This technique, also called zero-shot, is when you give a direct command without showing the AI any previous examples of the output you want.

Asking Without Examples

Giving the AI a few examples of a task helps it learn the pattern and style you expect for its final answer.

Providing Sample Examples

Asking the AI to explain its logic helps it work through complex problems more accurately instead of rushing to a quick conclusion.

Telling the AI to act like a professional, such as a travel agent or a software engineer, helps it adopt the right tone and expertise.

Instead of asking for everything at once, you split a large project into smaller, manageable pieces to get better results for each part.

Providing background information or 'the big picture' helps the AI understand the situation so its response is more relevant.

Telling the AI exactly who will read the response, like a five-year-old or a CEO, helps it choose the right level of complexity.

You can instruct the AI to present its answer in a specific way, such as a bulleted list, a table, or a short email draft.

Giving the AI clear 'do's and don'ts' ensures it follows your specific guidelines and avoids including unwanted information.

Using symbols like dashes, hashtags, or quotes helps the AI distinguish between your instructions and the data you want it to process.

Prompting is a conversation where you tweak and refine your original request based on the AI's first attempt to get a better answer.

Explicitly telling the AI it is okay to say 'I don't know' helps prevent it from making up facts when it doesn't have the information.

Starting your request with strong words like 'Summarize,' 'Rewrite,' or 'Analyze' tells the AI exactly what behavior to prioritize.

Specifying a word count or a sentence limit keeps the AI from being too wordy or too brief for your specific needs.

Asking the AI to provide three different versions of an answer lets you compare and choose the one that fits your needs best.