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「AI 末日」是今年最拥挤的交易——如果反过来呢?

Kobeissi Letter 的反共识论点:市场在为"AI 毁灭就业→消费崩塌→螺旋下行"定价,但历史上每次成本崩塌都扩张了需求而非收缩——真正被低估的不是末日,是富足。

2026-02-26 原文链接 ↗
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核心观点

  • "显而易见的交易从来不赢"是这篇的核心赌注。 8000 亿市值蒸发背后,市场在线性外推"AI 替代→裁员→消费萎缩"的厄运循环。但这个模型假设需求是固定的——历史上算力便宜 99.9% 后我们没有少用算力,而是用了几个数量级更多。认知成本崩塌大概率也是同样的剧本。
  • "富足 GDP"概念比"幽灵 GDP"更值得建模。 不需要名义收入暴涨,只需要价格下跌速度快于收入增长。如果 AI 把医疗行政、法律文书、报税、客服的成本砍掉一半,等效于一次隐形减税。这个框架比"AI 创造/消灭多少岗位"更有解释力。
  • Anthropic 的"打击"本质是商品化信号,不是崩溃信号。 IBM(COBOL)、Adobe(创意工作流)、CrowdStrike(安全扫描)被砸,不是因为这些需求消失了,而是因为认知劳动的定价权正在从卖方转向买方。商品化 ≠ 消亡,PC 商品化了算力、云商品化了基础设施,结果都是市场扩张。
  • 文章自身也是一个"反向拥挤交易"的推销。 Kobeissi 本质是付费投资通讯,文末硬推订阅服务。"我们跑赢标普 5 倍"这种话要打折听。论点框架有价值,但别把它当中立分析——它在卖乐观。

跟我们的关联

💰投资 — 如果你在做 AI 相关的投资决策,这篇提供了一个有用的反面框架:不要只看"谁会被替代",也要看"成本崩塌后哪些新需求会被释放"。尤其关注小企业创业门槛降低这条线。

🌍通用 — "富足 GDP"框架可以用来评估 AI 对任何行业的影响:不是问"会不会裁员",而是问"服务成本下降后,总需求会扩张还是收缩"。

讨论引子

💭 "认知商品化"跟之前的算力/分发/基础设施商品化真的可类比吗?认知劳动有没有什么特殊性让这次"不一样"?

💭 如果 AI 富足真的降低了全球冲突的经济动机,那"谁控制 AI 基础设施"会不会成为新的稀缺资源争夺点,反而制造新的冲突?

太显而易见了:如果 AI 其实并不会终结世界呢?

股市刚刚抹去了 -8000 亿美元的市值,因为“AI 接管世界”正在成为共识。这个观点太显而易见了。而“显而易见”的交易从来不会赢。在开始之前,把这篇文章加入书签,并在接下来的 12 个月里反复回来对照。

“末日情景”之所以病毒式传播,是因为它抓住了一种直觉上的恐惧。它把 AI 描绘成的不是生产力工具,而是能够引发负反馈循环的宏观经济“去稳定器”:裁员导致消费走弱,消费走弱推动更多自动化,而自动化又进一步加速裁员。

显而易见的事实:AI 不是另一个软件功能,也不只是效率提升。它是一种通用能力的冲击,会同时触达每一个白领工作流。不同于历史上的任何一次革命,AI 正在同时变得更擅长“所有事情”。

但是,如果末日情景是错的呢?它假设需求是固定的,假设生产率提升不会扩张市场,也假设系统无法比冲击更快地完成适应。

我们认为还有第二条路径,而市场对它的定价严重偏低。那些看起来像系统性崩溃早期信号的 Anthropic“打击”,最终可能反而是史上最大的生产力扩张的起点。

虽然下面的分析并非必然结果,但重要的是要记住:人类一直都能挺过去;而自由市场也总会自我出清。

ANTHROPIC 的“打击”是真实存在的

先说在前面:我们无法忽视市场。Anthropic 正通过 Claude 颠覆世界,财富 500 强公司因此蒸发了数千亿美元的市值。

这是一段我们在 2026 年已经见过好几次的剧情:Anthropic 发布新的 AI 工具,Claude 在编程与工作流自动化方面出现实质性跃升,而在数小时之内,目标行业的市场就崩了。

如果你还没留意,下面是一些例子:

https://x.com/@KobeissiLetter

  1. IBM 股票 $IBM 在 Anthropic 宣布 Claude 可以精简 COBOL 代码之后,录得自 2000 年 10 月以来最差单日表现

  2. Adobe $ADBE 年初至今(YTD)下跌 -30%,因为生成式能力正在压缩创意工作流

  3. “Claude Code Security”发布后,网络安全概念股集体崩盘

在上面的例子里,CrowdStrike 股票 $CRWD 的暴跌,几乎就是 Claude 宣布“Claude Code Security”的那一分钟发生的。

2 月 20 日下午 1 点(美东时间),Claude 宣布推出“Claude Code Security”。这是一个自动化 AI 工具,用于扫描代码库中的漏洞。

仅仅两个交易日之后,CrowdStrike 股票 $CRWD 因这一消息抹去了 -200 亿美元的市值。

这些反应并不非理性。市场试图为“实时的利润率压缩”定价。当 AI 复制了工人正在做的事,定价权就会向买方转移。这是一阶影响,而且非常真实。

商品化不等于崩溃。相反,它是技术降低成本、扩大可得性的方式。个人电脑让计算商品化,互联网让分发商品化,云让基础设施商品化,而 AI 正在让认知商品化。

毫无疑问,一些传统工作流会遭遇利润率压缩。问题在于:更低的认知成本会让经济崩塌,还是会让经济大幅扩张?

