Recent Discussions
The Daily Stand-Up Agent A Custom Copilot for Summarizing Jira & Azure DevOps Progress
Modern software teams move fast. Between sprint planning, backlog grooming, pull requests, deployments, and stakeholder updates, developers often spend more time discussing work than actually doing it. One of the biggest pain points in Agile workflows is the daily stand-up meeting especially when team members need to manually summarize updates across dozens of tickets in tools like Jira and Azure DevOps. https://dellenny.com/the-daily-stand-up-agent-a-custom-copilot-for-summarizing-jira-azure-devops-progress/
Copilot Studio + SharePoint: Markdown (.md) Files in Doc Libraries Supported as Knowledge Sources?
Hi all, We’ve been doing some deeper testing with Copilot Studio agents grounded in SharePoint knowledge sources, and I’m hoping to clarify whether what we’re seeing is a known limitation or an undocumented gap. Scenario A Copilot Studio agent uses SharePoint document libraries as a knowledge source The library contains Markdown (.md) files that are intentionally used as canonical design references The same .md files: ✅ Work well when uploaded directly to the agent ❌ Are not retrievable or citable when stored in a SharePoint library and added as a SharePoint knowledge source To help with grounding, we created modern SharePoint index pages that: Explain what the markdown collections are (Patterns, ADRs, Guardrails) Link directly to the canonical folders and files Explicitly state that the .md files are the source of truth The agent can: Discover and summarize the index pages correctly Understand that .md artifacts exist and where they live But it cannot: Read the content of the individual .md files Apply a specific pattern or ADR from those files in a design conversation Cite them as sources, even when permissions and search indexing are confirmed What We’ve Checked Permissions (agent user has access) Folder depth (kept shallow) Search results (markdown files appear in SharePoint search) SharePoint indexing status Work IQ enabled Same content works when attached directly to the agent This behavior also seems consistent with what others have reported here: Markdown works when uploaded directly Markdown retrieval degrades when hosted in SharePoint libraries Questions for the Product Team / Community Are Markdown (.md) files in SharePoint document libraries officially supported as Copilot Studio knowledge sources today? If yes, are there specific constraints (file size, rendering, parsing, indexing) that differ from Word/PDF? If no (or “not yet”), is this a known limitation on the roadmap? Is the recommended pattern to: Convert important markdown files into .aspx pages, or Use thin “index / summary” pages and keep markdown canonical until retrieval improves? We’re happy to adapt our information architecture — just trying to align with the intended platform direction rather than work against it. Thanks in advance for any guidance or clarification. This capability is extremely powerful, and clearer expectations here would help a lot of teams make the right design tradeoffs.Copilot in Excel-5 Minutes to Outperform 90% of Excel Users with AI
Quick note: I'm a native Chinese speaker. This article was translated with AI assistance — but I've personally tested every step in English before publishing. What you see here works exactly as shown. Prerequisites: This tutorial requires the Copilot feature in Excel (Microsoft 365 subscription). Availability may vary by region and may require additional configuration. Following my previous two articles in the Copilot from a User's Perspective series, this is the first article in a new companion series: AI Tutorials. I'll continue updating the previous series — I just think it's important to break up the rhythm with something immediately actionable from time to time. Why did I dare use this title? I'm sure many of you think I'm exaggerating. In 5 minutes, most people can't even explain what a cross-sheet lookup is — but if you follow this tutorial today, I'm confident you'll agree with the title. If you don't believe me, start your timer now. Step 1: Open Excel and Learn the Terminology Before we start, let's make sure we speak the same language: Column — The vertical axis, labeled with letters (e.g., Column A, Column B). Row — The horizontal axis, labeled with numbers (e.g., Row 1, Row 2). Cell — A single coordinate. For example, A3 means Column A, Row 3. Range — A span from one cell to another. For example, B3:B10 means Column B, Rows 3 through 10. B3:D4 includes six cells: B3, C3, D3, B4, C4, D4. Worksheet — The tabs at the bottom of your Excel file (Sheet1, Sheet2, etc.). Each tab is a separate table. Workbook — The Excel file itself. You might be thinking: "You're starting THIS basic? No way you'll deliver on that title!" But here's the thing — if you understand these terms, you already have everything you need to use Copilot in Excel. Step 2: Create a Practice Dataset Create a new Excel file, open Copilot, and enter this prompt. Make sure to click "Allow Edits" when prompted. Create Sheet2 first with these columns: Name, Gender, Student ID, Score, Height, Class, and Commute Method. Randomly generate 30 rows of data. Make sure the Student IDs are NOT sequential numbers. Then create Sheet1: randomly pick 10 Student IDs from Sheet2 and list them in Column A. For both