What is Prompt Engineering?

That probably didn't mean jack to about half of you.

Let's try this:

Imagine for a second that you're a software engineer. You're building a fridge app that orders Instacart delivery when your smart fridge tells you you're out of food. What happens?

On a high level, your code controls what's displayed on the app. It connects your app to the database, and uses Instacart's APIs to place an order automatically. In essence, the code you write tells the app what to do.

It's the exact same thing with prompting, but the coding and APIs and database stuff is abstracted away. Instead, the words you write tell the AI exactly what you want it to do within the parameters you specify. It can be as generic as "write me a song" or as specific as "write me a poem about a fat cat hunting birds with an ABAB rhyming scheme." (It can go even deeper). But that's what makes it interesting!

In this post, you'll learn all about prompt engineering, the different types of prompts you can use, and how you can get started writing prompts of your own.

Why You Need to Learn Prompting

You've probably heard about ChatGPT by now. It's the chatbot that's slowly but surely becoming integrated with all aspects of our lives. That's not a bad thing though - if you learn how to write the right prompts.

Prompt engineering is becoming increasingly important as the use of AI continues to grow in various industries. Every company large and small are either exploring integrations with OpenAI or building their own AI product.

As we continue to delegate decision-making to machines, it's essential to understand how these decisions are being made. Without proper guidance, machine learning models can perpetuate biases or make decisions that don't align with our values and ethics. Prompt engineering can help ensure that these decisions align with our intentions.

Types of Prompt Engineering

There are various types of prompt engineering, including:

  1. General Prompting - In this type of prompting, a single prompt is provided to guide the entire decision-making process. The prompt can be a question, a statement, or a combination of both.

  2. Role Prompting - Role prompting focuses on prompts that guide the model's understanding of specific roles. For example, in a medical diagnosis model, role prompts would guide the model's understanding of the roles of a doctor, a patient, and a disease.

  3. Chain of Thought Prompting - In chain of thought prompting, a series of prompts is created to guide the decision-making process. Each prompt builds on the previous one, guiding the model's thinking in a specific direction.

  4. Counterfactual Prompting - Counterfactual prompting involves creating prompts that help the model understand what might have happened if a different decision had been made.

  5. Exemplar Prompting - Exemplar prompting involves providing the model with examples of previous decisions to guide its decision-making in the future.

Benefits of Learning Prompt Engineering

Learning prompt engineering can be beneficial for individuals from all walks of life, regardless of their job function. By understanding how to create prompts, you can improve your critical thinking skills, data literacy skills, and future-proof your career.

With the increasing importance of AI in various industries, learning prompt engineering can help individuals stay ahead of the curve. In addition, prompt engineering can be a valuable addition to a resume, demonstrating a candidate's understanding of the latest technologies and their ability to innovate.

How to Get Started

There are several resources available for those interested in learning prompt engineering. These include:

  1. OpenAI's GPT-3 Playground - The GPT-3 Playground allows users to experiment with GPT-3 and explore its capabilities.

  2. Bing Chat - Bing Chat is available on a limited basis. You can try writing your own prompts into Bing and tweaking your prompts to modify your results. You only get 15 tries with Bing.

  3. The Prompt Library - The Prompt Library is a collection of prompts for various machine learning models, created by experts in the field. It can be a helpful resource for anyone looking to gain insight into how prompts are constructed and used.

Online courses on platforms like Coursera and Udemy can also be excellent options for those looking for a more structured approach to learning prompt engineering. These courses provide hands-on projects and real-world examples, making it easier to understand how prompt engineering can be used in practice.

Joining online communities and forums can also provide valuable networking opportunities and access to expert knowledge. Communities like Reddit's r/MachineLearning and r/learnmachinelearning can be a great place to ask questions and learn from others.

Finally, practicing prompt engineering on your own is an excellent way to gain practical experience and develop your skills. Experimenting with creating prompts for different machine learning models can help you understand the nuances of different types of prompting and how to tailor them to specific tasks.