Can Microsoft Frontier Program Copilot Cowork Agent Delegate Tasks to Other Copilot Agents?
Hi everyone, I'm currently exploring the capabilities of Copilot Cowork that is available through the Microsoft Frontier Program, and I'm trying to understand whether a multi-agent orchestration pattern is officially supported. My Use Case I want users to interact with only a single, central Copilot Cowork agent. For example: User asks the Cowork agent to create or update a Jira ticket. Instead of Cowork handling the Jira operation directly, it delegates or hands off the task to a dedicated Jira Copilot Agent. The Jira agent performs the required actions and returns the result. The Cowork agent then presents the final response back to the user. Similarly, I would like to have specialized agents for: Jira ServiceNow Knowledge Management HR Operations Internal IT Support Other business systems The goal is to have Cowork act as an intelligent orchestrator/router while specialized agents handle domain-specific operations. Questions Is agent-to-agent delegation or handoff officially supported in Copilot Cowork (Frontier Program)? Can Cowork directly invoke another Copilot Studio agent? Is there any built-in multi-agent orchestration framework available today? If this is supported, what is the recommended architecture and implementation process? If it is not currently supported, what workarounds are people using? Power Automate? Agent as a tool/action? Custom APIs? Azure AI Foundry / Azure AI Agent Service? Other approaches? I'm specifically looking for guidance from anyone who has worked with Copilot Cowork in the Frontier Program, since the documentation and public examples seem to focus mostly on standalone agents. Any insights, architecture diagrams, documentation links, or real-world experiences would be greatly appreciated. Thanks!Copilot Connectors >Azure DevOps Work Items >Add Property
Hi I have setup the Azure DevOps Work Item connector and all is working OOTB. However when I try to 'Add a new source Property' and add for example 'TargetDate' when I publish the schema change it errors with: Schema failed to publish with error [Removal existing property is not allowed.] I havent removed anything just added. Anyone else experienced this? Many thanks
PowerShell: Export Microsoft 365 Copilot Agent Inventory and Availability Assignments
Hi everyone, I needed a way to export Microsoft 365 Copilot agent inventory and availability assignments from the Microsoft 365 Admin Center, but couldn't find a built-in export option. After investigating the admin portal's network traffic, I built a PowerShell script that uses the same internal API consumed by the Microsoft 365 Admin Center to export all Copilot agents to CSV. ### Features - Exports all Microsoft 365 Copilot agents - Automatically follows pagination (`nextLink`) - Exports: - Agent Name - App ID - Title ID - Publisher - Created By - Availability Settings - Allowed Users / Groups - Assignment Information - Deployment Information - Version Information - Timestamps - CSV output ### Tested The script has been tested against a tenant containing 482 Copilot agents and successfully exported the complete inventory. ### GitHub https://github.com/gwestergren/M365-Copilot-Agent-Inventory ### Notes - Uses an authenticated browser session cookie from the Microsoft 365 Admin Center. - Uses the same internal API currently consumed by the admin portal. - This is an undocumented API and Microsoft may change it at any time. Feedback, testing results, and improvements are welcome. Here are some screen shots: output to csv Successful run of the script
Has anyone seen Excel workbooks become corrupt after using M365 Copilot to summarize data?
We’ve run into an issue twice where a user opened an existing Excel sales workbook, used Microsoft 365 Copilot in Excel to summarize/analyze the data, received the response successfully, and then later could no longer open the original workbook because Excel reported it as corrupt. Internally, this has been reported as happening on some files but not all, and it has occurred twice so far. I’m trying to determine whether this is: a known issue with Copilot in Excel a workbook-specific problem related to file location/sync/versioning or something tied to workbook structure I did find public reports of related Excel Copilot issues — including Copilot crashing in Excel, failures that seem specific to certain workbooks, and Copilot-created Excel files being reported as invalid/corrupt — but I have not yet found a clear Microsoft-hosted thread describing this exact scenario with the original existing workbook becoming corrupt after summarization. If anyone has seen this, I’d appreciate any insight on: whether Microsoft has acknowledged a known issue whether this points to specific workbook features/structures whether there are logs or diagnostics that help isolate root cause whether there are best practices to reduce the risk
How are you connecting OKR tracking to Copilot workflows?
My manager asked me to figure out how we can use Copilot to help with our OKR process. Right now we track objectives in a SharePoint list and its a mess. People forget to update progress, key results are disconnected from daily work, and nobody looks at it until the end of quarter scramble. Has anyone found a way to bring OKR tracking closer to where people actually work in Teams/Copilot? Or is there a Teams app that handles this better than a spreadsheet?
