memory-reflect

To consolidate insights into long-term memory, you can use a periodic reflection process that reviews recent notes and active tasks to distill key decisions and lessons learned into a central knowledge base.

The best way to extract lessons learned from daily notes automatically is to perform a scoped reflection on recent activity, which evaluates your daily logs and appends a summary to your current notes for traceability.

Reflection activity updates a permanent knowledge base by selectively evaluating recent conversational and note-taking activity, then integrating the distilled insights directly into a curated MEMORY.md file to prevent information loss.

Yes, updating long-term memory effectively requires scoping recent reflection to review active tasks alongside daily notes, ensuring that decisions, preferences, and relationship details are accurately captured.

You can maintain a curated knowledge base by selectively updating memory logs, which involves evaluating recent activity for crucial decisions and logging the reflection process to ensure your knowledge evolves over time.

A limitation of automated insight distillation is that it relies on the scope of recent activity reviewed, meaning insights outside the recent two-day window or not logged in notes may be missed during the consolidation process.