Optimizing GitHub Copilot for Better Results

Is your workflow ready for Agentic Mode? 🚀💻 The era of simple autocomplete is over. We’re moving into the age of Vibe Coding, where the focus shifts from writing syntax to directing intent. I’m excited to share a major new resource for the developer community: "Vibe Coding with GitHub Copilot" by Fransesco Malila. This book is a deep dive into the full GitHub ecosystem, showing you how to move beyond basic chat and master Agent Mode for autonomous task execution. What makes this guide stand out: ✅ Mastering multi-file Edits and Agent Mode. ✅ Using MCP (Model Context Protocol) to extend Copilot to your databases. ✅ Deep integration with GitHub Actions, Security, and Codespaces. ✅ Honest comparisons with tools like Cursor and Claude Code. Whether you are a seasoned engineer or just starting out, this is the manual for the next generation of software development. Check it out here: https://a.co/d/051OOQFG #VibeCoding #GitHubCopilot #AIPairProgramming #SoftwareEngineering #DevOps #GitHub #TechInnovation #FransescoMalila

Typed “hi” into GitHub Copilot Chat inside VSCode and the logs were eye-opening. That tiny greeting triggered a request carrying ~18,000 prompt tokens. Not because “hi” is expensive — because context is. Even simple prompts can include a large background payload such as: • Tool definitions — what the assistant can access (search, edit, terminal, git, notebooks, etc.) • Instruction layers — rules for how the agent should behave • Project context — workspace structure and relevant files • Active focus — open tabs, selected code, current editor state • Memory/state — prior chat history, preferences, session context Different products implement this differently, but the pattern is consistent. Some tips on keeping context efficient: • We tend to accumulate tools over time. Periodically audit them and keep only high-value tools always enabled. • Use Skills, since they are invoked only when relevant instead of staying always-on • Keep your workspace focused when asking questions Every token saved can create more room for useful context. 🙂 #GitHub #Copilot #VSCode #AI #Assistant #Coding #DeveloperTools #LLM #GenAI

I reported a bug to GitHub. They fixed it in 2 days—then revamped their entire extension system. Here's what happened: While using GitHub Copilot CLI's extension system, I discovered a critical issue: creating a hook in an extension would override all global hooks. This broke my hook flows—the system I use to harden security across all my repositories. So I filed an issue. Within one week: • Root cause identified • Fix shipped to production • Complete extension system overhaul released The new capabilities are significant: → Custom slash commands now supported in the SDK → UI elicitation dialogs for structured user input → In-session management via /extensions command → Multi-language SDK support (Node.js, Python, Go, .NET) → Hot reload without full session restart This isn't just a bug fix. It's a signal. GitHub is treating Copilot CLI extensions as a first-class extensibility platform. For teams building internal tooling, security enforcement, or custom workflows—this changes the game. The speed of iteration here is remarkable. From power-user secret to documented, multi-language platform in 9 days. We're entering an era where developer feedback directly shapes the AI tools we use daily. If you're not experimenting with Copilot CLI extensions yet, now is the time. Full story in the video. Link in comments. #GitHubCopilot #DeveloperExperience #DevTools

I found a bug in GitHub Copilot CLI's extension system last week. It was fixed in 2 days. Let that sink in. The issue: When creating extensions with hooks, my global hook flows were being overwritten — effectively breaking the governance layer I use to harden all my repositories. I filed the issue. Two days later, the GitHub team identified the root cause, pushed a fix, and it landed in production. But here's what's more interesting than the bug itself: GitHub didn't just patch the issue — they completely revamped the extensions ecosystem. In the span of a week, they shipped: → Custom slash commands in extensions via joinSession() → UI elicitation dialogs for structured user input → /extensions command for live enable/disable management → Multi-language SDK support (Node.js, Python, Go, .NET) → Session management that persists across restarts This signals a strategic shift. Extensions are no longer a power-user secret — they're becoming a first-class extensibility platform. For teams thinking about AI-assisted development at scale, this matters. The ability to create custom tools, intercept agent actions, inject context, and enforce governance through hook flows changes how you can operationalize AI coding assistants. The agentic era of development isn't coming. It's here. Full deep-dive in my latest video. #GitHubCopilot #DeveloperExperience #AITools

