Memory Management Strategies: When to Store, Retrieve, and Forget
~15 min read
Memory isn't a property of the model — it's a system design problem. Deciding explicitly what to write, what to read back in, and when to let something be forgotten is what actually makes agent memory work in practice.
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Key points
- •Memory is a system design problem, not a model property — the surrounding system must explicitly manage store/retrieve/forget decisions
- •'What to store': be selective — durable facts, meaningfully distinct episodes, and evidenced procedural improvements, not every raw event
- •'What to retrieve': similarity-based top-k plus relevance filtering, so weak or irrelevant matches don't flood the context window
- •'When to forget': stale, superseded, or low-value memories should be pruned or down-weighted, not left to accumulate forever
- •Time-based decay, explicit overwriting, and periodic consolidation into denser summaries are the standard forgetting strategies