Structured output: definition

Structured output is when a model is made to return data in a strict format such as JSON, so another system can use the result directly instead of parsing free text.

A model that answers in prose is fine for a chat window and useless for a pipeline. Structured output constrains the model to return exactly the fields you asked for, so the next step (a database write, an API call) can trust the shape.

It is the quiet enabler behind most real automation: the model decides, but it hands its decision over in a form a machine can act on without guesswork.

Related terms

Workflow automation: Workflow automation is the practice of moving a repeatable business process from manual steps to a system that runs it end to end, with a person involved only where judgement is actually needed.
Prompt engineering: Prompt engineering is the craft of writing the instructions, examples, and context you give a model so it produces reliable, correctly formatted output for a specific task.
Large language model (LLM): A large language model is a neural network trained on huge amounts of text to predict the next token, which lets it write, summarise, classify, and answer questions across almost any topic.