What is Prompt Engineering?

Prompt Engineer is one of the hottest jobs in IT today. There are thousands of AI prompt engineer jobs today, and thanks to the rise of ChatGPT, OpenAI, Bard, and other AI tools that require engineers can craft and create AI prompts and work with AI LLMs. I just searched LinkedIn and found over 1,500 jobs for the title Prompt Engineer.

But before we discuss how to become a prompt engineer, let’s talk about prompt engineering.

Prompt Engineering

Imagine you have a powerful robot that can do many things, but it doesn't know what to do unless you give it specific instructions.

Prompt engineering is like giving instructions to a robot. It's the process of carefully crafting instructions or prompts for artificial intelligence (AI) models to help them understand what you want them to do. Not only can you give AI some instructions, but you can also have a conversation like what you would have with your co-worker, friend, or even a professional. 

Here are some examples of prompt engineering in action:

• You want the AI model to write a poem about a flower. You might give it a prompt like, "Write a poem about a flower, using vivid imagery and metaphors."
• You want the AI model to translate a sentence from English to Spanish. You might give it a prompt like, "Translate the following sentence into Spanish: 'The cat sat on the mat.'"
• You want the AI model to write code samples for you. You might give it a prompt like, "Can you write a program in C# with a binary search example."
• Prompt engineering is a powerful tool that can be used to get the most out of AI models. By carefully crafting prompts, you can guide AI models to produce accurate, relevant, and creative results.

In essence, prompt engineering is both an art and a science, requiring a mix of creativity, technical understanding, and strategic thinking to maximize the effectiveness of interactions with AI models.

What is a prompt?

In generative AI, a prompt is the most important part of how good an answer you can get from AI. In generative AI, a prompt is an input or instruction given to an AI model, especially a large language model (LLM) like ChatGPT. A prompt can be a question, statement, or command that initiates the AI's response process. Crafting a prompt and continuing the conversation with AI models can change the quality of the outcome from a model.

A prompt can be more than just a question. It can be an instruction, or it can be a friendly chat with a tool like ChatGPT. But behind the scenes, it’s an instruction that is given to an LLM, and based on that, the LLM generates an output. However, the prompt should be something that the LLM understands and has been trained on related data. For example, if an LLM is trained on healthcare data and if you ask about weather, it may not understand your prompt.

Prompting is a science as well as an art. Check out Unleashing Prompting Techniques to understand prompting techniques.

Here are some examples of prompts:

• Questions: Simple or complex questions seeking information, clarification, or advice. For example, "What is the capital of France?" or "How does quantum computing work?"
• Commands or Requests: Instructions for the AI to perform a specific task, like "Write a short story about a space adventure" or "Generate a week-long meal plan for a vegetarian diet."
• Creative Prompts: Inputs aimed at eliciting creative output, like "Compose a poem about the ocean" or "Create a dialogue between two historical figures."
• Problem Statements: Present a problem or scenario for the AI to solve or provide solutions for, such as "How can I fix a leaking faucet?" or "Suggest strategies to improve online learning experiences."

Situational content:

Here is an example where I ask ChatGPT to pretend to be the CEO of a company and write a persuasive letter to a potential new employee. 

 

Benefits of prompt engineering

Prompt engineering can improve the quality and relevance of the output from an LLM. It can also make LLMs more user-friendly and accessible to a wider range of people.

As AI and prompt engineering demand and products grow, it will become a part of our daily lives. ChatGPT and Midjourney are two examples of that. Even Bing and Google search engines have AI chats now. MS Office, Azure, AWS, and Google Clouds are also implementing AI chats in their cloud services. All these AI services prompt.

Learning and understanding prompt engineering, as a user as well as an engineer, is going to be very beneficial to get your work done faster and also get a new job.

Here is an eBook on ChatGPT and prompting.

As a developer, you can use GitHub CoPilot and other coding AI tools to help improve your coding, write code, explain existing code, and more. 

Here is an eBook and ChatGPT for developers.

What are some examples of prompt engineering?

Prompt engineering can be used for a variety of tasks, including:

• Generating text, such as poems, code, scripts, musical pieces
• Creating images and videos 
• Writing emails, letters, and other work-related content.
• Translating languages
• Answering open-ended, challenging, or strange questions
• Writing different kinds of creative content
• Creating curated news and other content
• Creating personalizes chats and Q&As
• Writing research papers and doing research

What are some tips for prompt engineering?

Here are a few tips for prompt engineering:

• Be clear and concise in your instructions.
• Use natural language that the LLM can understand.
• Break down complex tasks into smaller, more manageable steps.
• Provide context and examples to help the LLM understand your task.
• Experiment with different prompts to find what works best for your task.
• Learn from existing prompts and their outputs.
• Continue learning and keep improving.

What are some of the challenges in prompt engineering?

As a user, understanding context and local languages is one of the major challenges. For example, if you are building a prompt engineering product for farmers, understanding their languages and needs is very important. 

1. Data plays a major role in building LLMs that are used by AI. Bad data may end up generating bad output. 
2. Generating misleading or false information: LLMs can be prompted to generate text that is factually incorrect or misleading. This can be used to create fake news articles, propaganda, or other forms of misinformation.
3. Creating harmful stereotypes: LLMs can be prompted to generate text that perpetuates harmful stereotypes. This can be used to create content that is offensive or discriminatory.
4. Spreading hate speech: LLMs can be prompted to generate text that is hateful or offensive. This can be used to promote violence or discrimination.
5. Creating spam or phishing content: LLMs can be prompted to generate text that is spammy or phishy. This can be used to trick users into revealing personal information or clicking on malicious links.

If you are a software developer, check out Most Common ChatGPT Prompts for Software Developers.

Next reading: What is Prompt Engineering and Why It Might Be Your Next Career Path