# Mission: Holistics AMQL/AQL fluency

## Why
Learn Holistics AMQL/AQL deeply enough to model metrics and datasets correctly, answer customer and presales questions with confidence, teach others the mental model, and debug existing AMQL/AQL code without guesswork.

## Success looks like
- Design reliable Holistics datasets with correct models, relationships, metrics, and field definitions.
- Translate business questions into AQL metrics and explore queries, then explain tradeoffs to customers or teammates.
- Teach AMQL/AQL concepts using clear examples, especially metric context, relationships, and reusable metric definitions.
- Debug broken or surprising AML/AQL by identifying whether issue lives in model fields, dataset relationships, metric context, filters, or visualization query shape.

## Constraints
- Prefer official Holistics docs and workspace examples over memory.
- Lessons should be short, practical, and tied to real modeling/presales/debugging scenarios.
- Use retrieval practice and small exercises, not long passive explanations.

## Out of scope
- Deep database administration unrelated to AMQL/AQL.
- Full frontend dashboard design unless needed to explain AQL/viz behavior.