Prompt Engineering Mastery

Why Prompt Engineering Is a Real Skill

If you've ever gotten a vague, generic, or slightly-wrong answer from AI, the model probably wasn't the problem — the prompt was. This lesson reframes what a prompt actually is and why getting good at writing them is worth real practice.

A Framework You Can Reuse on Any Prompt

Instead of reinventing a prompt from scratch every time, use the same repeatable checklist: Role, Task, Context, Format. This lesson builds and applies that framework on several real examples.

Showing, Not Just Telling: Examples & Step-by-Step Reasoning

Two techniques that dramatically improve harder tasks: giving the AI a few examples of exactly what you want (few-shot prompting), and asking it to reason step by step instead of jumping straight to an answer.

Getting Predictable, Structured Output

When you need an AI's answer to slot into a spreadsheet, a form, or another program, free-form prose isn't good enough. This lesson covers asking for — and reliably getting — structured formats like JSON, tables and fixed templates.

Iterating and Evaluating Your Prompts

Your first attempt at a prompt is rarely your best one. This lesson covers a simple process for testing, comparing, and systematically improving a prompt — instead of just retyping it and hoping.

Applying This at Work: Writing, Code, Data and Support

The final lesson: pulling every technique from this course together across four common, real jobs prompt engineering gets used for — so you leave with templates you can adapt immediately, not just theory.

Prompt Injection: Why It Matters When You Build With AI

The moment you build something on top of AI — a support bot, an internal tool, anything that feeds someone else's input into a prompt — a new problem appears: that input might not have your best interest in mind. This lesson covers prompt injection and how to defend against it.

Multi-Turn Conversation Design

Every example so far has been a single prompt, single response. Real usage is often a long back-and-forth — and keeping that conversation reliable over many turns is its own skill, distinct from writing any one individual prompt well.

Evaluating AI Output for Accuracy & Bias

Every lesson so far has focused on getting a BETTER response. This one covers the equally important skill of not automatically trusting whatever comes back, no matter how confident and well-formatted it sounds.

Building Reusable Prompt Templates

The iteration lesson mentioned saving a perfected prompt for reuse. This lesson goes further: designing that saved prompt as a genuine template, with clearly marked placeholders, so anyone can fill it in reliably — not just re-editing a block of text by hand each time.

Chaining Prompts for Multi-Step Workflows

The most powerful real-world AI workflows rarely rely on a single prompt. This capstone lesson covers chaining — using the output of one prompt as the input to the next — to break a complex task into focused, reliable stages.