This module teaches prompting as a practical specification skill. The goal is not to memorize magic phrases. It is to understand how context, constraints, structure, repair, and follow-up shape the answer you get.
Module summary
Module 01 starts with the basic mental model of a prompt, then introduces the strongest levers: context, constraints, output format, iteration, reusable patterns, and debugging. The lessons are designed to make prompting feel less mysterious and more operational.
This module is intentionally practical. Instead of treating prompting as a collection of clever examples, it teaches the reader how to describe work clearly, repair weak prompts, and build a small personal prompt system that survives real use.
Lessons in this module
what-a-prompt-really-is- Stop hunting for magic words and start writing prompts like small specifications.context-constraints-and-output-format- Use the three levers that improve most prompts faster than anything else.iteration-and-follow-ups- Use follow-up turns to diagnose and repair answers instead of starting over blindly.reusable-prompt-patterns- Turn repeated task shapes into reusable prompt patterns you can actually keep using.fixing-bad-prompts- Use a debugging checklist so weak prompts become repairable instead of frustrating.
How to use this module
Read the lessons in order and practice the mini labs in the same week. Prompting improves fastest when you apply each concept to a task you already do, rather than to invented examples only.
If Module 00 taught you how to choose the right ChatGPT surface, Module 01 teaches you how to steer that surface once you are there. By the end of the module, you should have a cleaner mental model, a short reusable prompt library, and a practical debugging loop for weak prompts.