“厄运循环”假设需求是固定的

看空的循环给出一个简化的线性模型:AI 变得更强,企业减少人数与工资,于是购买力下降,企业为了捍卫利润率再次投资 AI,然后下行循环重复。这等于假设经济完全停滞不前。

历史并不支持这种假设。当生产某种东西的成本崩塌时,需求很少保持不变,它往往会扩张。当算力成本下降时,我们并不是以更低的价格消费同样数量的算力;我们消费了数量级更高的算力,并在其上构建了全新的行业。

如下所示,个人电脑的价格如今相比 1980 年已经便宜了 99.9%。

https://www.thekobeissiletter.com/pricing

AI 会降低各个行业的成本;当服务成本下降时,无论工资是否增长,购买力都会上升。

只有在 AI 替代劳动力却没有实质性扩张需求时,“厄运循环”才会占据主导。而当更便宜的算力与更高的生产率带来全新的消费类别与经济活动时,乐观情景就会出现。

真正的冲击是价格崩塌,而不是裁员

可见的裁员更容易被投资者用来讲故事,但更大的故事是服务正在经历价格压缩。只要涉及知识的工作,历来都很昂贵,因为知识是稀缺的——听起来简单,但确实如此。知识供给变得充裕,会带来知识工作的价格下降。

想想医疗行政、法律文书、报税、合规、营销制作、基础编程、客服、教育辅导。这些服务之所以消耗巨大的经济资源,很大程度上是因为它们需要受训的人类持续投入注意力。AI 降低了这种注意力的边际成本。

事实上,如下所示,美国服务业对美国 GDP 的贡献接近 80%。

如果经营一家企业的成本下降,小企业就更容易实现;如果获取服务的成本下降,更多家庭就会参与其中。从某种意义上说,AI 的进步可以像一次“隐形”的减税。

那些利润率依赖高成本认知劳动的公司可能会受损,但更广泛的经济会从更低的服务业通胀与更高的实际购买力中受益。

从“幽灵 GDP”到“富足 GDP”

看空观点依赖于“幽灵 GDP”——也就是在数据里体现为产出,却并没有让家庭受益的产出。与之相对的乐观答案,是我们称之为“富足 GDP”的东西,即产出增长与生活成本下降同时发生。

富足 GDP 并不要求名义收入暴涨,它要求价格下跌的速度快于收入增长。如果 AI 降低了许多人必需的服务成本,即便工资增长放缓,家庭也会获得真实的收益。因此,生产率提升不会消失,而是通过更低的价格被传导出来。

或许这就是为什么过去 70 多年里,生产率的表现一直领先于工资增长:

互联网、电力、大规模制造与抗生素都提供了扩张产出、降低成本的新方式,过程同样充满扰动与波动。但回过头看,这些变化永久性地提高了生活水平。

一个社会如果浪费更少的时间在穿梭于各种系统之间、为重复性的服务付费,那么从功能意义上说,它就更富有。

劳动力市场会重构,而不会消失

一个关键担忧是:AI 会不成比例地影响白领就业,而白领就业驱动着可选消费与住房需求。这确实如此,也是一个合理的担忧,尤其是在贫富差距已经如此巨大的情况下。

然而,AI 在现实世界的灵巧操作与人类身份相关的事务上更吃力。技术工种、需要上手的医疗护理、先进制造,以及以体验驱动的行业,仍然保有结构性需求。很多时候,AI 是在补强这些角色,而不是取代它们。

更重要的是,AI 降低了创业门槛。当一个人就能把会计、营销、支持与编程等任务自动化,小规模创业就更容易发生。我们看多小企业。

事实上,通过 AI 移除准入门槛,可能正是解决我们当前所面对贫富分化问题的办法。

互联网杀死了一些岗位类别,但也创造了全新的岗位。AI 也可能遵循类似的模式:压缩部分白领职能,同时在别处扩展更自驱的经济参与。

SaaS 的“死亡”叙事

AI 显然正在挤压传统的 SaaS 商业模式。采购团队谈判更强硬,一些长尾软件产品面临结构性逆风。但 SaaS 只是交付机制,不是价值创造的终点。

下一代软件将是自适应的、由代理驱动的、以结果为导向的,并且深度集成。赢家不会是静态工具的提供者,而是最能适应变化的人。

每一次技术转移都会重排技术栈,那些给静态工作流定价的公司将会举步维艰。拥有数据、信任、算力、能源与验证能力的公司可能会繁荣。

某一层的利润率压缩并不意味着整个数字经济的崩溃。它意味着转型。

AI 商务重塑市场

看空叙事认为,代理式商务会摧毁中介并消灭手续费。在某种程度上确实如此:当摩擦下降,抽取费用就更困难。

如下所示,在 AI 还没发展到今天的程度之前,稳定币交易量就已经在飙升。为什么?因为市场永远偏好效率。

系统性摩擦降低也会扩大交易量。当价格发现更好、交易成本更低时,会发生更多经济活动。这是一个看多的趋势。

代表消费者行动的代理,可能会压缩那些依赖用户习惯的平台的利润率;但与此同时,它们也可以通过降低搜索成本、提升效率来增加总需求。

生产率是核心变量

决定乐观结果的最终变量是生产率。如果 AI 能在医疗、政府行政、物流、制造与能源优化等领域带来持续的生产率提升,那么结果就是富足,以及更广泛的可及性。

即便是持续的 1–2% 额外生产率提升,在十年尺度上也会产生惊人的复利效应。

AI 给宏观经济带来的这些变化,正在创造历史上最好的投资机会之一。我们为此投入了无数时间,并持续走在前面。如果你有兴趣获取我们的高级分析,了解我们在这段动荡时期如何布局,请访问 thekobeissiletter.com 查看更多研究。

如下所示,生产率已经因为 AI 而在快速增长。美国劳动生产率在 2025 年第三季度加速至两年来最强:

https://x.com/search?q=%24IBM&src=cashtag_click

悲观观点假设生产率提升只会被构建 AI 模型的人独占,无法转化为更广泛的收益。乐观观点则认为,价格压缩与新市场的形成会让收益更广泛地传导出去。

富足减少的不只是成本,还有冲突

AI 驱动的富足有一个最少被讨论的含义:地缘政治。现代历史的大多数战争都围绕稀缺展开:能源、食物、贸易路线、工业产能、劳动力与技术。当资源受限、增长显得零和时,国家就会竞争。但富足会改变一切。

