Glossary / Prompt engineering
What is prompt engineering?
Prompt engineering is the practice of writing instructions for an AI model so that it gives you reliable, useful results, by being clear about the goal, the context, the constraints and the format you want.
A vague prompt gets a generic answer. A clear one says who the result is for, what it must include, what to avoid, and what a good outcome looks like. The model has not been in your head, so the prompt has to carry the context.
For building apps, this means describing users, screens and data rather than only the look: "customers book a 30-minute slot, staff see today's bookings and can cancel them, every booking saves name, phone and service".
It also means working in steps. Ask for the core flow first, check it, then add the extras one at a time. Small, specific requests are easier for the model to get right and easier for you to test.
Examples
- Weak: "make a gym app"
- Better: "a gym members app where members see class times, book a spot, and staff mark attendance"
Questions
Is prompt engineering a real skill?
Yes, though it is mostly clear writing. Knowing what to include, how to break a job into steps and how to describe what you see when something is wrong makes a large difference to results.
How long should a prompt be?
Long enough to cover the goal, the users, the main screens and the data. For a first app that is often a short paragraph. Add detail as you refine.