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Module
Module 1 of 6Lesson 1 of 1~3 min

Course overview

This course is for PMs whose product needs to use an AI model's answers, not just display them. Over five modules, you learn to turn an answer into reliable data and leave with the output contract for one of your own features, tested on cases chosen specifically to make it fail.

Take this lesson: your first course is freeSee the full syllabus

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.

Topics covered

  • structured outputs
  • JSON Schema
  • function calling
  • LLMs in production
  • output contract

Where it fits

Overview

What will I produce in this course, and in what order?

Lessons in this module

  1. 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.

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