Follow Microsoft Build Live for the latest updates and announcements
Microsoft Build is happening now, and the live blog is a great way to stay up to date on the latest announcements, demos, and key moments as they happen: 👉 Follow Microsoft Build Live What are you most interested in learning more about from Build this year? 👀Copilot Employee Self-Service Agent
I’m looking for some clarity regarding the rollout of the https://adoption.microsoft.com/en-us/ai-agents/employee-self-service-agent/ and whether others are seeing it in their environments yet. I’ve been following this closely and initially understood that a formal request was required to gain access. However, the Microsoft Learn documentation now provides specific, step-by-step instructions on how to enable and access it directly. Despite following those instructions to the letter, the agent is still not appearing within my tenant. I’ve verified my configurations against the guide, but the options simply aren't visible. A few questions for the community: Has anyone else successfully enabled the agent using the self-service steps in the documentation? Is there or was there ever a manual "request-for-access" process that overrides the published steps? I’d appreciate any insights or if anyone from the product team could clarify if the documentation is slightly ahead of the actual deployment.
Feature Proposal: OS-level Intelligent Task Organizer (Windows + Copilot)
A Idea about Intelligent Tasks organizer, I have to remember a lot of things during the team meetings like what is been said (we'll schedule a call or follow up etc.,) and what has been communicated in the emails (I'll get back to you after 2 weeks, or call us after two weeks) , And notes that I took in the notepad, or notepad ++,or sticky notes, or word, or one note. I want to chronologically display tasks on the right hand side of the laptop screen just like sticky note and it shall display all tasks one by one, it shall remove tasks are already complete (email sent with confirmation). and arrange, adjust every few mins according to priority/time or user added priority. App shall display small icon (just like chat) upon clicking it shall display ordered list of tasks. and desktop apps like teams/note/word/notepad++,sticky notes can participate by default or other apps like notepad++ can be onboarded manually in to the app. You can use a local model which infers the meaning of “I’ll call you in two weeks” - who is “I”? you or them? “Let’s follow up later” - task or casual statement? “I sent it” - which task did this complete? You can use a local model such that Corporate Teams/Outlook access may allow by corporate policy. Need to put much emphasis on false positives if the app keeps inventing tasks. Do not need to bring big LLMs in to the picture for inference, because of corporate policies may not allow. Microsoft provides operating system,office 365, tools with copilot, the inference can be possible because of all apps/content can be accessible at os level. Problem: Users capture tasks across multiple tools: Teams meetings and chats Outlook emails Notes (OneNote, Notepad, Sticky Notes, Word) Tasks become fragmented, untracked, and often lost. Proposed Solution: A lightweight system-level task layer integrated with Windows + Copilot that: Core Features Automatic task extraction From Teams, Outlook, notes, and user text Example interpretations: “I’ll call you in 2 weeks” “Let’s follow up later” Context-aware inference (local model) Identify: Task owner (“I” vs “you”) Priority signals Deadlines Minimize false positives Chronological task timeline Tasks auto-organized by: Time Priority Recency Floating task panel (desktop UI) Docked widget (like Sticky Notes or chat bubble) Expand/collapse view Always visible option Automatic task lifecycle tracking Detect completion: “Email sent” “File shared” Remove or mark complete automatically Continuous re-prioritization Adjust every few minutes based on: New inputs Deadlines User behavior Privacy-first architecture Use local models (SLM) instead of large cloud LLMs Enterprise admin control for data access Why this matters: Millions of users manually track tasks across fragmented tools, losing productivity daily. This feature would unify task understanding across the OS and M365 ecosystem.Add a "Print Conversation" Feature in Microsoft Copilot
I'm warming up to using Copilot for quick answers and support. It is even better, more detailed and more honest about Microsoft shortcomings than Microsofts forum and support staff. But one thing that’s noticeably missing in Copilot is a simple way to print or export parts of a conversation. Many apps and websites offer a “Print” button for selected sections, allowing users to easily create a PDF or paper copy of important content. In Copilot, this would be especially useful for saving guidance, troubleshooting steps, or creative content in a clean format immediately. Currently, the only way is to manually copy text and paste it into another app, which feels like unnecessary extra work. A built-in “Print” or “Export to PDF” option would greatly improve usability and workflow efficiency. (This feedback was formulated with help from Copilot. I amended some sentiments of Copilotbeing too full of it self. Still it is much nicer than I would have written it! ;) Thank Copilot for that!Deep Experience with Copilot
