What makes answers smarter

The AI is only as good as what it knows about your data. GoPie gives you four places to invest, each with a different job. This page is the map; the rest of the section covers each in depth.

Know the four layers#

1. Dataset & column descriptions — what each table and column means. The foundation: descriptions are indexed for the agent's semantic search and injected into every prompt. If you do one thing, do this.
2. Context documents — project-level reference material: data dictionaries, codebooks, metric definitions, methodology notes. The AI searches them when a question needs background, and reports cite them.
3. Custom AI prompts — standing instructions attached to a project, dataset, or view: "revenue figures are in EUR", "always exclude test accounts". Injected verbatim, every time.
4. Dictionaries — CSV lookup tables mapping coded values to labels, used by data cleaning during ingestion.

See what reaches which feature#

Two rows worth reading twice: the project custom prompt reaches chat but not the playground's Ask AI bar (per-dataset instructions belong on the dataset), and dictionaries influence no query-time feature at all — they act during data cleaning.

Invest where it pays#

• Answers keep missing the right column? Fix the column descriptions — discovery is a search over them.
• The AI misuses a metric? Put the definition in a dataset custom prompt ("gross_revenue is pre-discount; use net_revenue for 'revenue'").
• Questions need business background? Upload the methodology doc as a context document — chat will cite it, and report questions can be grounded in it.
• Coded values confuse ingestion? That's a dictionary.