Mastering the Art of Prompt Engineering: Starter Guide

Article by Nadežda Jakubková.

Developing your own approach to using generative AI models such as ChatGPT — one that is both practical AND ethically sound — is perhaps the best way of proving naysayers wrong and ensuring that you get the most out of this promising piece of technology. Perhaps surprisingly, the first key to success with generative AI models is to learn how to talk to them. 

The advancement and increased (and newly-discovered) accessibility of AI have sparked a spectrum of reactions from different communities, ranging from fear and panic to hope and optimism. It's not the first time humanity, faced with radical technological progress, has found itself staring at a fork in the road pondering which road to travel. Think of it this way, when the first excavator was brought to a construction site, those who relied on handheld shovels for their work must have felt threatened by this new machine. But the people were left to deal with the new reality and so some learned to operate it and found higher-paying (and safer) jobs as a result. Today, the once-scary excavator is perceived as a magnificent piece of machinery. What’s more, shovels have not gone away and we still see construction workers using them today. 

We are continuously coming upon such forks in the road. In truth, it's impossible to predict how AI, or for that matter any technology, will continue to impact our jobs and industries. However, what we do know is that a few months ago all these new tools like ChatGPT, Bard, AutoGPT, etc. were made accessible to the masses, and the best course of action is to learn how to use them to your advantage.

This article will cover the topic of prompt engineering, including prompt attributes and techniques for prompting large language models (LLMs) such as ChatGPT. By the end of this piece, all you will need to do to start harnessing the potential of these AI tools is… to ask the right questions. 

What is prompt engineering?

Prompt engineering is the process of designing and optimizing prompts to get the desired, high-quality outputs from large language models (LLMs).

This report has been researched and written by Nimdzi's Localization Researcher, Nadežda Jakubková. If you want to learn more about this topic, reach out to Nadežda at [email protected].