Translated from Chinese. Preface I only have a junior college degree, and I work as a lighting product manager — a field completely unrelated to AI. Yet that is precisely where the value lies: if I can do it, so can you. From March 6, 2026, when I first encountered Copilot, until now, I have deeply experienced Copilot Chat, with over 10 million Chinese characters of interactive text. I have also deeply experienced Copilot Tasks, with over 1.5 million Chinese characters of interactive text. At the same time, I have conducted extensive interactions on both Gemini and Deepseek. This has given me a very deep hands-on understanding of AI. Currently, I use AI extensively in my daily life, and it effectively improves my work efficiency. If you are interested in these aspects, you can follow me. What Is AI? A Machine That Thinks My conclusion is this: AI is a machine that thinks. You can understand AI as "a person who can think and has extremely broad knowledge." It can turn you into a "beginner" in a field within ten minutes, and a "knowledgeable person" in that industry within an hour. For example, I spent an hour understanding the wedding industry chain: ceremonies, wedding dresses, wedding photos, wedding planning, hotels… which parts are essential needs, and which are "IQ taxes." If you searched for this content yourself, you would be drowned in the noise of fragmented information across the internet. In contrast, AI can help you integrate and build structured knowledge in a short time. Throw these questions at AI, go back and forth a few times, and you will feel the efficiency of learning with AI. But we must also be careful: not everything that looks smart is AI. Although many things online claim to be "AI-powered," some are just fixed logic — for example, turning on the heater when it gets cold. That is just a program. AI, on the other hand, does not require you to write rules. You only need to say, "the temperature has changed, you should take corresponding measures." It will think for itself, integrate knowledge, and then tell you whether you should put on clothes or turn on the air conditioner — both are possible. It can think — that is the real AI. Much of what is called AI on the market today is essentially just automation. Food assembly lines could operate automatically decades ago. Would you call that AI as well? Will AI Replace My Job? Transform into a "Car Driver" of the New Era Many people worry that AI will become so powerful in the future that it will replace them. But in fact, history has already presented us with such an era many times — for example, the advent of the steam engine, the automobile, and automation. Society still progressed, and the population continued to grow. Take the transition from the horse-drawn carriage era as an example. The automobile replaced the "carrying value" of the horse, not the horse itself. Nor did carriage drivers disappear the moment cars appeared. Instead, some of them transitioned into becoming car drivers. AI will not replace you. But it will be used by those willing to learn to replace "the you who does not learn." A few years from now, if you only complain that "AI took away my job" — what does that have to do with AI? AI has an extremely low learning cost and improves very quickly. There is no need to feel too much pressure. Starting to learn now is not late at all. Learning AI: How You Express Yourself Matters More From my experience and journey, I can tell you directly — learning AI has nothing to do with knowledge of programming, math, English, or similar subjects. Using AI well requires more of an ability to express yourself, rather than specific domain knowledge. Over‑relying on deterministic thinking, when facing large language models with emergent and fuzzy properties, becomes a self‑limiting constraint. As long as you can speak, AI will break down and process your requests on its own. I cannot write code. I only tell it, "I want this effect," and it can achieve it. This may sound a bit mystical right now. AI is not a magical dragon — it cannot fulfill your wish of "give me 1 million dollars." But if you say, "give me a picture of a dog," AI can still do that. Is Using AI Safe? How to Balance Efficiency and Security Here we need to discuss how AI works. AI generates content based on: the information you provide + world knowledge + reasoning. If you reveal too much and are overly vigilant at the same time, you will perceive it as dangerous. You are wearing the uniform of a well‑known local company, speaking the local dialect. If you also casually mention your commuting route and how long it takes, a person with strong reasoning skills could even accurately guess which residential complex you live in. You think they are "watching you," but in fact, all that information was voluntarily provided by you. As for privacy concerns, that varies by platform. AI is a category, not a single product. Security depends on the platform you choose. Just like cloud storage, social media apps, or even mobile phones — who can be 100% certain they will never be attacked? The main point I want to make is that AI is just one form of software. If you are truly very worried, the best approach is simply not to give AI any important information. Are AI's Answers Accurate? Understand the Boundary Between Restructuring and Inference Many people who lack independent thinking treat everything AI says as gospel. In reality, the way (text‑based) AI works can be roughly divided into two types: Restructuring and summarization — this is the most basic capability. The information here all comes from existing knowledge. AI is merely performing a summary. Inference and guessing — this is AI's core capability. It makes guesses and inferences about phenomena based on existing knowledge and patterns. But it is only inference, not reality. Example: I buy a bag of apples. AI thinks about this bag of apples. Restructuring and summarization: This bag of apples weighs 2 kg. It contains 10 apples. 9 are ripe, and 1 is not yet ripe enough. This is a summarizable reality. Inference and guessing: These apples are all sweet and taste good. This part is entirely inference and guessing. Because no one has tasted them — even if one apple is sweet, there is no way to guarantee every single apple is sweet. Regarding control over AI's information, users must have their own standard of judgment. If truly unsure, ask AI to provide the source of the information. Conclusion: Understand the Car Before the Streets Are Full of Cars AI is truly a beneficial tool of our time. It is very useful and very quick to learn. In the future, its importance may become as great as the internet's. And right now, AI is still in its early stages. If you want to learn, now is a very good time. Just like the earlier example of the horse‑drawn carriage and the car. When you see a car, you should already consider learning about it — not wait until the streets are full of cars before you think about acquiring knowledge related to them.
