Prompt

Prompting is a central part of interacting with artificial intelligence (AI) and describes the method of entering targeted instructions or questions – i.e. prompts – into an AI system to generate specific, helpful answers or content. The right technique enables you to control AI models such as ChatGPT, Midjourney and other tools efficiently and accurately. Particularly for creative or complex tasks, well-thought-out prompts can make the difference between relevant, valuable results and unclear, unhelpful answers.

Purpose of prompts and application in practice

Prompts are used in many areas today – from content creation to the automation of business processes. Prompts play a central role in marketing, customer communication and creative projects, such as creating AI-generated online texts.

What makes a good prompt?

A good prompt is formulated precisely, explains exactly which result is expected, and contains all the relevant information for the context. Let’s take as an example the task of having an AI write a blog post about the advantages of sustainable packaging material.

Example of a good prompt:

‘Write a short blog post about the advantages of sustainable packaging material for companies. Discuss how sustainable packaging can protect the environment, reduce costs in the long term and improve brand image. Start with a short introduction that sensitises readers to the topic and end with a conclusion that summarises the main points.’

Strengths of the detailed prompt:

The prompt puts the focus on the advantages of sustainable packaging material and already specifies specific advantages that the post should cover. In addition, the target audience is explicitly named and the AI is given clear instructions regarding the desired content and the structure to be used, as well as the desired word count if needed. With this information, a chat AI like ChatGPT can now provide the following text, for example:

Negative example for general prompt

‘Write about packaging material’

The problem is obvious: the AI does not know that the question is specifically about sustainable packaging material, nor who the target group is or which aspects of packaging material should be highlighted. Of course, ChatGPT can also work with this, but the result is as general as the prompt itself:

Prompt engineering

Not only users, but also developers have to deal with the question of how to enter prompts correctly and how to optimise the output of results on a daily basis. Prompt engineering is the further development of prompting and aims to iteratively improve prompts in order to get the best results from an AI. Prompt engineers systematically develop detailed instructions that guide AI models reliably and repeatably to meaningful results. This is important because large AI models often react variably and need to be adapted to the respective input. To exploit the full potential of AI models, various techniques such as tokenisation, top-K sampling and model parameter tuning are used.

Prompt templates: efficiency through reuse and structure

Aside from specialising in the further development of prompting itself, it is interesting to create reusable templates that make everyday work and private life easier. Prompt templates are pre-built input templates that enable fast and consistent creation of prompts using proven wording and structures. Especially for frequently recurring tasks, such as text generation, data analysis or image generation, you save time and have a reliable basis for precise results. Templates also promote quality assurance by integrating proven best practices. The challenge is to design them flexibly enough to allow for customisation to specific requirements. Well-maintained templates are a valuable tool for using the full potential of AI efficiently and in a targeted manner.

Advantages and challenges of prompting

A well-formulated prompt is the key to successful results with AI tools and helps to optimally support you in your day-to-day work. At the same time, every technology comes with its own challenges, here is a brief overview:

Advantages

• Precise control: Targeted prompting can achieve accurate and often more creative results
• Time saving: A well-thought-out prompt leads faster to the desired results
• Wide range of applications: From text creation to image generation and data set analysis: prompting is highly versatile
• Reusability: Recurring tasks can be completed more efficiently by creating prompt templates

Challenges

• Experience required: Developing effective prompts requires practice and knowledge of how AI works
• Limited control: Even the best prompt does not always guarantee the perfect result, as AI models can sometimes react unpredictably
• Data protection: prompts can contain sensitive information, which requires an awareness of compliance with data protection guidelines
• Effort vs. added value: very specific or complex requirements may require extensive testing and optimisation to achieve the desired results

As a result, knowledge of how to prompt correctly is increasingly becoming a sought-after skill. This is fundamentally changing the way people and businesses can use and benefit from AI.