learn

To extract durable insights from conversations, apply a memory extraction protocol that normalizes content, detects deltas, compares against existing memory, and passes a four-criteria durability test before persisting reusable knowledge.

Capturing wisdom from learning materials requires a wisdom extraction protocol that identifies durable insights, persists them into memory folders, and generates related tasks or journal entries to support further learning and decision-making.

The durability test works by applying canonical name normalization, detecting deltas in new information, comparing against existing memory, and evaluating four specific criteria to ensure only long-lasting, actionable insights are persisted.

Yes, memory extraction automatically assigns validated insights to specific memory folders and updates index references, enabling long-term reuse and structured knowledge management without manual organization.

Memory extraction targets durable insights from live conversations, while wisdom extraction processes learning content to capture knowledge, with both protocols requiring normalization, delta detection, comparison, and a four-criteria durability test before persistence.

Knowledge management from conversations automatically generates related tasks and journal entries alongside persisting durable insights, supporting further learning and decision-making without requiring manual follow-up task creation.