<p>Prompt Engineering is an essential skill when working with large language models like ChatGPT. Whether you're building chatbots, automating workflows, or generating creative content, the way you frame your prompt can dramatically affect the output quality.</p>

<h3>Here are 5 best practices to keep in mind:</h3>

<ol>
 <li><strong>Be Clear and Specific:</strong> Avoid vague prompts. Instead of saying “Tell me about history,” ask “Summarize the causes of World War I in 3 bullet points.”</li>
 <li><strong>Use Role Instructions:</strong> You can frame prompts like: “Act as a professional HR Manager. Write a job description for a Full Stack Developer.”</li>
 <li><strong>Provide Examples:</strong> Few-shot prompting gives the model context. Example: “Here are 2 similar answers. Now complete the third.”</li>
 <li><strong>Limit Scope:</strong> Give clear boundaries like word count, format, or tone (e.g., “Write in a formal tone using 100 words”).</li>
 <li><strong>Iterate Often:</strong> Test and refine your prompts. Prompt engineering is about experimentation and learning what works best.</li>
</ol>

<p><em>Want to go deeper? Check out this quick explainer video below!</em></p>

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