Generative AI models are evolving rapidly—so should our prompting techniques. The answer is a resounding yes.
Here are the top 10 prompting strategies that have consistently helped me get more accurate, relevant, and reliable results from leading GenAI platforms like ChatGPT, Gemini, and Perplexity.
1. Be Clear and Direct with Your Request
Don’t leave GenAI guessing. Start with a simple, precise instruction like:
“Summarize this article in three bullet points” or “Write a LinkedIn post for this product launch.”
2. Provide Enough Context
These models are powerful, but they’re not mind readers. The more context you provide, the better they’ll perform.
Add background, intent, audience type, or constraints to steer responses.
3. Specify the Desired Format
Need the output as a list, table, or in a certain writing style (e.g., professional, conversational, technical)? Tell the model upfront.
Example: “Present the comparison in a markdown table.”
4. Break Down Complex Requests
If your query is multi-layered, split it into smaller, sequential prompts. You’ll get better results than trying to bundle everything in one shot.
5. Experiment with Prompt Variants
A slight change in phrasing can yield vastly different outputs. Iterate and reframe until the response aligns with your expectations.
6. Use "Thinking" Models
Platforms like ChatGPT-4.5, Gemini 2.5 Pro, and others now show reasoning steps. This allows you to follow the model’s logic and improve your prompts based on how it thinks.
7. Leverage Tool-Augmented Prompts (Search & Code Execution)
If your GenAI supports tools like search or code execution, use them:
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Search Example:
“What’s the current weather in Coimbatore? Use live search.” -
Code Execution Example 1:
“Calculate the square root of 144, then add 10. Use Python.” -
Code Execution Example 2:
“Write a Python function to reverse a string. Test it with the word ‘hello’.” -
Enterprise Use Case:
If integrated with tools like FactSet and Python, you can prompt:
“Generate a list of 1,000 US East Coast enterprises with $5B+ in revenue and 10,000+ employees.”
8. Use “Few-Shot” Prompting
Provide 1–3 examples of the input and expected output. This dramatically improves model alignment and accuracy.
9. Define Model Behavior and Tone
Set expectations explicitly:
“Respond as a professional analyst with a neutral tone.” or
“Write in a humorous, informal tone for a Gen Z audience.”
10. Ask for Verification or Source Review
Always a good habit:
“Can you explain your reasoning?” or “List the sources used for this response.”
Try incorporating these 10 prompting techniques into your GenAI workflows. You’ll notice a measurable difference in clarity, quality, and consistency of results—across writing, analysis, coding, and more.
