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.
Related terms:
AI Agent
An AI agent is a system that autonomously breaks a goal into steps—calling tools, reading results, and adjusting course—without waiting for a human prompt.
Zero-Shot Prompting
Zero-shot prompting is the most basic form of AI interaction where questions are posed without any examples or guidance, relying entirely on the model’s...
Linting
Linting is the automated analysis of code or any structured output to flag errors, enforce style rules, and catch problems before production.