How do you architect memory systems for conversational LLM applications?

LLM memory systems combine short-term context windows, long-term vector memory, and structured user state storage.

LLMs have limited context windows, so production systems implement layered memory: short-term (recent messages), long-term semantic memory (vector DB), and structured memory (user profiles, preferences). Memory retrieval is dynamically injected into prompts based on relevance scoring.