Cloud native infrastructure is evolving into an 'AI native' operating model as agentic systems demand more than containers and Kubernetes can provide. While the existing cloud-native stack remains foundational, AI-native systems require new layers: agent orchestration, memory management, context routing, policy-aware execution, and a new kind of observability that handles probabilistic behavior. Research benchmarks like AI-NativeBench and AgentArch highlight that architecture — not just model intelligence — is the critical challenge. Platform engineering teams will need to govern agentic execution with approved tool catalogs, identity controls, audit trails, and workflow approvals. Open source standards and interoperability are essential to avoid vendor lock-in. The transition mirrors prior stack shifts (VMs to containers to Kubernetes) but moves the control plane from infrastructure into execution itself.
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