By default, an LLM forgets you the moment a conversation ends. Start a new chat and it has no idea who you are, what you told it last week, or what you prefer. For a real product, that is a dealbreaker. Users expect the app to remember.
The standard fix is a memory pipeline you build yourself. Extract the important facts from each conversation. Turn them into embeddings. Store the vectors in a database. On every new message, run a similarity search, pull the relevant facts, and inject them into the prompt. That is a meaningful chunk of engineering, and you maintain it forever.
Backboard collapses that into one parameter: memory. Set it to "Auto" and your assistant remembers.
The one parameter
Memory is stored on the assistant, so pass the same assistant_id and memory="Auto". Facts the user shares in one conversation are recalled in the next.
