Agent Memory Garbage Collection: Engineering Strategic Forgetting at Scale
Every production agent team eventually builds the same thing: a memory store that grows without bound, retrieval that degrades silently, and a frantic sprint to add forgetting after users report that the agent is referencing their old job, a deprecated API, or a project that was cancelled three months ago. The industry has poured enormous effort into giving agents memory. The harder engineering problem — garbage collecting that memory — is where the real production reliability lives.
The parallel to software garbage collection is more than metaphorical. Agent memory systems face the same fundamental tension: you need to reclaim resources (context budget, retrieval relevance) without destroying data that's still reachable (semantically relevant to future queries). The algorithms that solve this look surprisingly similar to the ones your runtime already uses.
