Meta has never made more money. Meta’s employees have never been more miserable. Those two facts aren’t in tension. They’re the same story.

Next week, Meta begins cutting roughly 10 percent of its workforce, a reduction that will touch thousands of people across the company. Wired spoke with more than a dozen current and former employees, and the portrait they paint is of a company where, in their words, “everyone is unhappy.” Record profits. Record low morale.

This is what the AI productivity era looks like from the inside.

The Economics Are Working Perfectly

From a pure financial standpoint, Meta’s strategy is delivering. The company has been among the most aggressive in the industry when it comes to betting on AI, and those bets have come with a deliberate restructuring logic: if AI tools can do more work, you need fewer people to do it. That’s not a side effect. It’s the goal.

What’s notable about the current round of cuts isn’t the scale, it’s the timing. Meta is not laying people off because it’s struggling. It’s laying people off while posting record earnings. That framing matters enormously for how the rest of the industry reads the signal. The message to other large tech companies is simple: you don’t have to be in trouble to cut headcount. AI gives you cover to do it even when the numbers are good.

For investors, this is the story they’ve been waiting for. For employees, it’s a different calculation entirely.

What It Actually Feels Like Inside

The Wired reporting is worth sitting with. More than a dozen current and former Meta employees described an environment defined by anxiety and distrust. The cultural contract that existed at pre-pandemic Meta, where strong performance and team loyalty bought some degree of job security, has been replaced by something colder and more transactional.

Zuckerberg has been unusually direct about the reasoning. Meta is building AI systems aggressively, restructuring teams around AI capabilities, and shedding people who don’t fit that new shape. The company framed earlier layoff rounds as cutting “low performers,” a framing that many employees found demoralizing not because it was wrong about those specific individuals, but because it shifted the entire atmosphere toward hypervigilance.

When the company is growing and profitable and still cutting staff, it’s hard for employees to find a stable footing. The question changes from “am I doing good work?” to “am I defensible?”

That psychological shift has real costs. Some of them show up in ways that are hard to quantify. Some of them eventually show up in attrition of people who had choices, which is the kind of talent drain that doesn’t show up on earnings calls until later.

The Broader Pattern

Meta isn’t alone here, and that’s what makes this worth paying attention to as an industry signal rather than just a company-specific drama.

Across the sector, the largest AI spenders are quietly running a version of the same experiment: invest heavily in AI capabilities while systematically reducing the number of humans required to operate the business. The theory is that AI-augmented workers are significantly more productive, which means you need fewer of them to produce the same or better output.

The theory is probably correct in many cases. The human consequences are real regardless.

What’s changing right now is the speed and openness of the process. Earlier tech layoff waves, after the 2022 rate shock, were easy to explain as corrections to pandemic-era overhiring. This wave is harder to explain that way. Companies are healthy. Revenue is up. AI is the explicit reason for the restructuring, not a cover story for financial distress.

The Software Side of This

There’s a separate thread in today’s news that connects to the same underlying shift. The Verge has a piece on what writers there are calling the “personal software revolution,” the idea that vibe coding tools and AI-assisted development are beginning to make it possible for non-programmers to build functional software for their own needs.

The piece argues that the tyranny of off-the-shelf software, where users are forced to work within the constraints of what professional developers decided to build, is starting to crack. When a lawyer or a doctor or a small business owner can describe what they want and have something functional emerge from that description, the relationship between software makers and software users changes fundamentally.

For the AI industry, this is a genuinely interesting development. It expands the addressable market for AI tools dramatically, because it means the relevant user base is no longer just developers. Every knowledge worker with a specific workflow need is a potential customer for this category.

For professional software developers, it’s a more complicated signal. The tools that let non-developers build simple personal software are not yet replacing production engineering work. But they’re getting better fast, and they’re compressing the lower end of what requires a professional to accomplish.

Meta cutting engineers while also building AI systems that write code, while also operating in a world where non-engineers can increasingly build their own tools, is not a coincidence. These are all parts of the same structural shift.

What to Watch

The Meta story will keep developing. The actual layoffs begin next week, and how the company handles the process, what teams get hit hardest, whether AI-adjacent roles are protected while others aren’t, will tell us more about how seriously Zuckerberg is treating AI as an organizational redesign project rather than just a product strategy.

More broadly, watch for other major tech companies to read Meta’s results carefully. When record profits and staff reductions coexist without apparent market punishment, that’s a template. Other companies will notice.

The employee morale piece is the variable that’s hardest to model. Low morale at a company with record profits is a solved problem in the short term. Whether it becomes a talent retention problem depends on how many of those unhappy employees have somewhere better to go, and in an industry that’s restructuring broadly, that’s not obvious.

The AI productivity story has always had two sides. We’ve spent a lot of time on the side that looks like efficiency gains and margin expansion. The other side looks like what’s happening inside Meta right now.