Five Common Failure Modes That Can Silently Break AI Agent Memory Stores

AI agent memory bugs rarely cause crashes — instead, they surface as confidently wrong answers, such as an agent recalling an outdated address or an expired preference. A key failure mode involves LLMs running on the write path, where hallucinated metadata gets persisted as structured fields that are later trusted and queried. Another common issue arises in insert-only memory stores, where a new fact does not automatically replace an older one, leaving both to coexist and allowing stale data to be retrieved. The article identifies five such failure modes spanning correctness and security, using the Engrava memory library as a reference point for design tradeoffs. The author acknowledges a conflict of interest, noting they work on Engrava, which avoids LLM involvement in its write path by design.