workflow that anyone actually depends on.

你能‘自信地’讲清楚 MCP,并不意味着你能搭出一个,或者你真做过哪怕一个别人离不开的工作流。

Case study and work trials become absolutely necessary to cut through the bullshit.

要想穿透这些扯淡,案例作业和试岗就变得绝对必要。

All this leaves people feeling demoralized.

这一切让人心灰意冷。

Instead of getting excited about how these tools could help, it mostly just feels like we are all terribly behind and it’s all completely impossible.

本该为这些工具能帮上什么忙而兴奋,结果更多的感觉却是:我们全都被远远甩在后面,而且这事根本追不上。

Overall, our brains just can’t comprehend this level of change.

总的来说,我们的大脑根本消化不了这种程度的变化。

Especially for people in tech, this is all happening so fast.

尤其对科技行业的人来说,这一切发生得太快了。

Think about the fact that 200 years ago, we were just getting basic sanitation figured out, and now we have to figure out how to manage all-powerful (but also really inconsistent and sometimes disappointing!?) artificial intelligence that is going to help/replace our jobs?

想想看:200 年前我们才刚搞明白基本的卫生设施,而现在我们却要琢磨怎么驾驭一种无所不能(但又极不稳定、有时还挺让人失望!?)、即将帮忙 / 取代我们工作的人工智能?

It’s just so much.

这实在太多了。

We don’t need people yelling at us all the time about how we’re behind.

我们不需要有人整天冲我们嚷嚷,说我们落后了。

What I don’t like about it is that it creates a fake baseline.

我不喜欢它的一点是:它制造了一条虚假的基准线。

If everyone around you appears to have figured something out about AI that has transformed their work, then using AI to summarize meetings suddenly feels embarrassingly basic.

如果你周围每个人看起来都摸透了某种能彻底改变工作的 AI 用法,那用 AI 来总结会议突然就显得基础得让人难堪。

You stop appreciating the things that genuinely save you time because someone else claims they’ve done so much more.

你不再珍惜那些真正帮你省时间的东西,只因为别人声称他们做到了多得多的事。

There are a few big reasons that come together to make this happen: social media rewards superficial hype, the stuff AI can do is evolving faster than we can keep up, and companies are incentivizing this sort of behavior all up and down the org chart.

有几个大原因凑到一起促成了这件事:社交媒体奖励浮于表面的炒作,AI 能做的事进化得比我们跟得上的速度还快,而公司又在自上而下的每一层激励这种行为。

We live in a world where attention is the currency.

我们生活在一个注意力即货币的世界。

And that attention is generally measured in impressions.

而这种注意力通常是用曝光量来衡量的。

This is the dopamine hit that people are chasing - can you go viral?

这就是人们追逐的多巴胺快感——你能不能刷屏爆火?

Can you get everyone to engage?

你能不能让所有人都来互动?

The way to capture attention is to say something shocking or unexpected, so everything gets exaggerated.

抓住注意力的办法,就是说点惊人或出人意料的话,于是一切都被夸大。

Legitimately cool use cases get elevated from ‘This saves me 15 annoying minutes every week’ to ‘ZOMG THIS CHANGED MY LIFE’ or ‘USE THIS WORKFLOW OR YOU’LL BE PERMANENTLY UNEMPLOYED.’

真正不错的用例,被从‘这每周帮我省下 15 分钟糟心时间’一路拔高成‘我的天这改变了我的人生’,或者‘用这个工作流,不然你就要永久失业了’。

When we’re talking about content creators sharing their magical use cases on LinkedIn and X, the tricky thing is that AI really CAN do crazy stuff.

当我们说内容创作者在 LinkedIn 和 X 上分享他们神乎其神的用例时,棘手的地方在于:AI 确实能干出些疯狂的事。

If it were all fake, then we could all just ignore it.

如果全是假的,那我们大可以直接无视。

But people actually are building stuff all the time that could totally change how you and I work every day.

但人们确实一直在做出一些东西,足以彻底改变你我每天的工作方式。

So, we can’t just ignore it.

所以,我们没法直接无视。

But it’s also hard to confirm.

但它也很难求证。

Like, are they using a different LLM model than me?

比如,他们用的 LLM 模型跟我不一样?

Is my data not structured right?

是我的数据结构没弄对?

Did I mess something up in setting up the workflow?

是我在搭工作流时搞砸了哪一步?

Or… did they just fake it, and all of this is impossible?

还是说……他们纯粹在造假,这一切压根不可能?

There’s no way to know.

