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The Art of Prompt Engineering: Mastering the Dance with Large Language Models

Updated: May 22

Welcome to our exploration of prompt engineering—an essential skill for anyone, especially data scientists and engineers aiming to unlock the full potential of large language models (LLMs). In this blog, we'll dive into the intricacies of prompt engineering and how it shapes the interactions with LLMs.

Understanding Prompt Engineering

Think of an LLM as a super-powered research assistant. It can write different kinds of creative content, translate languages and even answer your questions in an informative way. But just like any good assistant, it needs clear instructions to perform well. That's where prompt engineering comes in!

While we're used to searching Google for answers, prompting an LLM requires a different approach. It's an art –  getting the prompt just right can make the difference between an insightful, helpful response and an unhelpful or nonsensical one. By strategically writing our prompts, we can activate different knowledge pathways within the model's neural architecture. 

Exploring LLM Capabilities

Today’s most advanced language models, like Gemini and GPT-4 have multimodal capabilities, meaning they can understand and generate outputs based on text, images, PDFs, and other data formats. 

While disconnected models like GPT-3.5 rely solely on their predetermined training data and lack internet connectivity, the paid version of Gemini offers Internet access, allowing users to query the latest news. Moreover, Gemini seamlessly integrates with a variety of Google services, such as Gmail, Google Drive, Google Maps, and Google Flights. This integration provides users with convenient access to a wide range of functionalities. For example, users can effortlessly search their Google Drive and conveniently look up flights. 

Furthermore, both the paid Gemini and GPT versions possess the capability to create a painting from a text prompt, showcasing their versatility and creative potential.

The language model ClaudeAI prioritizes safe and accurate training methods, with a specific focus on mitigating biased or harmful outputs.

Top Tips for Effective Prompt Writing

With that background out of the way, here are my top recommendations for writing effective prompts. Remember to be specific and channel your inner teacher.

  • Act as" 

Using phrases like "Act as “ for example, one can steer the model's persona and knowledge base for your intended use case.

  • You can specify Tones like professional or friendly, explain complexity levels and more.

  • "Do NOT reply instantly" 

Adding this prevents premature responses.

  • Use Formatting 

Embrace markdown, quotes, section breaks, and other formatting to separate prompt parts. 

  • Specify a Target Audience

Clearly define the intended audience for the prompt to ensure the AI model tailors its response accordingly.

  • Double-Check Claims 

Language models can hallucinate facts or make assertions without being properly grounded. Always verify key claims, statistics, and references independently.

  • Examples

For code-related tasks, provide sample inputs and outputs to illustrate constraints and desired functionality.

  • Zero-Shot CoT (chains of thoughts): If your prompt involves multiple steps, consider asking the LLM to specify the response step-by-step. This may result in a different final response.

Some prompt examples:

  • Summarize the attached PDF, explaining the top 10 concepts in layman's terms for a beginner

  • Act as a marketing professional, write a blog about... The target audience is...The following sentences should be included: “..”, “...”. Do not mention ... Use a friendly tone. Do NOT reply instantly, If you have any questions on this prompt, please ask first.


We've come a long way, but human oversight and critical thinking remain essential when working with these powerful language models.

And here’s a fun fact: This blog was created with the assistance of 3 chatbots – GPT, Gemini, and ClaudeAI — but rest assured, our content has been thoroughly reviewed for accuracy and relevance.


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