alt Hacker NewsOne thing I've been wrestling with building persistent agents is memory quality. Most frameworks treat memory as a vector store — everything goes in, nothing gets resolved. Over time the agent is recalling contradictory facts with equal confidence.
The architecture we landed on: ingest goes through a certainty scoring layer before storage. Contradictions get flagged rather than silently stacked. Memories that get recalled frequently get promoted; stale ones fade.
It's early but the difference in agent coherence over long sessions is noticeable. Happy to share more if anyone's going down this path.
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Sounds interesting, would like to learn more about this.
How do you imokement the scoring layer and when and how is it invoked?
certainty scoring sounds useful but fwiw the harder problem is temporal - a fact that was true yesterday might be wrong today, and your agent has no way to know which version to trust without some kind of causal ordering on the writes.
Interesting. I’ve been playing with something similar, at the coding agent harness message sequence level (memory, I guess). I’m looking at human driven UX for compaction and resolving/pruning dead ends