Prompt Engineering describes the systematic development, optimisation and management of AI prompts. The aim is to design AI requests in such a way that they consistently deliver high-quality and reproducible results.
While individual prompts are often created spontaneously, Prompt Engineering follows a structured approach. Prompts are developed, tested and continuously improved. In a business context, terminology, style guides, reference documents and other company knowledge are also incorporated so that the AI delivers results that meet the company's standards.
The key tasks of Prompt Engineering include:
- Development of professional AI prompts
- Optimisation of existing prompts
- Standardisation of recurring tasks
- Integration of company knowledge
- Consideration of terminology and style guides
- Continuous improvement of results
An example:
❌ Without Prompt Engineering:
A new prompt is created manually for each translation.
✅ With Prompt Engineering:
A company develops a standardised prompt template that automatically takes terminology, the style guide and company knowledge into account and is reused for all marketing texts.
In short:
Prompt Engineering ensures that AI systems consistently deliver high-quality and transparent results.