[felixlu2026]

The pruning framing makes sense to me. More memory is not automatically better for agents.

One thing I’d want to preserve carefully is the type of memory, not just its relevance score. In coding-agent workflows, a note can be a durable architecture decision, a temporary debugging hypothesis, a personal preference, a failed path, or a constraint that only applied before a refactor.

Those should probably age and prune very differently.

The failure mode I keep seeing is not only bloated context. It is stale or low-authority context being reused with high confidence. A small memory that knows why something was kept, who it applies to, and when it should stop being trusted seems more useful than a large memory with better retrieval.

[SachitRafa]

I agree to your point, in our current system we are not treating each memory as same. Based on the importance, category and recall frequency we decide a decay rate which would not be same for all the memories. A architectural decision will have a higher importance and although if it's not recalled frequently enough, it will still have a slower decay rate.