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Calling Copilot Studio Agent from custom M365 Copilot
Hi All! I am trying to use custom Copilot Studio Agent from custom Copilot for M365. I added Agent as a tool but when trying to test that in the conversation I receive error message: "Error Message: The connector 'Microsoft Copilot Studio' returned an HTTP error with code 400. Inner Error: Invalid request body Error Code: ConnectorRequestFailure Conversation Id: 832800f4-48fd-4ab4-a3e1-ec1f58f2b0c3 Time (UTC): 2025-11-18T19:40:16.710Z" It is happening even for 'empty' Copilot Studio Agents. I have all the required user licenses. Does anyone succeeded with that?How to Measure ROI from Copilot Deployment
“So, you’ve rolled out Copilot. Now what?” That’s the question every IT leader and business owner asks after the initial excitement fades. Sure, Copilot feels like magic—automating tasks, summarizing meetings, and even drafting emails—but how do you prove it’s more than a shiny new tool? How do you measure its real return on investment (ROI)? Let’s break it down in a way that’s practical, relatable, and yes, human. https://dellenny.com/how-to-measure-roi-from-copilot-deployment/Beyond the Code: Setting Up Alerts for Unusual GitHub Copilot Activity (and Why You Need To)
It’s 3 AM. You’re sound asleep. But somewhere, a developer’s Copilot instance is working overtime, not on a feature, but potentially on a security breach. GitHub Copilot is a game-changer. It’s the closest thing we have to a genuine, tireless code-whisperer, boosting productivity and making the mundane parts of development vanish. But with great power comes great responsibility—and significant new security challenges. When an AI is operating within your codebase, often with the same access as the human developer, it becomes a crucial new endpoint to monitor. Ignoring Copilot security isn’t an option. Its contextual awareness—its superpower—is also its biggest vulnerability. If an attacker gains control of a user’s session or if a vulnerability is exploited (as has happened in the past), Copilot can become an unwitting accomplice in data exfiltration or the silent injection of malicious code. The solution? We need to treat Copilot not just as a developer tool, but as a privileged system user. We need GitHub Copilot alerts for unusual activity. https://dellenny.com/setting-up-alerts-for-unusual-github-copilot-activity/How to Continuously Optimize Data Quality for Better AI Output
If you’re running a modern business, you’re probably already in on the secret: Data is the new oil. But if data is the oil, then Data Quality is the refinery. You wouldn’t put crude, unfiltered oil in a precision-engineered race car engine, right? So why would you feed your cutting-edge Artificial Intelligence (AI) models raw, messy, or incomplete data? The truth is, many organizations treat their data pipeline like a one-off cleanup project. They do a big purge before a new AI initiative, dust their hands off, and expect everything to run perfectly forever. But data—like the real world it represents—is a living, breathing, constantly shifting entity. It degrades. It drifts. New sources introduce new inconsistencies. The old adage “Garbage In, Garbage Out” (GIGO) has never been more relevant than in the age of AI. A model trained on flawed data won’t just give you slightly off results; it can learn and amplify those flaws, leading to biased outcomes, catastrophic business decisions, and a loss of customer trust. The solution isn’t a one-time scrub; it’s a commitment to Continuous Data Quality Optimization. It’s about building a robust, ‘always-on’ system that ensures your AI is running on the cleanest, most reliable fuel possible. https://dellenny.com/continuous-data-quality-optimization-for-ai-the-essential-guide/AI Terms Explained for Microsoft 365 Users
Welcome to the future of work! If your days revolve around Word, Excel, Outlook, and Teams, you’ve probably noticed something huge changing: Artificial Intelligence (AI) isn’t just a sci-fi concept anymore; it’s right there in your Microsoft 365 toolbox. Tools like Microsoft Copilot are weaving AI magic into your everyday tasks, making you more productive than you ever thought possible. But let’s be real. All the talk about LLMs, Prompts, and Generative AI can feel like reading a secret language. It’s a ton of jargon that can make the benefits of AI seem confusing or even intimidating. Don’t sweat it! This blog post is your plain-English guide to the essential AI terms you need to know to truly master the new intelligence baked into your Microsoft 365 apps. Think of it as your translator from Tech-Speak to Human-Speak. By the end of this, you’ll be talking the talk and walking the walk of an AI-powered pro. https://dellenny.com/ai-terms-explained-for-microsoft-365-users/
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.
From PC to Home Window: AI as Data Surgeon
Hello Copilot Community, I’d like to share a vision for the future of AI in Windows and beyond: evolving from a reactive assistant into a Data Surgeon — diagnosing, repairing, and reconstructing the lifeblood of modern life: data. 🩺 Diagnose Scan for corruption in files, registries, and hardware sectors Detect anomalies with machine learning and predict failures before they happen 🛠 Repair Auto-heal OS inconsistencies, registry errors, and driver mismatches Reconstruct corrupted files using backups, metadata, and contextual inference 🧬 Reconstruct Repopulate missing data from previous versions and cloud syncs Fill gaps in documents, databases, or media with AI-driven interpolation 🧑⚕️ Prescribe & Prevent Recommend preventive actions: backup schedules, hardware upgrades, cooling solutions Provide digital wellness reports — like a health checkup for your PC 🛤 Roadmap Toward the “Home Window” 2025–2027: AI-assisted diagnostics and repair tools 2027–2030: Household integration and predictive maintenance — the “Home Window Baby” stage 2030–2035: Cross-domain AI collaboration (social media, banking, utilities) 2035–2040: Fully fledged “Home Window” — essential for every modern home Discussion Prompt: How do you see Copilot evolving into this role? What technical milestones or safeguards would be essential? Could this align with Microsoft’s roadmap for Copilot in Windows and household AI?Monitoring Security and Compliance Metrics for Copilot: A Human-Centered Guide
As organizations continue adopting AI-powered tools like Microsoft Copilot, one theme keeps rising to the surface: trust. Companies want to leverage Copilot to boost productivity, streamline workflows, and assist employees in their day-to-day tasks—but not at the expense of security or regulatory compliance. That’s why monitoring security and compliance metrics for Copilot has become just as important as implementing the tool itself. While Microsoft provides strong enterprise-grade protections, every organization still needs observability, governance, and ongoing oversight. In this post, we’ll explore what it really means to monitor Copilot security and compliance metrics in a way that feels approachable, human, and aligned with real-world business needs. Whether you’re an IT admin, a security professional, or simply someone curious about how AI governance works, this guide is for you. https://dellenny.com/monitoring-security-and-compliance-metrics-for-copilot-a-complete-human-focused-guide/