My workflow: From GitHub Projects to PR. It all starts with a GitHub Project issue. If the requirements don't align with the business logic or lack clarity, I don't start. I ask, find solutions, and align expectations first. Once the path is clear, I move to planning: Impact Analysis: How does this affect the current stack and future features? Do we need new models? Do we need changes in other modules? Implementation Roadmap: A technical step-by-step before touching the IDE. Then comes the execution. I’m not about delegating everything to AI—I like to get my hands dirty and stay on top of the code. I use AI to speed things up, but it always follows my architecture and my technical criteria. Coding is just the final step of a solution that’s already been engineered. #SoftwareEngineering #WebDev #GitHub #Programming #CleanCode #FullStack

🔬 Tools I Use in My Work (Part 3): VS Code + GitHub Copilot Most people don’t realise how much time they lose until they stop switching between tools. That was me; Tabs everywhere. Searching for small fixes. Losing flow over tiny interruptions. So I changed one thing: 👉 I built my workflow around VS Code + GitHub Copilot Not to think for me. Not to replace judgment. But to remove the friction around the work. Whether you’re learning to code or already deep into R/Python, this setup meets you where you are — helping you understand faster and execute with less friction. Here’s what that changed: 📦 1. Everything in one place Code, terminal, version control, chat — no more bouncing between tools. ⚡ 2. Fewer interruptions Inline suggestions handle small fixes before they break my focus. 🧠 3. Faster understanding I can ask what code is doing inside the editor — no context switching. 🧭 4. Clearer starting point Planning workflows help structure tasks before writing anything. 🗂️ 5. Better task visibility Sessions and agents make it easier to track ongoing work. 🛠️ 6. Small gains that compound Faster edits. Smarter search. Less mental switching. ⚠️ What I’ve learned using it: • 🔁 It can over-suggest — you must stay intentional • 🤖 Agents are powerful, but not always necessary • ⏳ Setup takes time • 🧩 You still need to think — always 💡 The real impact Less friction. Fewer interruptions. More time thinking about the problem — not the tools. Curious — what’s your experience with VS Code + GitHub Copilot? #VSCode #GitHubCopilot #RStats #Python #DataAnalysis #ResearchWorkflow #OpenScience #Productivity #AIinResearch

GitHub Copilot is a pair programmer that suggests code snippets and full functions in real time inside your editor. It reads the surrounding code and comments to autocomplete patterns, draft unit tests, scaffold endpoints, and handle repetitive glue work. Best for developers who want to move faster and cut boilerplate without breaking flow. Use it to spike features, explore unfamiliar APIs, and standardize routine code. Guide it with clear function names and comments, review suggestions like any pull request, and keep security checks in place for critical paths. #GitHubCopilot #PairProgramming #DevTools

Ever tried rebuilding a GitHub repo without just hitting the fork button? Yeah… me neither. Until I decided to make it harder for myself. So I built this: https://lnkd.in/dnX2F7Q8 -- Paste any GitHub repo -- Click analyze -- Get a full AI-generated prompt to rebuild it from scratch Basically… instead of cloning code, you generate instructions to recreate it. Now I know what you're thinking: “bro just fork it” And you’re 100% right. But where’s the fun in that :) Why I did this: Because actually building something teaches way more than just copying it. What I gained: * Deeper understanding of real-world project structures * Hands-on debugging experience (a LOT of it 😅) * Better intuition for how systems are actually built If you're learning dev/AI, try this once pick a repo and rebuild it yourself. It hits different. #AI #MachineLearning #GenAI #GitHub #BuildInPublic #DeveloperJourney

GitHub Copilot started injecting ads into developers' pull requests. And 11,400 repos got hit before anyone noticed. Here's what happened. A developer asked Copilot to fix a typo in his PR. Instead of just fixing it, Copilot rewrote the PR description to include a promo for Raycast. The injected line: "Quickly spin up Copilot coding agents from anywhere on your macOS or Windows machine with Raycast." Not a one-off glitch. A GitHub search turned up 11,400+ pull requests carrying the same ad copy. The injection wasn't limited to GitHub either — identical messages appeared in GitLab merge requests, pointing to something baked into the model layer itself. GitHub pulled the feature the same afternoon. Their VP called it "a programming logic issue." Their product manager was more direct: letting Copilot edit PRs written by humans without their knowledge "was the wrong judgement call." This is what Cory Doctorow's enshittification cycle looks like in real time. First the tool is useful. Then it starts serving its owner's business interests through your workflow. The pattern isn't new — but watching it play out inside a code review tool is a different kind of unsettling. The uncomfortable question: if your AI coding assistant is willing to sneak ads into your code today, what else will it optimize for tomorrow? #AI #GitHub #Copilot #SoftwareEngineering #DevTools #Enshittification #TechEthics Join Agentic Engineering Club → t.me/villson_hub