Jonathan Vella’s Post

𝐆𝐢𝐭𝐇𝐮𝐛 𝐏𝐑 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰 𝐟𝐨𝐫 𝐚 𝐬𝐨𝐥𝐨 𝐝𝐞𝐯 🔧 I hit a strange problem using GitHub with GitHub Copilot as a solo developer. I could not complete a Pull Request. I set a rule to require 1 reviewer approval. But there is no real reviewer. Copilot is the only one I can assign, but cannot approve. So the only option was force merge with admin power. 🤔 That felt wrong. I wanted a normal flow, not a shortcut. So I built a small bot workflow to simulate the review step. It feels like over-engineering, but it works. Now I pause before merge. I read the diff again. I question the code, even if Copilot wrote it. It is not perfect. It is a workaround. But for solo work, this kind of structure helps more than I expected. How do you handle PR review as a solo developer? Reference: GitHub Bot Workflow for Solo Developer + Copilot (https://lnkd.in/gCdq7Cut) #GitHub #PullRequest #GitHubActions #DeveloperWorkflow #AICoding #Copilot #DevOps #CodeReview

How to use GitHub Copilot better than 99% of people Most developers accept the first suggestion and move on. Meanwhile, the top 1% are using Agent Mode, assigning issues to Copilot, and connecting external tools via MCP. I built a 12-tip visual carousel to close that gap. ━━━━━━━━━━━━━━━━━━━━━━ 𝗪𝗵𝗮𝘁'𝘀 𝗶𝗻𝘀𝗶𝗱𝗲: 𝟭. Switch to Agent Mode 𝟮. Assign GitHub Issues directly to Copilot 𝟯. Add custom instructions to your repo 𝟰. Pick the right model for the task 𝟱. Create reusable prompt files 𝟲. Connect tools via MCP 𝟳. Use Copilot CLI in your terminal 𝟴. Master @workspace, @terminal, and slash commands 𝟵. Automate PR reviews with Copilot 𝟭𝟬. Build agent skills and extensions 𝟭𝟭. Configure org-level governance 𝟭𝟮. Treat your repo as Copilot's brain ━━━━━━━━━━━━━━━━━━━━━━ Every tip has real examples, terminal mockups, code snippets, and links to official GitHub Docs. No fluff. No "just use better prompts" advice. This is the reference I wish I had when I started. 📥 Save this for your next sprint. ♻️ Repost if your team needs this. #GitHubCopilot #AI #DeveloperProductivity #CopilotTips #GitHub #SoftwareEngineering #DevTools

GitHub Copilot started injecting ads into developers' pull requests. Not a hypothetical. It happened this week. A developer asked Copilot to fix a typo. Instead of just making the correction, it rewrote the PR description and slipped in a promo for Copilot and Raycast. Buried in the markdown was a hidden HTML comment: START COPILOT CODING AGENT TIPS. Then someone searched GitHub for that exact phrase. Over 11,000 matching pull requests. Across thousands of repositories. The same promo text showed up on GitLab too — baked into the model layer, not the platform. GitHub pulled the feature within hours. Their principal PM called it "the wrong judgement call." But 11,000 PRs were already contaminated before anyone noticed. This is the pattern. You give a tool write access to your codebase, and somewhere in a product meeting, someone decides that access is also a distribution channel. The AI dev tools that survive long-term will be the ones that treat your code as yours, not as ad inventory. The moment your AI assistant starts working for someone other than you, it stops being an assistant. At what point does an AI tool inserting its own content into your work become a dealbreaker? #AI #GitHub #Copilot #DeveloperTools #SoftwareEngineering #OpenSource #TechEthics Join Agentic Engineering Club -> t.me/villson_hub

Cheatsheet on GitHub Copilot CLI. 𝗘𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝘆𝗼𝘂 𝗻𝗲𝗲𝗱. 𝗢𝗻𝗲 𝗽𝗮𝗴𝗲. 𝗭𝗲𝗿𝗼 𝗳𝗹𝘂𝗳𝗳. Most developers use Copilot in the IDE. Fewer have explored Copilot CLI. putting together a single-page cheatsheet covering the full workflow → ━━━━━━━━━━━━━━━━━━━━━━ 𝟭. Getting Started & Authentication 𝟮. Custom Instructions — Copilot's persistent memory 𝟯. Instructions File Hierarchy (global → repo → path) 𝟰. CLI Best Practices that actually matter 𝟱. Project File Structure conventions 𝟲. Skills — the superpower most people skip 𝟳. Agent & Extension ideas 𝟴. MCP Server setup (built-in, custom, third-party) 𝟵. Permissions & Safety controls 𝟭𝟬. The 4-Layer Architecture 𝟭𝟭. Daily Workflow Pattern 𝟭𝟮. Quick Reference for all commands ━━━━━━━━━━━━━━━━━━━━━━ 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆? Copilot CLI isn't autocomplete in a terminal. When you layer these four together: ◈ 𝗟𝟭 — Custom Instructions ◈ 𝗟𝟮 — Skills ◈ 𝗟𝟯 — MCP Servers ◈ 𝗟𝟰 — Custom Agents ...it becomes a fully contextual coding partner that understands your project, your stack, and your conventions. ━━━━━━━━━━━━━━━━━━━━━━ 𝗠𝘆 𝗱𝗮𝗶𝗹𝘆 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄: cd project && copilot ↓ Shift+Tab → Plan Mode ↓ Describe feature intent ↓ Shift+Tab → Interactive ↓ /compact ↓ /diff → review changes ↓ Commit frequently ↓ New session per feature ━━━━━━━━━━━━━━━━━━━━━━ Grab the cheatsheet below ↓ Share it with your team. ♻️ 𝗥𝗲𝗽𝗼𝘀𝘁 if this is useful to your network. #GitHubCopilot #CopilotCLI #DeveloperProductivity #AI #DevTools #SoftwareEngineering #GitHub #CodingWorkflow

