ai-memory

To store and retrieve context across AI conversations, you can use a memory skill to save personal data like schedules, contacts, and notes, which the AI fetches in future interactions to maintain continuity.

The best way to save user preferences for long-running AI interactions is to ingest your preference data into a memory store, allowing the AI to recall relevant information and reduce repetition across sessions.

Yes, you can use memory notes to maintain meeting schedules across different sessions by asking the AI to remember your appointment details and then retrieving that stored data before a new meeting.

You retrieve stored contacts and notes before a new AI session by activating the memory function, which accesses previously ingested personal data to provide operational guidance and context for your current task.

AI memory uses a structured YAML frontmatter containing a name and description for metadata, alongside a Markdown body that provides operational guidance when the stored information is activated.

Your AI assistant forgets preferences after each chat session because it lacks persistent memory; applying a memory skill enables it to store and retrieve user data, maintaining context across interactions.