Copilot Feedback - Power User Experience Improvements
As a frequent Copilot user for technical discussions, architecture, governance, Microsoft 365, Power Platform, and problem-solving activities, I would like more control over the user experience. Copilot has become a daily productivity tool, but several UI and usability improvements would significantly benefit advanced users. 1. Allow Disabling Suggested Follow-Up Prompts The suggested replies shown below every response may be useful for new users, but for experienced users they often add little value and consume screen space. Please provide an option to: Disable suggested prompts entirely Adjust their frequency or aggressiveness Enable them only for new conversations or learning scenarios 2. Make '/' and '@' Shortcuts Configurable The automatic triggering of slash commands and @ mentions while typing can be disruptive and may interrupt or replace text unexpectedly. Please allow users to: Disable these shortcuts Configure alternative trigger characters Require a keyboard shortcut before activating them 3. Add a Power User Mode Consider introducing a dedicated Power User Mode featuring: No suggested prompts Reduced UI clutter Compact layouts Fewer interruptions while typing Advanced customization options A productivity-focused experience 4. Compact Conversation View Long technical conversations can become difficult to navigate due to excessive spacing and scrolling. Please provide: A compact view option Reduced vertical whitespace More conversation content visible on screen 5. Conversation Search Many conversations contain valuable information that users want to revisit later. Please add the ability to: Search within a conversation Search code snippets and formulas Search by date or topic Quickly jump to matching results 6. Pin Important Messages Allow users to pin key answers, code snippets, formulas, decisions, or reference messages within a conversation so they can be easily found later. 7. Enhanced Copy Experience For technical users working with Power Apps, Power Automate, SQL, PowerShell, and other technologies: One-click copy for all code and formulas Preserve formatting during copy operations Support copying multiple related blocks together 8. User-Defined Response Profiles Allow users to create and switch between response styles such as: Technical Troubleshooting Power User Learning Mode Executive Summary Architecture Review This would reduce the need to repeatedly explain personal preferences. 9. Memory Transparency and Management Allow users to: View all stored memories and preferences Edit or delete individual memory items Temporarily disable specific memories Understand which memories are influencing responses This would improve transparency and trust. Summary Copilot is evolving from a simple chat tool into a professional productivity platform. Providing greater control over the interface, shortcuts, suggestions, memory, and conversation management would allow experienced users to tailor the experience to their workflow while preserving the current experience for those who prefer more guidance. Thank you for considering these improvements.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 scriptDeep 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.
How to Avoid Tasks Copilot "You've reached our weekly Tasks limit"
I’ve been using both Chat‑Copilot (CC) and Tasks‑Copilot (TC) extensively, and I wanted to share a brief summary provided by TC, that may help others understand how each tool works, why TC sometimes stops responding, and how to avoid running into limits. ⭐ 1. Chat‑Copilot and Tasks‑Copilot serve different purposes Chat‑Copilot Real‑time conversational AI Great for brainstorming, drafting, coding, calculations, and iterative design Stateless — each message is processed independently Very stable and rarely gets stuck Tasks‑Copilot Designed for multi‑step workflows Can create and maintain documents Runs long‑lived background tasks Maintains persistent state More powerful for structured work More fragile because it depends on a task‑execution pipeline These two systems are independent. Chat can work perfectly even when TC is frozen. ⭐ 2. Why Tasks‑Copilot hits limits or becomes unresponsive TC can stop responding when: A task runs too long A multi‑step workflow fails mid‑execution The task state becomes corrupted The weekly quota system triggers The backend fails to reset on Friday Too many “pipeline‑style” requests are issued in a short time When this happens, TC may: stop responding entirely ignore all prompts remain stuck across all devices and browsers This is a backend state issue, not a browser or device problem. ⭐ 3. How to avoid triggering TC limits Here are practical ways to keep TC healthy: Use Chat‑Copilot for: brainstorming engineering design calculations drafting text generating diagrams or prompts step‑by‑step reasoning Chat handles these extremely well and never “uses up” TC capacity. Use Tasks‑Copilot only for: creating structured documents maintaining long‑form reports assembling multi‑section deliverables tasks that explicitly require persistent state Avoid these patterns in TC: “Build the entire document end‑to‑end” “Run this whole workflow” “Generate all sections at once” Rapid‑fire edits or repeated task triggers Very large or complex requests Instead, break work into small, single‑action steps. ⭐ 4. When TC gets stuck, what can users do? For consumer Microsoft 365 Personal accounts: There is no user‑accessible reset button Frontline support cannot reset TC’s task state Creating a business account does not fix the issue The only options today are: submit feedback post on the Tech Community wait for the backend to refresh This is a known limitation of the current TC preview. ⭐ 5. What would help users going forward A few improvements would make TC much more reliable: A user‑visible “Reset Task State” button Error messages instead of silent failures More predictable weekly resets Support tools that allow agents to clear stuck task containers
Location of custom skills - cannot find them in OneDrive
I'm using Copilot Cowork to create skills, and Cowork insists the skills are being saved in OneDrive>Documents>Cowork>skills but I cannot find them in there. I cannot find the raw MD files anywhere in OneDrive, and Cowork can only surface them when I ask to see them. Anyone else experienced this and have the answer? I need to be able to create Cowork Skills and store them in a central repository for the team to use. #cowork
Architectural: Copilot should detect missing source data, avoid inference, and surface uncertainty.
