AI factories are interconnected systems where fleet economics depend on how efficiently the entire stack converts power and capital into completed agent tasks. While GPUs run the models, CPUs handle orchestration, tool execution, and sandboxed computation. Unlike conventional computing with stable runtime profiles, agentic workloads are unpredictable and highly variable. Based on telemetry from 163,594 agentic sessions, over 97% of sessions showed unique trajectory profiles (Figure 1). This variability makes it impractical to right-size a fleet using multiple specialized CPU design points.

Figure 1. Telemetry data from 163,594 agentic sessions showing over 97% unique profile s

Production telemetry also reveals how these diverse trajectories unfold: across sessions, execution follows a long sequential chain of reasoning interspersed with sporadic bursts of parallel work.…