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Cross-session knowledge capture works by extracting non-obvious discoveries from your current session and converting them into structured Skill Units that persist across sessions, preserving tacit knowledge for future work, debugging, and cross-team collaboration.

Capturing workflow automation discoveries requires applying a repeatable process at the end of a session to extract non-obvious findings into structured Skill Units, ensuring actionable, reusable outputs persist across sessions for future work and collaboration.

Yes, you can preserve decision rationales during cross-team collaboration by extracting session insights into structured Skill Units that capture workflows, best practices, and decision rationales, ensuring tacit knowledge persists across sessions for future reference.

Yes, extracting reusable skills requires a structured Skill Unit format containing frontmatter metadata, clear problem and solution sections, and passing a quality gate workflow to ensure the captured session insights produce actionable, reusable outputs.

You should use cross-session knowledge capture during research and development when you need to extract non-obvious discoveries, preserve tacit knowledge, and convert session insights into reusable skills for future debugging, workflow automation, and cross-team collaboration.