如果 AI 实质性降低了能源、制造设计、物流与服务的生产成本,全球“蛋糕”就会变大。当生产率上升、边际成本下降时,经济增长就不再那么依赖从别人那里榨取优势。这将终结战争,并可能带来人类历史上一些最和平的时期。

经济战也是如此,比如我们现在正经历的这场持续一年的贸易战。

关税是在一个国内产业难以在成本上竞争的世界里,用来保护的工具。但如果 AI 让各处的生产成本都崩塌了,我们还为什么需要关税?在高度富足的环境里,保护主义会变得在经济上低效。

历史表明,从长期看,技术加速的时期往往会降低全球冲突。二战后的工业扩张降低了主要大国之间直接对抗的激励。

AI 驱动的富足可能会加速这种动态。如果能源管理更高效、供应链更有韧性、通过自动化实现更本地化的生产,那么国家的脆弱性就会降低。当经济安全上升,地缘政治侵略就变得不那么理性。

最乐观的 AI 结果,不只是更高的生产率或更高的股指,而是一个经济增长更不零和的世界。

结论:如果世界并不会终结呢?

AI 会放大结果。如果制度无法适应,它会放大脆弱性;如果生产率跑赢扰动,它也会放大繁荣。

Anthropic 的“打击”是在发出信号:工作流正在被重新定价,认知劳动正在变得更便宜——这是一场清晰的转型。

但转型不等于崩溃。每一次重大的技术革命在开始时看起来都像去稳定化。

今天最被低估的可能性不是反乌托邦,而是富足。AI 可能压缩寻租、减少摩擦、重构劳动力市场,但它也可能带来现代史上最大的真实生产力扩张。

“全球智能危机”和“全球智能繁荣”的差别不在于能力,而在于适应。

而世界一直都有办法适应。

最后,那些能够在当下的动荡时期保持客观、并遵循流程的人,正在经历一些有史以来最好的交易环境。

客观且系统化的方法,让我们的表现跑赢了市场基准。如下所示,自 2020 年以来,我们的投资策略回报接近标普 500 的五倍。

如果你有兴趣接收我们的付费每日分析,可以通过加入我们的服务来实现。

关注我们 @KobeissiLetter,获取这一进展过程中的实时分析。

链接: http://x.com/i/article/2026102137047126016

相关笔记

The stock market just erased -$800 BILLION in market cap because AI "taking over the world" is becoming the consensus view. That view is too obvious. And the "obvious" trade never actually wins. Before we begin, BOOKMARK this article and refer back to it over the next 12 months.

股市刚刚抹去了 -8000 亿美元的市值,因为“AI 接管世界”正在成为共识。这个观点太显而易见了。而“显而易见”的交易从来不会赢。在开始之前,把这篇文章加入书签,并在接下来的 12 个月里反复回来对照。

The doomsday scenario went viral because it captured something visceral. It framed AI not as a productivity tool, but as a macroeconomic destabilizer capable of triggering a negative feedback loop: layoffs lead to weaker consumption, weaker consumption leads to more automation, and automation accelerates layoffs.

“末日情景”之所以病毒式传播,是因为它抓住了一种直觉上的恐惧。它把 AI 描绘成的不是生产力工具,而是能够引发负反馈循环的宏观经济“去稳定器”:裁员导致消费走弱,消费走弱推动更多自动化,而自动化又进一步加速裁员。

What's obviously true: AI is not another software feature or efficiency gain. It is a general-purpose capability shock that touches every white-collar workflow simultaneously. Unlikely any revolution in history, AI is getting better at EVERYTHING simultaneously.

显而易见的事实:AI 不是另一个软件功能,也不只是效率提升。它是一种通用能力的冲击,会同时触达每一个白领工作流。不同于历史上的任何一次革命,AI 正在同时变得更擅长“所有事情”。

But, what if the doomsday scenario is false? It assumes demand is fixed, that productivity gains don’t expand markets, and that the system cannot adapt faster than the disruption.

但是,如果末日情景是错的呢?它假设需求是固定的,假设生产率提升不会扩张市场,也假设系统无法比冲击更快地完成适应。

We believe there is a second path that is being dramatically underpriced. The same Anthropic “takedowns” that look like early signs of systemic collapse may ultimately be the start of the largest productivity expansion EVER.

我们认为还有第二条路径,而市场对它的定价严重偏低。那些看起来像系统性崩溃早期信号的 Anthropic“打击”,最终可能反而是史上最大的生产力扩张的起点。

While the below analysis is not a certain outcome, it is important to remember that humanity has ALWAYS prevailed; and the free market ALWAYS works itself out.

虽然下面的分析并非必然结果,但重要的是要记住:人类一直都能挺过去;而自由市场也总会自我出清。

THE ANTHROPIC TAKEDOWNS ARE REAL

ANTHROPIC 的“打击”是真实存在的

Let's start by saying we cannot ignore the market. Anthropic is disrupting the world through Claude, with Fortune 500 companies shedding hundreds of billions of market cap as a result.

先说在前面:我们无法忽视市场。Anthropic 正通过 Claude 颠覆世界,财富 500 强公司因此蒸发了数千亿美元的市值。

It's a story we have seen several times already in 2026: Anthropic releases a new AI tool, Claude gets materially better at coding and workflow automation, and within hours the market collapses for the targeted industry.

这是一段我们在 2026 年已经见过好几次的剧情:Anthropic 发布新的 AI 工具,Claude 在编程与工作流自动化方面出现实质性跃升,而在数小时之内,目标行业的市场就崩了。

If you haven't been paying attention, below are some examples:

如果你还没留意,下面是一些例子:

  1. IBM stock, $IBM, just posted its worst day since October 2000 after Anthropic announced that Claude can streamline COBOL code
  1. IBM 股票 $IBM 在 Anthropic 宣布 Claude 可以精简 COBOL 代码之后,录得自 2000 年 10 月以来最差单日表现
  1. Adobe, $ADBE, falls -30% YTD as generative capabilities compress creative workflows
  1. Adobe $ADBE 年初至今(YTD)下跌 -30%,因为生成式能力正在压缩创意工作流
  1. Cybersecurity names collapse on "Claude Code Security" release
  1. “Claude Code Security”发布后,网络安全概念股集体崩盘

In the above example, the crash in CrowdStrike stock, $CRWD, was literally seen the minute Claude announced "Claude Code Security."

