Summary
This chapter introduces four key principles—clarity, specificity, context, and role assignment—for constructing precise and effective prompts when implementing code that interacts with AI models.

General domain of usage
Natural language processing

To create effective prompts, you need to follow **four key principles**:
- Clarity;
- Specificity;
- Context;
- Role assignment. 

**Clarity** means using unambiguous language. **Specificity** involves providing detailed instructions. **Context** gives the AI background information. **Role assignment** tells the AI to respond as a particular expert or persona.

#### Example
`As a professional nutritionist, list three healthy breakfast options for children aged 3 to 6.` This prompt is **clear** (asks for three options), **specific** (healthy breakfast for children), provides **context** (children aged 3 to 6), and assigns a **role** (professional nutritionist).

Which principle is demonstrated by asking the AI to "act as a professional nutritionist"

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.

Principles of Effective Prompting

Example