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

Meta built a pre-compute engine with 50+ specialized AI agents to systematically document tribal knowledge in a 4,100-file data pipeline spanning three languages.

• •Identified non-obvious patterns, design choices, and cross-module dependencies previously known only to engineers
• •Generated 59 concise context files (~1,000 tokens) using "compass, not encyclopedia" principle
• •Increased AI context coverage from 5% to 100% of all code modules
• •Achieved 40% fewer AI agent tool calls per task
• •System auto-refreshes to validate coverage and fix stale references

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