Prompt engineering made easier with AI Builder

Prompts are the way to communicate with large language models (LLMs), the driving force behind generative AI technologies like ChatGPT and copilots. They serve as specific instructions that guide and steer the LLM to understand the context of a request to deliver the most relevant and accurate response. Crafting effective prompts is crucial for harnessing the capabilities of generative AI. A well-designed prompt can significantly enhance the relevance and efficacy of the output, aligning it closely with your intended goals.

Today, we are excited to launch a new set of prebuilt AI functions that can be easily added to a low-code solution without having to engineer a custom prompt. These prebuilt functions provide a great starting point to combine the power of LLMs and power of low-code, but they are just scratching the surface of what is possible. We will also cover how Projectum, a Microsoft partner, was able to leverage prompt builder, Microsoft Power Platform no-code prompt engineering interface, to build and incorporate custom, generative AI actions into their low-code project management solution. If you do choose to try out custom prompts, then please check out the newly published AI Builder prompt engineering guide for some great strategies on how to get started.

Start with prebuilt functions to quickly implement generative AI capabilities 

Starting today, prebuilt AI functions can be used to quickly incorporate generative AI into your Microsoft Power Apps solutions or your Microsoft Power Automate flows without having to engineer your own prompt. Then, if needed, makers can utilize the prebuilt prompt template and customize it to their needs in Microsoft Copilot Studio. 

These readily accessible AI functions are designed to facilitate common AI-driven tasks across the platform. Whether it’s summarizing emails or conversations, categorizing complaints or reviews, extracting critical information from extensive text, crafting responses or drafts to specific messages, or discerning the sentiment of product evaluations, AI functions provide quick-start access to generative AI capabilities.

Here are some examples of how you can use these ready-made prebuilt prompts today:

AI Summarize: Summarize text from an email or document and add the summary to a Microsoft Dataverse table record. Your application end users would benefit from the summary and can quickly evaluate the next steps.

AI Classify: Quickly classify customer inquiries into your own categories to ensure the inquiry is assigned to the correct team. You could use this from your custom copilot to route the inquiry and reduce customer frustration from being redirected multiple times.

AI Reply: Help staff move past writer’s block by drafting a reply message. For example, draft a reply to a customer’s review of a product.

AI Extract: Automate data augmentation by extracting data like phone numbers or names of people from incoming correspondence. This saves time and improves data quality by prepopulating the data.

AI Sentiment: Build in the ability to your apps or automations to quickly check if text is positive, negative, or neutral. For example, for the staff reviewing customer feedback, you could provide an indicator in the application of the sentiment.

Projectum: Empowering project management with AI-driven insights

Projectum is a leader in strategic portfolio management, delivering solutions that streamline project management and yield superior outcomes. Specializing in portfolio management, resource and capacity demand management, and time registration, Projectum is the go-to partner for businesses aiming to turn strategy into successful execution. With Projectum, organizations enhance project delivery, optimize efficiency, and boost their bottom line. 

Last year, Projectum unlocked new product opportunities with generative AI capabilities in its Power PPM (project portfolio management) product. Using AI Builder’s prompt builder, Projectum allows project managers to create strengths, weaknesses, opportunities, and threats (SWOT) analysis, identify project risks, summarize project reports, and generate real-time project status updates—all using natural language. With AI Builder’s custom prompts, Projectum can easily control the generative response, invoke prompts via Power Apps, and ensure governance through integrated monitoring. AI Builder also enables Projectum to ground the generative AI’s responses in enterprise knowledge, thereby delivering accurate and relevant responses to its customers. 

“AI Builder and Copilot in Power Platform products have been transformative for Projectum. Our users can now wield powerful AI capabilities right within our Power PPM solution. The ability to create custom prompts, invoke AI-driven SWOT analysis, and generate new types of insights has elevated our product’s value proposition.

It’s a win-win for us and our customers, and we see AI Builder supporting all three categories of Project Management AI use cases: automation (improving approval flows and data summarization), assistance (draft schedules and risks logs), and augmentation (business case validation)” 

— Peter Charquero Kestenholz, Founder and Head of Innovation & AI at Projectum 

Best practices for combining prompts and low-code: AI Builder prompt engineering guide

Prompts act as the foundational elements for integrating generative AI capabilities within Microsoft Power Platform, embedding seamlessly into its comprehensive suite, including Power Apps, Power Automate, and Copilot Studio. Facing unlimited possibilities for content generation and data transformation, low-code makers and developers can reference the AI Builder prompt engineering guide for creating efficient and accurate GPT prompts. The following example visualizes a GPT prompt that makers could use to analyze a complaint from a customer on delivery of their order. Makers can incorporate the customer complaint and the shipping policy as input parameters.

Prompts empower makers to develop bespoke AI functions tailored to business needs and binds them as actions to controls in Power Apps. Leveraging Microsoft Power Fx, makers can effortlessly activate these prompts through various user interactions, such as page refreshes or button clicks. The new prompt engineering experience allows the addition of input parameters to prompts, providing a more contextually relevant data input to LLMs at runtime, thereby eliciting more precisely aligned responses from GPT models.

Prompts find significant utility in Copilot Studio, where they can operate as custom AI plugin actions using just natural language. These plugins serve as a powerful method to extend the native capabilities of your copilots, ensuring their responses are finely tuned to meet specific business requirements. Copilots are designed to call upon these custom plugins to fulfill tasks in response to end-user prompts, enabling a custom copilot experience that leverages these uniquely defined plugin actions for relevant user queries.

Furthermore, prompts can play a crucial role in Power Automate, where they simplify the creation of AI-driven actions for intelligent workflow design. By enabling the extraction of data from unstructured sources and transforming it into structured output, prompts enhance the efficiency and intelligence of downstream processing, making them an indispensable tool for building and infusing generative AI capabilities throughout the Microsoft Power Platform ecosystem.

How you can get started with prompt builder in AI Builder

Try prompt builder

Prompt engineering guide

Prompts overview documentation

Learning videos:

Overview video

GPT prompts with Excel video

Governance: learn about administrating generative AI features and cross region availability

The post Prompt engineering made easier with AI Builder appeared first on Microsoft Power Platform Blog.
Source: Microsoft Power Platform