Author: The Kobeissi Letter

Translated by: ShenChao TechFlow

ShenChao Guide: As AI tools like Anthropic demonstrate astonishing capabilities in code and workflow automation, the market has fallen into a panic over "AI doomsday theories," resulting in the evaporation of hundreds of billions of dollars in market value. However, this article presents an incredibly enlightening counter-perspective: the short-term impacts triggered by AI are not a harbinger of economic collapse, but rather an inevitable process of drastically lower "cognitive costs." The author points out through comparisons with the PC revolution of the 1980s and historical productivity data that a true "Abundance GDP" era will only be ushered in when technology makes knowledge acquisition cheap and plentiful. This is not just a reconstruction of the labor force; it is the only way to geopolitics easing and a global productivity explosion.

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

The stock market has just erased -800 billion dollars in value because the idea that "AI will take over the world" is becoming a consensus viewpoint. This viewpoint is too obvious. And "obvious" trades never truly win.

This doomsday scenario has gone viral because it captures something instinctual. It portrays AI not as a productivity tool, but as a macroeconomic destabilizer that can trigger negative feedback loops: layoffs lead to weakened consumption, weakened consumption leads to more automation, and automation accelerates layoffs.

The obvious fact is: AI is not just another software feature or efficiency-improving tool. It is a general capability shock that impacts every white-collar workflow. Unlike any previous revolution in history, AI is simultaneously becoming skilled at "everything."

But what if the doomsday scenario is wrong? It assumes that demand is fixed, that productivity gains will not expand the market, and that the speed of system adaptation cannot exceed the speed of destruction.

We believe there is a second path, one that is greatly underestimated. What appear to be early signs of systemic collapse, such as Anthropic "takedowns," may ultimately be the beginning of the largest productivity expansion in history.

Before we begin, please bookmark this article and refer back to it over the next 12 months. While the analysis that follows is not a certain outcome, it is important to remember that humanity has always managed to turn defeat into victory; and that free markets can always self-correct.

Anthropic's "Takedowns" are Real

First, we must clarify that we cannot ignore the market. Anthropic is disrupting the world through Claude, resulting in a loss of hundreds of billions in market value for Fortune 500 companies.

This is a story we have seen multiple times in 2026: Anthropic releases a new AI tool, Claude makes substantial progress in programming and workflow automation, and within hours, the market in the target industry collapses.

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

Stock reaction to Claude's announcement

• IBM stock ($IBM) just recorded its worst day since October 2000, after Anthropic announced that Claude could simplify COBOL code.
• Adobe ($ADBE) has dropped -30% this year, as generative capabilities have compressed creative workflows.
• The cybersecurity sector collapsed after the release of "Claude Code Security."

In the above examples, CrowdStrike stock ($CRWD) nearly plummeted the minute Claude announced "Claude Code Security."

On February 20 at 1 PM Eastern Time, Claude announced "Claude Code Security." This is an automated AI tool that can scan for vulnerabilities in codebases.

Just two trading days later, CrowdStrike stock ($CRWD) evaporated -20 billion dollars in market value in response to that news.

These reactions are not irrational. The market is trying to price real-time profit compression. When AI replicates workers' tasks, the pricing power shifts to the buyers. This is a first-order effect, and it's very real.

Commoditization is not the same as collapse. On the contrary, it is a way for technology to lower costs and expand access. Personal computers commoditized computing, the internet commoditized distribution, cloud computing commoditized infrastructure, and AI is commoditizing cognition.

There is no doubt that some traditional workflows will experience a compression of profit margins. The question is whether lower cognitive costs will lead to economic collapse, or allow for significant expansion?

"Doomsday Cycle" Assumes Fixed Demand

The bearish cycle creates a simplified linear model: AI gets better, companies reduce layoffs and wages, then purchasing power declines, leading companies to reinvest in AI to defend profits, and so the cycle repeats. This assumes a completely stagnant economy.

