Beyond the Basics

The Ceiling

Here’s something frustrating about AI: you can write a great prompt, get a perfect response, then try the exact same prompt an hour later and get garbage.

You tweak a word. Better. You run it again. Worse. You have no idea why.

This is the ceiling that basic prompting hits. You’re getting results, but you can’t control them. You can’t predict them. And when something breaks, you’re just guessing at fixes.

Professional prompt engineers don’t guess. They build prompts systematically—so they know exactly why something works and what to adjust when it doesn’t.

That’s what this course teaches you.

What to Expect

This course is broken into focused, practical lessons. Each one builds on the last, with hands-on exercises and quizzes to lock in what you learn. You can work through the whole course in one sitting or tackle a lesson a day.

What Makes This Different

In AI Fundamentals, you learned to write clear prompts. That’s table stakes. This course goes deeper:

The difference isn’t magic. It’s method.

The RACE Framework

Every well-engineered prompt has four components. I use the acronym RACE:

R - Role Who is the AI being? A senior developer? A patient teacher? A skeptical editor? The role shapes everything—tone, expertise level, what details to include.

A - Action What specific task should the AI complete? Not vague (“help me”) but concrete (“write a 200-word product description”).

C - Context What background information does the AI need? Who’s the audience? What constraints exist? What’s already been tried?

E - Examples What does good output look like? Examples are the most powerful component—they show rather than tell.

Here’s the same request, before and after RACE:

Before:

Help me write a product description for our new headphones.

After:

Role: You’re a conversion-focused copywriter who writes for premium audio brands.

Action: Write a 150-word product description for wireless noise-canceling headphones priced at $299.

Context: Target audience is remote workers aged 25-45 who take lots of video calls. Competitors emphasize technical specs. We want to emphasize the feeling of focus and calm.

Example of tone we like: “Block out the world. Hear what matters. These headphones don’t just cancel noise—they create space for your best thinking.”

The second version doesn’t just get better results. It gets predictable results. Run it ten times, you’ll get ten usable descriptions.

What You’ll Learn

Over the next seven lessons:

1. Anatomy of Prompts – Why word order and structure matter more than you think
2. Roles and Personas – How to create AI “characters” that behave consistently
3. Few-Shot Learning – Teaching AI by example (this one’s a game-changer)
4. Chain-of-Thought – Making AI show its work for better reasoning
5. Prompt Patterns – Battle-tested templates for common tasks
6. Debugging Prompts – Systematic fixes when things go wrong
7. Capstone – Build a production-ready prompt from scratch

Each lesson builds on the last. By the end, you’ll approach prompting completely differently.

A Quick Diagnostic

Before we dive in, try this exercise. Write a prompt for this task:

Generate three creative taglines for a sustainable coffee brand called “Groundwork.”

Write your prompt however you normally would. Save it somewhere.

At the end of this course, you’ll write a prompt for the same task using everything you’ve learned. The difference will surprise you.

Key Takeaways

• Basic prompting works but lacks reliability and predictability
• Professional prompt engineering uses systematic methods, not guesswork
• The RACE framework (Role, Action, Context, Examples) structures effective prompts
• This course teaches techniques you can apply immediately

Ready to go deeper? Let’s start with the anatomy of prompts.

Up next: In the next lesson, we’ll dive into Anatomy of a Prompt.