Quick fixes to boost your Copilot responses
Did Copilot disappoint you recently? Who has never complained about Copilot responses? Myself included. You know that moment when you try to get a good Copilot response, and all you get is vague one? Yep. Been there. It’s Not You, It's not Copilot either, It's Your Prompt People tend to treat Copilot like a search engine, but Copilot isn’t a search engine. I know it feels like it should be—type in your query, get a polished answer. Here's the deal: Copilot (and all other LLMs) work with recognizing patterns and context based on your prompts. Copilot does not retrieve information, but generates answers. Copilot relies on the context and specificity of your prompts to generate useful responses. That means vague, lazy prompts are setting it up to give vague responses. If you want great output, you need great input. So let’s talk about how to give Copilot the kind of prompt it can actually work with. 10 Quick Fixes to Boost Your Copilot Responses Write clear prompts: ❌ “Make it better” → ✅ “Summarize in 3 points” Be specific: ❌ “Write an email” → ✅ “Draft a friendly reminder email for project deadline” Be direct: ❌ “Could you try to…” → ✅ “Generate a bulleted list of main takeaways” Give context: ❌ “Draft an email” → ✅ “Draft a response to the client email /<youremail> to apologyse for the delivery delays” Divide to conquer: ❌ “Write a report” → ✅ “Outline the report in sections: intro, analysis, and conclusion” Choose wisely: ❌ Copilot is not equal Copilot. → ✅ Understand the differences between M365 Copilot Chat and M365 Copilot and learn when to use what. I wrote a post about this topic already, here you can find it: Copilot Chats vsus. M365 Copilot: What's the difference? Try rephrasing: ❌ “Try again” → ✅ “Rephrase the sentence” Sometimes, a small word change makes a big difference. Iterate: Unhappy? ✅ If your plan A did not work, go for plan B. You can start a new chat, adjust your initial prompt, and try again! Include web content when relevant: ✅ Enrich your Copilot responses with web content. Toggle on web content like this: Click on the 3 elipses on the top, right corner of Copilot chat in Work mode. Give it another shot! ✅ LLMs are evolving quickly. What it did not work last month, it may work today! Want Copilot to stop disappointing you? Prompt like you mean it. 💡 Got your own favorite Copilot trick? Share it in the comments below.
Microsoft copilot stops while giving a response.
Why is this happening? Is there a solution for this? It just stops while giving response. And it has happened several times. And you can't even give prompt to continue from there. You should restart it. Does anyone have a solution for this? and I have restarted and reinstalled it 1000 times.Boost Your Productivity: How to Automate and Schedule Prompts in Copilot
In this tutorial, I'll show you how to automate and schedule prompts in Copilot to maximize your productivity. Whether you're a seasoned user or new to Copilot, this guide will help you streamline your workflow and save valuable time. In this video, you'll learn: - The basics of setting up automated prompts in Copilot. - How to schedule prompts to fit your daily routine. - Tips and tricks to enhance your efficiency with Copilot. Don't forget to like, subscribe, and hit the notification bell to stay updated with our latest productivity hacks! #AI #Copilot #Automate #MVPbuzz #Microsoft365Copilot
Copilot in Outlook
One of my users trying to extract all calendar items from their Outlook through out the year to an excel to be created by Copilot. 1-When prompting the Excel file is generated but not clickable looks like corrupted. 2-When prompting Copilot to list all calendar items through out the year it shows only few results but not the full list of meetings. Anyone has an idea pleaseCoPilot Teams Minutes
Hi All I hope you are well. Anyway, I normally work in the Intune workspace but I have been asked to research CoPilot for Teams Minutes. Could someone please point me in the right direction regarding: Proof of Concept setup Implementation UAT How and where the data is stoed any info would be really helpful. Stuart
Word: 'Give all nouns that appear >X times' not working as expected
Hi! When using Copilot in Word, I tried several iterations of the question 'Give me all nouns that appear over 6 times. Provide your information in a table and include the number of times the noun occurred'. Copilot provided a nice table, but it was not complete by far. The document was under 7500 words so that should not have been the issue. What prompt should I use to achieve my goal? Anyone any idea? I want to put repeating input fields in the document and wanted to see for which words/terms this would be worthwhile, which is why I was hoping Copilot could provide me with a quick overview of repeating terms. Thanks, Merel
Building Copilot Agents with User Experience in Mind
Understand where and how the user will be accessing the Copilot agent Create multiple-modal experiences for your Copilot using voice To enhance the accessibility and user-friendliness of your copilot agent, consider developing a voice agent for voice interactions. This hands-free experience is not only inclusive but also particularly beneficial in customer scenarios where associates are using their hands and need to interact with the agent quickly and effectively without typing. Before deploying the agent to your user base, ensure thorough testing in the work environment to validate a good end-user experience, especially considering the loudness of the environment. For step-by-step instructions on testing the voice agent experience, you can view this blog Determine the proper channel deployment Selecting the appropriate channel for deployment is crucial. Ensure you reach users where they perform their work, whether it's through M365 Copilot, M365 Copilot chat, embedding into a website, or other channels. It's essential to deploy the agent to the channels that best suit the use case. Creating multilingual agents Creating multilingual agents is essential for providing a personalized and inclusive experience. By enabling your agent to interact in multiple languages, you can cater to a diverse user base and ensure effective communication without language barriers. This feature enhances accessibility, user satisfaction, and expands the agent's reach in global contexts. For more specific