Glossary · 3 · Working with models: prompts and context
Prompt engineering
Also known as: Prompt design, Prompting
Prompt engineering is the practice of designing, testing and refining prompts so that a generative AI model produces the desired output reliably — through clear instructions, relevant context, examples, output formats and systematic comparison of variants.
- Beginner
- Intermediate
- Technical writers
- Technical marketers
- Technical project managers
In one sentence
Prompt engineering explained: designing and testing prompts for reliable AI output — a core skill for writers, marketers and project managers.
Example
A writer compares three prompt versions for generating troubleshooting topics on ten test cases and keeps the one that never omits the safety note.
Why it matters on your learning path
- Technical writers: Technical writers are natural prompt engineers: precision, structure and audience analysis are transferable skills.
- Technical marketers: Test prompts for tone, claims and compliance, not only for creativity.
- Technical project managers: Treat prompt changes like changes to a specification — reviewed, versioned and regression-tested.
Prompt engineering vs. context engineering
Prompt engineering optimizes the wording of an instruction. Context engineering designs everything the model sees — retrieved documents, tool results, memory — and is where most effort goes in production systems.