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 comply with company standards.
The most important tasks in prompt engineering include:
- Developing professional AI prompts
- Optimising existing prompts
- Standardising recurring tasks
- Incorporating company knowledge
- Taking terminology and style guides into account
- Continuously improving 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, traceable results over time.