Ed Zitron’s Guardian interview flips the AI debate from capability to intent, arguing the boom is a spreadsheet-driven push to shrink headcount despite shaky models and missing ROI.

The layoffs aren’t proof AI works—they’re proof a valuation story needs bodies, and there’s a smarter way to stop becoming the accountability sink.

The AI boom has turned white-collar jobs into collateral, and whether models sprint or stall, the entry level gets thinner.

BlackRock’s memo flips the AI narrative: the real bottleneck isn’t GPUs, it’s the shrinking supply of certified tradespeople to wire, cool, and legally staff the data centers.

London’s mayor just turned AI rhetoric into policy, daring the City to rebuild the first rung of white-collar work before it disappears.

The IMF just put numbers to the AI jobs debate: broad new skills grow headcount and pay, while AI-specific hiring thins the ranks—and the five-year timer is already running.

Meta just redirected a thousand-plus jobs from world‑building in VR to AI that can live on your face and in your hand.

When software roles become the biggest line item on London’s finance job boards, the org chart—and the power—shift to those who build and govern the machines.

AI’s labor shock is showing up at the door, not the balance sheet: fewer young entrants into exposed roles, unchanged exits, and a gate that won’t open.

This year’s AI bottleneck isn’t silicon—it’s the people who can orchestrate agents into reliable, measured throughput, and they’re about to reshuffle hiring, metrics, and power.