Behind Oracle's layoff of 30k employees at 6 a.m.: The true rewriting in the AI era is the fundamental factor of enterprise production

Asking AI · How does migration-based layoffs reveal a shift in corporate growth logic?

While laying off employees and pouring money into AI infrastructure, the capital markets are choosing to applaud—what does this mean?

In the past, we typically had two explanations for layoffs in a large company: the company is in trouble, or it has no money.

But this time, even Oracle is not the case. It’s more like doing something more proactive and cold-blooded: current business still has good growth, the organization is still operating in an orderly manner, and the company’s profits are still industry-leading, but the company has decided that the most important resources in the future will no longer be invested here.

In fact, Oracle launched a new round of layoffs by the end of March 2026. The company’s restructuring costs for fiscal year 2026 are expected to reach as high as $2.1 billion, and as of the end of February, related confirmed expenses are close to $1 billion.

But it’s worth noting that on the day the layoffs were announced, Oracle’s stock price temporarily rose by over 5%. A quick note: such a 5% increase in a stable, established tech company is already a very impressive and positive signal.

Therefore, Oracle’s layoffs are not a cry of crisis, but an active procedure blessed by the market.

Attention! The question is no longer “Why is Oracle laying off,” but—what does it mean when a large company that is not immediately in crisis, with still functional core businesses, actively shifts resources from the old system to the new system?

It indicates that the true growth logic of the enterprise is changing. It shows that the capital market is no longer rewarding just scale, profit, and stability, but a different, more future-oriented capability: shifting resources to the next-generation engine before the old one completely stalls.

Oracle is not doing decline-based layoffs but migration-based layoffs

Both are called layoffs, but the underlying logic behind them is entirely different.

We are very familiar with the language of decline-based layoffs: business downturn, fewer orders, cash flow tightness, insufficient profits, leading to organizational cuts and stopping losses. The essence of this kind of layoff is being chased by reality—a company using a smaller body and fewer resources to endure a colder winter.

But migration-based layoffs are not that. The implication is not that the company cannot survive, but that it has judged that continuing to invest the most valuable resources in the old place is no longer worthwhile.

This is more brutal than decline and more difficult than decline. Because decline layoffs are usually passive—management can explain themselves as helpless and powerless; migration layoffs, on the other hand, mean management actively admits one thing: although some businesses are still profitable, some organizations are still operational, and some positions are still working, they no longer deserve the company’s most precious budgets, core attention, and key personnel.

The reason this is worth thinking about is precisely because the old system is not yet completely broken.

If a business has already collapsed, everyone knows how to shrink. The real test for decision-makers is not to see the bleak current situation, but to recognize a still-living system that might become narrower in the future, and then decide to reallocate resources accordingly.

Oracle’s recent move is especially typical. It plans to increase capital expenditure by an additional $15 billion in FY2026 to support AI data center expansion (note: layoffs cost $2.1B, but investment in AI infrastructure is $15 billion), and announced plans to raise $45–50 billion to support overall expansion. For a traditional, somewhat old-school software company, this is no longer about patching up but transforming itself into a different kind of entity.

Oracle is not an isolated case; leading tech giants are doing the same thing

More noteworthy is that this is not just a single company’s reactive move but a clearer industry consensus.

Over the past year, almost all tech giants have been doing one thing simultaneously: adjusting personnel structures while massively increasing investments in AI and data centers.

Google laid off staff in Android, Pixel, and other hardware and platform divisions in 2025, while shifting expenditure focus toward data centers and AI development;

Meta repeatedly pushed layoffs and internal restructuring in 2026, with AI-related capital expenditure expectations continuing to rise;

Microsoft, citing alignment with AI-era business directions, advanced phased personnel adjustments, while promising to invest $80 billion in capital expenditure in FY2025.

I saw data indicating that major tech giants like Microsoft, Amazon, Google, and Meta plan to invest a total of $635 billion in AI infrastructure in 2026, far exceeding previous years’ figures.

This set of numbers indicates not an industry downturn, but a resource shift for the next main battlefield.

Cost reduction and efficiency improvement are tactical; resource migration is strategic.

The core question of cost reduction and efficiency is: can we spend less? The core question of resource migration is: where should the saved resources be reinvested?

In the past, the moat of large companies might have been operating systems, databases, advertising systems, massive customer bases, and extensive sales networks. Today, the new battleground is about: computing power supply, model capabilities, chip collaboration, data centers, cloud platform hosting, and AI commercial ecosystems.

As the vocabulary changes, resource allocation will necessarily change. If the words have changed, but money still stays in old places, and people remain in old structures, while organizations pretend everything is normal, that is the real danger.

Why does the capital market applaud the ruthless layoffs and huge AI investments of big companies?

Many people feel uncomfortable about this: why are these actions so cold to employees, yet the capital markets respond enthusiastically?

For employees, a morning email, silent freezing of permissions, or sudden job termination are real and direct cruelties.

