Structured Outputs

Free-form text is easy for humans to read, but applications often need structured data. If a model response is going to drive automation, populate a UI, call an API, or trigger a business workflow, you usually want structured outputs such as JSON, typed objects, or schema-constrained fields.

Structured outputs reduce three common failure modes:

• Parsing failures — the model adds extra prose or changes the format.
• Field drift — keys, enums, or value types vary across runs.
• Unsafe automation — downstream systems act on text that was never validated.

For extraction, classification, tool arguments, routing, and automated decisions, structured outputs should be your default.

The strongest approach is to define the output shape before asking the model to generate it. A good schema specifies:

• Field names and types
• Required vs optional fields
• Enum values where possible
• Descriptions for ambiguous fields
• Validation constraints for downstream safety

{
  "type": "object",
  "properties": {
    "priority": { "type": "string", "enum": ["low", "medium", "high"] },
    "requires_human_review": { "type": "boolean" },
    "summary": { "type": "string" }
  },
  "required": ["priority", "requires_human_review", "summary"]
}

Explicit schemas narrow the output space and make it much easier to reject invalid results automatically.

Reliable structured generation usually has two layers:

1. Constrain generation — use native structured-output or JSON-schema support when your provider offers it.
2. Validate after generation — always run the result through application-side validation before trusting it.

result = call_model_with_schema(...)
parsed = schema_validator.parse(result)

if not parsed.valid:
    retry_or_escalate()

Even when provider-side structured output works well, application-side validation is still where business rules are enforced.

Keep schemas simple enough for the model to satisfy reliably:

• Prefer shallow schemas first — deep nesting is harder to generate and debug.
• Use enums where possible — bounded outputs are more reliable than open-ended strings.
• Separate reasoning from the final object — the object should be small, clean, and typed.
• Retry intentionally — malformed output may deserve a retry, but cap attempts.
• Log validation failures — they reveal prompt, schema, or model weaknesses.

Whenever the model's response is consumed by code rather than a human, structured outputs are usually worth the extra design effort.