The Great Acceleration

The “stable 30-year career” is dead. The question isn’t whether change is coming – it’s whether you’ll be ready when it does.

Individual retraining is insufficient. Going solo means competing with AI for scraps.

This is what structural unemployment looks like. It’s not individual failure. It’s systemic failure.

This article examines why companies are building massive centralized AI infrastructure for workloads that don’t technically require it, who profits from that choice, and what communities need to understand before approving deals that subsidize extraction infrastructure instead of supporting adaptation alternatives.

While Meta signs multi-gigawatt nuclear deals and communities approve billion-dollar data centers, Swiss researchers proved that 80-90% of AI work doesn’t need massive facilities at all. It is now capable of running on 4-10 computers locally.

When technology hits the “good enough AND cheaper” threshold, change happens FAST. Distributed computing didn’t gradually replace mainframes over 20 years—it happened in 3-5 years once the technology crossed that line.

We just crossed that line. Last week.

December’s numbers paint the picture clearly: 122,000 jobs added according to ADP. 209,838 tech workers laid off in 2025. The disconnect isn’t an accident. Companies are hiring people who build the automation while laying off people the automation replaces. Workers using AI are taking jobs from workers who don’t.

Infrastructure buildout accelerating despite financing uncertainty. Workers caught between automation pressure and infrastructure job promises that don’t materialize.