AI Engineering/Phase 11/Lesson 03

Structured Outputs: JSON, Schema Validation, Constrained Decoding

Your LLM returns a string. Your application needs JSON. That gap has crashed more production systems than any model hallucination. Structured output is the bridge between natural language and typed data. Get it right and your LLM becomes a reliable API. Get it wrong and you're parsing free-text with regex at 3am.

Build 1.5 hr Python

Prerequisites: Phase 10, Lessons 01-05 (LLMs from Scratch)

#Learning Objectives

Implement JSON-mode and schema-constrained outputs using OpenAI and Anthropic API parameters
Build a Pydantic validation layer that rejects malformed LLM outputs and retries with error feedback
Explain how constrained decoding forces valid JSON at the token level without post-processing
Design robust extraction prompts that reliably convert unstructured text into typed data structures

Full Access lesson

Keep going. The rest of this lesson is one step away.

Unlock all 503 lessons, video, code, quizzes and every future update. Pay in your own currency with Paystack.

See plans Sign in

The text and code of this lesson are based on AI Engineering from Scratch by Rohit Ghumare, MIT licensed.