AI doomsday theory is a massive shorting opportunity

AI is not an end-of-days prophecy but a new starting point for a prosperous economy brought about by the collapse of cognitive costs.

Author: The Kobeissi Letter

Translation: Deep Tide TechFlow

**Deep Tide Guide: ** As AI tools like Anthropic demonstrate astonishing code and workflow automation capabilities, the market has fallen into a panic of “AI doomsday,” with trillions of dollars in market value evaporating instantly. However, this article offers a highly insightful counter perspective: the short-term shocks triggered by AI are not signs of an economic collapse but an inevitable process of “cognitive cost” drastically decreasing. By comparing the PC revolution of the 1980s and productivity data, the author points out that when technology makes knowledge acquisition cheap and abundant, the true era of “abundant GDP” begins. This is not only a labor restructuring but a necessary path toward geopolitical détente and a global productivity explosion.

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

The stock market just wiped out $800 billion in market value because “AI taking over the world” is becoming a consensus view. This idea is too obvious. And “obvious” trades have never truly won.

The reason this doomsday scenario spreads so wildly is because it taps into some primal instincts. It depicts AI not just as a productivity tool but as a macroeconomic stabilizer capable of triggering negative feedback loops: layoffs weaken consumption, weaker consumption leads to more automation, and automation accelerates layoffs.

The obvious fact is: AI is not just another software feature or efficiency tool. It’s a general capability shock that touches every white-collar workflow. Unlike any revolution in history, AI is becoming proficient at “everything” simultaneously.

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

We believe there is a second path, and it is greatly underestimated. The Anthropic “breakdowns” that seem like early signs of systemic collapse may ultimately be the beginning of the largest productivity expansion in history.

Before we begin, save this article and revisit it repeatedly over the next 12 months. While the analysis below is not an inevitable outcome, it’s important to remember that humans can always turn the tide; free markets can always self-correct.

Anthropic’s “Breakdowns” Are Real

First, we must acknowledge the market. Anthropic is disrupting the world with Claude, causing Fortune 500 companies to lose trillions in market value.

This is a story we’ve seen several times by 2026: Anthropic releases a new AI tool, Claude makes substantial progress in coding and workflow automation, and within hours, the target industry’s market collapses.

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

Market reactions to Claude announcements

• IBM ($IBM) just had its worst day since October 2000, after Anthropic announced Claude can simplify COBOL code.
• Adobe ($ADBE) has fallen 30% this year, as generative capabilities compress creative workflows.
• The cybersecurity sector crashed after “Claude Code Security” was released.

In these examples, CrowdStrike ($CRWD) stock plunged almost simultaneously with the announcement of “Claude Code Security.”

On February 20, at 1 p.m. Eastern, Claude announced “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 due to this news.

These reactions are not irrational. The market is pricing in real-time profit compression. When AI replicates workers’ jobs, pricing power shifts to buyers. This is the first-order impact—and it’s very real.

Commodity-ification does not mean collapse. On the contrary, it’s how technology lowers costs and expands access. PCs commoditized computing, the internet commoditized distribution, cloud commoditized infrastructure, and AI is commoditizing cognition.

Undoubtedly, some traditional workflows will see profit margins squeezed. The question is: will lower cognitive costs lead to economic collapse or enable explosive expansion?

The “Doom Loop” Assumes Demand Is Fixed

The bearish cycle creates a simplified linear model: AI gets better, companies cut layoffs and wages, purchasing power declines, companies reinvest in AI to defend profits, and the cycle repeats. It assumes a stagnant economy.

History shows that’s not true. When the cost of producing something crashes, demand rarely stays the same; it expands. When computing costs fall, we don’t buy the same amount of computing cheaper—we buy orders of magnitude more and build entirely new industries on top.

As shown below, today’s personal computer prices are 99.9% cheaper than in 1980.

Caption: Price trend of personal computers from 1980-2015

AI reduces costs across industries, and when service costs fall, purchasing power increases regardless of wage growth.

Only if AI replaces labor without substantially expanding demand will the doom loop dominate. If cheap computing and productivity create new consumption categories and economic activities, the optimistic scenario emerges.

The Real Shock Is Price Collapse, Not Unemployment

Investors are more eager to promote the “obvious” story of layoffs, but the bigger story is the price compression happening in services. Knowledge-based work is expensive because of the scarcity of knowledge—this sounds simple, but it’s true. Abundant knowledge supply drives down the prices of knowledge work.

Think healthcare management, legal documents, tax filings, compliance checks, marketing production, basic programming, customer support, and tutoring. These services consume large economic resources mainly because they require trained human attention. AI reduces the marginal cost of that attention.

In fact, as shown below, the US service sector accounts for nearly 80% of US GDP.

If operating costs decline, small businesses become more accessible; if service access costs fall, more households participate. To some extent, AI’s progress acts as an “invisible” tax cut.

Companies relying on high-cost cognitive labor may suffer losses, but the broader economy benefits from lower service inflation and higher real purchasing power.