information on multilingual agents see below. Take Time During the Configuration to Set Up the Agent for Success Creating a name for the agent In a world where multi-agents are on the rise, it's essential to be as descriptive as possible in the name and description for the intended use. This helps users understand the agent's purpose and functionality. Planning out your multi-agent scenarios early and defining clear names is especially important to avoid confusion. Add starter prompts Starter prompts guide users on how to interact with the agent effectively. These prompts should be clear and concise. When selecting starter prompts, consider defining the most common use cases for the agent. For example, if you are creating an IT Support agent, you might include prompts like "create a support ticket" or "check request status" to cover the most asked questions. Provide description and general instructions A detailed description of the agent's capabilities and intended use helps users understand what they can expect from the interaction. This description also assists the language model in identifying and utilizing your agent for specific tasks or situations. Ensure that the description is concise yet informative. For the instructions (declarative and generative mode), you should be as detailed as possible. Include the purpose, guidelines on what the agent should and should not do, tone, and the skills the agent will possess. Below are resources that provide detailed instructions on how to construct the verbiage effectively. Add key knowledge resources Adding key knowledge sources to the agent is crucial for its effectiveness and reliability. By integrating relevant documentation and connecting to essential business systems, the agent can provide accurate and timely information, ensuring users receive the support they need. These connections enable the agent to perform specific tasks efficiently, leveraging up-to-date data and resources. This not only enhances the user’s experience but also ensures the agent remains a valuable tool in various scenarios, from customer support to internal business operations. Offer alternative ways to answer questions Connecting to a live agent Provide users with the option to connect to a live agent for more complex queries or issues that the agent cannot resolve. Customizing the escalation topic is another way to track potential opportunities for agent improvement. Creating a step in the topic to record the escalation to ensure it is captured for agent performance is key to ensuring agent success and continued feedback on areas of improvement. Create adaptive cards Using adaptive cards in a Copilot agent enhances user interaction by providing a visually appealing and interactive interface. They facilitate structured data collection, ensuring consistency and ease of processing. Adaptive cards offer customization and flexibility, allowing them to be tailored to various scenarios and use cases. They improve communication by presenting information clearly and concisely, reducing ambiguity. Additionally, adaptive cards integrate seamlessly across different platforms and devices, ensuring consistent user experience. Overall, they significantly enhance the functionality and user experience of Copilot agents. Provide documentation references or links In the agent's response, include links to additional resources. Offer links to documentation or external sites where users can find more detailed information. Automate, Automate, Automate Enhancing efficiency with automation Using automation in Copilot agents (agent flows and agent actions) can significantly improve efficiency and reduce manual workload by identifying key processes that can be automated. Incorporating messages that inform users when the agent is processing their request helps manage user expectations and enhances the overall experience. By automating repetitive tasks and providing real-time updates, Copilot agents can streamline workflows, allowing users to focus on more complex and value-added activities. This approach not only boosts productivity but also ensures smoother and more transparent interaction with the agent. Monitor Agents for Insights Actively review the analytics for the agent Regularly reviewing analytics is essential for assessing the agent's performance and identifying areas for improvement, ensuring a high-quality user experience. By analyzing metrics such as engagement outcomes, knowledge source usage, action success rates, and user feedback, you can gain valuable insights into how effectively your agent is meeting user needs. Resources like Microsoft Copilot Studio Analytic, Topic Analytic Autonomous agent health, and Application Insights telemetry provide detailed guidance on measuring and enhancing agent performance. For more information see the discussion on monitoring performance and effectiveness of M365 Copilot agents. Collect Feedback Integrate feedback mechanisms Use adaptive cards to collect user feedback after every interaction with your agent. This allows you to assess and enhance the quality of agent responses while ensuring user satisfaction. Implementing this feedback mechanism helps in obtaining valuable insights into how well your agent is performing and identifying areas for improvement. Conclusion To create an effective Copilot agent, focus on providing easy accessibility by developing voice interactions and multilingual capabilities. Ensure you set up the agent properly in a world of multi-agents to decrease complexity and avoid confusion. Be creative in how you answer prompts, using adaptive cards and alternative ways to respond. Automate crucial business processes associated with the agent's purpose to enhance efficiency and reduce manual workload. Finally, actively collect feedback and apply it to continuously improve the user experience, ensuring the agent remains a valuable tool. A special thanks to IvicaIvancic ((3) Create your first custom AI enabled Copilot Studio Voice Agent – step-by-step guide | LinkedIn) and TrevorNorcross (Monitoring performance and effectiveness of Microsoft 365 Copilot agents | Microsoft Community Hub) for their incredible support in allowing me to link to their insightful blogs.Clarity around the different types of connectors available for Microsoft 365 Copilot
