This month, we are addressing the topic requested by our colleague Heinke and learning everything one needs to know about prompting.
The hype surrounding chatbots has not subsided even two and a half years after the release of ChatGPT, and by now, almost everyone has experimented with a chatbot. While chatbots are already being used in many companies, others have not yet recognized their benefits or were dissatisfied with their test results. But what could be the reason for this? One cause for unsatisfactory answers can be insufficient prompts. To ensure you achieve the best possible results in the future, we have compiled an overview of what to consider when prompting.
What is Prompting?
A prompt is the input given to the language model or chatbot to obtain a specific answer or a certain behavior. Prompting has evolved into a veritable sport for many people, serving not only to achieve the best possible results but also capable of being misused. For instance, there are individuals who deliberately try to obtain erroneous results through prompting, for example, to harm the providing companies.
Why is Prompting Important?
Prompting is important because it influences the quality and relevance of a language model’s responses. A well-formulated prompt can help the model deliver precisely the information needed while avoiding unnecessary or irrelevant information. This saves time and improves efficiency when using language models.
Tips for Effective Prompting
- Be clear and precise:
A good prompt should be clear and precise. Avoid vague or ambiguous phrasing. Provide the model with as much context as possible to obtain the desired answer. - Use specific questions:
Ask specific questions instead of making general requests. For example: “What steps are necessary to start a new project?” instead of “Tell me about project management.” - Use examples:
Provide the model with examples to clarify the desired answer. For example: “Create an email thanking a customer for their order. Here is an example: ‘Thank you for your order. We look forward to delivering your goods soon.’” - Use instructions:
Give the model clear instructions on what it should do. For example: “Write a blog post about the benefits of artificial intelligence. The post should be at least 500 words long and written in an informative tone.” - Avoid ambiguities:
Avoid ambiguities and unnecessary information. A clear and precise prompt helps the model deliver the desired answer faster and more accurately.
Examples of Effective Prompting
- Answering Questions:
- Prompt: “Explain the basics of artificial intelligence.”
- Answer: “Artificial Intelligence (AI) is a field of computer science concerned with the development of systems capable of performing tasks that normally require human intelligence.”
- Creating Texts:
- Prompt: “Write a blog post about the benefits of artificial intelligence. The post should be at least 500 words long and written in an informative tone.”
- Answer: “Artificial Intelligence (AI) has made enormous progress in recent years and offers a variety of benefits for various industries. From automating routine tasks to improving decision-making – AI has the potential to significantly increase efficiency and productivity in many areas…”
- Translations:
- Prompt: “Translate the following text into German: ‘The quick brown fox jumps over the lazy dog.’”
- Answer: “Der schnelle braune Fuchs springt über den faulen Hund.”
Conclusion
Prompting is a powerful tool that helps you get the best results from language models. With the right techniques and tips, you can ensure that your prompts are clear, precise, and effective. Utilize these strategies to improve the accuracy and relevance of responses and make your work more efficient.