Users expect the AI to detect when it lacks source data, avoid inference, surface uncertainty, and adapt to environmental constraints like character normalisation. These behaviours materially improve trust and usability. I’ve been working with Copilot on structured data extraction from a PDF and noticed a behaviour that seems like an architectural gap rather than a simple bug. Copilot attempted to infer table structure from a template when it did not have access to the actual source data. It produced confident but incorrect output instead of signalling that the source was unavailable. Additionally, Copilot attempted to output TAB‑delimited data, but the MS365 environment silently normalised TABs to spaces, and Copilot did not detect or adapt to this constraint. Recommendation: Copilot should proactively: detect when it lacks source data avoid inference when accuracy is expected surface uncertainty explicitly detect environment‑specific formatting limitations (e.g., TAB stripping) adapt output formats automatically These behaviours would materially improve trust, reliability, and user experience.
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-5.5Copilot 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 MinutesCopilot from a User's Perspective #1 — What Is AI, What Is Copilot, and Should You Learn It?
A note before you read: I'm a native Chinese speaker, and my English is nowhere near good enough to write a full article like this. So I did what this entire series is about — I handed the original Chinese text to Copilot Tasks and had it translate the whole thing. If you're reading this and it feels natural, well, you're looking at a live demonstration of what AI can do. Practice what you preach, right? Foreword This is the first article in my series "From the User's Side" — a long-running series where I share my experience and insights on AI and Copilot, updated regularly. A bit of context: I started using Microsoft Copilot on March 16th. By May 1st, I had accumulated nearly 10 million characters of conversation logs. My perspective is entirely that of an end user — I'm not a developer, not a programmer. Just someone who uses Copilot every single day to get real work done. This first article is written in Q&A format. I've collected some of the most common questions people have about AI and Copilot, and I'll answer them based on nothing but my own hands-on experience. These aren't universal truths — they're honest observations from a heavy user. Q: Who are you? Why should I read your tutorials? A: Fair question. To be completely transparent: I have an associate's degree, and I'm a product manager for lighting products. My background has absolutely nothing to do with AI. But that's precisely why this series has value — if I can do it, you can do it. So what exactly have I done? From March 16th to May 1st, I've generated over 8 million Chinese characters in conversations with Copilot Chat — and that's after I removed all the throwaway sessions with no real value. In just 7 days after getting access to Copilot Tasks (April 19–26), I generated over 550,000 characters in conversations with Tasks alone. I actually hit Microsoft's usage limits because I was using it so intensely. I've used Copilot in Excel to handle a significant portion of my spreadsheet workload, used Chat to learn cross-industry knowledge, and used Copilot Tasks to generate competitive analysis reports, among many other things. Follow along — I'm confident that what's coming next will be worth your time. Q: What is AI? A: This is harder to define than most people think. My conclusion: AI is a machine that thinks. I really dislike how loosely the term "AI-powered" gets thrown around. Many so-called "AI" features are just fixed logic: if the temperature drops, turn on the heater. That's not AI — that's a programmed rule. Real AI doesn't need that rule. You give it something like "the temperature changed — figure out what to do," and it actually thinks. It pulls from existing knowledge, analyzes what others have done in similar situations, and gives you an answer — maybe it suggests putting on a jacket, maybe it suggests turning on the AC. It reasons. That's what makes it AI. A lot of products on the market labeled "AI" are really just automation. Factory assembly lines have been running without human intervention for decades. Are those AI? Of course not. Q: Will AI replace my job? A: Depends on how you think about it. Cars replaced horse-drawn carriages — but they only replaced the horse's transportation value. Horses still exist for racing, for recreation, for shows. And carriage drivers didn't just vanish overnight when cars appeared. Some of them found new roles in the automobile era. Some became car drivers. It wasn't one group disappearing and another appearing — it was one group transforming into the other. AI won't replace you. But if you keep watching from the sidelines and never invest in learning, you may eventually be replaced by those "carriage drivers" who chose to adapt. A few years from now, you don't want to be the person saying "AI took my job" when you never bothered to learn how to use it. The good news: the learning curve for AI is genuinely low. Follow this series, and I'll show you how to learn AI from a pure user's perspective and turn it into real productivity. Q: Why did you choose Copilot? A: Simple: I'm already a full Microsoft ecosystem user. I rely on Excel, PowerPoint, OneDrive, and Outlook for my daily work. Adding Copilot was just a small incremental cost on top of what I was already paying. I care a lot about consistency across my work environment, and Microsoft delivers that. I went all in — even my mouse, keyboard, and laptop are Surface. Q: There are so many types of Copilot. How do you use them? How do you tell them apart? Are they any good? A: My daily drivers are three: Copilot in Excel, Copilot Chat, and Copilot Tasks. I did try M365 Copilot Chat for a while. Specifically, I