在上面的例子里,CrowdStrike 股票 $CRWD 的暴跌,几乎就是 Claude 宣布“Claude Code Security”的那一分钟发生的。

On February 20th, at 1 PM ET, Claude announced "Claude Code Security." This is an automated AI tool that scans codebases for vulnerabilities.

2 月 20 日下午 1 点(美东时间),Claude 宣布推出“Claude Code Security”。这是一个自动化 AI 工具,用于扫描代码库中的漏洞。

Just two trading days later, CrowdStrike stock, $CRWD, erased -$20 BILLION of market cap on the news.

仅仅两个交易日之后,CrowdStrike 股票 $CRWD 因这一消息抹去了 -200 亿美元的市值。

These reactions are not irrational. Markets try to price real time margin compression. When AI replicates what workers do, pricing power shifts to the buyer. That is the first-order impact, and it is very real.

这些反应并不非理性。市场试图为“实时的利润率压缩”定价。当 AI 复制了工人正在做的事,定价权就会向买方转移。这是一阶影响,而且非常真实。

Commoditization is not collapse. Rather, it is how technology lowers costs and expands access. The personal computer commoditized computing, the internet commoditized distribution, cloud commoditized infrastructure, and AI is commoditizing cognition.

商品化不等于崩溃。相反,它是技术降低成本、扩大可得性的方式。个人电脑让计算商品化,互联网让分发商品化,云让基础设施商品化,而 AI 正在让认知商品化。

There is no question that some legacy workflows will experience compression of margins. The question is, do lower cognitive costs collapse the economy or do they allow it to expand dramatically?

毫无疑问,一些传统工作流会遭遇利润率压缩。问题在于:更低的认知成本会让经济崩塌,还是会让经济大幅扩张?

THE DOOM LOOP ASSUMES DEMAND IS FIXED

“厄运循环”假设需求是固定的

The bearish loop creates a simplified linear model: AI gets better, businesses reduce headcount and wages, then buying drops, businesses invest in AI again to defend their margins, and the downward cycle repeats. This assumes a completely stagnant economy.

看空的循环给出一个简化的线性模型:AI 变得更强,企业减少人数与工资,于是购买力下降,企业为了捍卫利润率再次投资 AI,然后下行循环重复。这等于假设经济完全停滞不前。

History suggests otherwise. When the cost of producing something collapses, demand rarely stays flat, it expands. When compute costs fell, we did not consume the same amount of compute more cheaply. We consumed orders of magnitude more of it and built entirely new industries on top.

历史并不支持这种假设。当生产某种东西的成本崩塌时,需求很少保持不变,它往往会扩张。当算力成本下降时,我们并不是以更低的价格消费同样数量的算力;我们消费了数量级更高的算力,并在其上构建了全新的行业。

As shown below, the price of personal computers are now 99.9% cheaper today than they were in 1980.

如下所示,个人电脑的价格如今相比 1980 年已经便宜了 99.9%。

AI decreases costs in every sector and when service costs go down, purchasing power increases with or without wage growth.

AI 会降低各个行业的成本;当服务成本下降时,无论工资是否增长,购买力都会上升。

The doom loop becomes dominant only if AI replaces labor without materially expanding demand. The optimistic scenario emerges if cheaper compute and productivity yields entirely new categories of consumption and economic activity.

只有在 AI 替代劳动力却没有实质性扩张需求时,“厄运循环”才会占据主导。而当更便宜的算力与更高的生产率带来全新的消费类别与经济活动时,乐观情景就会出现。

THE REAL SHOCK IS PRICE COLLAPSE, NOT LAYOFFS

真正的冲击是价格崩塌,而不是裁员

The observable layoffs are an easier story for investors to sell, but services undergoing price compression is the bigger story. Work that involves knowledge has always been expensive because of the scarcity of knowledge, as simple as it sounds, it's true. An abundant knowledge supply leads to a reduction in the price of knowledge work.

可见的裁员更容易被投资者用来讲故事,但更大的故事是服务正在经历价格压缩。只要涉及知识的工作,历来都很昂贵,因为知识是稀缺的——听起来简单,但确实如此。知识供给变得充裕,会带来知识工作的价格下降。

Consider healthcare administration, legal documentation, tax preparation, compliance, marketing production, basic coding, customer service, and educational tutoring. These services consume massive economic resources largely because they require trained human attention. AI reduces the marginal cost of that attention.

想想医疗行政、法律文书、报税、合规、营销制作、基础编程、客服、教育辅导。这些服务之所以消耗巨大的经济资源,很大程度上是因为它们需要受训的人类持续投入注意力。AI 降低了这种注意力的边际成本。

In fact, as shown below, the US Services Sector contributes close to 80% of US GDP.

事实上,如下所示,美国服务业对美国 GDP 的贡献接近 80%。

If the cost of running a business falls, small businesses become more attainable and if the cost of accessing services falls, more households participate. In a way, AI advancements can function as an "invisible" tax cut.

如果经营一家企业的成本下降,小企业就更容易实现;如果获取服务的成本下降,更多家庭就会参与其中。从某种意义上说,AI 的进步可以像一次“隐形”的减税。

The companies whose margins depend on high-cost cognitive labor may suffer, but the broader economy benefits from lower service inflation and higher real purchasing power.

那些利润率依赖高成本认知劳动的公司可能会受损,但更广泛的经济会从更低的服务业通胀与更高的实际购买力中受益。

FROM “GHOST GDP” TO “ABUNDANCE GDP”

从“幽灵 GDP”到“富足 GDP”

The bear case relies on "Ghost GDP," which is output that shows up in data but does not benefit households. The optimistic counter is what we are calling “Abundance GDP," which is output growth combined with falling costs of living.

