Powering agents with Context Graphs & Ontologies

To move to autonomous AI Agents, we need to solve the problem of memory. Agents need more than just retrieval; they need a way to collaborate, query shared knowledge, trace their reasoning, and cache decisions for efficiency. The solution lies in self-modeling context graphs and ontologies. However, implementing thes architectures introduces two massive challenges: defining the "Agent Experience" (how agents interact with the graph) and operating these complex structures at scale. In this session, we will move past theory and dive into practical patterns for building and querying context graphs. Join us to learn how to architect a system where Agents and Humans can seamlessly collaborate on a foundation of shared, scalable knowledge.