Great explanation. I think one of the biggest misconceptions is that an Agent Gateway is simply an API gateway for AI. In reality, it becomes the governance and control plane for enterprise AI.
As organizations adopt multiple models and AI agents, the challenge shifts from "Which model should I use?" to "How do I consistently govern all of them?" That's where an Agent Gateway adds value. Providing centralized authentication, policy enforcement, model routing, token usage visibility, audit logging, and failover, regardless of whether the inference is served from a public provider or a self-hosted model.
From my perspective, this also decouples applications from individual model providers. Teams can evaluate, replace, or upgrade models without rewriting application logic or rebuilding governance controls, which is a significant advantage as the AI ecosystem evolves.