sheets, format the header row with a light gray fill, increase the font size by 1, and center-align. Most tutorials only teach you concepts — they never give you a dataset to practice with. Here, I just had AI generate a ready-made practice dataset so you can follow along with every step below. Now, let's get to work. Step 3: Use AI to Replace VLOOKUP VLOOKUP is the single most searched Excel function on the internet. Give me 30 seconds, and I'll make it irrelevant. With your tables ready, go to Sheet1. In the Copilot sidebar, type: Based on Column A in Sheet1, pull the values from Column D and Column E in Sheet2. That's it. You just accomplished what VLOOKUP does. Now here's where it gets interesting. VLOOKUP has a well-known limitation — it can only pull data from columns to the right of the lookup column, never to the left. Try this: Based on Column A in Sheet1, pull the values from Column A and Column B in Sheet2. If this works — and it will — you've just gone beyond what traditional VLOOKUP can do. And you never had to understand how VLOOKUP works under the hood. The prompts I used above are deliberately bare-bones. You can be much more specific: Based on Column A in Sheet1, pull the values from Column D and Column E in Sheet2. Insert these two columns before Column A in Sheet1, and fill them with a light gray background. The more Excel terminology you know, the more precise your prompts become — and the fewer errors you'll encounter. Did you notice something? Everything you just typed was nouns + logic. That is the core operating principle of generative AI. Let's keep going. Step 4: Multi-Condition Sorting Switch to Sheet2, where we have the full dataset. Sometimes you need complex sorting — Class in ascending order, Score in descending order within each class, and Student ID in ascending order within each score group. I consider myself an upper-intermediate Excel user, and I still couldn't do this manually — it requires nested sort configurations that most people never learn. But just describe what you want. In the Copilot sidebar, type: Sort the data with the following priority: Class ascending, Score descending, Student ID ascending. All three columns are sorted simultaneously, each with its own direction. If you could do this without AI, you'd already be an advanced Excel user. AI just eliminated that skill gap — and it's faster too. You might have noticed I didn't use column letter references (like "Column F") this time. In fact, I didn't need to in Step 3 either. AI can read the headers, think, and identify the right columns on its own. Step 5: Conditional Formatting Still on Sheet2. Sometimes you need visual differentiation — for example, blue highlighting for male students and pink for female students. In the Copilot sidebar, type: Fill the rows of male students with blue, and the rows of female students with pink. Without AI, I'd filter for males, apply the fill, then filter for females and repeat. That two-step process is surprisingly slow for something so simple. Sometimes you need to spot duplicates. Try: Bold the text in cells where Height values are duplicated. Without AI, this requires setting up conditional formatting rules — a skill that already puts you in intermediate-to-advanced territory. Now the sheet looks a bit messy. Let's reset: In Sheet2, reset all cells except the header row to default formatting. A Note on Prompting Style You'll notice that in Step 5, my prompts were almost entirely natural language — no column letters, no technical references. So why didn't I start the tutorial that way? Because I wanted to give you something you could copy-paste and get working immediately — something reliable and reproducible. I use natural language prompts because I've spent enough time with AI to understand its boundaries and behavior. The terminology-based approach from Step 3 is what I call "The Noun Method" — combine domain-specific nouns with natural-language logic to form complete instructions: Based on (logic) Column A (noun) pull (logic) from Sheet2 (noun) Column B (noun) and (logic) Column C (noun) Once you understand The Noun Method, you can effectively operate any generative AI tool. The key is learning the relevant nouns for each domain — and in Excel's case, there are remarkably few to learn. Closing Thoughts If you followed along with every step, the whole process probably took 10–15 minutes. But I believe that the moment you successfully ran the VLOOKUP prompt in Step 3, you stopped doubting the title. If you'd like more Excel + AI tutorials, follow me and leave a comment. I'll keep them coming. Next up: What You Need to Know About TokensThe Architecture of Copilot Agents: Building Intelligent Assistants for the Modern Era
The rapid evolution of artificial intelligence has ushered in a new class of systems often referred to as copilot agents. These agents are not fully autonomous decision-makers, nor are they passive tools they sit in the middle, augmenting human capability by assisting with tasks, providing insights, and automating workflows while keeping humans in the loop. From coding assistants to enterprise productivity tools, copilot agents are becoming foundational to how we interact with software. https://dellenny.com/the-architecture-of-copilot-agents-building-intelligent-assistants-for-the-modern-era/
Using Copilot meeting summaries for performance reviews - how?
