Yes or YES? Get your #GitHubUniverse pass 👇 githubuniverse.com/?utm_sour…

Dependabot pull requests are easy to review one at a time ... and tedious to review by the dozen. Build a GitHub Copilot app automation that does the first pass for you. Once it reviews open Dependabot pull requests, groups them by risk, verifies CI status, it'll provide a short summary. You write the instructions in plain language, so you can shape the automation to match how your team works. Schedule it before your workday starts and the results are ready when you log in. Try it out 👇 github.blog/ai-and-ml/github…

More #GitHubUniverse sessions just dropped 🆕 Grab your pass, and we'll see you October 28-29 🌁 githubuniverse.com/?utm_sour…

GitHub 🤝 @Muse A new way to connect your GitHub account to review PRs, catch up on issues and notifications, and leave comments without switching tabs.

Check out the deep dive on making million-line pull requests with hundreds of comments feel like ordinary reviews. 👇 github.blog/engineering/user…

The team also built a measurement loop that ran unattended against a huge pull request, using production instrumentation to detect blank gaps, jank, leaked observers, and scroll corrections.

The solution was two independent geometries: • Deterministic code height, known up front • Dynamic comment blocks, measured lazily and corrected near the viewport That keeps comment reflows from rebuilding the code layout.

Code is the easy part: virtualize the rows, keep the DOM small, and use known line heights. Comments are harder. Their height changes with markdown, replies, expandable sections, images, and async content.

A pull request with 2,200 files, 1M+ changed lines, and 400+ inline comments. Impossible to review? Not if you have the GitHub Copilot app. ✨ The rebuilt pull request view keeps even this extreme diff fast and smooth. 🧵

➡️ Coming soon: Let's Learn GitHub Copilot SDK Starting September 24, we'll host beginner-friendly livestreams on how to build agentic applications with the GitHub Copilot SDK, without implementing the agent loop yourself. Includes sessions specifically for .NET and Java development. Sign up for English, Chinese, Portuguese, Spanish, Japanese, or Korean. gh.io/letslearn

Should you review your AI-generated code? Is RAG over? Did Skills make MCP obsolete? The GitHub Podcast responds to these hot takes 👇 github.blog/ai-and-ml/should…

📣 @OpenAIDevs's GPT-6 family is expanding in GitHub Copilot with two additional models now generally available. ☀️ GPT-6 Sol: the balanced model for interactive and agentic coding. 🌕 GPT-6 Luna: a lightweight, cost-efficient model for smaller tasks and the lowest-cost option in the family. Try them in the GitHub Copilot app or @code. github.blog/changelog/2026-0…

🚀 @AnthropicAI's Claude Opus 5.5 is now generally available in GitHub Copilot. Our early testing shows it stands out in efficiency, delivering task resolution comparable to Claude Opus 5 while using significantly fewer steps and tokens, with fast error recovery on multistep tasks. Try it out for agentic coding, long-running agentic tasks, and knowledge work. Find it in the GitHub Copilot app, CLI, and @code. github.blog/changelog/2026-0…

Just one engineer and a team of agents ported the GitHub Copilot agent runtime to Rust, shipping 800,000 lines of production code while retaining code quality. 🚀 How it worked 👇 github.blog/ai-and-ml/genera…

There's a lot of new vocabulary popping up in software development these days. The GitHub Podcast chats about some of the AI terms developers are learning right now. Grab your headphones 🎧 github.blog/ai-and-ml/decodi…