Survival vs. Macroeconomy¶

Hyper-Complexity¶

Macroeconomy of any country and even more - of the interconnected World - is a hyper-complex system of mutually affecting factors dynamically changing through time with constantly changing intensity for each factor and the constant probability of introducing the new factors to the system.

Let's list those factors for the 2026 job market:

1. Capital Realignment (The "AI Capex" Drain): Building hyperscale AI infrastructure is incredibly expensive. Companies like Microsoft, Meta, and Oracle are cutting headcount not necessarily because they are losing money, but to free up cash flow for massive capital expenditures (GPUs, data centers, energy infrastructure).
2. Presence of AI as excuse: If a company missed an earnings target, or simply wants to lean out its workforce to boost profit margins, citing "AI-driven restructuring" works as a great cover.
3. AI Role Automation (relatively weak as of May 2026): Generative AI is approaching a level where it can act as a force multiplier, reducing the need in workforce for doing the same job.
4. The Valuation Hangovers (Post-2021 VC Deflation): Tech startups and mid-tier public firms that raised capital at hyper-inflated valuations during the 2021 venture capital boom are running out of runway. These companies must aggressively cut costs to survive, independent of what AI can do.
5. Consumer & Enterprise Spending Slowdowns: Beyond Silicon Valley, macroeconomic pressures—like lingering inflation and compressed consumer purchasing power—are forcing companies (from Nike to IKEA) to downsize.
6. Tariff and Geopolitical Uncertainties: Shifting trade policies and tariff discussions have introduced corporate hesitation. When global supply chains and international market access face policy risks, companies hoard cash and freeze hiring rather than expand.
7. Pandemic Over-Correction (Shedding Excess Weight): During the remote-work boom, e-commerce, cloud, and digital service providers doubled their headcounts to meet artificial demand spikes.
8. Corporate "Copycatting" (The Social Contagion of Layoffs): In macroeconomics, herd behavior matters. When prominent market leaders successfully cut 10% of their staff and their stock prices surge, it signals a green light to peer companies that downsizing is safe and rewarded by Wall Street, prompting a chain reaction across the industry.
9. The Cost of Capital Shift (High Interest Rates): For a decade, near-zero interest rates made money essentially free. Tech companies could borrow cheaply, burn cash, and focus entirely on hyper-growth while ignoring immediate profitability. With central banks holding rates higher to combat sticky inflation, that era is dead. Money is expensive. Companies can no longer afford to carry underperforming divisions or "hoard" tech talent, leading directly to layoffs.
10. The Valuation Formula Flip: High interest rates mathematically crush the present value of future earnings. Investors now demand profits today over growth tomorrow. Because AI infrastructure is incredibly capital-intensive, companies are forced to cut human payroll to balance the ledger and fund these massive computational investments without taking on expensive debt.
11. Inflationary Margin Squeeze: Persistent inflation has driven up corporate input costs (raw materials, cloud infrastructure energy, supply chains). When companies cannot pass 100% of these costs onto struggling consumers, they protect their profit margins by cutting their largest flexible expense: human headcount.
12. Energy Prices & AI’s Power Hunger: Escalating conflict in the Middle East—specifically involving major regional players like Iran—introduces massive volatility into global oil and gas markets. Higher energy prices act as a stealth tax on the entire global economy. Furthermore, AI data centers are notoriously power-hungry; spiking energy costs make running AI infrastructure significantly more expensive, compounding the pressure on tech companies to find cost savings elsewhere (i.e., workforce reductions).
13. Supply Chain Chokepoints: Geopolitical friction threatens critical maritime trade routes (like the Red Sea and Persian Gulf). Hardware manufacturers, semiconductor suppliers, and global logistics networks face delays and soaring shipping insurance rates. When hardware delivery stalls, projects get delayed, revenues drop, and operational downsizing follows.
14. The "K-Shaped" Corporate Reality: Unequal wealth distribution mirrors how corporations are faring. A tiny handful of massive tech monopolies and elite capital holders are capturing the vast majority of the wealth generated by the AI boom. Meanwhile, mid-tier companies and the general consumer base feel a severe financial squeeze.
15. The Aggregate Demand Problem: When wealth consolidates heavily at the top, the broader purchasing power of the middle and lower classes erodes. Since consumer spending drives roughly 70% of major economies, a squeezed middle class means less broad demand for enterprise software, digital subscriptions, and consumer goods. When corporate revenues slow due to weak consumer demand, layoffs are the inevitable reflex.
