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Core
Constrained and Structured Decoding
Asking a model nicely for JSON sometimes fails; constrained decoding guarantees valid output by masking, at each generation step, every token that would violate a schema or grammar, so only valid continuations can be sampled. It is the reliable way to get JSON, enums, or function-call arguments, and it underpins tool calling. The caveat: it guarantees structural validity, not semantic correctness. Applied-AI interviews probe it because production systems depend on parseable output, and 'just prompt for JSON' breaks at scale.
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TAUGHT IN THESE COURSES
This concept is a reference. These lessons put it in sequence, with what comes before and after it.
Applied AI Engineering·How language models work, enough to build onFree12mWhy the same prompt gives a different answer twiceRandomness in a model is a setting, not a mystery, and knowing which knob does what is the difference between a feature that behaves and one that surprises you in production. This lesson also covers why turning it all the way down still does not give you exact repeatability.Applied AI Engineering·Prompting as an engineering disciplineFree14mGetting output your program can actually rely onThe step that turns a chat toy into a component you can build on. Three levels of guarantee, why asking politely is the weakest of them, and the validation layer you need even when the format is guaranteed.
RELATED CONCEPTS
PRACTICE THIS IN REAL QUESTIONS
LLM & GenAI FundamentalsHow does constrained / structured decoding force an LLM to emit valid JSON or grammar?→RAG & Agent System DesignHow do you get reliable structured output (JSON / function calls) from an LLM in production?→LLM & GenAI FundamentalsHow does LLM tool calling (function calling) actually work under the hood?→System Design for AI in ProductionDesign a text-to-SQL feature: let users ask questions in natural language over a real database.→RAG & Agent System DesignWhat is the Model Context Protocol (MCP), and how do you design good tools for an agent?→LLM & GenAI FundamentalsHow do you design system prompts and prompt templates for production?→
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