Prompt engineering is an important aspect of generative AI because, using prompt engineering strategies, users can create better inputs. This way, users will make sure that each artificial intelligence model or chatbot used will be able to handle any complex tasks based on a well-written AI prompt.
It’s important to know that AI chatbots are now trained on large amounts of data, and a weak prompt can determine the AI models to provide the wrong content or even take too long to offer a good answer. So, to avoid all of these situations, a detailed AI prompt that gives all the details about a certain task will help the chatbot search for the right information in order to generate the best answer possible.
The final answer is generated using a combination of machine learning techniques and NLP, also known as natural language processing. So, when users provide their input, the artificial intelligence chatbot analyzes its structure in context, along with past interactions, in order to generate the most relevant response for you.
It’s already known that all artificial intelligence models are fully trained on large amounts of data based on deep learning algorithms. This way, AI chatbots can offer the best response.
After the model truly understands your prompt, will then use already already-trained AI algorithms to use content, logic, and text formatting to generate an answer that is relevant to the given AI prompt.
- Add as many details as possible to get the most relevant answers.
It’s important to mention as many details as possible because they provide a certain context to your prompt. If the artificial intelligence model receives fewer additional information and details, it will start to make different assumptions, and will probably generate a result that is not according to your specific needs and desires.
Instead of asking “How do I add numbers in an Excel spreadsheet”? Try to ask about specific tasks or details, such as “How to add a row of numbers to have the final amount in this cell”.
Another AI prompt engineering example is instead of just asking to summarize your recent meeting notes, tell the AI to summarize them in just a single paragraph and highlight the key points about a topic. This way, the artificial intelligence chatbot will know exactly what to analyze and summarize to give the best outcome from the first interactions.
Keep in mind that the more information you give to your AI assistant, the more appropriate your results will be.
- Ask the AI assistant to think like a real person.
If you want the chatbot to offer more human responses, you must ask it to act like a real person. This way, the AI assistant will create different responses as if they are coming from a certain person.
Make sure to determine the context and the role that the chatbot must fulfill. Users can also say the persona before the actual AI prompt, and highlight how exactly the task should be done, for different purposes.
Prompt engineering example:
“ You are a young software engineer with a limited experience level. You ask a senior engineer developer for advice about how to solve a coding problem. Explain it with simpler terms, to be understood by junior engineers”.
- Indicate the exact steps that must be followed to complete a task.
Some tasks need a certain step plan, so instead of relying on the AI assistant to figure out what the steps are, it’s best to provide them from the first interaction. This way, users will make sure that the AI chatbot will complete a certain prompt in a certain order, without avoiding important details.
Prompt engineering examples:
“Summarize my meeting notes, and then translate them into Spanish, Italian, and German in order to send them to all my meeting collaborators. “
This way, you will avoid the need to ask the chatbot again to translate them, and you will have your answers much faster.
- Tell the AI assistant the exact length of the response.
To make sure that your response is generated according to your needs, you can also tell the AI chatbot what specific length it should have. In some cases, the artificial intelligence assistant will generate the correct information according to your AI prompt, but it may not structured as you might need.
So, try and indicate the number of words, or how the response can be structured with bullet points and paragraphs. It should be mentioned that the model will probably not provide the exact number of words, but it will try to stick to your given prompt.
AI Prompt engineering example:
“Please generate a short story about my summer holiday in about 150 words. Please keep this limit when generating my story”.
- Don’t forget to provide examples.
AI chatbots and models usually need large amounts of data in order to learn something completely new. However, in prompt engineering, they don’t need many examples to generate responses in a desired tone. It’s enough to provide one or two examples, and then the AI assistant will understand how its responses need to be generated.
So, if you want to generate a response in a certain way or with specific words, it’s important to provide a couple of examples.
Prompt example:
“Generate a message for my mom’s birthday, but use these words….(example). And it needs to sound like this….(example)”
AI Prompt engineering represents the best way for users to learn how to interact with artificial intelligence assistants and how to integrate them into daily activities to streamline their workflows. Sometimes it can be a challenging process to achieve the best prompt, but once you figure out how to create the best prompt at every interaction, each communication will become more enjoyable and easier.
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