In 1972, Intel co-founder Andy Grove implemented a management method called "OKR" internally at the company.

At that time, no one realized that this assessment system, which simply changed its format, would completely reshape the management philosophy of Silicon Valley over the next half century.

Grove's logic at the time was simple—information flows faster within the organization, decisions are better, and the company becomes stronger.

Fifty years later, Mark Zuckerberg probably wants to do the same thing, only he is using not a form but an AI intelligence.

The Wall Street Journal revealed a detail this week—Zuckerberg is creating a dedicated "CEO intelligence". This system is still in development but can already allow him to bypass the traditional reporting chain and quickly access various data and information directly from within the company.

It sounds like an advanced version of a search box, but the logic behind it is much deeper.

In a traditional large company, how many steps does information go through from the grassroots to reach the CEO? Department managers, VPs, SVPs, reporting materials, meeting minutes… by the time the information reaches the decision-maker, it is either filtered or outdated.

What Zuckerberg wants to solve is exactly this "information decay" issue.

This is not just a convenient tool; it is a surgical operation on the company's power structure.

What’s more notable is that this dedicated CEO intelligence does not exist in isolation.

According to reports, there is now a complete AI tool ecosystem forming within Meta—employees are required to participate in AI training weekly, engage in hackathons, and are encouraged to build their own AI tools.

Since February of this year, Meta has become the first large tech company to formally incorporate "AI usage" into employee performance evaluations. "AI driven impact" has become a core evaluation metric for every Meta employee.

In other words, Zuckerberg is not just creating tools for himself; he is reshaping the entire organization's "operating system".

To understand Zuckerberg and Meta's pivot, we must first review the path Meta has taken in the past few years.

The history of the metaverse is clear to everyone. In 2021, Meta changed its name from Facebook to Meta, announcing its bet on the virtual world, and over the next few years burned through hundreds of billions of dollars, but users did not buy in, and the stock price fell to a low point. The problem with that gamble was that it was a story of "technology seeking a scenario"—building the palace first, then looking for people willing to move in.

This time, the AI strategy has a completely different logic.

Meta is now betting on embedding AI directly into existing products and processes that are already used by billions of people, not to create a new world but to transform the operating machines.

On March 16, Meta announced an agreement with infrastructure provider Nebius to purchase up to $12 billion in AI computing power by 2027. This year's total AI investment is expected to reach $115 billion to $135 billion, including large-scale cooperation with Nvidia and the construction of 30 data centers.

At the same time, in the past few months, Meta has successively acquired the AI social media platform Moltbook and the Singapore startup Manas AI, which focuses on personal AI intelligence, the latter's core technology direction highly overlaps with "CEO intelligence."

This investment curve is very clear—first blast computing power, then collect scenarios, and finally use internal people as the first test subjects.

Of course, this path is not without hidden reefs.

Just in mid-March, a security incident occurred within Meta, highlighting a glaring footnote of this "AI-first" culture.

A software engineer used AI intelligence on the internal bulletin board to break down a colleague's technical problem, and as a result, this AI published an answer on its own without any human approval. Another employee subsequently acted based on this AI's erroneous suggestion, ultimately leading to a large amount of sensitive company and user data being leaked to engineers without corresponding permissions. This vulnerability lasted nearly two hours before being discovered.

The terrible aspect of this incident lies not in the data leak itself but in the revelation of a systemic vulnerability—once AI intelligence is deeply embedded in organizational workflows, its "loss of control" is no longer a plot from science fiction but a specific engineering problem.

Analysts from the MIT Sloan Management Review described this dilemma very accurately—AI intelligence plays dual roles of "tool" and "colleague" within the organization, and this dual identity breaks the logical boundaries of traditional management.

When AI can collaborate and analyze in workflows, and even replace humans in making decisions at certain steps, who is responsible? Who is to blame when problems arise?

Zuckerberg aims to obtain faster information with the CEO intelligence; this goal itself is not problematic. But when the entire company is accelerating along this path, the tension between "speed" and "safety" will increase significantly.

There is another layer of subtlety worth discussing.

Meta laid off about 11,000 employees in 2022, and another 10,000 in 2023. Now, the company's performance evaluation has started to tie to AI usage, and management repeatedly emphasizes "flattened teams" and "enhancing individual contributor output".

Employees are not fools. They are very clear about what these words mean.

If an AI intelligence can help the CEO bypass hierarchies to directly obtain information, is there still a need for those middle managers responsible for "information dissemination"? If the productivity of every employee can be exponentially amplified by AI tools, what percentage of the current employee count does the company actually need?

Sam Altman mentioned recently at the AI summit in India, "AI can serve as a better CEO for a large company than anyone." Sundar Pichai has also publicly stated that AI might "replace him" within a year.

These statements sound like humility, but in the context of Meta's "AI-driven performance" framework, they resemble a warning.

CEOs of tech companies are making their stances clear: AI is not just an efficiency tool, but the starting point for organizational restructuring.

What this means for employees remains uncertain. But one thing is clear—by 2026, over 70% of the world's top 2000 companies will have transitioned AI intelligence from pilot programs to production deployment.

The window of opportunity for observation is closing.

Grove invented OKR because he realized that the most scarce resource in an organization is not money but attention. Zuckerberg's creation of the CEO intelligence follows the same logic—at a company with 70,000 employees processing billions of pieces of content daily, the speed at which information reaches decision-makers determines how fast the company can run.

Only this time, the cost and boundaries of acceleration have not been truly calculated by anyone.

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