Concept Status
Why Relevance Changes Over Time
Not every saved memory remains equally important forever. A memory about a specific bug you fixed in a project you no longer work on is less relevant than a memory about a pattern you use every week. Relevance scoring aims to reflect this reality.
Factors That Influence Relevance
| Factor | Effect |
|---|---|
| Recency | Memories you saved recently start with higher relevance |
| Frequency of access | Memories you view often stay more relevant |
| Search interaction | Clicking a result in search increases its score |
| Time without access | Memories not accessed over long periods gradually reduce in prominence |
Decay vs. Deletion
Memory decay is not the same as deletion. A memory with low relevance does not disappear — it simply appears lower in default sort order and search ranking. It remains fully accessible when you search for it directly or browse by tag.
Why Old Memories Should Not Disappear
The value of a knowledge base comes partly from its history. A memory about a programming concept you learned two years ago might still be exactly what you need when you return to that technology. Permanent deletion would destroy that long-term value.
The goal of relevance scoring is to surface the most useful knowledge first, not to discard what you have built up over time.