AI Doomsday Theory Is a Massive Short Play
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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.
Navigating Web3 tides with focused insightsAuthor: The Kobeissi Letter
Translation & Editing: TechFlow
TechFlow Insight: As AI tools like Anthropic demonstrate astonishing capabilities in code generation and workflow automation, markets have plunged into panic over “AI doomism,” wiping out hundreds of billions of dollars in market capitalization overnight. Yet this article offers a highly illuminating counter-perspective: the short-term shock triggered by AI is not a harbinger of economic collapse—but rather an inevitable phase in the dramatic decline of “cognitive cost.” Drawing parallels with the PC revolution of the 1980s and historical productivity data, the author argues that true “Abundance GDP” emerges only when knowledge acquisition becomes cheap and abundant. This is not merely a labor-force restructuring—it is a necessary passage toward geopolitical de-escalation and a global productivity explosion.
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The stock market has just erased $800 billion in market cap—because “AI taking over the world” has become a consensus view. That view is too obvious. And “obvious” trades never truly win.
This doomsday scenario spreads so rapidly because it taps into something instinctive. It portrays AI not as a productivity tool, but as a macroeconomic destabilizer capable of triggering a negative feedback loop: layoffs reduce consumption, reduced consumption drives more automation, and automation accelerates further layoffs.
The obvious truth is: AI is not just another software feature or efficiency booster. It is a general-purpose capability shock—simultaneously impacting every white-collar workflow. Unlike any prior revolution, AI is becoming proficient at “everything”—all at once.
But what if the doomsday scenario is wrong? It assumes demand is fixed, assumes productivity gains won’t expand markets, and assumes system adaptation cannot outpace disruption.
We believe a second path exists—and it is vastly underestimated. What appear to be early signs of systemic collapse—the “takedowns” driven by Anthropic—may ultimately mark the beginning of the largest productivity expansion in human history.
Before proceeding, bookmark this article and revisit it repeatedly over the next 12 months. While the analysis below is not inevitable, it’s vital to remember that humanity always finds a way to rebound—and free markets always self-correct.
Anthropic’s “Takedowns” Are Real
First, let’s acknowledge reality: we cannot ignore the market. Anthropic is reshaping the world through Claude—and Fortune 500 companies are losing hundreds of billions in market value as a result.
We’ve already witnessed this story multiple times in 2026: Anthropic releases a new AI tool; Claude makes substantial progress in programming and workflow automation; within hours, markets in targeted sectors collapse.
If you’ve been out of the loop, here are some examples:
Stock reactions to Claude announcements
- IBM ($IBM) posted its worst single-day performance 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 the announcement of “Claude Code Security.”
At 1:00 p.m. ET on February 20, Claude launched “Claude Code Security”—an automated AI tool that scans codebases for vulnerabilities.
Just two trading days later, CrowdStrike’s market cap evaporated by $20 billion under the weight of that announcement.
These reactions are not irrational. Markets are pricing 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 broadens 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: will lower cognitive costs trigger economic collapse—or enable explosive expansion?
The “Doomsday Loop” Assumes Fixed Demand
Bearish narratives construct a simplified linear model: AI improves → firms cut jobs and wages → purchasing power falls → firms invest further in AI to protect margins → repeat. This presumes a completely stagnant economy.
History shows 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: Personal computer price trend, 1980–2015
AI reduces 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 generate entirely new categories of consumption and economic activity, the optimistic scenario prevails.
The Real Shock Is Price Collapse—Not Unemployment
Investors find it easier to sell the “obvious” layoff narrative—but the far bigger story is price compression across services. Knowledge work is expensive because knowledge is scarce—a simple statement, yet fundamentally true. Abundant knowledge supply drives down the price of knowledge work.
Consider medical billing, legal documentation, tax filing, compliance checks, marketing production, basic programming, customer service, and tutoring. These services absorb vast economic resources largely because they require trained human attention. AI lowers the marginal cost of that attention.
In fact, as illustrated 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 can function 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 rely on “Ghost GDP”—output recorded in data but delivering no tangible benefit to households. The optimistic counterargument is what we call “Abundance GDP”: output growth coupled with falling living costs.
“Abundance GDP” doesn’t 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 manifest as lower prices.
This may help explain why productivity has consistently outpaced wage growth for over 70 years:
The internet, electricity, mass manufacturing, and antibiotics all delivered new ways to scale output and slash costs—despite being deeply disruptive and volatile. Yet in hindsight, these changes permanently raised living standards.
A society that spends less time navigating bureaucratic 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 segment that fuels discretionary consumption and housing demand. This is true—and a legitimate concern, especially amid already extreme inequality.
Yet AI faces greater hurdles in physical-world dexterity and human identity. Skilled trades, hands-on healthcare, advanced manufacturing, and experience-driven industries 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 businesses becomes dramatically easier. We’re bullish on small businesses.
In fact, eliminating entry barriers via AI may be the solution to our current inequality crisis.
The internet killed certain job categories—but created entirely new ones. AI may follow a similar pattern: compressing certain 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 perspective: how AI-driven abundance may reduce global conflict.
The “Death of SaaS” Narrative
AI is clearly pressuring the traditional SaaS (Software-as-a-Service) business model. Procurement teams negotiate harder; 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 possessing data, trust, compute, energy, and verification may thrive.
Margin compression at one layer doesn’t mean collapse of the entire digital economy—it signals transformation.
AI Commercially Restructures Markets
Bearish views hold that agentic commerce will eliminate intermediaries and fees. To some extent, yes—when friction declines, fee extraction becomes harder.
As shown below, stablecoin transaction volumes were already surging—even before AI matured into its current form. Why? Because markets always favor efficiency.
Lower systemic friction also expands transaction volume. When price discovery improves and transaction costs fall, more economic activity occurs—a bullish trend.
Agents acting on behalf of consumers may compress platform profits built on “habit.” Yet simultaneously, they boost total demand by lowering search costs and increasing 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 broader access for all humanity.
Even persistent 1–2% incremental productivity growth compounds into massive effects over a decade.
The macroeconomic transformation driven by AI has already birthed some of the best investment opportunities in history. This is the field we’ve spent countless hours researching—and where we maintain continuous leadership.
As shown below, productivity has begun accelerating rapidly under AI’s influence. U.S. labor productivity surged in Q3 2025—posting its strongest growth in two years:
The bearish view assumes productivity gains flow 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
One of 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. When productivity rises and marginal costs fall, 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 in.
Tariffs are tools of protectionism in a resource-scarce world—shielding domestic industry from cost competition. But if AI collapses production costs globally, why do we need tariffs? In a high-abundance environment, protectionism becomes economically inefficient.
History shows that periods of accelerated technological progress tend to reduce global conflict over the long term. Post-WWII industrial expansion lowered the incentive 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 through automation, nations grow less vulnerable. When economic security rises, geopolitical aggression ceases to be rational.
The most optimistic AI outcome isn’t merely higher productivity or elevated stock indices—it’s a world where economic growth is no longer 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 destruction, 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—as every major technological revolution initially appeared destabilizing.
The most underestimated 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 process-driven during this turbulent period are entering the best trading environment in history.
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