Show HN: SelMem – selective reconstructive memory for LLMs
A project which explores whether LLM agents can develop persistent behavioural divergence through a reconstructive memory system that forgets, distorts, and consolidates experiences over time.
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Recorded metrics
points · 2 votes
2026-10-23 06:00:15.058Z
cumulative since publication
Research analysis
Project record
Repository: jbsalles/Selmem. Source account: A project which explores whether LLM agents can develop persistent behavioural divergence through a reconstructive memory system that forgets, distorts, and consolidates experiences over time.
Observed adoption & comparisons
Source votes: 2 votes (Oct 23, 2026 UTC; cumulative since publication); previous same-scope observation: 2 (Oct 22, 2026 UTC). These observations do not establish demand growth. Recent records to compare: “google/skills” (GitHub Trending, Nov 6, 2026); “mattpocock/skills” (GitHub Trending, Nov 6, 2026). Shared themes are navigation hints; they have not been verified as the same need or independent corroboration.
Adoption decision
Evaluate it against the tool or manual workflow it would replace. The stored record supports discovery; it does not yet establish reliability, lower operating cost or commercial adoption.
Unverified requirements
Not verified: license permissions, required hardware, installation steps, maintenance status and a representative task with its failure cases.
Next test
Choose one real task and a current alternative. Record the commit, environment, input, output, elapsed time and failure behavior; retain the result before recommending adoption.