GitHub Copilot: AI Pair Programmer for Engineers

AI developers spend a lot of time prompting. But shipping anything beyond a script means working with code — branching, versioning, collaborating with others. And in that area, Git and GitHub are non-negotiable: incredibly powerful, but their core concepts are often skipped over. I felt I was missing those fundamentals while building my own projects. So I built a Git & GitHub course from scratch — using Claude Code itself as the instructor. It's hands-on. 11 progressive lessons, each with theory and a real practice session on a real repo. You don't type git or gh commands — you tell Claude what you want to do in plain English, Claude runs the real commands, and walks you through every state change step by step. You'll build the mental model of where your code actually lives at any moment. And that's what actually matters. Sharing it because I think it can save someone else the same gap. Download the repo and open it in Claude Code, say "start lesson 1", and Claude will guide you. Progress is tracked inside the repo itself, so you can pick up right where you left off. Link below.  #git #github #claudecode #aidevelopment #devtools

One tool that quietly changed my daily workflow: GitHub Copilot. Not because it writes perfect code. But because it removes friction. Things that used to take minutes… Now take seconds. Writing boilerplate. Creating DTOs. Generating test cases. Handling repetitive logic. And that adds up. The real value of Copilot isn’t just speed. It’s momentum. You stay in flow longer. You switch context less. You explore ideas faster. But here’s what makes the difference: How you use it. Copilot is powerful when: 🔹 You know what you’re building 🔹 You can review and validate suggestions 🔹 You guide it with clear intent It’s not a shortcut for thinking. It’s a tool that amplifies it. The developers who benefit the most are not beginners… They’re the ones who already understand the fundamentals. Because they know what to accept. And what to reject. In the end, Copilot doesn’t make you a better engineer. But it can make a good engineer… significantly faster. How has GitHub Copilot changed your workflow? #GitHubCopilot #AI #SoftwareEngineering #Java #Developers #Productivity #Coding #Tech

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

GitHub Copilot has crossed the line from autocomplete to coding agent. The early version helped you finish a line. The current version can open a pull request, write the tests, run them, review its own work, and ask for human input only when it hits a real decision point. Engineering leaders are reporting meaningful gains on well scoped work, often in the 30 to 55 percent range for net delivery speed. The gains concentrate on tasks that are clear, repetitive, and well specified. Ambiguous work still needs humans leading the thinking. The skill that matters most now is not clever coding. It is writing clear specifications, designing clean interfaces, and knowing when to trust the agent and when to step in. Senior engineers are more valuable than ever. Their judgment is what keeps AI generated code from quietly eroding a codebase. #GitHubCopilot #DeveloperProductivity #AIEngineering #AkashInnoTech

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

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

I’ve been spending a ton of my personal time with GitHub Copilot, Claude and a few of the newer dev tools showing up every week. My honest take: most of us are still describing this wrong. “Vibe coding” isn’t the shift. That was just the warm-up. We’re already moving into what I’d call Vibe Coding 2.0. In 1.0, you were still in control. In 2.0, the posture completely changes. You define the intent. Everything else starts to get figured out for you. And, this is not theoretical. You step away for a bit, grab a coffee, water your plants 🪴and come back to: - a repo that didn’t exist before - flows that are already wired - something that’s actually runnable Not perfect. But very real. Now, here’s where I think people are underestimating what’s happening. We’re entering a world where counting tokens won’t matter. Right now, the conversation is stuck at: cost per call, model efficiency, prompt optimization. That’s a temporary phase. As agents take over: - they will manage cost - they will optimize usage - they will decide when to call what The unit of value won’t be tokens. It will be outcomes. And, that’s a very different game. At the same time, there’s a real risk building underneath all of this. In 2.0: - abstraction increases - visibility decreases - failure shifts downstream This X post by @hartdrawss captures something important - we are moving to nudging systems into existence... https://lnkd.in/gZHrkdZm Agents are starting to look like the primary users of software. If you connect the dots, it’s pointing to: software talking to software, making decisions, and increasingly - transacting. Which is why ideas like x402 (that I wrote about a few months ago) start to feel less “forward-looking” and more… inevitable. This post by @shivsakhuja talks about companies building an entire ecosystem around agents - https://lnkd.in/gga7JDFp If you have not, check out shipper.now. They’re interesting not because of what they do today, but because of what they signal: idea → build → deploy is collapsing into a single motion. That has second-order effects most teams aren’t prepared for... This is where it gets uncomfortable. Because the constraint is no longer execution, it’s "judgment". With 2.0: - small teams outperform large ones - individuals can build at scale - iteration is effectively unconstrained $1B, 1-person companies are starting to become real, and < 10-member teams running a billion $ startup stop sounding extreme. So the real question isn’t “how do I use these tools better?” It’s: - Do I understand and believe in what is actually being built? - Can I reason about failure before it happens? - Am I designing systems... or just reacting to outputs? Because Vibe Coding 2.0 doesn’t reward speed, it rewards the clarity of thought. And... that’s a much higher bar than most of us are used to. #AIAgents #FutureOfSoftware #VibeCoding

