Prompt engineering
Prompt engineering is the skill of asking AI for what you want clearly enough to get it. It’s not coding. The same model gives you dramatically different results depending on how you ask, and this course teaches you to ask well — then puts it into practice with five real business scenarios.
What you’ll be able to do
By the end of this course you’ll be able to:
- Structure any prompt with the four parts that matter: role, context, task, and format
- Apply advanced techniques — chain-of-thought, few-shot examples, system prompts, structured output, and multi-step prompting — and know when each one fits
- Choose the right tool for the job across Claude, ChatGPT, Gemini, and Perplexity, and weigh free against paid tiers
- Draft client emails, analyze contracts, document processes, and prepare for meetings with AI assistance
Lessons
Work through the lessons in order — each builds on the last.
pen-line1. Prompt engineering basicsThe prompt-response loop, and a bad prompt versus a good prompt side by side. 2 min read.
ruler2. Writing effective promptsThe four-part structure — role, context, task, format — with five worked examples across business functions. 2 min read.
layers3. Advanced techniquesChain-of-thought, few-shot examples, system prompts, structured output, and multi-step prompting, plus when to use each. 3 min read.
wrench4. Tools and modelsThe strengths of Claude, ChatGPT, Gemini, and Perplexity, free versus paid tiers, and business considerations like data privacy. 2 min read.
graduation-cap5. ExercisesFive hands-on scenarios: overdue invoices, contract review, process documentation, competitive research, and meeting prep. 3 min read.
Time and prerequisites
Total reading time is about 12 minutes. The exercises lesson is hands-on — set aside additional time at a keyboard with an AI tool open to work through all five scenarios.
If you haven’t covered the basics of what AI can and can’t do, start with AI foundations first.
Start with Prompt engineering basicsLast updated on