看空观点依赖于“幽灵 GDP”——也就是在数据里体现为产出,却并没有让家庭受益的产出。与之相对的乐观答案,是我们称之为“富足 GDP”的东西,即产出增长与生活成本下降同时发生。

Abundance GDP does not require nominal incomes to surge, it requires prices to fall faster than incomes. If AI reduces the cost of services which are essential to many, households experience real gains even if their wage growth slows. As a result, productivity gains do not disappear, rather they are transmitted through lower prices.

富足 GDP 并不要求名义收入暴涨,它要求价格下跌的速度快于收入增长。如果 AI 降低了许多人必需的服务成本,即便工资增长放缓,家庭也会获得真实的收益。因此,生产率提升不会消失,而是通过更低的价格被传导出来。

Perhaps this is why productivity has outperformed wage growth over the last 70+ years:

或许这就是为什么过去 70 多年里,生产率的表现一直领先于工资增长:

The internet, electricity, mass manufacturing, and antibiotics each provided new ways to expand output and reduce cost which still being disruptive and volatile. However, in retrospect, those changes increased the standard of living permanently.

互联网、电力、大规模制造与抗生素都提供了扩张产出、降低成本的新方式,过程同样充满扰动与波动。但回过头看,这些变化永久性地提高了生活水平。

A society that wastes fewer hours navigating systems and paying for redundant services is, functionally, wealthier.

一个社会如果浪费更少的时间在穿梭于各种系统之间、为重复性的服务付费,那么从功能意义上说,它就更富有。

LABOR MARKETS RESTRUCTURE, NOT VANISH

劳动力市场会重构,而不会消失

A key concern is that AI disproportionately affects white-collar employment, which drives discretionary consumption and housing demand. This is true, and a legitimate concern, particularly as the wealth divide is already so massive.

一个关键担忧是:AI 会不成比例地影响白领就业,而白领就业驱动着可选消费与住房需求。这确实如此,也是一个合理的担忧,尤其是在贫富差距已经如此巨大的情况下。

However, AI struggles more with physical-world dexterity and human identity. Skilled trades, hands-on healthcare, advanced manufacturing, and experience-driven industries retain structural demand. In many cases, AI complements these roles rather than replaces them.

然而,AI 在现实世界的灵巧操作与人类身份相关的事务上更吃力。技术工种、需要上手的医疗护理、先进制造,以及以体验驱动的行业,仍然保有结构性需求。很多时候,AI 是在补强这些角色,而不是取代它们。

More importantly, AI lowers the barrier to entrepreneurship. When one individual can automate accounting, marketing, support, and coding tasks, small-scale business formation becomes easier. We are BULLISH on small businesses.

更重要的是,AI 降低了创业门槛。当一个人就能把会计、营销、支持与编程等任务自动化,小规模创业就更容易发生。我们看多小企业。

In fact, the removal of barriers to entry through AI may be the solution to flatten the wealth divide that we currently face.

事实上,通过 AI 移除准入门槛,可能正是解决我们当前所面对贫富分化问题的办法。

The internet killed certain job categories but created entirely new ones. AI may follow a similar pattern, compressing some white-collar functions while expanding self-directed economic participation elsewhere.

互联网杀死了一些岗位类别,但也创造了全新的岗位。AI 也可能遵循类似的模式:压缩部分白领职能,同时在别处扩展更自驱的经济参与。

THE SaaS “DEATH” STORY

SaaS 的“死亡”叙事

AI clearly pressures the traditional SaaS business model. Procurement teams are negotiating harder and some long-tail software products face structural headwinds. But SaaS is a delivery mechanism, not the endpoint of value creation.

AI 显然正在挤压传统的 SaaS 商业模式。采购团队谈判更强硬,一些长尾软件产品面临结构性逆风。但 SaaS 只是交付机制,不是价值创造的终点。

The next generation of software is adaptive, agent-driven, outcome-based, and deeply integrated. The winners will not be static tool providers, they will be those who can best adapt to change.

下一代软件将是自适应的、由代理驱动的、以结果为导向的,并且深度集成。赢家不会是静态工具的提供者,而是最能适应变化的人。

Every technological shift reorders the stack and the companies pricing static workflows WILL struggle. The companies owning data, trust, compute, energy, and verification may thrive.

每一次技术转移都会重排技术栈,那些给静态工作流定价的公司将会举步维艰。拥有数据、信任、算力、能源与验证能力的公司可能会繁荣。

Margin compression in one layer does not imply collapse of the entire digital economy. It signals transition.

某一层的利润率压缩并不意味着整个数字经济的崩溃。它意味着转型。

AI COMMERCE RESRUCTURES MARKETS

AI 商务重塑市场

The bearish narrative argues that agentic commerce destroys intermediation and eliminates fees. In part, it does. When friction declines, fee extraction becomes harder.

看空叙事认为,代理式商务会摧毁中介并消灭手续费。在某种程度上确实如此:当摩擦下降,抽取费用就更困难。

As shown below, Stablecoin transaction volumes are already skyrocketing, even before AI became with it is today. Why? Because the market always favors efficiency.

如下所示,在 AI 还没发展到今天的程度之前,稳定币交易量就已经在飙升。为什么?因为市场永远偏好效率。

Lower systemic friction also expands transaction volume. When price discovery improves and transaction costs fall, more economic activity occurs. This is a BULLISH trend.

系统性摩擦降低也会扩大交易量。当价格发现更好、交易成本更低时,会发生更多经济活动。这是一个看多的趋势。

Agents acting on behalf of consumers may compress margins for platforms built on habit. Yet, they can simultaneously increase total demand by lowering search costs and improving efficiency.

代表消费者行动的代理,可能会压缩那些依赖用户习惯的平台的利润率;但与此同时,它们也可以通过降低搜索成本、提升效率来增加总需求。

PRODUCTIVITY IS THE CORE VARIABLE

生产率是核心变量

The ultimate determinant of the optimistic outcome is productivity. If AI delivers sustained productivity gains across healthcare, government administration, logistics, manufacturing, and energy optimization, then the result is abundance and increased access for all.

