Show HN: Persistent Mind Model (PMM) – Update: an model-agnostic "mind-layer" A few weeks ago I shared the Persistent Mind Model (PMM) — a Python framework for giving an AI assistant a durable identity and memory across sessions, devices, and even model back-ends. Since then, I’ve added some big updates: - DevTaskManager — PMM can now autonomously open, track, and close its own development tasks, with event-logged lifecycle (task_created, task_progress, task_closed). - BehaviorEngine hook — scans replies for artifacts (e.g. Done: lines, PR links, file references) and uto-generates evidence events; commitments now close with confidence thresholds instead of vibes. - Autonomy probes — new API endpoints (/autonomy/tasks, /autonomy/status) expose live metrics: open tasks, commitment close rates, reflection contract pass-rate, drift signals. - Slow-burn evolution — identity and personality traits evolve steadily through reflections and “drift,” rather than resetting each session. ...