What actually makes production AI fast, reliable, and economical
 

Most teams still ship AI like it is 2023: a closed API, a prompt, and a chat box. That works for prototypes. It breaks when AI becomes the product.

At Nebius, we think production AI needs four connected layers: Reason, Know, Improve, Govern. This talk starts with that stack, then zooms into the foundation beneath the Reason layer: production inference.

We will unpack the serving primitives that determine real cost, speed, and reliability at scale: prefill/decode disaggregation, KV cache management, cache-aware routing, MoE, and speculative decoding. The takeaway: moving from calling AI to engineering it starts with understanding the inference system underneath.