This post is Part 2 of prompt engineering course. If you haven’t read Part 1 of Prompt Engineering course, you must read it first.
Prompt Engineering course part-1
In this post we will discuss in detail, how you can become master at the art of Communicating with AI
Imagine you’re working on creating the perfect prompt. You could end up spending hours defining every tiny detail—like specifying whether you want a brief explanation or a detailed analysis, or choosing between a simple overview suitable for beginners or a complex discussion meant for experts. You might even dictate the tone, asking for a humorous touch or a professional demeanor.
For instance, if you’re asking for a summary of a scientific concept, you might specify,
“Explain quantum physics in under 200 words in a way a high school student could understand,”
Ensuring the response matches your exact needs. While this meticulous approach can yield precise results, it’s important to consider the time invested in crafting just one prompt.
The Trade off
Conversely, using quicker, less detailed prompts means you’ll have to create and manage many of them, each potentially leading to varying degrees of relevance and coherence. You might find yourself stitching together bits of information from multiple AI responses, like assembling a puzzle without the picture on the box as a guide. This method can be more time-consuming due to the sheer volume of prompts and the manual effort required to synthesize the information.
Becoming an adept prompt engineer involves striking a balance between these approaches. It’s about developing an intuition for how much detail to include to get useful responses quickly. This skill evolves over time as you experiment with different prompts and observe the outcomes.
For example, a content creator might start with broad prompts like “Write a blog post about healthy eating,” but later learn to add specifics such as target audience, desired article length, and key points to cover, leading to more targeted and useful content.
Remember, the effectiveness of Large Language Models (LLMs) hinges on their training data. The more diverse and extensive the data, the more capable the model. The data set or ‘corpus’ the AI learns from can vary based on your specific needs, whether it’s legal documents, scientific papers, or creative writing. Despite these variations, there are universally applicable strategies that can significantly enhance the efficiency of your prompts. As you grow in your role, innovating new prompt strategies and sharing these insights with the community will not only improve your own skills but also advance the field of prompt engineering as a whole.
Define what you need
When you want to get something from AI, like a piece of code, an email, learning something new, or understanding a concept, you need to know what you’re looking for first. Once you know, you can start making your prompt better until you’re happy with the AI’s answer. Here are some tips to help you along the way.
Be Clear
Make sure your prompts are easy to understand to get the right answers.
- Ineffective: “Tell me about Paris.”
- Effective: “What’s the weather like in Paris today?”
Give Context
Explain the situation so the AI knows what you’re talking about
- Ineffective: “How to open files?”
- Effective: “In Python, how do I open a file in read-only mode.?”
Be Specific
Tell exactly what you need to avoid answers that don’t help you
- Ineffective: “Write an email.”
- Effective: “Write an email apologizing for a delayed project submission.”
Set the Tone
Let the AI know if you want the answer to be serious, friendly, or funny.
- Ineffective: “Tell me a joke.”
- Effective: “Tell me a funny joke about computers.”
Keep it Simple
Don’t make things too complicated, especially with tough topics.
- Ineffective: “Discuss the theory of relativity.”
- Effective: “Explain gravity in simple terms.”
Be Brief
Get to the point to avoid confusing the AI.
- Ineffective: “I’m thinking of baking something sweet, maybe something like a cake, you know, with chocolate.”
- Effective: “List the ingredients for a chocolate cake and suggest step by step way to bake it”
Give Instructions:
If you’re looking for something specific, like a list or summary, say so.
- Ineffective: “Tell me about the article.”
- Effective: “Summarize the key points of the article above.”
Prompt Engineering Course: General Techniques
Guide AI with Examples
To help AI understand better and give you the right answers, it’s a good idea to give examples in your questions. These examples can be things like a small piece of writing, how your data is set up, templates, bits of code, pictures or charts, and other stuff like that.
When you give examples, it’s like showing the AI exactly what you want. It makes things clearer for the AI, so you’re more likely to get the answer you’re looking for. Examples are like showing the AI a picture of what you mean, which helps it give you better and more on-point answers.
Not so good question: “Make me a program.”
Without any examples, the AI might not know exactly what you want, so the answer might not be very helpful.
Better question: “I need a Python program that can look at a CSV file and figure out the average number from the ‘Sales’ column. The CSV looks something like this: ‘Date, Sales; 2021-01-01, 150’. The program should say something like: ‘Average Sales: [the average number]’ at the end.”
This question tells the AI more clearly what you need by explaining the task, showing how the data looks, and telling it what the answer should look like. This way, the AI can give you an answer that fits what you’re looking for.
Get it in or before 3rd attempt
Remember, you’re not perfect, and neither is the process of asking AI for help. When we talk to AI, we’re just sharing our thoughts, and sometimes we make mistakes, forget things, or say things that don’t make much sense. The key is to get better at asking so that you usually only need to ask twice to get the answer you want, not three times. Getting the right answer with fewer tries shows you’re getting the hang of talking to AI.
Some Tasks are worth 100s of Prompts
Think about trying to explain how to build a whole social media site like Instagram with all its features in just one or two questions. It’s pretty much impossible, even if you asked a hundred times. For big jobs like this, you break them down into smaller bits, figure out each piece with AI, and then put everything together using both AI and your own smarts.
Sequential Prompts
Think about trying to explain how to build a whole social media site like Instagram with all its features in just one or two questions. It’s pretty much impossible, even if you asked a hundred times. For big jobs like this, you break them down into smaller bits, figure out each piece with AI, and then put everything together using both AI and your own smarts.
Nested Prompts
Let’s say you’ve managed to get some good answers after a few tries. Now you want to combine those five questions into one big question. You can make a new question that includes all five smaller ones, kind of like how you can have loops or if-statements inside each other when you’re coding.
Use Templates
For bigger tasks you can develop a set of prompt templates for different types of inquiries (e.g., summaries, explanations, creative tasks). This can speed up the process and ensure consistency.
Incorporate Feedback Loops
After receiving a response, use it to modify your next prompt. This feedback loop can progressively refine the interaction and improve the relevance of the AI’s output.
Continuous Learning
Stay updated with the latest AI developments and prompt engineering strategies by participating in forums, workshops, and discussions.
In conclusion, mastering prompt engineering is an essential skill that goes beyond mere interaction with AI—it empowers you to harness AI’s capabilities effectively.
As we’ve explored in “Prompt Engineering Course Part 2: Practical Techniques,” the journey involves balancing the granularity of your prompts with the practical need for efficient response generation. By learning to specify context, tone, and detail, and by continually refining your prompts based on feedback, you can improve both the quality and relevance of AI-generated content.
This course has equipped you with the tools and insights needed to transform your interactions with AI, ensuring that you not only keep pace with technological advancements but also leverage them to achieve your strategic goals. As you continue to develop your skills, remember that each prompt is a step towards deeper understanding and more sophisticated technological fluency. Keep experimenting, keep learning, and share your journey to inspire others in the ever-evolving field of AI.