Prompt Engineering | Good and Bad Prompts

In this video, we’ll explore the fascinating world of Prompt Engineering — the art of communicating effectively with AI models to get accurate and meaningful results.

Prompt Engineering is a vast topic, so in this session, we’ll focus only on the most important and practical concepts that every AI enthusiast and developer should know.

What You’ll Learn in This Video:

???? Understanding Prompt Engineering:
What is a prompt, and how do we differentiate between a good prompt and a bad prompt to guide AI responses better.

???? Zero-Shot Prompting:
How to make an AI model perform tasks without providing any examples — just using clear and concise instructions.

???? Few-Shot Prompting:
How giving a few examples helps the model understand the pattern better — we’ll demonstrate this by generating Git commit messages.

???? Chain of Thought (COT):
Learn how AI models can reason step-by-step by solving a simple mathematical problem — like calculating web server disk space.

???? Role Prompting:
Discover how to assign specific roles to the AI model, such as “Act as a teacher” or “Act as a software developer,” to make responses more context-aware.

???? Structured Output Prompting:
Learn how to make the model return clean, predictable formats such as JSON, tables, or lists — essential for AI-powered applications.

This video gives you a practical, beginner-friendly introduction to the core techniques of Prompt Engineering, explained in simple terms with real examples. Perfect for anyone looking to master AI communication and enhance their projects!

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