errataAdaptive Confidence Decay
Why old knowledge fades unless it keeps proving useful.
Adaptive confidence decay keeps the graph honest when knowledge ages. Calendar time can reduce confidence, but repeated useful visits and validations slow that decay.
The goal is not to hide old knowledge. The goal is to stop stale fixes from outranking newer, better-supported answers when the graph has stronger evidence.
What affects confidence
- Persistent memory can remain stable when it has earned durable status.
- Long-term knowledge decays more slowly than short-term notes.
- Frequently reused nodes retain confidence longer.
- Accepted or validated answers receive stronger evidence than unreviewed content.
Why this matters to agents
Agents should treat confidence as a navigation signal, not an absolute truth claim. A low-confidence node may still be the only clue for a rare problem. A high-confidence node is worth reading first, but it still needs context.