2.1. Introduction

Artificial intelligence tools like ChatGPT, Gemini, or Claude may appear to generate answers as if by magic. In reality, the quality of their responses depends heavily on how we phrase our requests. This process is called prompt engineering, the practice of crafting effective inputs to guide AI toward useful, accurate, and context-aware outputs (Prompt Engineering with ChatGPT, 2023).

In this module, we will explore the basics of AI communication: how prompts shape responses, the difference between weak and strong prompts, and how intentional design can transform AI from a novelty into a powerful tool for teaching, learning, research, and everyday tasks.

Module 2 Learning Outcomes

• Explain what prompt engineering is and why it matters for effective AI communication.
• Recognize the difference between weak and strong prompts.
• Identify strategies for improving prompts through specificity, context, and structure.

Key Idea: Prompts Matter

Think of interacting with an AI like giving directions to a visitor in your city. If you say, “Go downtown,” they might end up lost or confused. But if you say, “Walk two blocks east, turn right at the library, and look for the café with the red awning,” they will likely arrive at exactly the place you had in mind. Prompts work the same way: vague instructions lead to vague outputs, while clear, detailed guidance produces richer and more reliable results.

Looking Ahead

Now that we’ve introduced the concept of prompt engineering, the next section will compare weak and strong prompts side by side. This will help you see how small changes in phrasing can make a big difference in AI responses.