Structured Generation
Constraining decoding to match a schema at every token.
/ quick answer
Structured generation (Outlines, Instructor, Gemini controlled generation) uses grammar constraints during decoding so the output is guaranteed valid — no parse-retry loop. Constraining decoding to match a schema at every token.
/ frequently asked
What is Structured Generation?
Structured generation (Outlines, Instructor, Gemini controlled generation) uses grammar constraints during decoding so the output is guaranteed valid — no parse-retry loop.
What is an example of Structured Generation?
A Zod schema is compiled to a JSON grammar and enforced token-by-token.
Why does Structured Generation matter?
Constraining decoding to match a schema at every token.
What should I learn after Structured Generation?
Open the related workflows and prompts further down this page: they show how this idea is applied in a real task, step by step.
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Related concepts
The vocabulary this page depends on.
- →Few-Shot Prompting
Showing the model 2–5 examples of the task inside the prompt so it mirrors the pattern.
- →Chain-of-Thought Prompting
Instructing a model to think step by step before answering.
- →Zero-Shot Prompting
Asking a model to do a task with no examples in the prompt.
- →Prompt Chaining
Pipelining LLM calls where each step's output feeds the next.
Related workflows
Turn this into a repeatable process.
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Related tool stacks
The tools that run it in production.
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Related prompts
Reusable prompts for this job.
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Comparisons & alternatives
Pick between the options.
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Prompt-to-app builder vs AI-assisted code editor — which one should you reach for?