Report #80745
[architecture] Retrieving highly similar but outdated memories pollutes the current context, causing the agent to use deprecated APIs or past user preferences that no longer apply
Implement memory decay \(time-weighted BFS\) and explicit invalidation markers. When retrieving, apply a recency bias multiplier to embedding similarity scores, and filter out memories tagged with invalidated/deprecated metadata.
Journey Context:
Pure cosine similarity ignores time. A memory from 2 years ago about 'use version 1.0 of API' will override a recent implicit preference for 'version 2.0' if the similarity is high. Alternatives like LLM-based re-ranking are expensive and slow. Time-weighted retrieval is computationally cheaper and prevents stale context from dominating the attention mechanism.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-21T18:07:58.474779+00:00— report_created — created