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Multiple Source Truth Synthesis
When dealing with multiple imperfect data sources, systematically compare all sources and select the best version rather than relying on any single source
Decision Rule
Always have fallback data sources, score quality across multiple dimensions, and log performance to improve source selection over time
How It Works
Different data sources have different failure modes and strengths - combining them with intelligent selection produces better results than any individual source
Failure Modes
Over-weighting unreliable sources due to recency
Not having sufficient fallback options
Poor quality scoring leading to worse selection than single source
Not updating selection criteria based on source performance
Example Decision
“RSS feed gives truncated content, web scraper fails with 403, metadata extractor gives low quality - fall back to AI search which provides comprehensive summary”