决定乐观结果的最终变量是生产率。如果 AI 能在医疗、政府行政、物流、制造与能源优化等领域带来持续的生产率提升,那么结果就是富足,以及更广泛的可及性。

Even a sustained 1–2% incremental productivity boost compounds dramatically over a decade.

即便是持续的 1–2% 额外生产率提升,在十年尺度上也会产生惊人的复利效应。

The shifts we are seeing in the macroeconomy as a result of AI have resulted in some of the best investment opportunities in history. This is something we have spent countless hours on and continue to get ahead of. If you are interested in receiving our premium analysis and seeing how we are positioned in these times of disruption, see thekobeissiletter.com for more of our research.

AI 给宏观经济带来的这些变化,正在创造历史上最好的投资机会之一。我们为此投入了无数时间,并持续走在前面。如果你有兴趣获取我们的高级分析,了解我们在这段动荡时期如何布局,请访问 thekobeissiletter.com 查看更多研究。

As shown below, productivity is already growing at a rapid pace as a result of AI. US labor productivity accelerated Q3 2025 to its strongest pace in two years:

如下所示,生产率已经因为 AI 而在快速增长。美国劳动生产率在 2025 年第三季度加速至两年来最强:

The pessimistic view assumes productivity gains accrue exclusively to those who build the AI models and do not translate into broader benefits. The optimistic view assumes price compression and new market formation transmit gains more widely.

悲观观点假设生产率提升只会被构建 AI 模型的人独占,无法转化为更广泛的收益。乐观观点则认为,价格压缩与新市场的形成会让收益更广泛地传导出去。

ABUNDANCE REDUCES CONFLICT, NOT JUST COSTS

富足减少的不只是成本,还有冲突

One of the most under-discussed implications of AI-driven abundance is geopolitical. For most of modern history, wars have been fought over scarcity: energy, food, trade routes, industrial capacity, labor, and technology. Nations compete when resources are constrained and growth feels zero-sum. But abundance changes EVERYTHING.

AI 驱动的富足有一个最少被讨论的含义:地缘政治。现代历史的大多数战争都围绕稀缺展开:能源、食物、贸易路线、工业产能、劳动力与技术。当资源受限、增长显得零和时,国家就会竞争。但富足会改变一切。

If AI materially lowers the cost of production across energy, manufacturing design, logistics, and services, the global pie expands. When productivity rises and marginal costs fall, economic growth becomes less dependent on extracting advantage from others. This will end wars, and potential result in some of the most peaceful times in human history.

如果 AI 实质性降低了能源、制造设计、物流与服务的生产成本,全球“蛋糕”就会变大。当生产率上升、边际成本下降时,经济增长就不再那么依赖从别人那里榨取优势。这将终结战争,并可能带来人类历史上一些最和平的时期。

The same goes with economic warfare, such as the year-long trade war we are in now.

经济战也是如此,比如我们现在正经历的这场持续一年的贸易战。

Tariffs are tools of protection in a world where domestic industries struggle to compete on cost. But if AI collapses production costs everywhere, why would we need tariffs anymore? In a high-abundance environment, protectionism becomes economically inefficient.

关税是在一个国内产业难以在成本上竞争的世界里,用来保护的工具。但如果 AI 让各处的生产成本都崩塌了,我们还为什么需要关税?在高度富足的环境里,保护主义会变得在经济上低效。

History shows that periods of technological acceleration often reduce global conflict in the long run. Post-World War II industrial expansion reduced incentives for direct confrontation among major powers.

历史表明,从长期看,技术加速的时期往往会降低全球冲突。二战后的工业扩张降低了主要大国之间直接对抗的激励。

AI-driven abundance could accelerate that dynamic. If energy becomes more efficiently managed, supply chains more resilient, and production more localized through automation, nations become less vulnerable. When economic security rises, geopolitical aggression becomes less rational.

AI 驱动的富足可能会加速这种动态。如果能源管理更高效、供应链更有韧性、通过自动化实现更本地化的生产,那么国家的脆弱性就会降低。当经济安全上升,地缘政治侵略就变得不那么理性。

The most optimistic AI outcome is not just higher productivity or higher equity indices. It is a world where economic growth is less zero-sum.

最乐观的 AI 结果,不只是更高的生产率或更高的股指,而是一个经济增长更不零和的世界。

CONCLUSION: WHAT IF THE WORLD DOESN'T END?

结论:如果世界并不会终结呢?

AI amplifies outcomes. It can amplify fragility if institutions fail to adapt and it can also amplify prosperity if productivity outpaces disruption.

AI 会放大结果。如果制度无法适应,它会放大脆弱性;如果生产率跑赢扰动,它也会放大繁荣。

The Anthropic takedowns are signals that workflows are being repriced and cognitive labor is becoming cheaper, a clear transition.

Anthropic 的“打击”是在发出信号:工作流正在被重新定价,认知劳动正在变得更便宜——这是一场清晰的转型。

But transition is not the same as collapse as every major technological revolution has looked destabilizing at the start.

但转型不等于崩溃。每一次重大的技术革命在开始时看起来都像去稳定化。

The most underpriced possibility today is not dystopia, it's abundance. AI may compress rents, reduce friction, and restructure labor markets, but it may also deliver the largest real productivity expansion in modern history.

今天最被低估的可能性不是反乌托邦,而是富足。AI 可能压缩寻租、减少摩擦、重构劳动力市场,但它也可能带来现代史上最大的真实生产力扩张。

The difference between “Global Intelligence Crisis” and “Global Intelligence Boom” is not capability, it is adaptation.

“全球智能危机”和“全球智能繁荣”的差别不在于能力,而在于适应。

And the world has always found a way to adapt.

而世界一直都有办法适应。

Lastly, those who are able to remain objective and follow a process during the current times of disruption are realizing some of the best trading conditions ever.

