Structured Output

Structured output is when a language model returns data in a predictable, machine-readable format—JSON, XML, typed objects—rather than free-form prose. This is what makes LLMs usable as components in software systems rather than just conversational interfaces. If you need the model to extract a name, date, and dollar amount from an invoice, you need those values in fields your code can parse, not embedded in a sentence. Most model providers now support constrained generation—forcing the model's output to conform to a JSON schema—which eliminates the parsing failures that plagued early integrations. OpenAI's structured output mode, Anthropic's tool use, and open-source libraries like Instructor all solve this problem. Structured output is the bridge between AI as a chat feature and AI as a system component, and getting it right is prerequisite to any serious automation.