Automated Cryptographic Agility Frameworks for AI Resource Orchestration

This blog post argues that AI-driven workflows break traditional cloud security models and reframes the four C's—Cloud, Cluster, Container, and Code—around AI-specific risks such as model context leakage, GPU-aware infrastructure, control plane integrity, containerized model weights, and insecure AI-generated code; it promotes standards like a Model Context Protocol (MCP), tools such as Gopher Security, and policy/risk controls (e.g., runtime protection, granular policy engines, living audit logs) to future-proof AI deployments.