最后,那些能够在当下的动荡时期保持客观、并遵循流程的人,正在经历一些有史以来最好的交易环境。

An objective and systematic approach is what has led to our outperformance of market benchmarks. As shown below, our investment strategy has returned nearly five times the S&P 500 since 2020.

客观且系统化的方法,让我们的表现跑赢了市场基准。如下所示,自 2020 年以来,我们的投资策略回报接近标普 500 的五倍。

If you are interested in receiving our premium daily analysis, you may do so by joining our service here.

如果你有兴趣接收我们的付费每日分析,可以通过加入我们的服务来实现。

Follow us @KobeissiLetter for real time analysis as this develops.

关注我们 @KobeissiLetter,获取这一进展过程中的实时分析。

Link: http://x.com/i/article/2026102137047126016

链接: http://x.com/i/article/2026102137047126016

相关笔记

It's Too Obvious. What If AI Doesn't Actually End The World?

  • Source: https://x.com/kobeissiletter/status/2026125293149163694?s=46
  • Mirror: https://x.com/kobeissiletter/status/2026125293149163694?s=46
  • Published: 2026-02-24T02:41:28+00:00
  • Saved: 2026-02-26

Content

The stock market just erased -$800 BILLION in market cap because AI "taking over the world" is becoming the consensus view. That view is too obvious. And the "obvious" trade never actually wins. Before we begin, BOOKMARK this article and refer back to it over the next 12 months.

The doomsday scenario went viral because it captured something visceral. It framed AI not as a productivity tool, but as a macroeconomic destabilizer capable of triggering a negative feedback loop: layoffs lead to weaker consumption, weaker consumption leads to more automation, and automation accelerates layoffs.

What's obviously true: AI is not another software feature or efficiency gain. It is a general-purpose capability shock that touches every white-collar workflow simultaneously. Unlikely any revolution in history, AI is getting better at EVERYTHING simultaneously.

But, what if the doomsday scenario is false? It assumes demand is fixed, that productivity gains don’t expand markets, and that the system cannot adapt faster than the disruption.

We believe there is a second path that is being dramatically underpriced. The same Anthropic “takedowns” that look like early signs of systemic collapse may ultimately be the start of the largest productivity expansion EVER.

While the below analysis is not a certain outcome, it is important to remember that humanity has ALWAYS prevailed; and the free market ALWAYS works itself out.

THE ANTHROPIC TAKEDOWNS ARE REAL

Let's start by saying we cannot ignore the market. Anthropic is disrupting the world through Claude, with Fortune 500 companies shedding hundreds of billions of market cap as a result.

It's a story we have seen several times already in 2026: Anthropic releases a new AI tool, Claude gets materially better at coding and workflow automation, and within hours the market collapses for the targeted industry.

If you haven't been paying attention, below are some examples:

https://x.com/@KobeissiLetter

  1. IBM stock, $IBM, just posted its worst day since October 2000 after Anthropic announced that Claude can streamline COBOL code

  2. Adobe, $ADBE, falls -30% YTD as generative capabilities compress creative workflows

  3. Cybersecurity names collapse on "Claude Code Security" release

In the above example, the crash in CrowdStrike stock, $CRWD, was literally seen the minute Claude announced "Claude Code Security."

On February 20th, at 1 PM ET, Claude announced "Claude Code Security." This is an automated AI tool that scans codebases for vulnerabilities.

Just two trading days later, CrowdStrike stock, $CRWD, erased -$20 BILLION of market cap on the news.

These reactions are not irrational. Markets try to price real time margin compression. When AI replicates what workers do, pricing power shifts to the buyer. That is the first-order impact, and it is very real.

Commoditization is not collapse. Rather, it is how technology lowers costs and expands access. The personal computer commoditized computing, the internet commoditized distribution, cloud commoditized infrastructure, and AI is commoditizing cognition.

There is no question that some legacy workflows will experience compression of margins. The question is, do lower cognitive costs collapse the economy or do they allow it to expand dramatically?

THE DOOM LOOP ASSUMES DEMAND IS FIXED

The bearish loop creates a simplified linear model: AI gets better, businesses reduce headcount and wages, then buying drops, businesses invest in AI again to defend their margins, and the downward cycle repeats. This assumes a completely stagnant economy.

History suggests otherwise. When the cost of producing something collapses, demand rarely stays flat, it expands. When compute costs fell, we did not consume the same amount of compute more cheaply. We consumed orders of magnitude more of it and built entirely new industries on top.

As shown below, the price of personal computers are now 99.9% cheaper today than they were in 1980.

https://www.thekobeissiletter.com/pricing

AI decreases costs in every sector and when service costs go down, purchasing power increases with or without wage growth.

The doom loop becomes dominant only if AI replaces labor without materially expanding demand. The optimistic scenario emerges if cheaper compute and productivity yields entirely new categories of consumption and economic activity.

THE REAL SHOCK IS PRICE COLLAPSE, NOT LAYOFFS

The observable layoffs are an easier story for investors to sell, but services undergoing price compression is the bigger story. Work that involves knowledge has always been expensive because of the scarcity of knowledge, as simple as it sounds, it's true. An abundant knowledge supply leads to a reduction in the price of knowledge work.

Consider healthcare administration, legal documentation, tax preparation, compliance, marketing production, basic coding, customer service, and educational tutoring. These services consume massive economic resources largely because they require trained human attention. AI reduces the marginal cost of that attention.

In fact, as shown below, the US Services Sector contributes close to 80% of US GDP.

If the cost of running a business falls, small businesses become more attainable and if the cost of accessing services falls, more households participate. In a way, AI advancements can function as an "invisible" tax cut.

The companies whose margins depend on high-cost cognitive labor may suffer, but the broader economy benefits from lower service inflation and higher real purchasing power.

FROM “GHOST GDP” TO “ABUNDANCE GDP”

The bear case relies on "Ghost GDP," which is output that shows up in data but does not benefit households. The optimistic counter is what we are calling “Abundance GDP," which is output growth combined with falling costs of living.

Abundance GDP does not require nominal incomes to surge, it requires prices to fall faster than incomes. If AI reduces the cost of services which are essential to many, households experience real gains even if their wage growth slows. As a result, productivity gains do not disappear, rather they are transmitted through lower prices.

