LLM providers are trying to build enterprise guardrails directly into their products, but it won't work. Companies don't run on a single LLM any more, they're often using a mix of frontier models plus open-source and specialized vertical models spread across various use cases. Model providers can improve their guardrails, but that won't fix the fragmentation problem. The industry tried this before! In the early microservices era, every team baked auth, rate limiting, and logging directly into their apps, which worked fine until you had hundreds of services and no consistent enforcement or unified observability. We abstracted the connectivity logic to the traffic layer back then, and you need to do it again with AI. Effective AI governance (token budgets, permissions, compliance, etc) can't live inside a single model. You need a neutral layer that sits in front of everything. A "Switzerland for AI" as Khozema Shipchandler called it. A single control tower that manages all traffic regardless of source.