Working on a system that saves key context from multi-model conversations (across GPT, Gemini, Grok, Deepseek, Claude) to a persistent store. The memory layer is working - the interesting problem I'm now looking at is extracting "commitments" from unstructured conversation and attaching temporal context to them.
The goal is session-triggered proactive recall: when a user logs in, the system surfaces relevant unresolved commitments from previous sessions without being prompted.
The challenges I'm thinking through:
- How to reliably identify commitment signals in natural conversation ("I'll finish this tonight" vs casual mention)
- Staleness logic - when does a commitment expire or become irrelevant
- Avoiding false positives that make the system feel intrusive
Has anyone implemented something similar? Interested in approaches to the NLP extraction side specifically, and any papers on commitment/intention detection in dialogue that are worth reading.
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