remember

Capturing debugging insights involves categorizing the lesson and writing it into a domain-organized memory file. This transforms isolated workflow discoveries into persistent instructions, creating a searchable knowledge base that prevents repeating mistakes.

Organizing workflow discoveries by domain involves matching new learnings to specific categories like git-workflow or clojure. The system intelligently routes insights into existing or new domain files, keeping related technical knowledge structured and easily retrievable.

Memory storage supports both global persistence for cross-project recall and local workspace scoping for project-specific lessons. This ensures domain-organized instructions are saved at the correct level, keeping your knowledge base relevant to the current context.

Recording recurring mistakes requires transforming them into explicit memory instructions mapped to a specific domain. By capturing the error context and the correct workflow approach, the AI can recall the lesson and avoid repeating the same debugging missteps.

Creating a persistent knowledge base from development lessons requires automated file management to handle categorization and storage. The system automatically creates or updates domain memory files based on new learnings, eliminating manual organization overhead.