AI Engineering Design Patterns | S01 | E2.1: Structured Output

Structured output makes an LLM return JSON your code can parse: generation is constrained to a schema, so the output matches the shape you asked for. In Episode 02 of AI Engineering Design Patterns, we go past "just ask the model for JSON". We open up how constrained decoding actually works inside the model, the cases that still break it in production, and the code to do it properly. What you'll learn: • Why prompting for JSON isn't enough: prose around the output, missing keys, wrong types • How LLMs actually work in a auto-regressive manner • How a JSON Schema becomes a state machine that decides which tokens are allowed next • Tokenizer, logits and masking: how invalid tokens are ruled out at every step • What changes with thinking mode and redacted thinking • How refusals surface when the model won't answer inside your schema • Where model distillation attack surfaces Code: https://github.com/gensokudevs/AI-Eng... AI System Design Mock Interview: https://topmate.io/gensoku_devs/2379685 AI Engineer Mock Interview: https://topmate.io/gensoku_devs/2379705 Tech Career Guidance: https://topmate.io/gensoku_devs/2141067 Other Services: https://topmate.io/gensoku_devs Previous episode (E01, Tool Use):    • AI Engineering Design Patterns | S01 | E01...   Follow the full course:    • AI Engineering Design Patterns Full Course   TIMESTAMPS 0:00 Intro - Structured Output 7:36 How does a LLMs work? 10:48 Tokens, Model Vocabulary, Embeddings, Sampler & Token IDs 21:16 Constrained Decoding, Logits, Mask & State Machine 35: 31 Anthropic's transform_schema() 39:06 Thinking Models & thinking tokens 45:01 Thinking modes (Extended, Adaptive) & Effort Levels (L, M, H, E) 50:41 Important Note !! 51:10 Interleaving Thinking 57:31 Redacted Thinking, Refusal Stop Reason & Model Distillation Attacks 1:11:50 Coding Gensoku Devs (原則, "fundamental principle") goes depth-first through the structural decisions real production AI systems are built on. If it isn't deep, it isn't Gensoku. Collaborations: gensokudevs@gmail.com #AIEngineering #Constraineddecoding #LLM