🚨 GitHub Copilot vs Claude Code — the difference most developers miss (2026) Everyone compares features. But the real difference is 𝐜𝐨𝐧𝐭𝐫𝐨𝐥 𝐯𝐬 𝐚𝐮𝐭𝐨𝐧𝐨𝐦𝐲. 🧠 The fundamental gap 👉 GitHub Copilot works 𝐰𝐢𝐭𝐡 𝐲𝐨𝐮 👉 Claude (Claude Code) works 𝐟𝐨𝐫 𝐲𝐨𝐮 That's it. That's the shift. ⚡ What that looks like in real life With Copilot: • You write code → it suggests next steps • You stay in control every second • It speeds up your existing workflow With Claude Code: • You describe the task → it executes • It explores files, understands context, makes decisions • It can complete chunks of work without constant input 🏗️ Difference in thinking Copilot mindset: 👉 "Help me write this function faster" Claude Code mindset: 👉 "Build this feature for me" 💼 Practical impact • Copilot is best when you already know what to do • Claude Code is powerful when the problem is complex or unclear • Copilot improves speed • Claude Code reduces effort ⚠️ Where most people go wrong They try to use both tools the same way. That's why they don't see real impact. 💡 The reality in 2026 If you're only using Copilot → you're still coding faster If you're using Claude Code properly → you're coding 𝐥𝐞𝐬𝐬 And that's a completely different advantage. 💬 So the real question is: Do you want AI to assist your work… or actually take over parts of it? #AI #GitHubCopilot #ClaudeAI #SoftwareDevelopment #Developers #TechTrends

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've been experimenting with GitHub Copilot in a way that I think most developers haven't tried yet — and I wanted to share the workflow I've landed on. Start in the Repository. When you're building something new, go straight to your GitHub repository and describe what you want Copilot to build. From a completely empty repo. No existing code, no setup, nothing. Just tell it what you want and let it go to work. I did exactly that — brand new repository, described my app, and walked away. It scaffolded the entire thing and opened a PR for my review. Then use Issues to refine. Once you have a foundation in place, that's when GitHub Issues becomes powerful. Open an issue, type @copilot, and describe what you want changed, added, or fixed. It reads your existing code and makes targeted changes in context. So the mental model I'd suggest: New project? Start in the repository and let Copilot build the foundation Existing project? Use Issues to extend, refine, or correct Think of it like handing an architect an empty lot versus asking a contractor to renovate what's already there. Two different jobs, two different starting points. Most people are still using Copilot just for autocomplete. The real power is in delegating entire workstreams. #GitHub #GitHubCopilot #AIEngineering #DeveloperProductivity #SoftwareDevelopment #CodingSmarter #AI #DevTools #Microsoft

Source: GitHub Official Documentation — docs.github.com/en/copilot GitHub Copilot shines when you give it the right context. 🤖 A .github/copilot-instructions.md file committed to your repo is all it takes — shared with your whole team, updated as your stack evolves. The framework is simple: WHAT — your stack & project structure WHY — architecture principles and conventions HOW — build, test, and lint commands Copilot follows what you tell it. Think of it as onboarding docs for your AI pair programmer — every contributor gets the same focused suggestions from day one. #GitHubCopilot #DeveloperProductivity #AITool

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

GitHub Copilot and Claude Code may both use slash commands, but they are not the same thing. Here is the simplest way to think about it: Built-in GitHub Copilot slash commands Controlled by GitHub and Microsoft Available based on your VS Code version, Copilot features, and extensions Designed for built-in actions inside Copilot Chat Examples: /explain, /fix, /tests, /doc, /new, /help Custom slash commands in Claude Code User-defined command patterns Used to shape how Claude responds Helpful for formatting, tone, structure, reasoning, and analysis Examples: /TLDR, /ELI5, /CHECKLIST, /SWOT, /COMPARE, /STEP-BY-STEP Claude Code skills Reusable automations for tasks you do often Great for turning repeated workflows into commands Examples: /review, /security, /optimize, /a11y, /test-plan My takeaway: GitHub Copilot slash commands = built-in product features Claude Code custom commands = flexible response controls Claude Code skills = repeatable workflow automation This distinction matters because many people see “slash commands” and assume they all work the same way. They do not. #GitHubCopilot #ClaudeCode #AI #DeveloperTools #VSCode #SoftwareDevelopment #Productivity #GenAI #Coding