GitHub Copilot Real Time Code Suggestions

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

I thought GitHub Copilot would just make me code faster… I was wrong. It actually made me a better developer. Not overnight—but in small ways that added up: • I stopped defaulting to old .NET patterns • I started writing async code more naturally • My code became cleaner without forcing it One example surprised me 👇 Before: WebClient, synchronous calls, tightly coupled code After (with Copilot nudges): HttpClient, async/await, dependency injection-friendly Same feature. Completely different quality. That’s what most people miss. Copilot isn’t just about speed— it quietly pushes you toward better engineering habits. If you’re working in C#/.NET (especially from legacy code)… you’ve probably seen this too. 👉 Have you noticed Copilot improving your coding style

GitHub Copilot Coding Agents are reshaping real sprint workflows. This is not the old autocomplete story. This is a look at what happens when an agent can take an issue, write the code, run the tests, and open the pull request. If you are curious about how agentic workflows actually work in practice or what this means for the future of engineering, you can read it here: https://zurl.co/KLCsB #GithubCopilotCLI

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

Most developers are using GitHub Copilot wrong. It’s not about better prompts. It’s about better context. Copilot performs based on what you feed into it — not what you ask it. Here’s what actually makes a difference: • Instructions → enforce coding standards • Skills → inject domain knowledge • Agents → simulate specialized roles • MCP → connect external systems I applied this in my project by defining clear backend rules and structuring responses consistently across modules. Result: more predictable, cleaner, and reusable code. Prompt engineering gets attention. Context engineering gets results. #GitHubCopilot #AI #SoftwareEngineering #Java #FullStackDeveloper #ContextEngineering GitHub Microsoft

GitHub is bringing remote control to Copilot CLI, letting developers run and manage coding sessions beyond the local terminal. The move mirrors what Anthropic already introduced with Claude Code, as both push toward agents that can run and be steered from just about anywhere. 🔗 Read the full story here: https://lnkd.in/gfP2iQQ7

Accidentally pushed code to my work GitHub instead of personal. Couldn't find a clear fix anywhere — so I built one. I made a complete open-source guide for managing multiple GitHub accounts on one machine: 1. SSH key setup for each account 2. ~/.ssh/config with host aliases 3. Interactive guide with Personal / Work toggle 4. Copy-ready commands for every step 100% free. No fluff. Link: https://lnkd.in/d6jcZMnb Star it if it helps ⭐ #github #git #developer #devtools #opensource #coding #programming

I've been using Claude Code for close to a year now. Watched it go from a promising CLI experiment to something I genuinely lean on daily. The jump in the last few months has been significant — agent teams shipped in February, the gstack ecosystem exploded in March, MCP integrations are everywhere now. Someone asked me to break down what actually matters across all of it. So I did. A few things I still see people get wrong: CLAUDE.md gets skipped. Every session starts from scratch, Claude asks what stack you're using, you re-explain the same context. One committed Markdown file fixes that for the whole team. It's the highest-ROI thing you can do in the first 10 minutes of any new project. Model selection gets ignored. Opus on everything is slow and expensive. Haiku on anything complex is frustrating. The tiers exist for a reason — using them deliberately makes a real difference. Hooks get underestimated. There's a difference between telling Claude "always run Prettier" and a PostToolUse hook that actually runs it. One is a suggestion. The other executes. Subagents changed how I think about context. Instead of one session getting bloated across a long task, I'll spawn a dedicated agent to grep through 80 files while my main context stays clean. Agent Teams (the February update) pushed this further — specialists can now talk to each other directly rather than routing everything through you. On gstack: Garry Tan open-sourced his personal Claude Code setup in March. 50K GitHub stars in 16 days. Worth looking at not just for the skills themselves (/cso, /autoplan, /ship are genuinely useful) but for the pattern it encodes — explicit roles per phase rather than one generalist session doing everything at once. Full breakdown with working examples at the link below — models, CLAUDE.md, hooks, subagents, agent teams, MCP, and gstack. What's something about Claude Code that took you longer to figure out than it should have? Curious what the recurring blind spots are. #ClaudeCode #AIEngineering #DeveloperTools

GitHub Copilot upping its debugging game on the web is fantastic news for developers! Finding and fixing those pesky bugs just got a lot more streamlined, directly in the browser. Definitely makes the dev process smoother. Less head-scratching, more coding! 💻 #GitHubCopilot #WebDev

Been using Claude Code and GitHub Copilot for a while now — at work and for personal projects — and the combination is genuinely good once you understand how to use them properly. One thing that changed the game for me is the Superpowers repository — it’s also available as an official plugin directly in the Claude Code marketplace. It comes with a set of predefined skills like brainstorming, writing plans, TDD, debugging, and subagent-driven development that just trigger automatically — you don’t have to do anything special. As soon as it sees you’re building something, it doesn’t jump into writing code. It steps back and asks what you’re really trying to do. That shift in behaviour is huge. And here’s the thing most people miss — writing code is actually the last step. The real heavy lifting is the planning. A well-structured plan markdown file, created through solid brainstorming, means even a lighter model can write good code from it. But if the plan is weak, even the best model won’t save you. Superpowers Skills handle exactly this part — the brainstorm → plan → implement flow — and it works. On top of that, I’ve started building my own custom Skills for specific use cases in my projects — things like documentation generation, commit intelligence, and test case flows — some of which are generic enough that any developer could plug them into real-world projects. If you’re using Claude Code or Copilot and haven’t looked at Superpowers yet, worth checking out 🔗 https://lnkd.in/g_GDMCqX #ClaudeCode #GitHubCopilot #Superpowers #AITools #DeveloperProductivity #SoftwareDevelopment #CodingSkills #AIAssistedDevelopment #ShipFaster #DevTools #OpenSource #AgenticAI #BuildInPublic #100xDeveloper #TechLinkedIn