Summary  
This chapter explains how to structure prompts by assigning a specific role and providing contextual background so that an AI generates responses with the appropriate expertise, tone, and level of detail.

General domain of usage  
Education and tutoring

Assigning a **role** in your prompt means telling the AI to respond as a specific expert, character, or profession. Adding **context** provides background information or a scenario for the AI to consider. Together, these techniques help the AI generate more relevant and accurate responses. Compare these two prompts:

- **Without role/context**: `Explain photosynthesis`;
- **With role/context**: `You are a high school biology teacher. Explain photosynthesis to a group of 15-year-old students using simple language`.

The second prompt guides the AI to use an appropriate tone and level of detail, resulting in an explanation that is better tailored to the intended audience.

Avoid vague roles like "expert" or "professional". Be specific, such as "as a pediatrician" or "as a travel guide".

Note

Assigning a clear role and context helps the AI avoid generic or overly technical answers.

Which of the following best describes context prompting?

A beginner-friendly, fully theoretical course introducing the core concepts and practical strategies of prompt engineering for large language models (LLMs). Learn how to structure, refine, and optimize prompts to achieve better AI-generated results.

Explore the essential building blocks of prompt engineering, including what prompts are, why they matter, and the key principles for effective communication with LLMs.

Practical prompting techniques for controlling AI behavior and improving response quality.

Learn how to refine, evaluate, and improve prompts for consistency and real-world use cases.

Role and Context Prompting