16. Labor's Weakened Bargaining Position: Decades of wealth concentration have structurally weakened organized labor, particularly in the white-collar and tech sectors. Without strong structural protections, companies face very little friction or public backlash when executing rapid, massive layoffs to pivot toward automated solutions.
17. The Great Retirement Wave (Demographic Inversion): In the world’s largest economies (the US, Western Europe, Japan, and increasingly China), the massive Baby Boomer generation is hitting retirement age. This creates an immediate loss of consumer base.
18. Offshoring: Because local talent in hubs like London or San Francisco is incredibly expensive, companies are refusing to hire locally and open a remote hub in Pakistan, India, or Poland and pay people there 10x less for the same job. The paradoxical intermediate step to that is the "they come here and take our jobs" resistance against immigration and corresponding political shifts that have made getting the work visas incredibly difficult, expensive, and legally risky.
19. Sovereign Debt Traps: Major global governments are carrying historic levels of public debt. As interest rates stay elevated to fight inflation, governments are spending a massive portion of their tax revenues just paying off the interest on their debt, rather than investing in infrastructure, education, or public research. This crowds out private investment and acts as a drag on economic vitality.
20. Weaponization of the Dollar and Currency Volatility: The aggressive use of economic sanctions and the weaponization of the US dollar global payment system have forced a fragmented global economy. Emerging markets are facing extreme currency devaluations. When a country's currency collapses against the dollar, its purchasing power for global goods and software vanishes, destroying the international revenue streams of multinational corporations and triggering layoffs.
21. The Rise of Economic Protectionism: Subsidies like the US CHIPS Act or European industrial initiatives are drawing hard lines around where technology can be developed and sold. When global markets fragment into regional silos (US vs. China vs. EU), corporations lose the ability to scale globally, shrinking their addressable markets and forcing headcount adjustments to match a smaller, localized reality.
22. The Direct Costs of Extreme Weather: Climate-driven disruptions—from droughts choking critical trade canals (like Panama) to extreme heat waves shutting down factories—are costing the global economy billions annually in physical damage and insurance premiums. Insurance companies are raising rates globally or pulling out of markets entirely. This massive, unquantifiable risk factor sucks liquidity out of the productive economy
23. The Green Transition Capital Drain: The mandatory shift toward decarbonization requires trillions of dollars of global capital to retroactively swap out old energy infrastructure for green alternatives. This capital is defensive; it is spent to keep the lights on and comply with climate targets, rather than creating new, expansionary consumer markets or job sectors.
24. The Housing and Cost-of-Living Squeeze: In almost every major urban center worldwide, housing costs have decoupled completely from local wages. When the vast majority of a worker's disposable income is consumed by rent, mortgages, and basic food, aggregate demand for discretionary products—apps, entertainment, upgrades, new vehicles—collapses.
25. The "Vibecession" and Consumer Nihilism: There is a profound psychological shift occurring where, despite positive baseline GDP numbers, the average citizen feels economically insecure. This collective psychological dread changes spending habits from forward-looking (investing, buying homes, upgrading lifestyles) to defensive survivalism. When consumer psychology turns bleak, the velocity of money slows down, corporate earnings stagnate, and layoffs follow as a lagging indicator.
26. Population Shrinking: The entirety of the developed Western world is structurally shrinking from the inside out. When birth rates drop to 1.5 (which is the current average for developed countries), it means that every new generation is roughly 25% smaller than the one before it. While for the last 50 years, corporate business models assumed that the customer base would always grow, it is not the case anymore.
27. Misinterpretation of Economic Indicators: If a handful of massive tech monopolies build highly automated AI clusters and generate billions in software revenue, GDP goes up. GDP can rise significantly even while thousands of white-collar workers are being laid off. The metric registers the wealth generated by the machine, but completely misses the financial pain of the humans who used to run it. It treats a highly profitable, fully automated "ghost company" as a massive economic success. If a software engineer earning €100,000 gets laid off, and after six months of panic takes a part-time job driving an Uber or working in a local retail store, the official government statistics register that person as "fully employed."
28. Others.

