How GitHub Copilot boosts C# development with AI

💡 Make GitHub Copilot Work With Your Team Using Prompt Files When working with GitHub Copilot in VS Code, you can create reusable prompt files that live right alongside your source code. 📦 These files can be stored in source control and executed anytime, making them perfect for tasks your team performs repeatedly. For example, my team uses a prompt file to: ✅ Add new properties across multiple layers of our API ✅ Generate consistent release notes for those properties Since creating it, we’ve used the same prompt file to add 20 new properties, saving time and keeping our output consistent across services. ⚙️ You can even define which AI mode and model Copilot uses when running the prompt, giving you predictable, repeatable results every time. If your team uses Copilot regularly, try building a few prompt files for your common workflows. It’s a small step that makes AI collaboration more structured, consistent, and team-friendly. 💬 Have you tried using prompt files with Copilot yet? I’d love to hear how your team’s using them. #GitHubCopilot #VSCode #AIinDevelopment #DeveloperProductivity #SoftwareEngineering #CodingTools

The first time I used GitHub Copilot Agent, it didn’t feel like a tool. It felt like I suddenly had a junior engineer sitting next to me who actually understood my codebase. I asked it to fix a failing test that had been bothering me for hours. Instead of giving me small suggestions, the agent walked through the entire file, understood the dependency chain, pointed out the mismatch in the mock, and rewrote the test end to end. I didn’t copy paste anything. I just reviewed and approved. That moment changed how I viewed my workflow. Earlier, I used AI for code snippets or help with syntax. But the agent worked differently. It understood context. It navigated files. It explained why something was broken. It made changes across the project instead of one line at a time. On some days it cleaned up old code I had been postponing for months. On other days it wrote migration scripts, handled refactoring, or even generated a clear technical explanation of what a complex module was doing. It didn’t replace my thinking. It replaced the friction. The hesitation before touching unfamiliar files. The mental load of switching between tabs. The hours lost in repetitive debugging. With Copilot Agent, I spend more time designing, reasoning, and making decisions, and less time wrestling with tedious implementation details. It feels like the gap between idea and execution got much smaller. AI won’t write your system design for you, but it will make sure implementation never slows down your imagination. If you have tried Copilot Agent, what was the first task that truly made you say, this feels different? #copilot #agent #ai

🚀 GitHub Copilot – Plan Mode is now in VS Code! Plan Mode helps teams think before they code — converting high-level requirements into clear, structured technical plans with tasks, dependencies, risks, and TODOs. For large initiatives like application modernization, API upgrades, refactoring waves, or vulnerability remediation across multiple repositories, Plan Mode brings clarity, consistency, and speed. A great accelerator for our GenAI + Copilot adoption work across teams. 🔗 More details: Planning in VS Code chat https://lnkd.in/gzxTke-5 #GitHubCopilot #PlanMode #GenAI #DeveloperExperience #Modernization #VSCode

🚀 Building Smarter with GitHub Actions + GitHub Copilot I recently set up a complete CI/CD pipeline using GitHub Actions, and I’m genuinely amazed by how seamless automation can be when paired with GitHub Copilot 🤖 Here’s what I built: ✅ Continuous Integration: Automatically runs tests and lint checks on every push or pull request. ✅ Continuous Deployment: Deploys successful builds straight to staging — no manual steps. ✅ GitHub Copilot: Helped me write clean YAML workflows, optimize test scripts, and even catch small logic mistakes while coding. This setup has made development faster, more reliable, and far more enjoyable. Watching code go from commit → test → deployment automatically still feels like magic ✨ If you haven’t tried combining GitHub Actions and Copilot, it’s a game-changer for any developer looking to speed up their workflow. #GitHub #GitHubActions #GitHubCopilot #CICD #DevOps #Automation #AI #SoftwareEngineering #Productivity

