On May 20, Meta will cut 8,000 employees — 10% of its workforce — and cancel 6,000 open roles, while spending up to $135 billion on AI infrastructure this year. CEO stock options are restructured around a $9 trillion market cap by 2031, with potential payouts of $921 million each for three top executives. Internal tooling now captures employee keystrokes to train AI agents. The trajectory: more AI, fewer people, and those who remain train the AI that makes the next round unnecessary.

Meanwhile, Marc Benioff is publicly running the opposite playbook. Salesforce has redeployed hundreds of customer support engineers into AI evaluation, forward-deployed engineering, and growth roles — keeping the workforce roughly flat while shifting its composition. The mechanism is Career Connect, an AI-powered talent marketplace surfacing transferable skills across the company. The Forward-Deployed Engineer team, which helps customers implement AI, has grown past 1,000 people. Internal language: "reshape, not reduce."

Two CEOs. Two opposite bets on what an AI-era workforce should look like. One of them is going to be the playbook everyone copies. The interesting question isn't who's right — it's what each one is actually betting on.

What Meta is betting

Meta's bet is about velocity. The premise: AI capability is doubling fast enough that maintaining a large general workforce will cost more than the severance, training, and culture damage from aggressive cuts. Employees laid off can train the agents replacing them on the way out — keystroke data captured by the Model Capability Initiative makes the loss productive on both ends.

The bet assumes AI agents will keep compounding rapidly in middle-management work, severance and morale costs are recoverable within 18–24 months, regulators won't intervene on workforce displacement, and the cultural cost of being the industry's most aggressive cutter is offset by the cost of being late.

What Salesforce is betting

Salesforce's bet is about institutional learning. The premise: the firms that pull ahead won't be those that swap humans for AI fastest, but those that build the operating muscle to continuously rebalance both. Domain knowledge compounds. Customer relationships compound. Internal mobility creates information flow that cut-and-rehire destroys.

The Forward-Deployed Engineer team is the most telling part. These aren't generalists — they carry deep Salesforce product knowledge into customer environments where AI is being deployed. They're the human layer between strategic intent and model capability. Salesforce is betting this layer becomes more valuable as AI improves, because the gap between what AI can do and what customers can specify keeps widening. (Which connects to the GenAI Wall study I wrote about last week: AI bridges adjacent expertise gaps, not distant ones.)

The bet assumes the cost of churn — knowledge loss, recruiting friction, talent brand damage — is structurally underestimated in cut-heavy strategies.

The question both CEOs are answering — and yours

Both are answering the same question: what is our implicit employment contract going to be over the next five years? Meta is rewriting it toward "we'll pay you well to train your replacement." Salesforce is rewriting it toward "we'll invest in your next chapter as heavily as we invest in the technology."

Most CEOs reading this don't have Meta's capex or Salesforce's brand permission to run either at extreme. But the bet you're making is happening, whether articulated or not. The internal mobility infrastructure you fund in 2026 determines which playbook you can run in 2028.

Salesforce built Career Connect. They bet that internal mobility is institutional infrastructure, not HR optics. Companies that don't build it choose the Meta path by default.

My read: the Meta playbook will look right on next quarter's earnings call and wrong by 2028, because the institutional capability Salesforce and Mizuho are building compounds in a way headcount cuts never have. The larger point isn't which playbook wins. It's that you're running one already — the only question is whether you know it.