Schema
A schema defines the shape of data: required fields, types, allowed values, and relationships between properties.
In AI products, schemas tell the model what to return and tell your UI what to render, validate, and store.
Share
What it means
A schema is the contract between prompt, model output, and interface: which fields exist, what they mean, and what “valid” looks like.
Why designers should care
Without a shared schema, teams get brittle prompts and broken UI when the model omits fields, renames keys, or drifts format across releases.
Example
A user-research synthesizer schema requires theme, evidence quote, severity, and recommendation. Missing fields show inline “Regenerate this section” instead of silent gaps.
Common mistakes
- • Letting the model invent field names per request with no stable schema.
- • Schemas too large for the context window, causing partial or hallucinated structure.
- • No versioning when schema changes break saved drafts or integrations.