AI Doomsday Theory Is a Massive Short Play

2026.02.24

AI Doomsday Theory Is a Massive Short Play

AI is not an apocalyptic prophecy, but rather a new starting point for an abundance economy brought about by the collapse of cognitive costs.

2026.02.24 - 11:15:30

Navigating Web3 tides with focused insights

AI is not an apocalyptic prophecy, but rather a new starting point for an abundance economy brought about by the collapse of cognitive costs.

Author: The Kobeissi Letter

Translation & Editing: TechFlow

TechFlow Insight: As AI tools like Anthropic demonstrate astonishing capabilities in coding and workflow automation, markets have plunged into panic over “AI doomsday” narratives—wiping out hundreds of billions of dollars in market capitalization overnight. Yet this article offers a profoundly counterintuitive perspective: the short-term shock triggered by AI is not a harbinger of economic collapse, but rather the inevitable process of a dramatic decline in “cognitive cost.” Drawing parallels with the PC revolution of the 1980s and historical productivity data, the author argues that when knowledge acquisition becomes cheap and abundant, the true “Abundance GDP” era begins—not merely a labor-market restructuring, but a necessary path toward geopolitical easing and a global productivity explosion.

The stock market has just erased $800 billion in market value, as “AI taking over the world” becomes a consensus view. That view is too obvious—and obvious trades never truly win.

This apocalyptic narrative spreads so rapidly because it taps into something instinctive. It portrays AI not as a productivity tool, but as a macroeconomic destabilizer capable of triggering a negative feedback loop: layoffs reduce consumption; reduced consumption triggers more automation; and automation accelerates further layoffs.

The obvious truth is this: AI is not just another software feature or efficiency booster. It is a general-purpose capability shock—one simultaneously impacting every white-collar workflow. Unlike any prior revolution, AI is becoming proficient at “everything,” all at once.

But what if the doomsday scenario is wrong? It assumes demand is fixed, assumes productivity gains won’t expand markets, and assumes system adaptation cannot outpace disruption.

We believe a second path exists—and it is vastly underappreciated. What appear to be early signs of systemic collapse—the “takedowns” driven by Anthropic—may instead mark the beginning of the largest productivity expansion in human history.

Before proceeding, bookmark this article and revisit it repeatedly over the next 12 months. While the analysis below is not inevitable, remember this: humanity always rebounds—and free markets always self-correct.

Anthropic’s “Takedowns” Are Real

First, let’s acknowledge reality: we cannot ignore the market. Anthropic is reshaping the world through Claude—and Fortune 500 companies are losing hundreds of billions in market value as a result.

We’ve already seen this story several times in 2026: Anthropic releases a new AI tool; Claude achieves meaningful progress in programming and workflow automation; and within hours, markets for targeted industries collapse.

If you’ve been out of the loop, here are some examples:

Stock reactions to Claude announcements

IBM ($IBM) posted its worst trading day since October 2000 after Anthropic announced Claude could simplify COBOL code.
Adobe ($ADBE) is down -30% year-to-date, as generative capabilities compress creative workflows.
The cybersecurity sector collapsed following the launch of “Claude Code Security.”

In the example above, CrowdStrike’s stock ($CRWD) plunged almost instantly upon announcement of “Claude Code Security.”

At 1:00 p.m. ET on February 20, Claude launched “Claude Code Security”—an automated AI tool designed to scan codebases for vulnerabilities.

Just two trading days later, CrowdStrike’s market cap had evaporated by $20 billion due to the announcement.

These reactions are not irrational. Markets are pricing in real-time profit compression. When AI replicates human labor, pricing power shifts decisively to buyers. This first-order effect is very real.

Commoditization does not equal collapse. Rather, it is how technology lowers costs and expands access. PCs commoditized computing; the internet commoditized distribution; cloud computing commoditized infrastructure; and AI is now commoditizing cognition.

Undoubtedly, some traditional workflows will face margin compression. The question is whether lower cognitive costs trigger economic collapse—or enable explosive expansion.

The “Doomsday Loop” Assumes Fixed Demand

Bearish models construct a simplified linear loop: AI improves → firms cut jobs and wages → purchasing power falls → firms invest further in AI to defend margins → repeat. This presumes a fully stagnant economy.

History says otherwise. When production costs for something collapse, demand rarely stays flat—it expands. When computing costs fell, we didn’t consume the same amount of computing at lower prices. We consumed orders-of-magnitude more computing—and built entirely new industries atop it.

As shown below, today’s personal computers cost 99.9% less than those from 1980.

Caption: PC price trend, 1980–2015

AI lowers costs across every industry—and when service costs fall, purchasing power rises regardless of wage growth.

The doomsday loop dominates only if AI replaces labor without meaningfully expanding demand. If cheap computing and productivity unlock entirely new categories of consumption and economic activity, the optimistic scenario emerges.

The Real Shock Is Price Collapse—Not Unemployment

Investors find it easier to sell the “obvious” layoff story—but the far bigger news is the price compression unfolding across services. Knowledge work is expensive because knowledge is scarce—a simple fact, yet fundamentally true. Abundant knowledge supply drives down the price of knowledge work.

Consider medical administration, legal documentation, tax filing, compliance checks, marketing production, basic programming, customer support, and educational tutoring. These services absorb enormous economic resources—largely because they require trained human attention. AI reduces the marginal cost of that attention.

In fact, as shown below, U.S. services contribute nearly 80% of U.S. GDP.

If business operation costs fall, small businesses become more accessible; if service acquisition costs fall, more households participate. In effect, AI advancement functions as an “invisible” tax cut.