Perhaps this is why productivity has outperformed wage growth over the last 70+ years:

The internet, electricity, mass manufacturing, and antibiotics each provided new ways to expand output and reduce cost which still being disruptive and volatile. However, in retrospect, those changes increased the standard of living permanently.

A society that wastes fewer hours navigating systems and paying for redundant services is, functionally, wealthier.

LABOR MARKETS RESTRUCTURE, NOT VANISH

A key concern is that AI disproportionately affects white-collar employment, which drives discretionary consumption and housing demand. This is true, and a legitimate concern, particularly as the wealth divide is already so massive.

However, AI struggles more with physical-world dexterity and human identity. Skilled trades, hands-on healthcare, advanced manufacturing, and experience-driven industries retain structural demand. In many cases, AI complements these roles rather than replaces them.

More importantly, AI lowers the barrier to entrepreneurship. When one individual can automate accounting, marketing, support, and coding tasks, small-scale business formation becomes easier. We are BULLISH on small businesses.

In fact, the removal of barriers to entry through AI may be the solution to flatten the wealth divide that we currently face.

The internet killed certain job categories but created entirely new ones. AI may follow a similar pattern, compressing some white-collar functions while expanding self-directed economic participation elsewhere.

THE SaaS “DEATH” STORY

AI clearly pressures the traditional SaaS business model. Procurement teams are negotiating harder and some long-tail software products face structural headwinds. But SaaS is a delivery mechanism, not the endpoint of value creation.

The next generation of software is adaptive, agent-driven, outcome-based, and deeply integrated. The winners will not be static tool providers, they will be those who can best adapt to change.

Every technological shift reorders the stack and the companies pricing static workflows WILL struggle. The companies owning data, trust, compute, energy, and verification may thrive.

Margin compression in one layer does not imply collapse of the entire digital economy. It signals transition.

AI COMMERCE RESRUCTURES MARKETS

The bearish narrative argues that agentic commerce destroys intermediation and eliminates fees. In part, it does. When friction declines, fee extraction becomes harder.

As shown below, Stablecoin transaction volumes are already skyrocketing, even before AI became with it is today. Why? Because the market always favors efficiency.

Lower systemic friction also expands transaction volume. When price discovery improves and transaction costs fall, more economic activity occurs. This is a BULLISH trend.

Agents acting on behalf of consumers may compress margins for platforms built on habit. Yet, they can simultaneously increase total demand by lowering search costs and improving efficiency.

PRODUCTIVITY IS THE CORE VARIABLE

The ultimate determinant of the optimistic outcome is productivity. If AI delivers sustained productivity gains across healthcare, government administration, logistics, manufacturing, and energy optimization, then the result is abundance and increased access for all.

Even a sustained 1–2% incremental productivity boost compounds dramatically over a decade.

The shifts we are seeing in the macroeconomy as a result of AI have resulted in some of the best investment opportunities in history. This is something we have spent countless hours on and continue to get ahead of. If you are interested in receiving our premium analysis and seeing how we are positioned in these times of disruption, see thekobeissiletter.com for more of our research.

As shown below, productivity is already growing at a rapid pace as a result of AI. US labor productivity accelerated Q3 2025 to its strongest pace in two years:

https://x.com/search?q=%24IBM&src=cashtag_click

The pessimistic view assumes productivity gains accrue exclusively to those who build the AI models and do not translate into broader benefits. The optimistic view assumes price compression and new market formation transmit gains more widely.

ABUNDANCE REDUCES CONFLICT, NOT JUST COSTS

One of the most under-discussed implications of AI-driven abundance is geopolitical. For most of modern history, wars have been fought over scarcity: energy, food, trade routes, industrial capacity, labor, and technology. Nations compete when resources are constrained and growth feels zero-sum. But abundance changes EVERYTHING.

If AI materially lowers the cost of production across energy, manufacturing design, logistics, and services, the global pie expands. When productivity rises and marginal costs fall, economic growth becomes less dependent on extracting advantage from others. This will end wars, and potential result in some of the most peaceful times in human history.

The same goes with economic warfare, such as the year-long trade war we are in now.

Tariffs are tools of protection in a world where domestic industries struggle to compete on cost. But if AI collapses production costs everywhere, why would we need tariffs anymore? In a high-abundance environment, protectionism becomes economically inefficient.

History shows that periods of technological acceleration often reduce global conflict in the long run. Post-World War II industrial expansion reduced incentives for direct confrontation among major powers.

AI-driven abundance could accelerate that dynamic. If energy becomes more efficiently managed, supply chains more resilient, and production more localized through automation, nations become less vulnerable. When economic security rises, geopolitical aggression becomes less rational.

The most optimistic AI outcome is not just higher productivity or higher equity indices. It is a world where economic growth is less zero-sum.

CONCLUSION: WHAT IF THE WORLD DOESN'T END?

AI amplifies outcomes. It can amplify fragility if institutions fail to adapt and it can also amplify prosperity if productivity outpaces disruption.

The Anthropic takedowns are signals that workflows are being repriced and cognitive labor is becoming cheaper, a clear transition.

But transition is not the same as collapse as every major technological revolution has looked destabilizing at the start.

The most underpriced possibility today is not dystopia, it's abundance. AI may compress rents, reduce friction, and restructure labor markets, but it may also deliver the largest real productivity expansion in modern history.

The difference between “Global Intelligence Crisis” and “Global Intelligence Boom” is not capability, it is adaptation.

And the world has always found a way to adapt.

Lastly, those who are able to remain objective and follow a process during the current times of disruption are realizing some of the best trading conditions ever.

An objective and systematic approach is what has led to our outperformance of market benchmarks. As shown below, our investment strategy has returned nearly five times the S&P 500 since 2020.

If you are interested in receiving our premium daily analysis, you may do so by joining our service here.

Follow us @KobeissiLetter for real time analysis as this develops.

Link: http://x.com/i/article/2026102137047126016

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