根本无从知晓。

This is not a problem that we had to deal with previous phases of tech.

这不是我们在之前几波科技浪潮里需要面对的问题。

No one was creating ‘I just built this INSANE setup with Dropbox’ posts to try to go viral… everyone would have just looked at the description and immediately called bulllllshit.

没人会发‘我刚用 Dropbox 搭了个疯狂到炸的系统’这种帖子去博爆火……大家扫一眼描述,就会当场大喊‘扯——淡’。

Traditional software was ‘easy’ to message.

传统软件‘好’做营销。

Click the button, get the outcome.

点这个按钮,得到那个结果。

AI doesn’t work like that.

AI 不是这么运作的。

It opens up more possibilities, use cases become loosely defined, and it needs the right context to succeed.

它打开了更多可能性,用例变得松散模糊,而且需要对的上下文才能成功。

Sometimes it’s incredible.

有时它惊为天人。

Sometimes it’s just stupid or confidently wrong.

有时它就是很蠢,或者错得理直气壮。

But read the landing pages and you’d think every AI product is a magical employee that never sleeps, never makes mistakes, and runs your company better than anyone else.

但读读那些落地页,你会以为每个 AI 产品都是个神奇员工:从不睡觉、从不出错,把你的公司打理得比谁都好。

The thing about all this AI innovation is that it’s also the era of trust-based growth.

所有这些 AI 创新还有一层意思:它同时也是‘基于信任的增长’的时代。

If you over-sell, it will be discovered and no one will trust you anymore.

如果你过度承诺,迟早会被拆穿,再也没人会信你。

Right now, maybe all of this hype feels like free attention and money.

眼下,这些炒作或许感觉像是免费的关注度和钞票。

But if you take that route, you’ll pay for it in the end.

但你要是走这条路,最终一定会付出代价。

P.S. I don’t even blame marketing teams.

P.S. 我甚至不怪市场团队。

They’re doing what marketing has always done: selling the best possible version of the product.

他们做的正是营销一直在做的事:兜售产品最好的那一面。

The problem is that with AI, the gap between the demo and day-to-day reality can be enormous.

问题在于,到了 AI 这里,demo 和日常实际之间的落差可能大得吓人。

And every exaggerated promise makes people trust the next AI product a little less.

而每一个被夸大的承诺,都会让人对下一个 AI 产品的信任又少一分。

Inside companies, this starts at the very top.

在公司内部,这一切始于最顶层。

Even above the execs - at VC level.

甚至在高管之上——在 VC 那一层。

Because the investors have been promised AI-powered miracles.

因为投资人被许诺了‘AI 驱动的奇迹’。

And this means that execs need to demand AI-powered miracles from their employees.

这意味着高管们又得向员工索要‘AI 驱动的奇迹’。

Which means that employees are being asked to do the impossible with (often underperforming) AI tools.

这又意味着,员工被要求用(往往并不给力的)AI 工具去完成不可能的任务。

Which means that employees are massively incentivized to perform the AI confidence theater to justify career progression, or maybe even protect their jobs.

这再意味着,员工有巨大的动力去上演这场 AI 自信表演,好为升职正名,甚至只是为了保住饭碗。

If we’re going to stop the charade, it’s gonna take a group effort.

要想停下这场闹剧,得靠大家一起使劲。

If you’re reading this and you’re guilty of posting exaggerated nonsense about your 100x AI Agent Workflows… stop it.

如果你正在读这篇文章,而且确实发过那种吹嘘‘100 倍 AI agent 工作流’的夸张废话……那就打住吧。

The good news is that there’s plenty of amazing stuff to be done.

好消息是,值得做的了不起的事多着呢。

You don’t need to make things up or exaggerate.

你根本不用编造或夸大。

Just go deep on the stuff you know, and spend the time to build something really cool that actually can make real impact.

只要在你懂的东西上钻深,花时间做出点真正酷、真正能产生实际影响的东西。

If you share something that seriously changes how people work, they’ll always remember you.

如果你分享的东西真能大幅改变人们的工作方式,他们会永远记住你。

Some clickbaity title and false promises makes you forgettable or hateable.

而一个标题党式的标题加上虚假承诺,只会让你变得可有可无、甚至招人厌。

And if you’re watching that kind of hyped content: You can be part of the solution, too.

而如果你是在看那类炒作内容:你同样可以成为解决方案的一部分。

Hold your favorite creators accountable!

让你喜欢的创作者为自己说的话负责!

Ask them to show you the receipts!

让他们拿出实锤!

