Data-engineering

Two dashboards disagree on active customers, and an agent asked to settle it invents a third number. The fix for both is declaring the model once.

A sceptic at our DAIS booth asked why documentation should drive the implementation. What happened at the booth that day is the answer.

Churn looked wrong on the office TV. An agent walked the platform's declarations to the root cause before standup ended, because there was nothing to guess.

Skill files and context documents drift because each one is a second copy of the truth. "Talk to your data" holds up when meaning is declared once, in a model, and every layer is generated from it, including the one the agent reads.

Skills, semantic layers, and ontologies make analytics agents work, until they hit the messy data underneath. The durable fix is structural, not more context.