But for the capital market, this is about a company’s future resource allocation. The stock price rising on the day of layoffs is not investors cheering unemployment, but rather applauding a judgment: management finally admits that the main battlefield has shifted, and the company’s resources should follow suit.

What the capital rewards is future-oriented resource efficiency.

The capital market is never a place that rewards warmth. It certainly doesn’t like chaos, but it dislikes sluggishness even more. The most valued ability is: forward-looking resource efficiency.

To put it more bluntly: when the existing system is still profitable, does the company have the courage to shift resources to the new system first?

This is also the hardest lesson for many entrepreneurs. Because most of the time, the real danger for a company is not when its financial statements are at their worst, but when internal busy-ness persists, revenue still flows, teams still have inertia, and everyone mistakenly believes the system can run for many more years.

Running does not mean it’s worth continuing to invest; making money does not mean it’s worth reallocating core resources; being alive does not guarantee a future.

What the capital market fears most is not short-term profit fluctuations but a company continuously wasting its most valuable resources in places that have lost their imagination. If old businesses only generate cash flow but cannot provide a sense of future, valuation will gradually decline; if old organizations can only maintain operations but cannot support the next round of competition, their existence will increasingly resemble costs rather than capabilities.

The same action is a fate for internal personnel but a signal for external capital. This is one of the most glaring divisions in today’s corporate world.

True change is not just resource allocation but the very factors of production themselves

From an insider’s perspective, the real change is in the factors of production themselves. This is the most worth deep reflection in the entire story.

1. From people to computing power and infrastructure

For a long time, the most direct way for enterprises to expand was to hire more people. To grow a business, first recruit; to occupy a region, first build a team; to cover a market, first establish layers. Back then, people themselves were the most important growth carriers.

But today, more and more large companies are answering another question: what are the truly scarce production resources in the next round of competition?

The answer is changing. In the past, large firms expanded by hiring more people. Today, many large firms expand by increasing computing power, data centers, chips, electricity, model capabilities, cloud hosting, and embedding these capabilities into organizational systems.

This is not just a technical detail change but a fundamental shift in growth logic. In other words, what enterprises are truly competing for is no longer just more labor but higher-density technological infrastructure and stronger capabilities in technology and business transformation—what can be called commercialization ability.

2. It’s not that people are no longer important, but that their value position has changed

This statement can be easily misunderstood, so I must clarify fully. In the past, an organization had many middle layers, coordination layers, and execution layers—these bureaucratic products could naturally share in the benefits of expansion. As the company grew and business boundaries expanded, these roles often made sense.

But in the AI era, many positions will be recalculated: those mainly relying on process transmission, information transfer, repetitive coordination, and standard execution will see their scarcity decrease; those only maintaining old systems but unable to help the company migrate to new systems will become increasingly dangerous—meaning, people who only hold meetings will become useless.

Conversely, those who will truly appreciate in value are no longer just team leaders; they are a different kind of person: those who can define problems, reengineer processes, translate business language into technical tasks, turn technical capabilities into operational results, handle major client orders, and identify where resources should migrate before the organization fully perceives it.

The most valuable future employees are not necessarily the most numerous but the few who can amplify machine, capital, and organizational efficiency.

From “more people equals strength” to “high-leverage talent is strength,” the gap is not just technological upgrading but a complete re-pricing of organizational value in this era.

This resource migration will bring several obvious externalities:

Any migration of factors of production will not only happen inside companies but will spill over, rewriting labor markets, management styles, organizational relationships, and even shaping a generation’s career perceptions.

Externality 1: The value map of the labor market will be redrawn

In the past, many people built their careers on a default premise: as long as I work long enough in a system, my experience will become more valuable, and my position more stable. But this premise is now shaking. More and more people will realize that what they thought was experience might actually be depreciation within an old system.

They are familiar with the old processes, mastered the coordination methods under the previous organizational structure, and excelled at management interfaces of the past. The problem is, companies are now rewriting these interfaces. So, the future labor market will not just see a reduction in jobs but a reevaluation of value: some will suddenly appreciate because they can turn AI into results; others will suddenly depreciate because their most skilled areas are the easiest to rewrite in the future.

Externality 2: Organizational governance will shift from headcount priority to capability priority

In the past, management meetings often started with whether to expand the team; increasingly, companies now first discuss: which processes can be rewritten, which positions should be recalculated, and which departments, though still busy, no longer constitute future barriers. Management language will undergo significant change.

Good managers in the past might have been those who kept people well, stabilized the team, and closely monitored execution; future good managers will be those willing to dismantle old processes, rebuild new interfaces, reduce inefficient layers, and let technology truly take over much of the repetitive work. When factors of production are migrating, organizations usually lose not efficiency but the illusion of warmth.

Externality 3: The psychological contract between companies and employees will continue to loosen

In the past, many felt secure in their careers based on a simple belief: as long as I work hard and stay loyal, and accumulate enough time, the company will give me a relatively stable position. Today, more people realize that “stability” is often just an illusion—what was considered core expertise yesterday might become a sunk cost tomorrow; positions deemed irreplaceable yesterday might lose significance as resources shift. The only truly stable thing is your ability to connect with new factors of production.

