How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines

This post details the development of a pre-compute engine using specialized AI agents to systematically map tribal knowledge within Meta's large-scale data processing pipelines. This engine creates concise context files that act as structured navigation guides for AI agents, significantly improving their understanding and efficiency when working with proprietary codebases. The system addresses the challenge of AI agents lacking context in complex, multi-repository, multi-language code by documenting non-obvious patterns and cross-module dependencies, leading to reduced AI tool calls and faster task completion.