Context Engineering - LLM Memory and Retrieval for AI Agents

AI Impact Summary

AI agents relying on LLMs require a robust memory system to handle complex, real-world tasks. Without context engineering, agents struggle with tasks that depend on past interactions, internal documentation, or external data, leading to inaccurate or irrelevant responses. This system focuses on managing the LLM's context window, combining short-term and long-term memory, and selectively delivering information to improve reliability in production environments. The core challenge is managing the finite context window and preventing issues like context poisoning, distraction, or confusion.