Course overview
Lesson 1 of the module "Overview" in the course "Get reliable, product-ready AI outputs (JSON, schemas, function calling)".
Lesson objective
By the end of this overview, you will know what you are going to produce (the output contract of a feature and its 20-case table) and in what order the five modules get you there.
Where it fits
Overview
What will I produce in this course, and in what order?
Lessons in this module
- Course overview (this lesson)
What you will learn in the course
This lesson is part of the course Get reliable, product-ready AI outputs (JSON, schemas, function calling)
- Diagnose where free-text output breaks a feature and decide which outputs require a contract.
- Choose between instructions alone, JSON mode, structured outputs and function calling for a given need, and justify the choice.
- Design an output schema (types, enums, required fields, nullable fields, descriptions, "unknown" values) where every field serves a consumer.
- Specify validation (syntax, schema, business rules), retries, handling of refusals and truncation, and the fallback path.
- Version and evolve an output contract without breaking its consumers, accounting for provider differences and the split of roles between PM and developers.
- Build a set of 20 robustness cases and set acceptance thresholds before going to production.
Related courses
- Build an AI assistant for your productAdvanced · ~3 hr
- Design a RAG architecture that fits your productAdvanced · ~3 hr 30 min
- Evaluate an AI feature: test sets, metrics and LLM judgesAdvanced · ~3 hr