We’re back with our AI experts for another practical learning session

Creating prompts for AI that elicit valuable (and truthful) responses involves more than meets the eye. You might be wondering, “What is the return on optimizing my prompts? Wouldn’t most prompts give me what I need?” But you’d be wrong. While creating prompts may seem simple, optimizing your prompts can be the difference between a somewhat helpful response from your AI engine and your new best friend.

In the session, the two Joels and Ian ran through our tried-and-true approaches to AI prompt creation. Then, the attendees took it away, asking questions that delved deep into prompt creation.

• Importance of Prompt Libraries and Frameworks: Developing and using prompt libraries can significantly improve efficiency and consistency in AI interactions. Frameworks like the Co-star prompt help you to provide information to AI models, which lead to more accurate and useful outputs.
• Application in Data Analysis: AI tools are being extensively used to analyze large volumes of unstructured data, such as open-ended responses from focus groups and surveys. These tools can efficiently summarize and filter data based on different themes and subgroups. However, the analysis of complex quantitative data with multiple filters remains a challenge, and there are ongoing efforts to improve AI capabilities in handling the data sets.
• Addressing Prompt Limitations and Rejections: The two Joels discussed strategies for dealing with situations where AI tools refuse to perform tasks that they are technically capable of. It’s important to tweak prompts and provide specific roles or contexts to guide the AI effectively. For example: if you’re looking for places to see in a new city, specifying a role such as “travel guide” can yield more precise and relevant recommendations from the AI​​.