Our HR team had this idea to use Copilot meeting recaps as input for performance reviews. Like, if a manager had 20 meetings with a direct report over the quarter, couldnt Copilot help surface key contributions and discussion themes? The problem is theres no way to aggregate multiple meeting summaries into something useful for a review. Each recap is a separate thing in each meeting. Has anyone figured out a workflow or workaround for this?
Got Copilot to use goal progress when drafting review feedback?
So I've been trying to experiment with how I use Copilot for performance management, reviews, goals, etc. When I manually feed goals, feedback results, etc into Copilot, it drafts pretty decent performance reviews. Now Im curious. Can I automatically feed these into copilot from any HR platform with API's or something? So it automatically views goal progress and drafts review feedback? I know if Viva Goals was still available, I would be able to do something along these lines. Anyone tried this?
Copilot pulling last weeks 1:1 action items into this weeks agenda, possible?
Spent 3 hours yesterday trying to get Copilot to pull open action items from last weeks 1:1 OneNote page and turn them into this weeks agenda. Gave up. Is this a prompt problem or just not possible with the current connectors?
Microsoft's Copilot: A Frustrating Flop in AI-Powered Productivity
Microsoft's Copilot was supposed to be the game-changer in productivity, but it's quickly proving to be a massive disappointment. The idea was simple: integrate AI directly into Word, Excel, PowerPoint, and other Office tools to make our lives easier. But when it comes to actually performing specific functions, Copilot falls flat. Here’s the problem: when you ask Copilot to alter a document, modify an Excel file, or adjust a PowerPoint presentation, it’s practically useless. Instead of performing the tasks as requested, it often leaves you hanging with vague suggestions or instructions. Users don't want to be told how to perform a task—they want it done. This is what an AI assistant should do: execute commands efficiently, not just offer advice. What makes this even more frustrating is that other AI tools, like ChatGPT, can handle these tasks effortlessly. When you ask ChatGPT to perform a specific function, it does so without hesitation. It’s able to understand the request and deliver exactly what’s needed. But Copilot? It struggles with the basics, and that’s unacceptable, especially from a company like Microsoft. It’s frankly embarrassing that Microsoft can’t get this right. The whole point of integrating AI into these tools was to streamline workflows and boost productivity. But if Copilot can’t even manage simple tasks like formatting a document or adjusting a spreadsheet, then what’s the point? Users don’t need another tool that tells them how to do something—they need one that does it for them. Microsoft, you’ve missed the mark with Copilot. It's not just a minor inconvenience; it's a serious flaw that undermines the value of your Office suite. When other AI tools can easily accomplish what Copilot can't, it's time to reevaluate. Users expect more, and frankly, they deserve more for their investment. What’s been your experience with Copilot? Is anyone else finding it as frustrating as I am? Let’s talk about it.Automating the feedback collection process before reviews. Is it possible with Copilot?
Every quarter, our HR team manually emails people asking for peer feedback before reviews start. Its a huge time sink and half the responses come in late. Someone mentioned Copilot agents might be able to handle this, like automatically reaching out to the right people, collecting responses, and organizing them. Has anyone tried building something like this? Or is there a simpler way to automate 360 feedback collection in M365?
