Developer context switching—searching for relevant functions, understanding legacy decisions, or locating tribal knowledge—consumes 15-30% of engineering capacity. This custom workflow automates that search by implementing a production-grade Retrieval-Augmented Generation (RAG) system. It connects to your Git repositories, Confluence, Slack archives, and Jira to create a unified, queryable knowledge graph. The business value is direct: faster onboarding, reduced interruption load on senior engineers, and measurable gains in feature velocity by eliminating hours of manual code navigation each week.




