Surviving Meta's 'year of intensity'

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Business Insider's Pranav Dixit has been covering Meta for a year now. He recently reported on the company's "year of intensity" with colleague Jyoti Mann. I asked Pranav for his take on a turbulent 12 months.

Q: You've been covering Meta for a year now. What has that been like?

"Intense" is the only way to describe it — exactly what Mark Zuckerberg promised employees. I joined BI a day before Meta scrapped third-party fact-checking, and almost immediately the culture shifted: DEI rollbacks, an embrace of "masculine" energy, and moves that seemed more aligned with the Trump administration. Then came thousands of layoffs of people labeled low performers and a noticeable spike in performance pressure.

The second half of the year brought a very different pivot. Meta effectively admitted Llama hadn't lived up to the hype and reset around a new mission: building "personal superintelligence." That meant hiring Alexandr Wang, reorganizing AI under Meta Superintelligence Labs, and aggressively poaching talent while high-profile figures — including Yann LeCun — departed. It felt like covering a company reinventing its business, values, and culture all at once.

Q: What stood out most from your reporting with Jyoti Mann on this "year of intensity"?

A pervasive survival mindset. Over and over, employees told us the goal wasn't to do great work — it was to avoid landing in the bottom performance tier. Some people left on principle, saying Meta no longer resembled the company they joined. Yet others insisted this is the best job in tech: great product challenges, unmatched scale, exceptional pay. Those two realities sit side by side — one group bracing for impact, another thriving.

Q: Your reporting found managers sometimes hiring people just to fill low-performance slots. How does that work?

Meta's forced ranking requires a set percentage of "low performers." Some managers gamed the system. Some told us they avoided backfilling roles; others hired into fuzzy positions with near-impossible expectations so they didn't have to put existing trusted team members in the bottom bucket. (Meta didn't respond to specific questions on this.)

Q: What will you be watching for in 2026?

The big question is whether Meta's massive AI spend becomes a durable business or an expensive experiment. Will Meta AI become a distinct, everyday product? Will the capex binge translate into real revenue and profit? And can the culture stabilize enough to keep the AI talent Meta is betting the company on? Meta can execute — history proves that — but "intensity" can't last forever. 2026 will show whether the trade-offs were worth it.

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