Creativity: AI Prompts with These Power Tips
All about AI
Jan 19, 2025 8:23 PM

Creativity: AI Prompts with These Power Tips

by HubSite 365 about Heidi Neuhauser [MVP]

Microsoft MVP | User Adoption, Dynamics 365 + Power Platform Expert at Reenhanced

Pro UserAll about AILearning Selection

AI Prompts: Discover their use in organizations with Microsoft Azure, Microsoft 365, and Power Platform.

Key insights

  • Be Clear and Specific: Clearly state your goal for the AI, provide context, and add constraints to guide the output effectively.

  • Include Examples (Few-Shot Prompting): Show desired outcomes with examples, highlighting correct and incorrect outputs to teach patterns.

  • Use Structured Prompts: Break down instructions into steps or bullet points and categorize data for clarity in AI responses.

  • Experiment and Iterate: Start simple, refine based on results, and adjust prompts iteratively for better AI performance.

  • Leverage AI Builder’s Custom Models: Train custom models for specific needs like text classification or form processing to enhance automation.

  • Provide Domain Context: Use industry-specific terms and organizational tone guidelines to ensure accurate and stylistically appropriate AI responses.

Introduction to AI Prompts in Microsoft Power Platform

The digital landscape is rapidly evolving, and artificial intelligence (AI) is at the forefront of this transformation. Organizations are increasingly adopting AI to enhance their operations, and Microsoft Power Platform offers robust tools to facilitate this integration. In a recent YouTube video by Heidi Neuhauser, an MVP in the field, viewers are introduced to the concept of AI prompts and how they can be effectively utilized within Microsoft Power Platform. This article delves into the key insights from the video, providing a comprehensive guide on creating efficient AI prompts for various applications.

Clarity and Specificity in AI Prompts

One of the fundamental aspects of designing effective AI prompts is clarity and specificity. According to Neuhauser, it is crucial to clearly state the goal of the AI task. Whether the objective is to generate text, extract information, or make predictions, defining the purpose helps in guiding the AI to produce accurate results. Additionally, providing context is essential, especially when the AI is used for customer inquiries. Mentioning the domain, such as healthcare or finance, ensures that the AI can tailor its responses appropriately. Furthermore, adding constraints like character limits, style requirements, or data formats keeps the AI output focused and relevant. For instance, a prompt might instruct the AI to summarize a customer complaint in no more than 100 words, focusing on specific issues like late deliveries.

Incorporating Examples Through Few-Shot Prompting

Another effective strategy highlighted in the video is the use of examples, known as few-shot prompting. By demonstrating the desired outcome through sample inputs and outputs, users can significantly enhance the AI's learning process. Providing examples of both correct and incorrect outputs helps the AI understand common errors and avoid undesirable results. For example, if a user complains about a product defect, the ideal AI response should express empathy and offer a solution, rather than suggesting alternatives that could be perceived as dismissive. By generating the ideal AI response for each user complaint, organizations can ensure a more consistent and satisfactory customer experience.

Structured Prompts for Better AI Performance

The use of structured prompts is another key takeaway from Neuhauser's video. Instead of presenting instructions in long paragraphs, breaking them down into bullet points or numbered steps can improve the AI's performance. This approach not only makes the instructions clearer but also helps in categorizing or labeling data effectively. For instance, a prompt might instruct the AI to read a user's message, identify references to timing or scheduling, and then provide a polite response offering scheduling options. By structuring prompts in this manner, users can guide the AI to perform tasks more efficiently and accurately.

Experimentation and Iteration in AI Prompt Design

Experimentation and iteration are vital components in the design of AI prompts. Neuhauser emphasizes starting with simple instructions and gradually adding more detail or constraints based on the AI's output. If the initial response is not satisfactory, users should refine their prompts by tweaking phrasing, adjusting examples, and experimenting with different levels of detail. For instance, a first draft prompt might ask the AI to write an apology to a customer. However, an improved prompt could specify writing a brief, empathetic apology that includes an offer to compensate for the inconvenience. Through iterative refinement, users can achieve more precise and effective AI responses.

Leveraging AI Builder's Custom Models

For specialized tasks, leveraging AI Builder's custom models can be highly beneficial. Neuhauser discusses the advantages of training custom models for text classification, object detection, or form processing. By building a custom AI Builder model, users can tailor the AI to their specific needs rather than relying solely on prebuilt models. Moreover, combining these models with Power Automate allows for automatic parsing of results, reducing manual work. For example, a custom Form Processing model can be trained to recognize fields like "Invoice Number," "Amount," and "Due Date" in invoices with varied layouts. This automated data extraction can be triggered by a Power Automate flow whenever a new invoice is uploaded, streamlining the workflow significantly.

Providing Domain Context for Improved AI Accuracy

Lastly, providing domain context is crucial for improving AI accuracy. When working in specialized fields like pharmaceuticals, legal, or manufacturing, including relevant industry jargon helps the AI identify and respond correctly. Additionally, organizations should provide brand guidelines or tone-of-voice instructions if a specific style is required. For example, a prompt might instruct the AI to use a friendly tone, as the brand guidelines are casual and should avoid overly technical terms. By incorporating domain context, organizations can ensure that the AI aligns with their branding and communication standards.

Conclusion

In conclusion, the insights shared by Heidi Neuhauser in her YouTube video offer valuable guidance for organizations looking to harness the power of AI within Microsoft Power Platform. By focusing on clarity, incorporating examples, using structured prompts, experimenting and iterating, leveraging custom models, and providing domain context, businesses can create effective AI prompts that enhance their operations and improve customer interactions. As AI continues to evolve, these best practices will be instrumental in maximizing its potential and driving innovation across various industries.

All about AI - Unlock Creativity: Master AI Prompts with These Power Tips

Keywords

AI prompts, power tips, SEO keywords, artificial intelligence, content creation, digital marketing, prompt engineering, AI tools