Prompt Engineering SIWhat prompt engineering means
A prompt is everything you give an AI system before it answers: the task, background facts, examples, and the format you want back. Prompt engineering is the habit of shaping those inputs deliberately, then testing what comes back and revising what actually failed.
The five parts of a good prompt
- Task. The deliverable, stated plainly.
- Context. The facts, sources, and audience that change the answer.
- Boundaries. What to avoid, and what to do when information is missing.
- Output format. Structure, length, and fields.
- Check. How you will tell a useful answer from a merely plausible one.
A simple four-step method
- Define the job and who will use the result.
- Add only the context that changes the answer.
- Make success observable with a format and a check.
- Test an ordinary case and an awkward one, then change what failed.
The worked examples guide shows this method on real before-and-after prompts.
What prompts cannot do
Wording cannot supply missing facts, unavailable tools, or guaranteed accuracy. Important claims still need verification, and a longer prompt is not automatically a better one. Include what changes the task or makes the result checkable, and remove the rest.
Where to go next
Turn a vague request into a structured brief with the free prompt builder, borrow a starting point from the templates, then learn few-shot prompting and prompt evaluation to improve results over time.