If you know that something doesn’t work, don’t just let it slide.

如果你知道某个东西不好使,别就这么放过它。

And do NOT amplify it unless you try it yourself.

而且,除非你自己试过,否则千万别去帮它扩散。

If it doesn’t work and you spread it, you’re responsible, too.

如果它不好使而你还传播了它,你也有责任。

The corporate side of this is a little bit trickier.

公司这一侧要稍微棘手一些。

Because again, it starts at the top.

因为老话重提:一切始于顶层。

Execs: Set reasonable expectations. This means managing your investors to tell them what you can actually do. This also means setting benchmarks for your organization - creating unreasonable expectations only comes back to burn you.

高管:设定合理的预期。 这意味着管理好你的投资人,如实告诉他们你到底能做到什么;也意味着为你的组织设定基准——制造不切实际的预期,最后只会反噬你自己。

Managers / Team Leads: Focus on outcomes. Show your leadership what your team can move and use AI to amplify that. Don’t just start with AI and shrug your way to how it connects to business impact. If your team is still experimenting with AI tools and workflows, give them the space to build something that will really last.

经理 / 团队 Lead:盯住结果。 向你的领导层展示你的团队能撬动什么,再用 AI 去放大它。别一上来就抱着 AI,然后含糊其辞地扯它跟业务影响有啥关系。如果你的团队还在试验 AI 工具和工作流,那就给他们空间,去做点真正能长久的东西。

Employees: Figure out the actual impact. Ask for the time and training to get better with the AI tools that interest you! Everyone is talking about AI, but if you can actually connect it to fixing core business problems, you’ll be a real hero. Figure out how to anchor in outcomes! (Understanding and delivering this kind of impact is how you become a Hi-C, btw.)

员工:搞清楚真实的影响。 主动争取时间和培训,把你感兴趣的 AI 工具用得更溜!人人都在谈 AI,但如果你能真正把它和解决核心业务问题挂上钩,你就会成为真正的英雄。想清楚怎么把自己锚定在结果上!(顺带一提,理解并交付这种影响,正是你成为 Hi-C 的方式。)

My biggest career advice for anyone right now: spend a few hours a week trying something new with AI.

我现在给所有人最重要的职业建议:每周花几个小时,用 AI 试点新东西。

It’s not a lunch, 5 mins between meetings, after work, or weekend activity.

这不是午饭时间、会议间隙那 5 分钟、下班后或周末才干的事。

Learning AI IS the job right now.

学 AI,现在本身就是工作。

Make legitimate space for it.

光明正大地为它腾出时间。

Seriously, people.

说真的,各位。

Content creators.

内容创作者。

Company leaders.

公司领导。

Employees.

员工。

Marketing teams.

市场团队。

Let’s just be honest about what we and our products can actually do with AI.

咱们就坦诚一点,承认我们和我们的产品用 AI 到底能做到什么。

The first prompt is the fun part.

第一条 prompt 是好玩的部分。

The next thousand prompts is where real value is created.

接下来的一千条 prompt,才是真正创造价值的地方。

Let’s make sure we cover THAT part - what happens when the models change, the prompts stop working, the API behavior shifts, or the integration breaks and no one notices.

咱们得确保把那部分也讲清楚——当模型变了、prompt 失灵了、API 行为变了,或者集成崩了却没人发现时,会发生什么。

AI systems aren’t ‘set it and forget it.’

AI 系统不是‘一劳永逸’的。

They’re living systems that need monitoring, evaluation, iteration, and constant tuning.

它们是活的系统,需要监控、评估、迭代和持续调优。

That’s where the real work happens.

真正的活儿就在这里。

That’s where the real value gets created.

真正的价值也在这里被创造。

And somehow, that’s the part nobody posts about.

而不知怎的,恰恰是这部分没人发帖去讲。

If you’ve built something amazing, tell people.

如果你做出了了不起的东西,那就告诉大家。

But if you’ve built a promising prototype, say just that.

但如果你做的只是一个有潜力的原型,那就照实这么说。

We will still be excited, promise.

我们照样会兴奋,我保证。

If your workflow saves you 20 minutes a day, celebrate that.

如果你的工作流每天帮你省 20 分钟,那就为此庆祝。

If your AI agent still needs babysitting or constantly messes up, admit it.

如果你的 AI agent 还得有人盯着、动不动就出岔子,那就承认。

AI is already the coolest tech innovation of our lives… we don’t need to pretend it’s magical too.

AI 已经是我们这辈子最酷的科技创新了……我们没必要再假装它有魔力。