Agents don't sleep — and that's breaking traditional compute architectures.

Mohamed Awad (EVP Cloud AI at Arm) nails the core bottleneck: CPUs are now always-on coordinators in agentic systems, not just interactive workload handlers.

The problem? Agent sprawl. One agent spawns 10, those spawn 100, then 1000 — recursive task delegation at scale. Every spawned agent needs orchestration, state management, and scheduling. That's all CPU work.

Energy becomes the real constraint. Every milliwatt burned on CPU overhead is a milliwatt you can't allocate to accelerators (GPUs/TPUs) or serving more agents. It's a zero-sum game at datacenter scale.

Implication: We need ultra-efficient CPUs purpose-built for agent coordination, not general-purpose compute. Think low-power, high-concurrency, optimized for context switching and async task graphs.

Arm's pitch here is obvious — their low-power architecture could dominate this coordination layer while leaving heavy lifting to accelerators. But the real insight is architectural: agentic AI demands a new compute hierarchy where CPUs are lightweight orchestrators, not heavyweight processors.