What is Prompt engineering?
Writing instructions and context so an AI model gives a more useful answer.
In plain English
Good prompts say who the model should act as, what the task is, what information to use, what format to answer in and what to avoid. Giving a few examples (few-shot prompting) often helps. Asking for reasoning step by step can improve results on multi-step problems. Prompts are tested and refined, not guessed once.
Example
“Summarise the text below in three bullet points for a busy manager. Use only the text provided.” usually beats “Summarise this.”
Easy to confuse with
- Fine-tuning: Prompting changes the instructions you give. Fine-tuning changes the model itself.
Where you will meet it
This idea belongs to the subject area of these practice tests. We do not publish or predict real exam questions.
- AWS AIF-C01 practice tests
- Microsoft AI-901 practice tests
- Google Cloud Generative AI Leader practice tests
- NVIDIA NCA-GENL practice tests
Related terms
- Large language model (LLM): A very large neural network trained on huge amounts of text to predict and generate language.
- Retrieval-augmented generation (RAG): Letting a model look up relevant documents first and answer using them.
- Hallucination: When an AI model states something false or invented as if it were true.
Test yourself
Practice tests with an explanation for every answer option, so each mistake teaches you something.
Browse practice testsAll glossary termsWritten and checked by the Be Ready Education team, last reviewed 2 November 2026. General study information, not professional advice. Providers change names and rules, so confirm details on the official documentation. Not affiliated with, endorsed by or sponsored by any certification vendor or exam body. Certification names, exam codes and product names are trademarks of their respective owners and are used only to identify the exam a practice product prepares for. Our questions are original and are not actual exam questions.