Prompt Engineering🏗️
How can I reliably control AI?
How can I reliably control AI?
How can I reliably
control AI?
Good prompts yield answers. Good guidance builds trust.
Why good prompting is the first step—and how structure, context, and the CO-STAR framework ensure reliable results.
Prompt Engineering as the Key to Better AI Results
Prompting is the beginning—not the solution
Since the breakthrough of ChatGPT and other large language models, prompt engineering has been considered the key to better AI results.
In fact, even a small change in the prompt can determine whether a response is helpful, incomplete, or simply wrong.
But the more AI is integrated into business processes, the more clearly a limitation becomes apparent: A good prompt alone does not make for a productive AI application.
In day-to-day business operations, responses must not only be well-formulated—they must also be consistent, aligned with the brand, and compliant with regulations. They should function regardless of which employee uses the AI or which model is running in the background.
That is precisely why prompting alone is not enough. Companies also need clear quality standards, defined processes, and technical guidelines so that AI can be deployed reliably and at scale.
A prompt generates a response.
A strategy ensures that this response is reliable.
In fact, even a small change in the prompt can determine whether a response is helpful, incomplete, or simply wrong.
But the more AI is integrated into business processes, the more clearly a limitation becomes apparent: A good prompt alone does not make for a productive AI application.
In day-to-day business operations, responses must not only be well-formulated—they must also be consistent, aligned with the brand, and compliant with regulations. They should function regardless of which employee uses the AI or which model is running in the background.
That is precisely why prompting alone is not enough. Companies also need clear quality standards, defined processes, and technical guidelines so that AI can be deployed reliably and at scale.
A prompt generates a response.
A strategy ensures that this response is reliable.
Tip from our experts
Dr. Anja LinnenbĂĽrger
Head of Research - Psychology & AI
"It's extremely easy to get the LLM to say something that sounds reasonable. At the same time, it's really hard to get the LLM to do exactly what you want it to do.
"
The Five Most Common Problems with Prompting
The CO-STAR Framework
The Anatomy of a Good Prompt
A good prompt consists of more than just a question. The CO-STAR framework allows tasks to be clearly structured and results to be better managed. It helps to clearly articulate expectations and sustainably improve the quality of responses.
Is your AI already delivering the results you expect?
If responses are still inconsistent or lack quality and transparency, it’s worth taking a closer look at prompting, control, and governance. Together, we’ll figure out how you can use your AI more reliably and efficiently.
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More About Prompting
Learn strategies for using language models precisely and efficiently.
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