Agent memory layers

Agent memory layers store what an LLM application learned in one session so it can be used in the next. They sit between your agent and one or more databases: on write, an LLM decides what is worth keeping; on read, a search picks what goes back into the prompt. The projects differ in the unit they store, from short facts about a user to a full knowledge graph built from documents. When choosing, look at the write path (how many LLM calls per message, and whether old facts are updated or only appended), what retrieval returns (ranked records or a finished answer), how isolation between users is enforced, which databases you must run, and which features exist only in a hosted version.