The era of the "one-size-fits-all" LLM is ending. We are shifting toward Compound AI Systems—complex meshes where the goal isn't just to query a model, but to dynamically select the best model for the specific task at hand. This shift creates a massive opportunity for cloud-native architectures: how do you govern non-deterministic routing at scale?

This session breaks down the infrastructure required to move from monolithic agents to multi-model orchestration. We will demonstrate how to implement Semantic Routing within an AI Gateway to act as a traffic controller, instantly analyzing user intent to route queries to the most capable (or cost-effective) model. You will learn patterns for "supervisor" workflows, where lightweight models handle routing and heavyweight models handle self-correction. Join us to discover how to build controlled AI systems on Kubernetes, ensuring your agents are not just powerful, but precise, effectively governed, and fundamentally safer.