Block workers challenge AI ‘efficiency’ narrative after 4,000 cuts

Block has become the highest‑profile example of a major public company explicitly blaming AI for mass layoffs, and this Guardian follow‑up shows how messy that story looks from the inside. Engineers and product staff describe being pushed to use internal AI tools, not because they were radically better, but because management wanted to justify a smaller workforce and signal “AI-first” discipline to investors. That gap between C‑suite narrative and ground truth is going to be a recurring theme as enterprises retrofit themselves around automation.

From an AGI race perspective, this matters less for the incremental capability of any one model and more for how quickly organizations are willing to rewire themselves around AI. Block is essentially running a live experiment in running a fintech conglomerate like a “mini‑AGI,” in Dorsey’s words, with thin management layers and high agentic‑tool penetration. If it works, expect copycats across finance, retail and logistics. If it fails, it will feed skepticism that current-generation systems are ready to substitute for deep domain expertise at scale, slowing aggressive restructuring elsewhere.