Agent OS in production: real cases without the marketing

An Agent OS is a runtime layer built to run AI agents rather than ordinary applications, and after six months of production deployments the trade-off is clear. A dedicated agent stack starts slower but stays stable; Kubernetes with orchestration bolted on top moves faster early, then hits observability and policy limits. It pays off from five active agents.

April 13, 2026 6 min 300 4.3

Architecture

Inference routers: choosing a model based on the request

An inference router decides which model answers each incoming request, weighing cost, latency and how hard the request actually is. Well-built inference routers cut total token spend by 30 to 70 percent with no quality loss the user can perceive. Four patterns cover most cases: length, task type, an auxiliary classifier, and learned routing.

November 26, 2025 5 min 250 4.1