AI systems fail because the data path underneath is broken in ways you can't see.

Your model is fine. Your data pipeline isn't.

5 things that break silently:

1. Schema changes (column renamed but joins keep running)

2. Duplicates (batch + streaming load the same data twice)

3. Completeness drift (nulls grow from 2% to 18%)

4. Semantic shifts (distance column switches from km to miles)

5. Freshness decay (data arrives late but no alerts)

Full data engineering guide: buildtolaunch.substack.…