Externality 4: Industry will set an example effect, and actions will accelerate spreading

Once the market proves that “layoffs + reinvestment in AI + stock price rising instead of falling” is a valid narrative, more companies will learn to package their adjustments with similar language. Reuters has already pointed out in its commentary on Meta that such large-scale adjustments could serve as templates for others, pushing more firms along the same path of “AI cost—personnel structure” rebalancing.

This is why Oracle’s case should not be seen only as Oracle’s own matter or just about those tech giants. It is a mirror and a farewell letter to the future.

For Chinese entrepreneurs, what is truly worth learning is not layoffs but how to identify old tracks

Writing here, a common misconception might be: should Chinese companies also follow the big firms, quickly cut staff, tighten organizations, and go all-in on AI?

When I discuss AI with some entrepreneurs, their first reaction is often that some people are no longer useful, but they overlook the real lesson: what’s truly worth learning is not just the surface action but the judgment behind it. The core of what big firms are doing today is not layoffs but admitting that the old system no longer deserves to receive the most valuable resources.

Many Chinese companies today face not a lack of resources but a flow of resources according to the previous growth logic: money still circulates in old businesses, people pile up in old structures, management attention is still pulled by old problems, and many organizations are busy every day—merely maintaining the old system.

A company truly aging is often not because it has stopped moving on the surface, but because internally it remains busy, yet the direction of that busyness is wrong—so even if it runs hard, it still regresses to yesterday.

The lessons for Chinese companies can be summarized as:

Lesson 1: Don’t ask whether to adopt AI first, but ask which resources are still circulating on the old track

Which businesses can still generate revenue but are no longer worth continuing to reallocate core resources? Which departments seem important but are actually remnants of the old growth logic? Which middle and senior managers are still good at old division and coordination but lack the ability to translate business into new systems? Which resources, if not migrated today, will cost more tomorrow?

These questions are more important than whether to adopt AI. Because many companies don’t lack an AI project—they lack a real resource shift. It’s not about lacking technology; it’s about the courage to admit that the old system no longer deserves to take the most precious resources.

Lesson 2: Entrepreneurs need to re-understand human efficiency

In the past, human efficiency was mostly measured in financial terms: how much output per person. In the future, human efficiency should be redefined: is a team repeating old processes, or amplifying new capabilities?

This means entrepreneurs should shift from simply nurturing a department to configuring a capability portfolio. Scale is not the issue; structure is. It’s not that more people are stronger, but that those who can amplify machine and model capabilities are the real strategic assets.

Lesson 3: The most dangerous middle and senior managers are not those replaced by AI but those who interpret the new era with old methods

The most dangerous middle and senior managers in the future are not those who do not work hard, but those who still explain resource allocation in the new era with old methods.

Only managing teams, reporting progress, coordinating, managing processes, and watching KPIs—these skills won’t disappear immediately, but their value will diminish over time. Because these skills mostly belong to old management interfaces, while what companies need today is a different capability: can you see which processes should be taken over by machines; can you break down a business problem into technical tasks; can you push cross-department collaboration from person-to-person to system-driven; can you help the company turn technical capabilities into results?

The truly valuable middle and senior managers in the future are not just those who manage people but those who can reorganize production relations. The ones who will truly be retained are not those who maintain the old order best but those who can help the company navigate the transition from old to new.

Lesson 4: The best companies start migrating before the old growth system stalls

For entrepreneurs, the hardest part is not seeing new opportunities but admitting that old advantages may be failing.

It’s not a resource shortage, but the courage to shift resources to the future; it’s not a lack of investment, but the resolve to reallocate resources to the future before the old business fully stalls. That is the real challenge in decision-making.

The ones who are truly cut may not just be positions but the old growth logic itself.

Returning to Oracle and these collective moves by major tech firms, they are uncomfortable because they expose the change of an era ahead of time.

The cruelest part of this change is that once a company judges that the most important factors of production have shifted, it will start to reprice everything—including jobs, departments, management, experience, even loyalty and seniority.

The old business is not immediately useless, nor is the old organization immediately broken, nor are the old personnel immediately unimportant. But they all have to accept a reordering. And once the order begins to shift, many seemingly stable things suddenly appear fragile.

Companies will not wait for the old system to completely die before fueling the new. The highest level of resource allocation actually occurs while the old system is still running.

In this sense, behind Oracle’s layoffs, what is truly being cut is not just thousands of jobs but perhaps an entire set of old growth logic.

In the past, companies believed that more people meant bigger scale; today, more companies believe that what truly defines the future is not more people but a stronger new production system and a few key high-leverage individuals.

What Chinese companies should truly learn is not how big firms lay off, but why they dare to give the throttle to the new engine before the old one stalls.

This is the most thought-provoking lesson today.