From “Ghost GDP” to “Abundant GDP”

Bearish arguments rely on “Ghost GDP,” which is output shown in data but not benefiting households. The optimistic counter is what we call “Abundant GDP,” where output growth combines with falling living costs.

“Abundant GDP” doesn’t require nominal income to skyrocket; it requires prices to fall faster than incomes decline. If AI lowers the costs of many essential services, even if household wages slow, real income increases. Productivity gains are not lost—they are passed on through lower prices.

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

Internet, electricity, mass manufacturing, and antibiotics all provided new ways to expand output and lower costs, despite being disruptive and volatile. But looking back, these changes permanently improved living standards.

A society that spends less time navigating complex systems and paying redundant services becomes functionally wealthier.

Labor Market Is a Restructuring, Not Disappearance

A core concern is that AI disproportionately impacts white-collar jobs, which drive discretionary consumption and housing demand. This is true and a reasonable worry, especially given the huge wealth gap.

However, AI faces more difficulties in the physical world and in human identity recognition. Skilled trades, hands-on healthcare, advanced manufacturing, and experience-driven industries still have structural demand. In many cases, AI complements these roles rather than replacing them.

More importantly, AI lowers barriers to entrepreneurship. When one can automate accounting, marketing, support, and coding tasks, starting small businesses becomes easier. We are optimistic about small enterprises.

In fact, removing entry barriers via AI might be a solution to the current wealth gap.

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

Received. Continuing with the modular analysis of Part 3 (final part). This section will explore the evolution of SaaS business models, AI’s reshaping of market structures, the real performance of productivity data, and an underestimated perspective: how AI-driven “abundance” reduces global conflicts.

The “Decline” of SaaS

AI clearly pressures traditional SaaS (Software as a Service) business models. Negotiations by procurement teams become tougher, and some long-tail software products face structural resistance. But SaaS is just a delivery mechanism, not the end of value creation.

Next-generation software will be adaptive, agent-driven, outcome-based, and deeply integrated. Winners won’t be providers of static tools but those best able to adapt to change.

Every technological revolution rearranges the stack; companies that price static workflows will struggle. Those with data, trust, compute, energy, and verification will thrive.

A layer of profit compression doesn’t mean the entire digital economy is collapsing—it signals transformation.

AI Reshaping the Market

Bearish views believe that agentic commerce will eliminate middlemen and transaction fees. To some extent, that’s true. When friction decreases, extracting fees becomes harder.

As shown below, even before AI became what it is today, stablecoin trading volume was soaring. Why? Because markets always favor efficiency.

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

Intelligent agents representing consumers may compress platform profits based on “habits,” but they can also increase overall demand by reducing search costs and improving efficiency.

Productivity Is the Key Variable

The ultimate determinant of an optimistic outcome is productivity. If AI can sustain productivity improvements in healthcare, government, logistics, manufacturing, and energy, the result is abundance and lower entry barriers for all.

Even a 1–2% incremental productivity growth sustained over ten years compounds into enormous gains.

The macroeconomic shifts driven by AI have already created some of the best investment opportunities in history. This is a field we’ve spent countless hours researching and continuously leading.

As shown below, productivity has begun to accelerate rapidly due to AI. In Q3 2025, US labor productivity surged, marking the strongest growth in two years:

Pessimists assume that all productivity gains flow solely to AI model builders and don’t benefit the wider economy. Optimists believe that price compression and new markets will broadly distribute these gains.

Abundance Reduces Conflict, Not Just Costs

One of the least discussed impacts of AI-driven “abundance” is geopolitics. For most of modern history, war has been about competing for scarce resources: energy, food, trade routes, industrial capacity, labor, and technology. When resources are limited and growth feels like a zero-sum game, nations compete. But abundance changes everything.

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

Economic warfare is also affected, such as the ongoing year-long trade war.

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

History shows that technological acceleration tends to reduce global conflict in the long run. Post-WWII industrial expansion lowered the incentives for major powers to confront each other directly.

AI-driven abundance could accelerate this trend. More efficient energy management, resilient supply chains, and localized production through automation make nations less vulnerable. As economic security increases, geopolitical aggression becomes less rational.

The most optimistic AI scenario isn’t just higher productivity or 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 can’t adapt, it can magnify vulnerabilities; if productivity outpaces destruction, it can amplify prosperity.

Anthropic’s “breakdowns” signal workflow re-pricing and the cheapening of cognitive labor—a clear transformation.

But transformation isn’t collapse, just as every major technological revolution initially appears destabilizing.

The most underestimated possibility today isn’t utopia but abundance. AI may compress rents, reduce friction, and restructure labor markets, but it could also bring the greatest real productivity expansion in history.

The difference between a “global intelligence crisis” and a “global intelligence prosperity” isn’t ability but adaptation.

And the world always finds a way to adapt.

Finally, those who remain objective and follow the process during these turbulent times are poised for the best trading environment in history.