Context Engineering for Agents

In this monologue, the speaker, Lance from LangChain, introduces the concept of "context engineering" in AI agents, defining it as the art and science of optimizing the information within an agent's context window. He categorizes context engineering strategies into four main areas: writing context (saving information outside the context window), selecting context (pulling relevant information into the context window), compressing context (retaining only essential tokens), and isolating context (splitting context to aid task performance). Lance provides examples of how these strategies are applied in popular AI agents and explains how LangGraph supports each of these approaches through features like state objects, long-term memory, and tools for summarizing and trimming message history, emphasizing the importance of token tracking and evaluation in context engineering efforts.