🛡️ "In Git We Trust" We're kicking off the useblocks X-as-Code Webinar Series - in collaboration with GitHub - next week, April 22nd. Still managing engineering artefacts outside Git? Then this is for you. The shift toward X-as-Code is accelerating, especially in safety-critical industries. And it starts with the fundamentals. 🚀 The Series Premiere: Arnaud Riess, a pioneer of X-as-Code at a global automotive Tier-1, opens the series with: "X-as-Code Foundations - In Git We Trust" What we’re covering: 🔹 Why document-centric engineering is failing to scale. 🔹 Treating requirements, architecture, and compliance as version-controlled assets. 🔹 Why this approach is the "secret sauce" for AI readiness. 🔹 Leveraging open-source foundations like Sphinx-Needs. No prior experience required. Structured content + live Q&A. All registrants receive slides and recording. 📅 When: April 22nd | 4 PM CET 📍 Where: Live Webinar (+ Recording for all registrants) Registration link in the first comment. #useblocks #XasCode #SpecDrivenDevelopment #GitHub #SafetyCritical #OpenSource #SphinxNeeds #AutomotiveSoftware

🚀 GitHub changed how I build. Earlier, I used to think of coding as just writing logic. Now I see it as building systems that evolve over time. GitHub is not just a code repository. 𝗜𝘁’𝘀 𝗮 𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝘁𝗼𝗼𝗹. Every commit = a decision Every branch = an experiment Every pull request = structured thinking Over time, I’ve built a simple workflow: 👉 𝗽𝘂𝗹𝗹 → 𝗯𝘂𝗶𝗹𝗱 → 𝘁𝗲𝘀𝘁 → 𝗰𝗼𝗺𝗺𝗶𝘁 → 𝗽𝘂𝘀𝗵 → 𝗶𝘁𝗲𝗿𝗮𝘁𝗲 Nothing fancy. Just consistent. And honestly, that consistency matters more than tools. Recently, I’ve been exploring AI-assisted development inside GitHub workflows. Using tools like: 𝗖𝗼𝗱𝗲𝘅-𝗯𝗮𝘀𝗲𝗱 𝗲𝘅𝘁𝗲𝗻𝘀𝗶𝗼𝗻𝘀 𝗔𝗜 𝗰𝗼𝗱𝗲 𝘀𝘂𝗴𝗴𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗣𝗿𝗼𝗺𝗽𝘁-𝗱𝗿𝗶𝘃𝗲𝗻 𝗱𝗲𝗯𝘂𝗴𝗴𝗶𝗻𝗴 What I’ve realized: AI doesn’t replace GitHub. It makes GitHub more 𝗽𝗼𝘄𝗲𝗿𝗳𝘂𝗹. Because now: You don’t just write code 𝗬𝗼𝘂 𝗰𝗼-𝗯𝘂𝗶𝗹𝗱 𝘄𝗶𝘁𝗵 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 For my current project (local AI content studio), GitHub is where everything comes together: 𝘣𝘢𝘤𝘬𝘦𝘯𝘥 𝘭𝘰𝘨𝘪𝘤 𝘌𝘭𝘦𝘤𝘵𝘳𝘰𝘯 𝘢𝘱𝘱 𝘣𝘶𝘪𝘭𝘥 𝘴𝘤𝘳𝘪𝘱𝘵𝘴 𝘦𝘹𝘱𝘦𝘳𝘪𝘮𝘦𝘯𝘵𝘴 All tracked. All versioned. All evolving. 💡 𝗠𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆: You don’t need complex setups. Start simple: learn basic git commands commit regularly use branches without fear experiment with AI tools That’s enough to level up. GitHub is not just where code lives. It’s where your 𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝘃𝗶𝘀𝗶𝗯𝗹𝗲. If you’re building and figuring things out— we’re probably on the same path. #GitHub #LocalAI #VsCode