Prompt Engineering

Composition of a Prompt

First, a good prompt should be clearly and concisely worded to minimize ambiguity and elicit the desired response. Second, it should provide context, as this helps the AI generate relevant and nuanced responses. Finally, a good prompt should be open-ended enough to encourage creative thinking and rich responses without being overly vague or non-specific.

Zero-Shot vs. Multi-Shot Prompts

There are a variety of tasks that can be solved using what is known as zero-shot prompting. In this model, an AI model is asked to perform a task without any explicit prior instructions or context. However, for other, more complex requirements, multi-shot prompts prove to be essential. These approaches provide more context or examples for the model to effectively perform a given task.

Prompt Parameters

Users of chat interfaces are often unaware that the underlying language model is automatically configured via parameters depending on the request. As a developer, you can set these parameters specifically to fine-tune the results. For example, the most important parameters of ChatGPT are the temperature, which controls the probability of predicting the subsequent words, and the maximum token count, which determines the length of the generated responses. In addition, there is also the "top_p" parameter, which influences the selection of words or phrases considered for the next passages in the text.

Length Restrictions

It is important to note that the length of a prompt can vary depending on the AI system used, and in some cases could be more or less restricted. This affects how verbose and precise the prompt can be designed.

Long prompts can significantly increase the cost of ownership of an AI solution. In such cases, fine-tuning language models may be the more economically viable approach.

Changes in AI Results Over Time

Another aspect of prompt engineering is the potential instability of the prompts. They can be very sensitive to changes, which may mean that the results the model produces change from one second to the next. This underscores the need for careful planning and tweaking when creating prompts for AI systems.

Different AI Language Models

Also worth noting is that prompts cannot always be directly applied to different language models. Each model has its specific characteristics and idiosyncrasies that must be taken into account when formulating prompts.