Working with some of the largest and most technical of Microsoft's partners in the Global System Integrators (GSI) team, we are still often met with confusion around the different types of connectors available in M365 Copilot. While agent extensibility could easily be a full week or more of discussion topics and sessions, I wanted to spend a moment to focus specifically on some of the various types of connectors available to agent makers working with M365 Copilot. GRAPH CONNECTORS Graph Connectors play a crucial role in enhancing the knowledge scope of Microsoft 365 Copilot, by enabling the integration of external data sources into the Microsoft Graph. This integration allows Copilot to reason over a broader range of enterprise content, thereby improving the relevance and accuracy of responses to user queries. By ingesting unstructured business data through Graph Connectors, organizations can ensure that their critical content is indexed and accessible within Microsoft 365 Copilot. This process involves semantic indexing, which optimizes data retrieval and enhances the matching of search queries to content, providing more relevant results than simple keyword matches. The relevance of Graph Connectors to Microsoft 365 Copilot is particularly significant in the context of enterprise search and data utilization. Copilot leverages these connectors to access and summarize information from various external sources, such as third-party applications, databases, and cloud services. This capability allows users to find, summarize, and learn from their business data through natural language prompts in Copilot. For example, when a user asks Copilot to summarize recent communications or project updates, Graph Connectors enable Copilot to utilize relevant data from integrated sources, ensuring comprehensive and accurate responses. As an agent maker using M365 Copilot, one important consideration of Graph Connectors is that they offer high-performance operations, due to direct access to information via the Large Language Model (LLM). However, keep in mind that data accessed is not pulled from the external data sources in real-time, as the Graph Connectors sync this business data on a set schedule. Additionally, your operations will be limited to retrieval-based ("read only") tasks when interacting with externally-synchronized Graph data. It should also be noted that these types of connectors will work best for working with unstructured data. Moreover, Graph Connectors are not limited to Microsoft 365 Copilot; they also power other intelligent experiences within the Microsoft ecosystem, such as Microsoft Search and Context IQ. This extensibility allows users to hover over in-text citations to preview external items referenced in responses and dive deeper into the referenced content by selecting links at the bottom of Copilot responses. The ability to configure custom connectors and utilize pre-built ones further enhances the flexibility and utility of Graph Connectors, making them a valuable tool for organizations looking to leverage their external data within Microsoft 365. By integrating these connectors, organizations can ensure that their data is not only accessible but also actionable, driving better decision-making and productivity. POWER PLATFORM (FLOW) CONNECTORS Power Platform Connectors are integral to extending the capabilities of Microsoft 365 Copilot by enabling seamless integration with various external applications and services. These connectors act as proxies or "wrappers" around APIs, allowing Copilot to interact with other apps and services within the Microsoft ecosystem and beyond. By leveraging Power Platform connectors, users can connect their accounts and utilize prebuilt actions and triggers to build sophisticated workflows and applications. This integration enhances Copilot's ability to retrieve and process data from diverse sources, thereby providing more comprehensive and actionable insights to users. In the context of Microsoft 365 Copilot, Power Platform connectors enable the creation of custom agents that can perform specific actions based on enterprise data. For instance, connectors can be used to retrieve sales opportunities, manage orders, or even check the weather at a customer's location for site visits. This functionality is particularly valuable for businesses looking to automate routine tasks and streamline operations. By integrating these connectors, Copilot can ground its responses in real-time data from various enterprise systems, ensuring that users receive accurate and relevant information. While the performance of a Power Platform Connector will inherently not be as speedy as data retrieval via Graph Connectors, agent makers should consider advantages to using Power Platform Connectors in the right scenarios. The API wrapper can perform real-time operations with the external business data, not requiring data synchronization to the Graph to access. Additionally, these types of connectors offer the ability to add and update records, in addition to retrieval. I have also seen use cases where Power Platform Connectors are preferred when dealing with structured data, even in retrieval-only agents and tasks. Beyond that, Power Platform Connectors are essential for extending Copilot's capabilities through Copilot Studio. This platform allows makers to add custom knowledge and skills to agents using connectors, thereby expanding the range of actions that Copilot can perform. For example, connectors can bring in data from Microsoft Graph, Dynamics 365, and other non-Microsoft enterprise sources, enabling Copilot to provide more nuanced and detailed responses. The ability to use these connectors in a no-code environment makes it accessible for users with varying technical expertise, empowering them to create intelligent, automated experiences that address unique business challenges. CONCLUSION By understanding the different types of connectors, the advantages and disadvantages of each, and the scenarios where each work best, agent makers can use one of the most powerful tools for working with external business data. For additional technical detail, please see the links below: Copilot connectors and actions overview (preview) - Microsoft Copilot Studio | Microsoft Learn Use Power Platform connectors (preview) - Microsoft Copilot Studio | Microsoft Learn Extend Copilot for Microsoft 365 with connectors | Microsoft Learn Build Microsoft Graph Connectors for Microsoft 365 Copilot | Microsoft Learn
