Quick Summary: Hey, please brainstorm a few ideas for my next social media post about pets”. “Suggest a few modern baby names”. These are prompts you might have found yourself giving to the ChatGPT, developed by OpenAI. Since its introduction, ChatGPT has been a powerful tool for various applications such as content generation, customer service, industry businesses, chatbots, etc. It is known for generating human-like content based on the prompts given. To make full and effective use of OpenAI, you need to know the science of Prompt Engineering, which involves crafting precise prompts to get the best advantage of OpenAI technology. 

How does ChatGPT work? 

ChatGPT has been a popular name for less than a year. However, the algorithms at the backend have been the reason behind powering many apps and services since 2020. So to understand how the popular AI tool works, we can’t skip talking about the language engines that power it. 

The GPT (Generative Pre-trained Transformer) in ChatGPT is two related algorithms- GPT-3.5 Turbo and GPT-4. Here, the numbers 3.5 and 4 represent the versions of the algorithm. These models were developed by OpenAI but they use everything from Bing’s AI features, and writing tools like Copy.ai. Most of the AI text generators use GPT-3, GPT-3.5, and GPT-4 algorithms. 

ChatGPT is being used by almost everyone now because it made the process of AI text generation really simple and most importantly open for all. Also, it’s a chatbot, that talks like a human, and people love interacting with a good chatbot who responds effectively and solves their problems. 

So, how does ChatGPT work.  

The answer is simple. It utilizes the algorithms GPT 3.5 and GPT 4 to generate text (strings of words) that it predicts will best answer your query. It works by understanding the prompt and giving answers based on the data it was trained on. While this may sound easy, the success lies in the complexity of algorithms working at the backend. 

Strategies for Effective Prompt Engineering

• Clarity 

The prompt should be very clear. It should clearly state what you want OpenAI to do for you. Avoid ambiguity. So for example, rather than saying, “Tell me about sports”, you may consider saying, “Discuss the evolution of sports culture, its impact on society, and the role of technology in modern sports”. 

•      Context

ChatGPT responds to the immediate context of the prompt. So, giving a clear context is crucial in getting the relevant and best possible response from ChatGPT. For example, the prompt “Give me a 7-day social media plan for my clothing business” provides clear context and instructions.  

• Precision

Precise prompts are more likely to yield precise responses. For example, if you are looking for new and innovative breakfast options, ask specifically for it: “Give me a list of the top 10 most innovative breakfast options in the world”.  

• Role-play

Role-playing can also provide a clear context for OpenAI to generate accurate responses. One example could be: “As a nutritionist, recommend a balanced meal plan for someone looking to lose weight.”

Debugging the prompts for a better response

Sometimes, even when you give a clear and precise prompt to ChatGPT, it fails to deliver the desired output. In such cases, it is beneficial to debug the given prompt. 

Adjust the tone and formality

If the output comes too formal or casual for what you are looking for, you can adjust the tone by adding new instructions like “this is too formal, use casual language and write it like I’m talking to someone..” or “explain it to me like I’m five..”. 

Tweaking the instructions

If you find the output to be too overly detailed, or confusing, adjust the prompt accordingly. Add words like “in detail” or “in short” to guide the response as per your requirements. 

Experiment and iterate

Put your creative hat on, and don’t be too afraid of experimenting with ChatGPT prompts. Sometimes, slight changes in the instructions and rephrasing them yield amazing results. 

For example, OpenAI can debug your Python codes in a fraction of a second. You may try giving this prompt which displays an effective use of role-play and clarity in instruction- “Be a Python programmer for me, here is a piece of Python code with this (problem)- insert code snippet- where I’m getting the following error (insert error). What can be the reason for the bug?”

Specify the length of the output

You can ask the model to give outputs of the desired length. It can be in terms of the count of words, sentences, or paragraphs. For example, you can give the prompt “Summarize the text in about 200 words” (insert your text). 

Copy and paste 

You don’t have to type all by yourself when it comes to using ChatGPT. There is no problem in pasting the text from other sources, be it Google, or WhatsApp. While there is a limit on the input of around 4000 words, you can still split the text into different sections and get OpenAI to remember what you have previously sent.

Conclusion-

Prompt Engineering is an important skill if you want to master ChatGPT. It requires understanding the algorithms and crafting clear, contextual, and precise prompts. With practice, you can master the art of prompt engineering and leverage the full use of OpenAI. 

Remember that the key lies in being specific about what you want AI to do and how you want it to do it. The outcome largely depends on the user’s ability to interact with the bot and experiment with different structures and instructions.