Memory is only the beginning
The path from shared AI memory to a contextual companion, with current limitations made explicit.
Make shared memory dependable
The immediate foundation is an understandable setup, one clearly selected memory location, reliable application connections and corrections that prevent stale instructions from persisting.
The preview already prepares files and startup rules. Consolidating older integrations, switching vaults and verifying behavior in real AI conversations remain work to complete.
Tracking is not understanding
Tracking an open commitment is a state-management problem: what is pending, what changed and whether a condition is met. Much of this can happen without continuously running a language model.
Understanding context requires an additional judgement: whether a change matters, what evidence supports it and whether approaching the user would help. The project keeps these responsibilities separate instead of treating a timer as a companion.
Understand changes over time
Retrieving a note answers what was recorded. A contextual companion must also understand what has changed, which evidence is relevant now and whether a possible intervention is welcome.
The research separates inexpensive state tracking from semantic synthesis. Neither a task timer nor a notes dashboard alone fulfills this goal. Physical, emotional and temporal context require careful treatment, and model inferences must remain correctable.
Choose when to reach out
The intended companion can offer continuity, a useful resource or a timely question without waiting for a new prompt. It must also know when to stay quiet.
Proactive contact, operation while the computer is off, sustainable reasoning costs and a future mobile application are open goals. No release date is promised.