AI psychosis grips tech CEOs

Levie's diagnosis is snarky, but the underlying point is solid: demo-level AI success gets overgeneralized into fantasies of full autonomy. That usually produces premature headcount cuts, inflated expectations, and a bigger verification burden for the people left behind.

• –Prototype wins hide the hard parts: edge cases, hallucinations, policy exceptions, and review overhead.
• –AI-driven layoffs often mix real automation with plain cost-cutting, then get explained away as strategy.
• –If AI raises output, the bottleneck usually shifts to approvals, QA, and governance rather than disappearing.
• –The useful near-term market is assistive workflows, not magical end-to-end replacement.