🚀 Leveling Up the Dev Experience with GitHub Copilot! I’m excited about the latest enhancements in GitHub Copilot — especially the new Agent Mode, Next-Edit Suggestions, and multi-model support that are transforming how we write and refactor code. Here’s why it matters to me (and to any engineering team): ✅ Agent Mode lets the Copilot act across multiple files and automate tedious tasks so I can focus on architecture & high-impact work. ✅ Next-Edit Suggestions anticipate the logical next change, speeding up iterations and reducing context switching. ✅ Multi-model support means choosing the best AI model for the job — giving more flexibility, smarter suggestions, and better quality. For a developer working with Java, Spring Boot, Microservices, and Cloud (like me), these updates open doors to: 🎯Building and refactoring large monoliths or microservices faster 🎯Automating coding tasks that repeat or are error-prone 🎯Leveraging AI as a true “pair programmer” rather than just auto-complete I’m diving into using these features in my current stack and keen to share my findings and best practices soon. 💡 What about you? Are you using Copilot’s newest features — or curious about how it can optimize your team’s workflow? Let’s connect, experiment, and elevate our code game together. #GitHubCopilot #AIforDev #DeveloperProductivity #Java #SpringBoot #Microservices #Cloud #ContinuousLearning #TechInnovation

This article breaks down the impactful role of Copilot in enhancing the GitHub platform. I found it interesting that Copilot not only streamlines coding processes but also empowers developers to be more creative and efficient. What stood out to me was how AI can evolve traditional workflows in significant ways. How do you see AI tools like Copilot changing the landscape of software development in the future?

💻 GitHub Copilot & Context Engineering - Internal Session with Alex Yochev. Last week we had the pleasure of hosting Alex Yochev, Senior Solution Engineer at Microsoft, for a special session on "GitHub Copilot Presentation: Context is King - Engineering Prompts That Actually Code". 🎯 In the age of AI-assisted development, writing good prompts is no longer just an advantage, but an essential skill. Alex shared practical techniques for crafting smarter prompts, managing context, and using tools like GitHub Copilot and VS Code to turn vague ideas into production-ready code. Discover more highlights from the event! 👇 #BoschDigital #AIEngineering #TechTalks

Exciting news! GitHub Enterprise launches the Copilot usage metrics dashboard and API in public preview. This tool empowers teams to measure AI integration in software development, moving beyond just adoption to impactful usage. Embrace the AI-driven future of coding! 🤖📊🚀 #GitHubEnterprise #Copilot #AIinSoftware #DevMetrics #Innovation ⬇️ https://lnkd.in/gj6CZ4nj

🚀 Creative Use of GitHub Copilot for Code Review A few months ago, I faced an interesting challenge during a code review. One of my colleagues had pushed 35-40 files - a lot of files, limited time, and everything bundled together in a single Bitbucket branch. Even though we had access to GitHub Copilot, we couldn’t use its built-in code review features directly since the repo was hosted on Bitbucket, not GitHub. So, I decided to get creative. Here’s what I did 👇 1. I pulled the latest code locally and took all the commits that were pushed to Bitbucket, keeping them in a staged state. 2. Then, I removed the files from staging, moving them under the Changes section in my local setup. 3. Once all the modified files appeared there, I used GitHub Copilot locally to review each file one by one, by prompting it with clear instructions for what to check and analyze. 4. I then went through each of Copilot’s suggestions, verified the logic, and made adjustments where needed. This approach turned out to be surprisingly effective - Copilot helped me quickly identify potential logic issues (like an extra for loop in a setup function), while I could focus on validating the reasoning and context. 💡 Key takeaway: Even when your workflow doesn’t perfectly align with your tools, creativity and the right prompts can help you get the most out of AI. #AI #CodeReview #GitHubCopilot #Bitbucket #SoftwareEngineering #DeveloperExperience #Innovation #Productivity #MERNSTACK #REACT

Just read how GitHub Copilot has seriously leveled up! It's gone way beyond autocomplete with "mission control" and agent mode, becoming a full workflow assistant. Think automated tests, PR reviews, and multi-step refactors right in VS Code or CLI. This is a game-changer for dev speed. 🤯 #GitHubCopilot #DevTools