Copilot won't edit text in existing oneNote Page
Hey All, I have tried the following in both the OneNote desktop app and the OneNote O365 web app. Both fail in the way described below. I have a oneNote page that I use for time tracking on projects. I asked oneNote to edit all listings of the date in one section to 2026-05-05. Copilot states that it is starting, but then quickly transitions to a blank white box. The copilot box remains completely empty. It is unresponsive for 10 minutes. Eventually, I can click the copilot button in the menu bar and close copilot -- if I try do this right away, nothing happens. Please let me know if there is some setting or something that I need to enable, so that copilot can edit oneNoteMicrosoft 365 Copilot Gets Smarter: GPT-5.5 Thinking and ChatGPT Images 2.0 Transform Workflows
The evolution of workplace AI is accelerating, and the latest update to Microsoft 365 Copilot signals a major leap forward. With the introduction of GPT-5.5 Thinking and ChatGPT Images 2.0, Copilot is no longer just an assistant it’s becoming a more capable collaborator for complex thinking, creative production, and multi-step problem-solving. https://dellenny.com/microsoft-365-copilot-gets-smarter-gpt-5-5-thinking-and-chatgpt-images-2-0-transform-workflows/Microsoft Launches Agent 365 to Bring Control, Security, and Visibility to the Age of AI Agents
In a move that signals how rapidly artificial intelligence is reshaping the modern workplace, Microsoft has officially announced the general availability of Agent 365, a new platform designed to help organizations manage, secure, and govern AI-powered agents at scale. https://dellenny.com/microsoft-launches-agent-365-to-bring-control-security-and-visibility-to-the-age-of-ai-agents/
All scheduled prompts failing — "couldn't be completed" error — Power Platform provisioning issue?
I'm hoping someone from Microsoft or the community has seen this. All my scheduled prompts are failing at execution time with this error: "This scheduled prompt couldn't be completed. It will be retried during the next scheduled run." Key facts: M365 Copilot license on a direct Business subscription The same prompts run correctly in Copilot Chat Even the simplest scheduled prompt fails: "List emails I received in the past 5 days. No analysis needed — just the list." The scheduling UI works fine — prompts appear in the Active list with correct schedules Failure is at execution time. Retries also fail. Admin-side investigation already completed: Power Platform environment: Ready No DLP policies in the tenant No admin toggle for scheduled prompts exists in M365 admin center (noted as unusual) Org-level optional connected experiences: enabled User-level optional connected experiences toggle absent (consistent with org locking it On) The absence of an admin toggle for scheduled prompts in the M365 admin center is the one thing that stood out — I wonder if this indicates the feature wasn't fully provisioned when the Copilot license was applied. Sharing here in case this is a known issue or others are experiencing the same. Any insight from Microsoft engineers or others who've resolved this would be appreciated.
Apologies for repeated prompts – account works but restricted / Cuenta ok pero restringida
Hola, mi cuenta fue marcada por una infracción de “Abuso de la plataforma” en M365 Copilot. Ya verifiqué con soporte de inicio de sesión y confirmaron que no hay problemas con mi cuenta. Sin embargo, sigo experimentando errores y desconexiones al usar Copilot. ¿Alguien del equipo de Microsoft puede ayudarme a revisar este bloqueo o indicarme cómo apelar la restricción? Este problema me impide usar Copilot con normalidad. Utilicé un promt una y otra vez intentado hacer una gráfica de pastel y la IA estuvo "alucinando" datos. Intenté tanto que me enojé. Me disculpo. Gracias. Hello, My account was flagged for a “Platform abuse” violation in M365 Copilot. I have already contacted sign-in support, and they confirmed that there are no issues with my account. However, I am still experiencing errors and disconnections when using Copilot. Could someone from the Microsoft team help review this restriction or guide me on how to appeal it? This issue is preventing me from using Copilot normally. I used a prompt over and over trying to make a pie chart and the AI was 'hallucinating' data. I tried so much that I got angry. I apologize. Thank you. Puedes responder en inglés o español, gracias. | You can respond in English or Spanish, thank you.
CoPilot Agent for copying and renaming Excel spreadsheets
Hi- Does CoPilot have the functionality to build copying and renaming Excel spreadsheets into an agent? I want to design an agent to take an excel file and copy the contents into another spreadsheet by use of a CoPilot prompt. These files would be resident in a Teams channel.How Project Managers Can Automate Weekly Reporting with Copilot
Weekly reporting has long been a necessary burden for project managers. It’s repetitive, detail-heavy, and often done under time pressure—usually at the end of the week when energy is already low. But with the rise of AI-powered assistants like Microsoft Copilot, the way project managers handle reporting is rapidly changing. https://dellenny.com/how-project-managers-can-automate-weekly-reporting-with-copilot/Is the Copilot model picker available in Word for the Microsoft 365 Premium (Individual) plan?