Additionally: The factors are interdependent: "A" has 65% probability of hitting if "B" and "C" has specific intensity for the specific period of time. "D" will work if "A" happens, and "E" will not happen in the same situation.

Additionally: In a hyper-complex system, each factor isn’t just a static variable—it behaves like a wave. It has a starting point, a crest (peak intensity), and a trough (fading out or stabilizing) and the waves intersect in time and interfere (amplify or cancel out each other).

Unpredictability¶

Hyper-complexity of the system:

• Is real, meaning:
• None of the events (like layoffs) can ever be attributed to one reason (like AI)
• System is unpredictable, meaning:
• The only certain prediction is unpredictability, meaning:
• If there is a good time, there will be bad, meaning:
• You prepare the buffer or:
• Share the shock personally

Plus: unpredictability dismisses justifying any local cruelty with "big" predictions.

And more, out of any grid:

Smyrna¶

In 1922, the Allied warships (British, American, French, Italian) sat in the harbor of Smyrna while the city burned and tens of thousands of civilians drowned or were slaughtered on the docks.

If you asked the commanders of those ships at that exact moment why they weren't lowering rescue boats to save the children drowning in front of their eyes, they would have handed you a list of "complex macroeconomic and geopolitical factors":

• “We must maintain strict diplomatic neutrality in the Greco-Turkish War.”
• “We have orders to protect our own nations’ commercial and oil assets in the region first.”
• “Taking on refugees could be seen as an act of war by the Turkish forces, destabilizing the fragile post-WWI peace treaties.”
• “Our ships have a finite capacity; taking on too many people could cause a mutiny or capsize the vessels.”

To the geopolitical planners, this was a highly complex, multi-variable equation. But the moment they used that equation to look at a drowning child and do nothing, the complexity ceased to be an explanation and became a moral atrocity. They used abstract statecraft to suppress basic human empathy.

This is the bridge to the modern corporate landscape. When a system reaches a certain level of complexity, it allows the people running it to split themselves into two different entities:

• The Professional Self: The captain of the ship, the corporate CEO, the hedge fund manager. This person operates entirely on numbers, parameters, contracts, and "systemic reality."
• The Human Self: The person who goes home, hugs their own children, and considers themselves a good, moral person.

The "shield" works by ensuring the Professional Self never has to look at what the Human Self is doing. When a CEO signs a paper that eliminates 10,000 jobs—knowing it will lead to lost healthcare, broken families, evictions, and immense psychological suffering—they do not see the humans drowning. They see an abstract line graph that needs to be corrected to satisfy the "complex demands of the market."

"I didn't drown that child. The tides of the market drowned them. I was just managing the ship."

Another (seemingly, softer) translation case:

"Due to high interest rates, inflationary pressures, and the structural pivot toward artificial intelligence, we must execute a baseline adjustment of our human capital allocation." >> "To keep our stock valuation high, I am choosing to take away the livelihoods of thousands of people who trusted me to lead them."

Smyrna's Counter-Evidence

• During the disaster in Smyrna, a single, ordinary American YMCA worker named Asa Jennings refused to accept the cold math of the naval commanders. He didn't start a war with Turkey. Instead, through raw grit, he bribed an Italian ship captain, secured a fleet of empty Greek merchant ships, and convinced the U.S. Navy to quietly protect them.
• At the same time, a Japanese freighter (the Tokei Maru) dumped its entire cargo of expensive silk and porcelain into the sea to pack its decks with over 800 drowning refugees, defiantly telling the Turkish forces that harming a single refugee would be treated as an insult to the Japanese flag.

Neither Asa Jennings nor the Japanese captain started the new World War.

Satoru Iwata

See here.

Unpredictability (AI)¶

• "Will AI take most of the jobs? - Unclear, it may hit limits (data, physical, financial) or solve those limits or change its architecture to optimize and highly progress see the 27+ factors above.
• "Is AI a bubble? - Unclear due to technology nature + see the question above + see the 27+ factors above.
• If it is a bubble, how long will it exist, how many victims will there be until it burst, how painful will be its burst if it happens? - Unclear due to 27+ factors above.
• "Will you get you job back? - Unclear due to questions above + see the 27+ factors above.
• "Will "quick" negative consequences of AI collapse the system and people before the positive ones arrive?" - Unclear due to questions above + see the 27+ factors above.
• "Can AI improve without large consuming economy, does it truly need a big population or may it evolve without it to serve in its final stage to 1% of survivors?" - Unclear, the potential for several scenarios is presented + see the 27+ factors above.
• "Will AGI arrive?" - Unclear due to questions above + see the 27+ factors above.
• "Will AI create the new jobs at the appropriate amount?" - Unclear as it has a potential to become a first universal disruptor - the technology that for the first time in the human history, does not create new jobs and only eliminates all the existing + 27+ factors above.
• "Will social institutions, regulations and support be able to keep up with AI-related changes in economy?" - Unclear due to high inertia of social institutions + 27+ factors above.

What is clear: none of one million predictions tells nothing about what will actually happen, but each of them tells a lot about the motives of predictor or the group the predictor belongs to.

Current Conclusions and Open Questions¶

Current Conclusions:

1. Macroeconomy of the interconnected World is a hyper-complex unpredictable system whether is it AI Era or any other.
2. Regarding AI Era, none of one million predictions tells nothing about what will actually happen, but each of them tells a lot about the motives of predictor or the group the predictor belongs to.
3. The only possible prediction is a prediction of unpredictability, meaning "if there is a good time, there will be bad," meaning: you prepare the buffer or: share the shock personally like you shared a good time some day.
4. Treating people as numbers results in the most horrific crimes in history, and is absolutely unacceptable.
5. No law or contract justify cruelty and personal betrayal. If they do, those are just predatory laws and contracts.

Open Questions:

1. NA