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To extract reusable patterns and decisions from a session to memory files, run an automated extraction process that identifies insights, enforces standardized formatting, performs conflict checks, and categorizes entries for future reuse.

You should capture session lessons for future workflow automation when ending a session or before running a compact operation. This ensures valuable insights and decisions are saved to memory and made available for future runs.

Yes, you need memory tooling to save lessons and patterns from your current session. The extraction mechanism requires this infrastructure to store insights, validate corrections, and apply standardized formatting constraints.

The best way to organize session memories for cross-project reuse is to apply automatic categorization, enforce conflict checks, and enable optional global lessons propagation to make insights transferable across multiple projects.

Yes, you can standardize the formatting of saved session lessons. The extraction process guides you through conformance steps to validate corrections, format entries consistently, and tag insights for structured memory organization.