Meta cut 8,000 jobs, burned through 91% of its free cash flow on AI infrastructure, and its CEO says AI is "creating jobs." Here's what he's not telling you.

Meta just disclosed it laid off 8,000 employees in May.

Reassigned another 7,000 to AI projects against their will.

Meanwhile, free cash flow collapsed from $8.55 billion to $784 million in a single quarter.

That's not a rounding error. That's a company that spent almost every dollar it generated on data centers.

$130-145 billion in planned capital expenditures for 2026.

32 data centers worldwide. Doubling computing capacity to 7 gigawatts this year. Then doubling again to 14 gigawatts by 2027.

Revenue is up 28% to $60.8 billion. But costs rose 55%. R&D jumped 67%. Operating margins fell from 43% to 31%.

Then Zuckerberg went on the Wall Street Journal and said AI is "net creating jobs."

The jobs he's talking about? Construction workers. Electricians. Cooling engineers.

Building the infrastructure to replace the people Meta just fired.

Here's the structural reality every executive needs to absorb:

Meta is trading knowledge workers for gigawatts.

The 8,000 people who got cut were engineers, product managers, operations staff. The people replacing them pour concrete and install power systems.

This is capital reallocation disguised as progress. The company is betting that physical infrastructure will generate more value than human capital.

And the market is skeptical. Stock fell 10% after earnings despite the revenue beat.

If your company's AI strategy involves cutting your best people to fund GPU clusters, you're running the same playbook.

Audit your workforce plan today. Ask one question: are the people we're cutting the ones who will build the ROI on the infrastructure we're funding?

If the answer is no, you're not transforming. You're liquidating.

SOURCE: https://siliconangle.com/2026/07/29/metas-ai-bill-swallows-nearly-free-cash-flow-profit-falls-14/
VERIFIED: Meta Q2 2026 earnings (SEC filing), SiliconANGLE, Economic Times
SIGNAL: Meta's cash flow collapse proves that cutting knowledge workers to fund AI infrastructure doesn't guarantee returns. The market is already pricing in the risk.