Auto-Detection
Auto-Detection monitors your coding conversations for knowledge-relevant signals. When it detects a question about past decisions, it silently searches the vault and surfaces relevant context. When it detects a learning worth capturing, it offers to save it. No explicit commands needed.
How it works
Auto-Detection runs as a background process in your AI coding session. It watches for patterns: questions about 'why did we...', 'how do we...', 'what is our convention for...' trigger automatic vault searches. Statements that capture new knowledge -- 'it turns out that...', 'the gotcha here is...', 'we decided to...' -- trigger save suggestions. You can accept, dismiss, or ignore these suggestions.
Auto-detection surfacing relevant vault knowledge during conversation
Screenshot coming soon
Why it matters
The best knowledge management happens invisibly. If you have to remember to search or save, you often will not. Auto-Detection removes this cognitive overhead. Knowledge surfaces when relevant and gets captured when it emerges, without interrupting your flow. It is the difference between a knowledge base that gets used and one that gets forgotten.
Comparison of explicit vs auto-detected knowledge interactions
Screenshot coming soon