What Repository Intelligence Is and How AI Coding Agents Map Codebases

AI coding agents often handle single-file fixes well but struggle to trace how changes ripple across a large, interconnected codebase. Repository intelligence refers to techniques such as vector embeddings, AST parsing, and knowledge graphs that help agents grasp a codebase's structure and dependencies rather than just the open file. The article argues that simply loading more code into a model's context window does not solve this, since understanding relationships is a structural problem. Research cited in the piece reports that graph-based indexing can reduce token usage by roughly tenfold compared with file-by-file exploration. The full article compares specific tools and offers guidance on evaluating their claims.