Intel: scaling agents isn't about tokens — it's about density

intel analyzed thousands of agentic ai workload experiments using an extended version of terminal-bench, an open-source profiling tool, to determine that enterprise success depends on treating agents as a systems problem rather than just an inference one. the study establishes agent density (agents per vcpu) as the primary metric for capacity planning, replacing simple agent counts, and emphasizes monitoring task latency instead of average cpu utilization. these findings indicate that enterprises can only reliably scale agents by implementing rigorous observability and memory management, moving beyond evaluating just the underlying llm. to manage costs and performance, operators should default to scale-out architectures while reserving scale-up for specific, compute-intensive constraints.