はてなブックマーク

As developers, we love to customize our environment, and to build tools that fit our unique preferences and workflows. We do this not just because it improves productivity and ergonomics, but also, because it makes our daily routine feel more personal. And when things feel personal, they’re typically more fun. However, while we may invest in things like managing dotfiles, writing automation script

As software developers we understand the importance of a tight feedback loop. When we can get instant syntax- and type-checking, rapid runs of the tests affected by a change, or live previews of the UI, then we can go fast with confidence, correcting little mistakes in logic or design before they become big ones. This fast feedback is especially powerful when we're not sure what we're doing (I can

When we as software developers instruct computers to do something, we use a programming language like Rust, TypeScript or CSS. Theoretically, the precision of formal languages allows us to predict exactly what behavior we'll get. But this comes at the expense of needing to explicitly specify every detail we want. On the other hand, if we are instructing a fellow human being, we usually leave out m

Our Explorations and Experiments Pull Requests have become a central part of many team's workflows. We love how they let us group changes into a single transactional chunk so they can be communicated, discussed and improved. But they also create overhead. It takes time to put them together, review them and sometimes it's hard to even merge them. In the Copilot for Pull Requests project we explored

Technical PreviewCopilot WorkspaceAn agentic dev environment, designed for everyday tasks. Getting started has never been simpler.Whether you’re addressing an Issue, iterating on a PR, or bootstrapping a project, Copilot Workspace helps you jumpstart every task by describing what you want in natural language. The plan agent captures your intent, proposes a plan of action, and uses that plan to imp

Difficulty typing? Use your voice to code without spelling things out by talking with GitHub Copilot. Copilot Voice was formerly known as "Hey, GitHub!". We concluded the technical preview of GitHub Copilot Voice on April 3, 2024. We have transferred all the learning and feedback from this technical preview to VS Code Speech extension , which is generally available for download today. We encourage

Whether you’re learning a new library or API or you’ve been using it for years, it can feel like the documentation gets in your way more than it helps. Maybe the tutorials are too basic, or the reference manual is too sketchy, or the relevant information is split across multiple pages full of irrelevant details. We’re exploring a way to get you the information you need, faster. By surfacing the mo

GitHub Copilot is a groundbreaking AI pair programer for developers, but we’re just beginning to explore the future of coding. Over the course of the technical preview, the Copilot team has improved the quality of suggestions and added safety features — but it’s not difficult to see the potential help that Copilot could offer beyond code suggestions. Today, we’re launching a companion VS Code exte

Can editing code feel more tactile, like painting with Photoshop brushes? We added a toolbox of brushes to our Visual Studio Code extension that can modify your code.

GitHub Next investigates the future of software development

The terminal is a powerful place: In a single line of arcane shell magic, you can transform files and parse data at will. But it can take many years of regular use to become a shell wizard. Even with solid proficiency, most of us regularly need to optimistically type --help or scroll through man pages. Oftentimes, you simply turn to a web search, hopefully finding something like a relevant StackOv

TestPilot takes the pain out of writing unit tests. It uses GitHub Copilot's AI technology to suggest tests based on your existing code and documentation. Unlike many other tools, TestPilot generates readable tests with meaningful assertions, and it can iteratively improve its suggestions based on your feedback.

That wasn’t terribly difficult, but it also probably took a bit of time and exploration. Can we do better? Instead of the typical folders & files view, we can create a visual representation of the code. Below, I've visualized the same repository, but instead of a directory structure, each file and folder as a circle: the circle’s color is the type of file, and the circle’s size represents the size

Flat explores how to make it easy to work with data in git and GitHub. It builds on the “git scraping” approach pioneered by Simon Willison to offer a simple pattern for bringing working datasets into your repositories and versioning them, because developing against local datasets is faster and easier than working with data over the wire.