History shows that reality is not so. When the cost of producing something collapses, demand rarely remains unchanged; instead, it expands. When computing costs decline, we do not consume the same amount of computing at a cheaper price. We consume orders of magnitude more computing and build entirely new industries on top of that.

As shown in the chart, today’s personal computers are 99.9% cheaper than they were in 1980.

Caption: Price trends of personal computers from 1980 to 2015

AI lowers costs across every industry, and when the cost of services declines, purchasing power increases, regardless of wage growth.

The doomsday cycle only dominates if AI replaces the workforce without significantly expanding demand. If cheap computing and productivity create entirely new categories of consumption and economic activity, then an optimistic scenario emerges.

The Real Shock is Price Collapse, Not Unemployment

Investors find it easier to promote the "obvious" layoff story, but the price compression that the services sector is experiencing is the bigger news. Knowledge work is expensive due to the scarcity of knowledge—this sounds simple, but it is indeed the case. The abundance of knowledge supply leads to a decline in the price of knowledge work.

Think of medical management, legal documentation, tax filings, compliance checks, marketing production, basic programming, customer service, and educational tutoring. These services consume significant economic resources, largely because they require trained human attention. AI lowers the marginal cost of that attention.

In fact, as shown in the chart, the services sector contributes nearly 80% of the US GDP.

If the cost of doing business goes down, small businesses become more accessible; if the cost of obtaining services decreases, more households will participate. To some extent, advances in AI can act as an "invisible" tax cut.

Those whose profits rely on high-cost cognitive labor may suffer losses, but the broader economy will benefit from lower service inflation and higher real purchasing power.

From "Ghost GDP" to "Abundance GDP"

The arguments of the bears rely on "Ghost GDP," which refers to outputs that are reflected in data but do not benefit households. The optimistic counter-argument is what we call "Abundance GDP," where output growth combines with a decrease in the cost of living.

"Abundance GDP" does not require nominal income to soar; it requires the rate of price decline to outpace the rate of income decline. If AI lowers the costs of services that many people need, then even if household wage growth slows, their real earnings will increase. Therefore, productivity gains do not disappear but are transmitted through lower prices.

This may explain why productivity performance has outpaced wage growth for over the past 70 years:

The internet, electricity, mass manufacturing, and antibiotics all provided new ways to expand output and reduce costs, although these processes were full of destruction and volatility. However, looking back, these changes permanently improved living standards.

A society that reduces time wasted in navigating complex systems and paying for redundant services will functionally become wealthier.

The Labor Market is Restructuring, Not Vanishing

A core concern is that AI will disproportionately impact white-collar jobs, which drive non-essential consumption and housing demand. This is a fact and a reasonable concern, especially in the context of such a massive wealth gap.

However, AI faces more difficulties in the physical world and in the identity of human beings. Skilled trades, hands-on healthcare, advanced manufacturing, and experience-driven industries still maintain structural demand. In many cases, AI is a supplement to these roles rather than a replacement.

More importantly, AI lowers the barriers to entry for entrepreneurship. When an individual can automate accounting, marketing, support, and programming tasks, it becomes easier to build small businesses. We are optimistic about small enterprises.

In fact, eliminating barriers to entry through AI may be a solution to the wealth gap issue we currently face.

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

Received, for you to continue modular compilation of the third part (last part). This section will explore the evolution of the SaaS business model, AI's reshaping of market structures, the actual performance of productivity data, and an undervalued perspective: how AI-driven "abundance" reduces global conflict.

The "Demise" Story of SaaS

AI has clearly put pressure on the traditional SaaS (Software as a Service) business model. Procurement teams find negotiations more challenging, and some long-tail software products face structural resistance. But SaaS is just a delivery mechanism, not the endpoint of value creation.

The next generation of software will be adaptive, agent-driven, outcomes-based, and deeply integrated. The winners will not be providers of static tools but those who can adapt to change the most.

