You assign a GitHub issue before lunch. By the time you're back — there's a pull request waiting. That's the GitHub Copilot Coding Agent. GitHub Copilot has evolved far beyond autocomplete. The Coding Agent now works asynchronously in the background — fixing bugs, writing tests, refactoring code — and hands you a ready-to-review PR when it's done. Here's what just shipped: 🎛️ Model picker — Choose Claude Opus, Claude Sonnet, GPT-Codex-Max, or let Auto decide. Pick the right model for the complexity of each task. 🔍 Self-review — The agent reviews its own diff before tagging you. By the time you're looking at it, someone already went through it once. 🔒 Built-in security — Code scanning, secret scanning & dependency vulnerability checks — all before the PR opens. Free with Copilot coding agent. 🔌 MCP servers — Plug in external tools, databases, and context via Model Context Protocol. Your agent now has eyes beyond the repo. The agent boots a VM, clones your repo, RAG-indexes your codebase, and starts coding. You track every step in session logs. Your branch protections, CI/CD approvals, and security posture? Untouched. Think of it as having a junior dev who never sleeps, never skips tests, and always opens a clean PR. What low-to-medium complexity tasks would you hand off to an agent first? Drop a comment 👇 #GitHubCopilot #AI #CodingAgent #SoftwareEngineering #DevTools #AgenticAI #GitHub
GitHub Copilot Coding Agent Evolved: Autocomplete Beyond
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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
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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
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For the past few weeks I've been putting together something I wish I'd had when I first started using GitHub. A complete, beginner-friendly GitHub Handbook — written so anyone can understand it, even with zero coding background. 📘 Volume I — The Foundation (27 pages) History of Git and GitHub, every core concept explained with real examples, all the main features, Git command cheat sheet, workflows, alternatives, best practices, and common mistakes. 📗 Volume II — Beyond the Basics & The Age of AI (18 pages) Advanced topics as pointer-cards (rebase, Actions deep dive, security stack, APIs, Enterprise features) plus a comprehensive, current look at how AI is reshaping GitHub — Copilot, agents, Autofix, Spark, MCP, and what it all means for software careers. Both volumes are available as HTML and Word documents. A few things I learned putting this together: → GitHub in 2026 is not the same platform it was five years ago. It has quietly become an AI company that happens to host Git repositories. → Copilot has performed 60M+ code reviews and auto-fixed 460,000+ security vulnerabilities in the past year. → The skills that matter most are shifting — from typing speed toward specification writing, code review, and judgement. If you're learning GitHub, mentoring someone who is, or just curious about where the platform is heading — drop a comment and I'll share it. #GitHub #Git #SoftwareDevelopment #AI #GitHubCopilot #LearningInPublic #DeveloperTools
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A question I keep turning over: How many developers actually understand Git — versus just knowing enough commands to survive? I've been writing a comprehensive GitHub Handbook (beginner-friendly, two volumes, covers everything from "what is a repository" to the AI agents now opening pull requests autonomously) and the experience has been clarifying. Most of us learned GitHub by osmosis. A teammate showed us `git push`. We got yelled at for force-pushing once. We figured out pull requests. We never quite learned why any of it works the way it does. That's fine — until something breaks. And in 2026 the stakes are higher than ever, because the tools around Git have exploded. Copilot agents write code. Autofix patches vulnerabilities. MCP servers connect agents to your whole stack. The people who thrive in this environment are the ones with solid fundamentals + willingness to learn the new surface area. So my handbook starts from zero and ends at the current frontier. Volume I is the foundation. Volume II covers advanced topics and the comprehensive AI future. If that sounds useful — comment below and I'll send it your way. Curious to hear: what's the one GitHub concept you wish someone had explained to you earlier? #GitHub #Git #SoftwareDevelopment #AI #GitHubCopilot #LearningInPublic
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I pushed .env files to GitHub. Quick fix: delete .gitignore commit Done? That’s where most of us stop. I almost did too. But this time, I paused. Because earlier, I had gone deeper into Git. So I asked: “What about the history?” And there it was. Those files weren’t gone. Just hidden—in commits. Public. Recoverable. So I fixed the real problem: rewriting history locally + remotely. If I hadn’t learned that earlier? I would’ve confidently shipped a broken fix. This is the Dunning-Kruger Effect in action: • Enough knowledge to act • Not enough to question Doing it often makes you fast. Understanding it makes you right.
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> GitHub stopped updating its own status page due to terrible availability ... 90.1% uptime - This means ... issues/degradations for 2.5 hours daily ... > GitHub struggles to keep up with the increase in load from AI agents generating more code and pull requests ... Claude Code bot contributions growth in the past 3 months has been enormous ... Stream of outages ... https://lnkd.in/eYHzasTh
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