Welcome to Prompt Engineering

If you've used ChatGPT or Claude, you've written prompts. So why does this need a course? Because most prompts fail. They're too vague. They miss context the model needs. They ask for the wrong format. They get answers that are technically right but practically useless. And when the prompt fails, most people blame the model. Professional prompting is a different skill. It's about clarity, structure, and treating the LLM like a junior collaborator who needs explicit briefing. It's about knowing which techniques work for which problems: chain-of-thought for reasoning, few-shot for format consistency, system prompts for behavior, ReAct for tool use. This course will take you from "I use ChatGPT sometimes" to "I can write prompts that consistently get production-quality outputs." We'll cover: • The mental model: what a prompt actually is, and why structure matters • The basics: clarity, context, format, examples • Few-shot prompting: when to show, not tell • Chain-of-thought: how thinking step-by-step changes outputs • Advanced techniques: self-consistency, meta-prompting, tree-of-thoughts • Production: testing, evals, iteration. Without these, you're guessing. No programming required. You'll get more out of the course if you have a real task in mind (a recurring email, a report, a creative project) you can use as a test case. Time: ~2 to 3 hours across 10 articles. Most steps include playground links so you can practice.