In this Techstrong AI Leadership interview, Simba Khadder, Context Engine Lead for Redis, warns that while the reasoning capabilities of Large Language Models (LLMs) are doubling every few months, the real winners will be the organizations that can feed these agents the right data at the right time through a dedicated "context engine". By moving beyond traditional Retrieval-Augmented Generation (RAG) to build stateful, semantic surfaces, enterprises can finally unlock the true value of their structured and unstructured data while avoiding the catastrophic risks of giving non-deterministic AI direct access to their core systems of record.