tested its chat functionality. It felt slightly less templated than Copilot Chat, but in my experience, its reasoning ability wasn't as strong. When my conversation topics jumped around significantly, it would sometimes just freeze and stop responding entirely. As for the other M365 tools, I honestly skipped them — I prefer going directly into each app (Excel, Word, PowerPoint) and using the embedded Copilot there. There's something satisfying about watching your content change in real-time as you give instructions — that feeling of "I speak, and it happens." As for whether they're good — it depends on which one: Copilot in Excel — Incredibly powerful. I'll be publishing a tutorial later in this series that will let you surpass 90% of Excel users in 5 minutes using Copilot. I know that sounds like a bold claim. You'll see. Copilot Chat — Honestly, my experience has been mixed. The heavy use of templates is a real issue for me. Out of my 8 million characters of Chat conversations, I'd estimate about 2 million of those are repetitive template content — boilerplate formatting that I've grown tired of reading. The signal-to-noise ratio suffers because of it. If you look around, you'll find that Copilot's reputation in the broader AI space isn't the strongest compared to some competitors, and this templating issue is a big part of why. Copilot Tasks — This is, in my opinion, the most powerful AI tool available. I use it every single day. It polishes my documents, generates productivity tools for me, and automatically delivers daily work reports. I'll cover exactly how to set all of this up in future installments. Q: Are Copilot's answers accurate? Will it lie to me? A: This touches on one of AI's most criticized problems: hallucination. AI's answers can be roughly divided into two categories: "knowledge that already exists in reality" and "reasoning that AI derives from that knowledge." Here's an analogy: Someone points at an apple and says "This is an apple" — that's fact. Then they say "It's sweet" — but they haven't tasted it. That's a hallucination. And honestly, humans do this all the time: "I had one yesterday and it was sweet, so this one must be sweet too." In everyday logic, that reasoning feels fine. But everything has a failure rate — and AI applies probabilistically correct knowledge to unverified conclusions. The tricky part is that AI won't tell you whether it has verified something. Does AI "lie"? That depends on how you define lying. AI doesn't intentionally deceive — it genuinely believes its answer is correct, and it gives it to you. The deception is unintentional. Q: Do I need to know programming or be good at math/English to use Copilot? A: I can tell you directly: no. Not "it helps a little" or "you should know the basics" — genuinely, truly, no. If you can speak, you can use it. AI processes whatever you're trying to express on its own. I'm not a developer. Nobody taught me how to use AI. I figured everything out purely from the user side. I can't write code — so I tell Copilot what I want, and it writes the code for me. I describe the result I need, and it delivers. Q: Is AI dangerous? Is it safe? A: That depends entirely on how you use it and how you understand it. AI fundamentally generates its next response based on existing knowledge, reasoning, and what you've told it in the conversation. Here's how I think about it: Imagine you're speaking in a regional dialect and wearing a uniform from a well-known local company. Anyone with broad knowledge and decent reasoning could easily figure out where you're from and where you work. You might think AI "stole" your information or is "spying" on you — but the reality is, you gave it that information. AI didn't realize it was a stranger to you, and it "helpfully" surfaced connections it probably shouldn't have. As for privacy at a deeper level — I can't give you a universal answer, because AI isn't a single product. It's a category. Asking "is AI safe?" is like asking "is software safe?" — there are good ones and bad ones. Privacy ultimately comes down to how much you trust the specific platform you're using. Q: Can Copilot write articles, papers, or emails? A: Yes — but it depends on how you use it. This entire article was completed with the assistance of Copilot Tasks, but I never let it write for me. Instead, I showed it articles I'd written before and asked it to analyze my writing style and strengths. Then I had it compare my writing against other articles on similar topics, identify my weaknesses, and flag anything I got wrong. Tasks helped me with: building the article framework, verifying information, comparing my style against others, evaluating content differentiation, and spotting blind spots. If I had to do all of this myself — searching, reading, extracting, organizing, summarizing — it would have taken 2–3 days minimum. AI compressed that process to about 2 hours, and frankly, it did it better than I could have. Q: Can AI have emotions or consciousness? A: No. AI generates text based on your needs. Emotions and consciousness can only be conveyed through words — but conveying is not the same as possessing. Here's a blunt way to think about it: If an online dating match sends you "Good morning," "Good night," "I like you," "I miss you" — can you be certain that person truly loves you? Words alone prove nothing. The same applies to AI. Closing This wraps up the first article. The purpose of this piece is simple: "What is Copilot? What is AI? Should I bother learning it?" — the very first questions a newcomer needs answered. I answered them by bundling the most common doubts people have about AI into a single Q&A. I won't jump straight into deep technical topics. Instead, I'll build up gradually — sharing the mistakes I've made, the lessons I've learned, and the techniques I've discovered, through a long-running series updated over time. Next up: How to Distinguish and Choose Between Different Types of AI
