Why memory is not enough: you need context management
The blog post argues that memory alone is insufficient for AI agents; effective context management is essential for handling complex, multi-step tasks, maintaining relevant information, and avoiding distractions in dynamic environments.
Background
- The "memory" being discussed is the long-term memory of Large Language Models (LLMs) like ChatGPT or Claude — systems that can recall facts across sessions but have no understanding of *when* or *why* that information is relevant.
- The article argues that true "context management" (knowing which memories matter right now, for this specific user, in this specific situation) is a harder, more important problem than simply storing more information.
- The author's company, Lore.ai, builds AI agents that manage context for enterprise workflows, so the piece is both a technical argument and an implicit pitch for their product.
- The core claim: human communication relies on shared, evolving context (what was just said, what the user is trying to do), and current AI memory systems mostly ignore this, leading to robotic and irrelevant responses.