What is Structured Output?
Forcing model replies into a machine-readable shape such as JSON with fixed fields. Required wherever AI output feeds code, databases, or UI components, since free text breaks parsers the moment formatting drifts.
Related terms
JSON Schema Mode
A structured-output setting where the caller supplies a JSON Schema and the model must conform to it. Types, required fields, and enums are validated automatically, which removes most post-processing repair code.
Function Calling
Letting a model request named tools with typed arguments instead of answering directly. The app executes the call and returns results, so the model can query data or trigger actions without inventing facts.
Evals
Repeatable tests that score model behavior on fixed cases before and after prompt or model changes. Without evals every tweak is a guess; with them, regressions in tone, accuracy, or format get caught early.
Temperature
Sampling randomness for generation: low values make output focused and repeatable, high values make it varied and surprising. BYOB chat configs default near 0.5 while tool calls use 0.3 for steadier structured actions.
Thinking Budget
The token allowance reserved for internal model reasoning before answering. Larger budgets suit hard multi-step problems; BYOB prices thinking tokens separately so runaway reasoning shows up in metering.
Prompt Pipeline
A staged chain of model calls where each stage output feeds the next step: classify, then draft, then verify. Pipelines beat single giant prompts on reliability, and each stage can use the cheapest capable model.