Meta is cutting 600 AI roles from FAIR (Fundamental AI Research), AI product, and infrastructure teams—while continuing to hire for TBD Lab, its superintelligence division. Alexandr Wang, Meta's Chief AI Officer, explained the cuts plainly: "By reducing the size of our team, fewer conversations will be required to make a decision, and each person will be more load-bearing and have more scope and impact."

Translation: the research team became bureaucratic. They're cutting the slowness.

The Organizational Shift

This isn't cost-cutting disguised as efficiency. It's a priority realignment. Wang (former Scale AI CEO) now runs Meta's AI. Yann LeCun, the legendary FAIR leader, now reports to him. That's the real story. Meta is choosing superintelligence speed over foundational research depth.

The numbers reinforce it. Meta invested $14.3 billion in Scale AI earlier this year and just closed a $27 billion financing deal for data centers. Those funds flow to TBD Lab's race for AGI, not to FAIR's long-term research agenda.

FAIR's work is important—theoretical breakthroughs eventually become products. But "eventually" doesn't matter when you're competing with OpenAI, Google, and Anthropic on superintelligence timelines. When the business question becomes "who gets to AGI first," organizations reshape around speed, not contemplation.

The Real Pattern

This connects to something I've written about before: AI as the backdoor layoff strategy. When companies want to reshape their workforce, they can either:

1. Announce layoffs → stock drops, media scrutiny, employee morale problems
2. Announce AI efficiency gains → stock goes up, narrative about innovation

But Meta is doing something different. They're being direct about restructuring—acknowledging the organizational problem explicitly. They're not claiming FAIR is failing. They're saying that in a superintelligence race, you optimize differently.

The question is whether they're right. FAIR has produced important research over the years. But research that doesn't ship is just cost. And if Meta believes AGI is the defining competition, then resources should flow there.

Yann LeCun will probably be fine. He's legendary enough to land anywhere, and Meta seems committed to keeping him in some capacity. But the message to the broader AI research community is clear: if you're working on foundational questions that won't ship this decade, you might want to work somewhere else.

The Timing

The cuts happen as Meta signals it's serious about superintelligence. Not someday. Now. The company is willing to reduce headcount and reorganize around that priority.

Whether TBD Lab delivers anything resembling superintelligence is a separate question. But the organizational commitment is real. No equivocating about research timelines. No "we support both" messaging. Just: this is what we're betting on.