Prompt engineering means knowing what to ask and how to ask to make AI deliver the right answers you are looking for – not just beating around the bush! Think of it as if you are the AI’s guide. You will show it how to explore ideas and bring the best solutions to the table.
The great thing is that you don’t need to be a tech expert to do this. Despite the mouthful name, prompt engineering is for anyone. It is for anyone who wants to make AI work better for their needs – whether in writing, design, coding, or research.
With AI tools like ChatGPT becoming widely available, learning to write effective prompts is a skill that anyone can benefit from. In this guide, we will go over the basics of prompt engineering and some simple techniques to help you get more accurate and relevant results from AI tools.
3 Key Elements of a Good AI Prompt
If you have worked with language models, you will know there are certain unsaid rules that you need to follow. Certain prompts return the perfect answer while certain others tend to return vague responses.
To learn how to give good prompts to AI, the first step is to understand the key components of a prompt. Elements help you design prompts that bring out the best and most relevant responses from AI. Here is what you need to know:
Clarity and Specificity
A well-defined and specific prompt helps the AI understand exactly what you need. Here is what we mean:
- Try asking a general question like: “Tell me about AI” and see the results.
- Now ask: “Describe how NLP is applied in virtual assistants, covering key concepts like language models, intent recognition, and response generation, with a real-world example.”
Context
If you are going to a good friend to ask for advice, would you start by directly asking for the advice? Or would you rather tell the story/context of what happened first? Similarly, the AI also needs context to direct it towards a more relevant and accurate response.
Constraints and Guidelines
Your prompt can include constraints (like word limits or tone preferences) to help AI fine-tune the output. It is important when you are looking to present ideas to an audience. It should follow a specific tone – like formal (for an office meeting) or simple explanation in Layman language (if you are explaining things to a 5-year-old).
8 Best Prompt Engineering Techniques
Prompt engineering is the process where you structure your prompts to be effective enough to guide AI models to deliver accurate answers. While some of these prompt engineering techniques might have a mouthful of a name, these are really very simple at their core.
It is similar to how you would try to find out an answer from another person through back-and-forth questioning. Here are some of the foundational techniques that will help you master prompt engineering:
Zero-Shot Prompting
Zero-shot prompting is when you ask the AI to perform a task without giving any specific examples or context to guide it. This prompt engineering technique is often used for straightforward queries or general knowledge requests.
Something like “Describe the process of photosynthesis” constitutes a zero-shot prompt. The AI will draw on its training to describe photosynthesis without needing any additional context.
This approach works well for questions where basic knowledge is enough. However, zero-shot prompting may not be ideal for more complex tasks where context is needed.
One-Shot Prompting
One-shot prompting involves providing the AI with a single example to guide its response. This is useful when the task is slightly more complex, or you want to establish a particular style or tone. The example acts as a model for how the AI should respond. It helps it understand the structure or level of detail you expect from it.
Here’s an example of a one-shot prompt:
“Write a product description for a fitness tracker. Here’s an example of a smartwatch: ‘This smartwatch combines cutting-edge health monitoring with seamless connectivity, offering 24/7 insights into your health.’ Now, describe a treadmill.”
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Information Retrieval
This prompt engineering strategy treats the AI like a search engine. This technique is useful when you need factually correct information on a particular topic. Some AI models with live data access (like Google’s Gemini) can retrieve current information from the web.
For example, take a look at this prompt “What were the key global environmental policies introduced in 2023?” Here, the AI is expected to list detailed, current information.
Creative Writing
Creative writing prompts are designed to help the AI generate imaginative or narrative content. This is mostly used by storytellers looking for some creativity. Creative prompts are usually open-ended and allow the AI to “imagine” within a given theme or style.
Prompt example: “Write a short story about a lonely robot who discovers a forest full of friendly animals.” The AI will bring together elements of creativity and storytelling to create a vivid story based on the themes of friendship and discovery.
Context Expansion
Context expansion is a simple prompt-writing method that makes the prompt rich with additional details or background information to help the AI fully understand the subject. By adding context, you guide the AI toward a more thorough answer. A useful approach for this is the “5 Ws and How” technique. Using this, you expand the prompt by considering – Who, What, Where, When, Why, and How.
An example of such a prompt would be “Explain why renewable energy is crucial. Who benefits, what types of technology are used, where is it most impactful, and how does it improve environmental health?”
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Focused Summarization
Focused summarization directs the AI to summarize content with an emphasis on specific points. This is useful when you want to condense a large body of text but need the summary to focus on particular aspects.
An example would be “Summarize this article on digital marketing trends, but only focus on strategies that improve organic search ranking.”
Template Filling
Template filling is a structured approach where you use placeholders within a template to generate customized responses. This is one of the top prompt-writing techniques to generate tailored outputs. Commonly, it is used in automated content generation for marketing, customer service, or eCommerce.
Example:
Prompt: “Use the template: ‘Welcome {Customer Name}, and thank you for choosing {Service Name}. We’re thrilled to have you on board! {Personal Message}.’”
Prompt Reframing
If you have worked with ChatGPT, you will know that reframing with different words yields slightly different answers. Prompt reframing is the art of rephrasing your original prompt to maintain the same goal but achieve varied responses. By using synonyms, you can nudge the AI to respond with new perspectives while staying on topic.
Example:
Original Prompt: “List some ways to improve website speed.”
Reframed Prompt: “What are techniques to decrease page load time on a website?”
Conclusion
Apart from the techniques discussed above, you will find a lot of other useful AI prompting techniques like iterative prompting, role-playing, etc. You can even play around to combine two or more techniques to come up with a prompt.
It takes some time to figure out the ways with AI as it is still in its nascent stage right now. As and how the models get more powerful, the amount of back-and-forth prompting will also likely reduce.
Prompt engineering is one of the most fun job profiles out there in the AI field. But even then, you need to know some basics to be able to get the answers while playing around.
If you are looking for prompt engineering training for employees, we have good news. EducationNest, India’s leading corporate training provider offers the best expert-designed, customizable training solutions for corporates to help their employees master new skills such as this.