Every technological shift rearranges the stack; those pricing static workflows will inevitably struggle. Meanwhile, companies with data, trust, computing power, energy, and validation may thrive.

A certain level of profit compression does not signify the collapse of the entire digital economy; it marks a transformation.

AI Restructures Business Markets

Bears believe that agentic commerce will destroy intermediaries and eliminate fees. To some extent, this is indeed the case. As friction diminishes, it becomes harder to extract fees.

As shown in the chart, even before AI became what it is today, the trading volume of stablecoins was already surging. Why? Because the market always favors efficiency.

Lower systemic friction will also expand transaction volumes. When price discovery mechanisms improve and transaction costs decrease, more economic activity occurs. This is a bullish trend.

Agents representing consumer actions may compress platform profits based on "habits." However, they can synchronously increase total demand by lowering search costs and improving efficiency.

Productivity is the Core Variable

The ultimate determinant of optimistic outcomes is productivity. If AI can provide sustained productivity gains in healthcare, government management, logistics, manufacturing, and energy optimization, the result will be abundance for all humanity and lower barriers to entry.

Even a continuous increase in productivity of 1–2% can lead to a massive compounding effect over a decade.

The macroeconomic shifts triggered by AI have already birthed some of the best investment opportunities in history. This is a space where we spend countless hours researching and maintaining a leading edge.

As shown in the chart, productivity has begun to accelerate rapidly under the influence of AI. In the third quarter of 2025, US labor productivity grew at its strongest rate in two years:

Pessimistic views assume that productivity gains flow entirely to the builders of AI models without translating into broader benefits. Optimistic views posit that price compression and the formation of new markets will distribute gains more widely.

Abundance Reduces Conflict, Not Just Cuts Costs

One of the least discussed impacts of AI-driven "abundance" is geopolitical. For most of modern history, wars have been fought over scarce resources: energy, food, trade routes, industrial capacity, labor, and technology. When resources are limited and growth feels like a zero-sum game, competition arises between nations. But abundance changes everything.

If AI substantively reduces the production costs of energy, manufacturing design, logistics, and services, the global economic pie will grow. As productivity rises and marginal costs decline, the economy’s dependence on predating others' advantages diminishes. This will end wars and may lead to the most peaceful period in human history.

The same holds true for economic warfare, as we are currently experiencing a year-long trade war.

Tariffs are tools for protecting domestic industries from cost competition in a resource-scarce world. But if AI causes production costs to collapse everywhere, why do we still need tariffs? In a high-abundance environment, protectionism becomes economically inefficient.

History shows that periods of technological acceleration often reduce global conflicts in the long run. The industrial expansion after World War II diminished the motivation for direct confrontation among major powers.

AI-driven abundance could accelerate this dynamic. If energy management is more efficient, supply chains become more resilient, and production becomes more localized through automation, nations become less vulnerable. As economic security increases, geopolitical aggression becomes no longer rational.

The most optimistic AI outcome is not just higher productivity or higher stock indices, but a world where economic growth is no longer a zero-sum game.

Conclusion: What if the World Does Not End?

AI amplifies outcomes. If institutions cannot adapt, it can amplify vulnerabilities; if productivity outpaces the speed of destruction, it can amplify prosperity.

Antrhopic’s "takedown" is a signal that workflows are being repriced, and cognitive labor is becoming cheap; it is a clear transformation.

But transformation does not equal collapse, just as every major technological revolution initially appears disruptive.

The most underestimated possibility today is not utopia, but abundance. AI may compress rents, reduce friction, and restructure labor markets, but it may also bring about the largest real productivity expansion in modern history.

The difference between the "global intelligence crisis" and "global intelligence abundance" lies not in capability, but in adaptation.

And this world always finds ways to adapt.

Finally, those who can remain objective and follow processes during the current tumultuous period are entering the best trading environment in history.