Hello, I would like to confirm whether the Copilot model picker is available in Microsoft Word for subscribers of the Microsoft 365 Premium Individual plan. Specifically, I am referring to the feature that allows users to switch between different AI models, such as: - Claude Opus 4.7 - GPT-5.5
M365 Copilot Agents – Credit Consumption Clarification
Scenario 1: User with M365 Copilot license creates an agent inside M365 Copilot app and uses it himself. However, it still consumes Copilot credits from the Copilot capacity pack in Power Platform. When does this happen? Which actions trigger credit usage? As per the documentation, this should not consume credits: https://learn.microsoft.com/en-us/microsoft-copilot-studio/requirements-messages-management#copilot-credits-billing-rates Scenario 2: User with M365 Copilot license creates an agent inside M365 Copilot app and shares it with a user who does not have a Copilot license. Will all interactions from the unlicensed user consume credits? Trying to clearly understand the boundary between included usage vs metered (credit-based) usage.Copilot from a User's Perspective #2 — Types of Copilot and How to Choose
I'm a native Chinese speaker, and my English isn't strong enough to write an entire article from scratch. So I had Copilot Tasks translate this piece for me. If you find it reads smoothly — well, that's a testament to what Tasks can do. This is the second article in my Copilot from a User's Perspective series, focusing on the different types of Copilot. After reading the first article, if Copilot caught your interest, you're probably wondering: with so many Copilots everywhere, what's the difference between them? Are they actually useful? Are they really worth your time? By the end of this article, you should have a much clearer picture of how to think about the different Copilot experiences. There are a LOT of Copilot variants out there. I first started using Copilot on March 6th, and since then I've tried virtually every Copilot experience available to me (I'm a Microsoft 365 Premium subscriber). As of May 1st, my conversations have exceeded 9 million Chinese characters（including both my inputs and AI responses across all Copilot surfaces）. So I'll take the liberty of offering my own user-perspective classification of the current Copilot landscape. I believe the AI tools we regularly interact with can be broadly divided into four categories: Chat AI, Tool AI, Search Engine AI, and Agent AI. In my view, AI's core value lies in working alongside humans to boost productivity — and that's the lens through which I built this classification. One important caveat: due to account permissions and the nature of my work, I haven't had the chance to try the Windows system sidebar Copilot, GitHub Copilot, or Copilot Studio. Quick Analogies Before diving in, here's how I think about each type: • Chat AI — A knowledgeable, quick-thinking colleague who's a bit too talkative and not great at actually doing things. Great for brainstorming, but the moment hands-on work is needed, they vanish. • Tool AI — The notebook, sketchpad, and toolbox sitting on your desk. Specialized for specific tasks, with minimal conversation ability. • Search Engine AI — A filing cabinet that organizes your scattered documents so you can find things faster. • Agent AI — The most powerful and practical of all. A knowledgeable, sharp-thinking assistant who doesn't ramble and can actually get things done for you. Chat AI Where you'll find it: Web-based Copilot (copilot.microsoft.com), Edge sidebar Copilot, and the chat panels within M365 apps. What it does: This is the most popular, most accessible, and lowest-barrier type of AI. Chat AI typically can't take action on its own — the most it can do is generate images for you (though M365 Copilot Chat can also create files in Microsoft formats like Word documents and PowerPoint presentations). But don't underestimate it. You can ask it to check the weather, or have it research topics across the web — for example: "What are the most popular conversational AI tools on the market right now, and how are they reviewed?" My take: I've settled on the web-based Copilot as my primary chat AI. In my experience, M365 Copilot feels narrower in its reasoning — its responses are more conservative and contained, while the web version is more open and expansive. You can clearly sense they come from different design philosophies. One notable thing about M365 Copilot is that it integrates your conversation history across all M365 tools, suggesting that all the chat experiences within M365 share the same underlying foundation. Tool AI Where you'll find it: Copilot embedded in Excel, PowerPoint, Word, and other M365 applications. What it does: This type of AI is far more powerful than you'd expect. How much value you get from it depends entirely on how well you understand the underlying tools and how creatively you use the AI within them. With Copilot's help, my Excel productivity has improved by at least 70%. I'll dedicate an upcoming article specifically to using Copilot in Excel. My take: Incredibly powerful and massively underestimated. Stay tuned — I'll be showing you how to use these in future articles. Search Engine AI Where you'll find it: Copilot integrated into Edge's search experience (Bing AI). What it does: Its primary function is