Your AI agents are lost: give them a graph w/ Anthony Alcaraz (AWS)

The race to build capable AI agents often focuses on model intelligence. Anthony Alcaraz argues that the harder, more durable problem is context: giving agents the right information, relationships, tools, and constraints at the moment they need them.Anthony is a Senior AI/ML Portfolio Growth Manager at AWS and co-author of O'Reilly's Agentic GraphRAG. He explains how graph-based architectures can improve retrieval, memory, planning, and multi-step reasoning while capturing the tribal knowledge that conventional enterprise systems leave behind.The conversation also looks beyond architecture. Anthony describes self-improving agent systems, feedback loops that connect technical performance to business outcomes, and a future where small teams manage large fleets of agents without losing sight of customers or value.