This release adds 7 notable features for engineering teams evaluating rollout.
✓ No known CVEs patched in this version
Topics
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Summary
AI summaryAdded lesson‑based learning commands, negative memory recording, automatic distillation, trust signals, audit and note features.
Full changelog
Full Changelog: https://github.com/oleksiijko/pmb/compare/v0.2.2...v0.2.3
Procedural memory layer - PMB now learns lessons and avoids repeating failures, on top of factual recall. The 94.5% LoCoMo recall@10 is unchanged.
Added
pmb learn "..."+pmb lessons- teach durable lessons ("this repo uses pnpm, never npm"); review them. Surfaced via the hybrid + predicate-aware ranker.pmb learn --failed- negative memory: record failures ("numpy 2.x broke lancedb") that recall flags so they're not repeated.pmb distill+ auto-distill on session end - an LLM extracts durable lessons/failures from a session automatically (zero-command when lessons.auto_distill_on_session_end is on). Reuses Claude CLI / Anthropic / Ollama.- Lesson-intent boost - on how-to/convention queries, lessons & failures are gently boosted. Scoped to lesson/failure events only, so recall on datasets without them (LoCoMo) is unchanged.
- Trust signals in recall - source attribution, confidence (high/med/low), staleness flag.
pmb auditmemory-health - lessons / failures / stale / low-confidence / conflicts.pmb noteinstant capture;pmb watchauto-ingest a notes file/folder.
Notes
- LoCoMo recall@10 = 94.5% (full 10-conv run) - unchanged.
- 50+ new regression tests; all green.
Install: pip install --upgrade pmb-ai
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About PMB
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Earlier breaking changes
- v0.9.0 Deletes `packs/ru.yaml` and `packs/uk.yaml`; default active packs set to empty tuple.
Beta — feedback welcome: [email protected]