Your AI Agent Has a Memory. But It's Not Chat History

In a recent article on Dev.to, developer Rijul explores the technical distinction between chat history and true agent memory in AI systems. While chat history is limited to the context of a single, ongoing conversation, agent memory allows systems to persist and retrieve relevant information across multiple sessions. The author explains that effective memory systems involve extracting useful data from interactions, storing it in persistent databases like PostgreSQL or vector stores, and then injecting that context into future LLM prompts. By combining chat history, persistent memory, and Retrieval-Augmented Generation (RAG), developers can create agents that provide more personalized and intelligent responses. The piece also introduces LiveReview, an AI-powered code review tool designed to prioritize changes based on their impact within a codebase, helping teams focus on high-risk areas rather than reviewing every line of code equally.