GitHub

So you forgot how you fixed that bug the other day. 😬 No worries. GitHub Copilot CLI remembers. With its local SQLite database of your session history (and a full-text search index), you can instantly pull up context from your previous work. ✅ Install Copilot CLI and save brain space. ⬇️ https://lnkd.in/g5nr8MEm

For everyone asking about the #GitHubUniverse badge, yes it does...

Developer talent is global. Access to AI tools should be, too. 🌍 💻 Stephen, a React developer working in Rwanda, shares how he uses GitHub Copilot to navigate complex code, and why AI is a tool for empowerment (and not replacement). Learn more about the partnership between GitHub and Andela to bring structured AI training to more than 3,000 developers across the globe. 💡 https://lnkd.in/gs693MiF

The developers who stand out today don’t just write code. They: • Delegate reasoning  • Turn repetition into workflows  • Operate systems over time Here’s how that plays out in real workflows 👇 

That gap between design and production? Closed. 🔁 We've brought GitHub Copilot, Visual Studio Code, and Figma together to create a continuous loop between design and development. With the new, bidirectional Figma MCP server, Copilot users can: 🔹 Pull design context directly into their code. 🔹 Push working UI back to the Figma canvas. 🔹 Keep components and production perfectly aligned, all without leaving VS Code. Code flows back to design. Design context flows into code. No more disconnected workflows or UI drift. What will your team build? Get started to find out. 👇 https://lnkd.in/e25nBRz5

We could tell you about how Copilot CLI can optimize your time, but we'd rather have Cassidy Williams sing about it instead.

If you’ve built a multi-agent workflow, you’ve probably seen it fail in a way that’s hard to explain. 🤔 The system completes, but somewhere along the way, something subtle goes wrong. Why is that? Because the moment multiple AI agents start handling related tasks (like triaging issues, proposing changes, opening PRs, etc.) they start making implicit assumptions about state and ordering. Through our work on agentic experiences at GitHub, we’ve learned a core lesson: Multi-agent systems behave much less like chat interfaces and much more like distributed systems. If you want them to be reliable, you have to treat them like code. Here are the three engineering patterns that make that happen: 1️⃣ Typed schemas: Natural language is messy. Add structure at every boundary so agents pass machine-checkable data. Treat schema violations like contract failures. 2️⃣ Action schemas: Vague intent breaks agents. Define the exact set of allowed actions (e.g., assign, close, escalate) so the outcome always resolves to a specific, explicit choice. 3️⃣ Model Context Protocol (MCP): Schemas define structure, but MCP enforces it. It acts as the contract layer, validating inputs and outputs before execution so agents can't invent fields or drift across interfaces. Design for failure first. Validate every boundary. Constrain actions. Get our full guide for engineers on building reliable, scalable multi-agent systems. 👇 https://lnkd.in/dUPnt7ny

Turn a WhatsApp message into a video. 📱🎬 We connected the Copilot SDK to Remotion to build a tool that generates a high-quality promo video in 5 minutes—triggered right from your phone. All thanks to pluggable, portable code. What will you build with the Copilot SDK? ⬇️ https://lnkd.in/giThByAa

Most developers already live in the terminal. And now, so does Copilot. 💻 We initialize projects, run tests, debug CI failures, and make fast changes in the terminal. GitHub Copilot CLI fits seamlessly into that environment, helping you move from an idea to reviewable diffs without context-switching. But the real magic isn't just writing starter code for you. It's how it fits naturally into the way you actually create and ship software. If you're building with AI, a helpful mental model looks like this: 💻 1. The CLI (For Momentum): Start with intent, not scaffolding. Tell Copilot what you want to build, or ask it why a test is failing right at the point of failure. Use the terminal to explore ideas, iterate fast, and get unstuck with low ceremony. 🛠️ 2. The IDE (For Precision): Eventually, speed matters less than exact architecture. Move into your editor to refine APIs, handle edge cases, and make design decisions you’ll defend in review. 🐙 3. GitHub (For Durability): Once the changes look good, use the CLI to commit and open a PR. Now the work is testable in CI, reviewable by your teammates, and ready to ship. The best part? You stay in control. Copilot CLI proposes plans, structures, and diffs, but it never silently runs commands without your approval. It’s a tool for momentum, not a replacement for judgment. Check out our full guide on building a practical Copilot CLI workflow. It includes a GitHub Skills exercise so you can try it yourself in a preconfigured, safe sandbox. 👇 https://lnkd.in/dE6Y7nNZ