Glossary
Memory staleness
Memory staleness is when an AI agent holds a stored fact that was true once and no longer is. The agent may answer from the old fact as if it were current.
What memory staleness is
A memory store keeps facts from past conversations and events. Facts change over time, such as a budget, a contact, or a plan. If the store keeps the old value and the agent reads it, the answer is out of date.
Staleness is a property of the stored data, not of the model. The model answers well from what it is given.
Why it is hard
- The old and new values can both sit in memory with no marker showing which is current.
- A person may change a fact without saying so, so nothing tells the store to update it.
- Retrieval can surface the old value because it matches the question better.
How it works in Harny
- Your app sends a changed value with a newer timestamp, and that value becomes the current one. The earlier value stays answerable by date.
- On paid plans, situation awareness marks a fact the person has since said no longer holds, so the agent does not repeat it.
Does a newer memory always replace an older one?
Not always. When you send the same id with changed text, Harny stores a new revision and deletes the memories built on the old revision. A changed value with a newer timestamp becomes the current value, and the earlier value stays answerable by date. When a person has said two things that cannot both be true, Harny keeps both and picks no winner.
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