Prompt Engineering Framework: 6 ChatGPT Principles for work

Large Language Models like ChatGPT are powerful — but only if you know how to talk to them properly.

Most people struggle not because AI is unreliable, but because their prompts are unclear, incomplete, or poorly structured. The result is generic answers, missed context, and wasted time fixing AI output.

This course teaches you Prompt Engineering from first principles.

You’ll learn a clear, practical framework that helps you write prompts that work consistently — across ChatGPT, Claude, Gemini, and other modern AI tools.

This is not a list of random prompt hacks.

Instead, you’ll learn how to think when writing prompts, so you can adapt to any task, any tool, and any future AI model.

What you’ll learn

What prompt engineering really is — and why most prompts fail

How large language models interpret your input (without technical jargon)

A simple, reusable framework to structure any prompt

How to control output using roles, context, task clarity, format, and quality standards

How to avoid common mistakes that cause vague or incorrect AI responses

How to create prompts that save time and reduce rework

Who this course is for

Professionals using ChatGPT or AI tools at work

Developers, architects, managers, educators, and analysts

Anyone frustrated with inconsistent AI responses

Beginners who want a solid foundation before advanced techniques

No prior AI or machine learning knowledge is required.

By the end of this course, you won’t be guessing what to type into ChatGPT.

You’ll have a clear system for writing prompts that produce useful, reliable results — every time.