summarizing your search results. You might not even notice it's there, because it doesn't present itself as a conversation — it simply provides a summary alongside your results. You think you haven't given it any instructions, but the moment you type something into the search bar and hit Enter, it's already at work. There's not much to choose here — search engine AI is tied directly to your browser. Nobody switches browsers just for an AI summary feature, and the quality of its output depends entirely on what it finds. If the search results are noisy, the summary will be noisy too. So don't overthink this one — and certainly don't abandon a browser you're comfortable with just because a competitor added this feature. My take: The good news is that search engine AI is usually free — it's essentially a feature enhancement that search engines build into their browsers. That said, some AI-native search engines like Perplexity offer a noticeably better experience. Overall, this is a category where we can sit back, let the companies compete, and enjoy the improvements. Agent AI Where you'll find it: Copilot Tasks (on web-based Copilot) and Office Agents (in M365 Copilot). What it does: This type of AI goes far beyond a chat window. It connects to your email, calendar, browser, cloud storage, and other tools. Think of it as an AI that doesn't just talk with you — it takes action. Tell it "Check my meeting schedule for tomorrow and send a reminder email to my colleagues," and it will open your calendar, draft the email, and send it — instead of handing you a block of text and leaving you to do the work yourself. Tasks can even run in the background. Close the page and go about your day — it will notify you when it's done. For example, I've set up Copilot Tasks to automatically compile and send a daily report (with content I define) and to gather competitive analysis based on my requirements. That said, today's agent AI is more like an intern you need to keep an eye on than a seasoned employee you can fully trust. But even so, it's a massive leap forward from chat AI — at least it's willing to roll up its sleeves. My take: Choosing an agent AI is much more complex than choosing a chat AI, because an agent's core value isn't about how well it talks — it's about what it can connect to and what it can do. Agent AI is the category most worth learning about right now. Tool AI excels at specific points; agent AI covers the entire surface (though in certain vertical domains, tool AI may still deliver a better experience). It's the only category that's genuinely changing how humans and AI work together. This category is still young, and the experience isn't fully polished yet. When choosing, don't focus on which one feels the most mature — focus on which one fits your workflow. Even if someone told me Google's AI experience is the best, I still wouldn't abandon my Microsoft ecosystem. Closing Thoughts These are the four types of AI tools as I see them from a user's perspective. Chat AI is the quickest to try. Tool AI gives you the most tangible sense of how AI is changing the way we work. But if you're willing to invest time in learning and adapting, agent AI can deliver productivity gains that the other three categories simply can't match. I'll also be publishing a Tasks guide in the future (assuming you have access to it). Trust me — you'll be amazed at what Tasks can do. Next up: AI Tutorial — Surpass 90% of Excel Users in 5 MinutesAll scheduled prompts failing — "couldn't be completed" error — Power Platform provisioning issue?
I'm hoping someone from Microsoft or the community has seen this. All my scheduled prompts are failing at execution time with this error: "This scheduled prompt couldn't be completed. It will be retried during the next scheduled run." Key facts: M365 Copilot license on a direct Business subscription The same prompts run correctly in Copilot Chat Even the simplest scheduled prompt fails: "List emails I received in the past 5 days. No analysis needed — just the list." The scheduling UI works fine — prompts appear in the Active list with correct schedules Failure is at execution time. Retries also fail. Admin-side investigation already completed: Power Platform environment: Ready No DLP policies in the tenant No admin toggle for scheduled prompts exists in M365 admin center (noted as unusual) Org-level optional connected experiences: enabled User-level optional connected experiences toggle absent (consistent with org locking it On) The absence of an admin toggle for scheduled prompts in the M365 admin center is the one thing that stood out — I wonder if this indicates the feature wasn't fully provisioned when the Copilot license was applied. Sharing here in case this is a known issue or others are experiencing the same. Any insight from Microsoft engineers or others who've resolved this would be appreciated. I am a small business teaching copilot and we are supposed to demo scheduled prompts on Monday and the failure of over 25 scheduled prompts over the past four days isn't a great sign.
Recent Blogs
- OpenAI's latest model—GPT-5.5 Instant is now available in Microsoft Copilot Studio and is rolling out to Copilot Chat experiences.May 07, 2026
- Two new features help get the most relevant, important agent metrics to the right people with the right level of access.May 05, 2026
