Behind the Meter: Why AI Data Centres Are Becoming Power Projects

For the last two years, AI infrastructure has been framed as a race for chips, then a race for power. Both remain true, but the next constraint is now becoming more specific: time to power. The issue is not simply whether enough electricity exists somewhere in the system. The issue

The Data Centre Backlash: Why Social Licence Is Becoming The Real Constraint

For the last two years, AI infrastructure has been framed as a race for GPUs, then a race for power. Both remain true, but the industry is now discovering a third constraint, public consent. The data centre sector has moved from being welcomed as invisible digital infrastructure to being challenged

Context Has Gravity: The Hidden Infrastructure Bottleneck Behind Agentic AI

For the last two years, AI scaling has been framed first as a race for GPUs, then as a race for power, then as a race for inference capacity. Now another important constraint is now becoming visible: context. At first, context sounds like a software problem, it sounds like prompt

The Inference Boom: Why Enterprise AI Will Be Won at the Workload Layer

For the last two years, AI scaling has been framed as a race for chips, then a race for power. Both are still true, but there is another race emerging, one where the ability to service real world workloads will be key to success. The next phase of enterprise AI

The AI Factory Is Moving: Why Distributed, Energy First Infrastructure Wins

For the last two years, AI infrastructure has been framed as a race for chips, but that framing is now too narrow. The harder problem is increasingly physical: energisation, land, cooling, electrical equipment, and the ability to turn compute demand into live operating capacity. The IEA now projects data centre