Firms whose profits rely 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”

Bearish arguments rest on “Ghost GDP”—output that appears in data but delivers no tangible benefit to households. The optimistic counterargument is what we call “Abundance GDP”: output growth coupled with falling cost-of-living.

“Abundance GDP” does not require nominal incomes to surge. It requires prices to fall faster than incomes decline. If AI lowers the cost of essential services for many people, real household gains rise—even if wage growth slows. Productivity gains don’t vanish; they’re passed through as lower prices.

This may explain why, over the past 70+ years, productivity growth has consistently outpaced wage growth:

The internet, electricity, mass manufacturing, and antibiotics all delivered new ways to scale output and cut costs—though the processes were disruptive and volatile. Yet in hindsight, these shifts permanently raised living standards.

A society that spends less time navigating cumbersome systems and paying for redundant services is functionally richer.

Labor Markets Are Restructuring—Not Disappearing

A core concern is that AI disproportionately impacts white-collar employment—the very engine of discretionary spending and housing demand. This is true—and a legitimate concern, especially against today’s backdrop of extreme inequality.

Yet AI faces greater hurdles in physical-world dexterity and human identity. Skilled trades, hands-on healthcare, advanced manufacturing, and experience-driven sectors retain structural demand. In many cases, AI augments—not replaces—these roles.

More importantly, AI lowers the barrier to entrepreneurship. When one person can automate accounting, marketing, support, and programming tasks, launching small-scale ventures becomes dramatically easier. We are bullish on small businesses.

In fact, AI-driven removal of entry barriers may be the solution to today’s widening wealth gap.

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.

Understood—we’ll continue modular translation of Part III (the final part). This section explores the evolution of SaaS business models, AI’s reshaping of market structure, actual productivity data, and an underappreciated angle: how AI-driven abundance may reduce global conflict.

The “Death of SaaS” Narrative

AI is clearly pressuring traditional SaaS (Software-as-a-Service) business models. Procurement teams’ negotiations have grown tougher; some long-tail software products face structural headwinds. But SaaS is merely a delivery mechanism—not the endpoint of value creation.

The next generation of software will be adaptive, agent-driven, outcome-based, and deeply integrated. Winners won’t be providers of static tools—but those most adept at adapting to change.

Every technological shift rearranges the stack. Companies pricing static workflows will inevitably struggle. Those with data, trust, compute, energy, and verification stand to thrive.

Margin compression at one layer doesn’t signal collapse of the entire digital economy—it signals transformation.

AI Commercially Restructures Markets

Bears argue “agentic commerce” will eliminate intermediaries and strip away fees. To some extent, yes—when friction falls, extracting fees grows harder.

As shown below, stablecoin transaction volumes were already surging even before AI reached its current state. Why? Because markets always reward efficiency.

Lower systemic friction also expands transaction volume. When price discovery improves and transaction costs fall, more economic activity occurs—a bullish dynamic.

Agents acting on consumers’ behalf may compress platform profits built on “habit.” Yet they simultaneously boost 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 in healthcare, government administration, logistics, manufacturing, and energy optimization, the result is abundance and lowered barriers to access for all humanity.

Even sustained incremental productivity gains of 1–2% compound into massive effects over a decade.

The macroeconomic transformation triggered by AI has already spawned some of the best investment opportunities in history—our team has spent countless hours researching and maintaining leadership in this space.

As shown below, productivity has already begun accelerating sharply due to AI. U.S. labor productivity surged in Q3 2025—the strongest growth in two years:

The bearish view assumes productivity gains accrue exclusively to AI model builders, without broad spillover. The optimistic view holds that price compression and new market formation will distribute those gains widely.

Abundance Reduces Conflict—Not Just Costs

Among the least-discussed implications of AI-driven abundance is geopolitics. For much of modern history, wars have been fought over scarce resources: energy, food, trade routes, industrial capacity, labor, and technology. When resources are constrained and growth feels zero-sum, nations compete. Abundance changes everything.

If AI substantially lowers production costs for energy, manufacturing design, logistics, and services, the global economic pie expands. As productivity rises and marginal costs fall, economic growth becomes less dependent on seizing others’ advantages. This could end war—and usher in the most peaceful era in human history.

Economic warfare follows the same logic—such as the year-long trade war we’re currently experiencing.

Tariffs are tools of resource-scarce worlds—designed to shield domestic industries from cost competition. But if AI collapses production costs everywhere, why do we need tariffs? In a high-abundance environment, protectionism becomes economically inefficient.

History shows that periods of accelerated technological adoption tend to reduce global conflict over the long term. Post-WWII industrial expansion dampened incentives for major powers to engage in direct confrontation.

AI-driven abundance may accelerate this dynamic. If energy management becomes more efficient, supply chains more resilient, and production more localized via automation, nations grow less vulnerable. As economic security rises, geopolitical aggression becomes irrational.

The most optimistic AI outcome isn’t merely higher productivity or elevated stock indices—it’s a world where economic growth ceases to be a zero-sum game.

Conclusion: What If the World Doesn’t End?

AI amplifies outcomes. If institutions fail to adapt, it amplifies fragility; if productivity outpaces disruption, it amplifies prosperity.

Anthropic’s “takedowns” signal that workflows are being repriced—and cognitive labor is becoming cheap. This is a clear transition.

But transition is not collapse—just as every major technological revolution initially appeared destabilizing.

The most underappreciated possibility today is not utopia—but 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 a “global intelligence crisis” and a “global intelligence boom” lies not in capability—but in adaptation.

And this world always finds a way to adapt.

Finally, those who remain objective and disciplined amid today’s turbulence are entering the best trading environment in history.