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I see the AI cycle entering its next phase.. Reports suggest $META could cut ~20% of staff (~15k jobs) while ramping $115–135B AI capex in 2026, next after $XYZ slashed ~40% of its workforce earlier this year. Translation: Meta isn’t just cutting costs it’s moving capital from people > compute. This is the first clear proof of the AI productivity trade. If AI tools allow one engineer to do the work of five, companies will naturally shrink teams and redeploy that money into GPUs, data centers, and models. Money leaving payroll is flowing straight into AI infra.. Big beneficiaries: $NVDA, $TSM, $AVGO, $AMD, $SMCI and others.. the companies building the compute backbone. Tech layoffs alone rarely move macro numbers. The real risk comes if the model spreads across industries, not just SF. What if other hyperscalers follow? Then the signal becomes structural. If $GOOGL, $AMZN, $MSFT also start cutting headcount to fund AI capex, it confirms a major economic shift from labor > compute. But this is different from Meta’s 2022–2023 layoffs. Back then, Zuckerberg cut ~21k jobs to restore margins after the metaverse overspend. 2022 layoffs = efficiency. 2026 layoffs = re-investment. Today the savings aren’t boosting profits, they’re funding AI infrastructure. That’s why investors are split.

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