Automating cross-repo documentation with GitHub Agentic Workflows
Explore how the Aspire team turns merged product changes into SME-reviewed docs pull requests, closing the gap between release and documentation.
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AI & ML
GitHub engineers and industry thought leaders offer tips, best practices, and practical explainers about various aspects of AI and ML, ranging from fundamental concepts to advanced techniques and real-world applications. For more detailed documentation and practical guides on GitHub’s own AI coding tool, GitHub Copilot, check out GitHub’s official documentation.
Featured
How GitHub Copilot enables zero DNS configuration for GitHub Pages
Go from an empty repository to a live custom domain with HTTPS in about 14 minutes, without manually editing a single DNS record.
Evaluating performance and efficiency of the GitHub Copilot agentic harness across models and tasks
Explore how the GitHub Copilot agentic harness delivers strong results across multiple benchmarks and leading token efficiency, while maintaining flexibility to choose among more than 20 models.
I automated my job (and it made me a better leader)
Explore how my day as a senior leader looks now that I use 40 automations to help, and learn more about some of my favorites.
Latest
How we built an internal data analytics agent
Qubot, our internal Copilot-powered analytics agent, allows any GitHub employee to ask questions about our data in plain language. Here’s what we learned as we built it.
Getting more from each token: How Copilot improves context handling and model routing
How GitHub Copilot is making more of each session go toward useful work, so your credits go further.
What are git worktrees, and why should I use them?
Git worktrees have been around since 2015, but it wasn’t until recently they became popular. Learn what they are, how to use them, and why you might.
GitHub Copilot CLI for Beginners: Overview of common slash commands
GitHub Copilot CLI for Beginners: Learn how to use slash commands to control your terminal AI agent.
Accelerating researchers and developers building multilingual AI with a new open dataset
A new repository-level dataset, published on GitHub under CC0-1.0, helps researchers and developers discover multilingual developer content across READMEs, issues, and pull requests.
How we made GitHub Copilot CLI more selective about delegation
Better orchestration, fewer handoffs, faster progress, without a single new knob.
Making secret scanning more trustworthy: Reducing false positives at scale
Alerts are more trustworthy and actionable when noise is reduced. See how we improved the verification step with context-aware LLM reasoning.
Give GitHub Copilot CLI real code intelligence with language servers
Install and configure LSP servers for GitHub Copilot CLI, replacing brute-force grep/decompile with real code intelligence.
From one-off prompts to workflows: How to use custom agents in GitHub Copilot CLI
Custom agents let GitHub Copilot CLI understand your stack and team workflows, turning one-off terminal prompts into repeatable, reviewable processes.
GitHub recognized as a Leader in the Gartner® Magic Quadrant™ for Enterprise AI Coding Agents for the third year in a row
We are committed to empowering every developer by building an open, secure, and AI-powered platform that defines the future of software development.
Take your local GitHub sessions anywhere
Kick off work in VS Code or the CLI, finish it from your phone. Remote control for GitHub Copilot sessions is now generally available on github.com and GitHub Mobile.
Building a general-purpose accessibility agent—and what we learned in the process
Learn about the experimental general-purpose accessibility agent that GitHub is piloting.
Dungeons & Desktops: Building a procedurally generated roguelike with GitHub Copilot CLI
Learn how one Hubber used GitHub Copilot CLI to build an extension that turns any codebase into a unique, roguelike dungeon.
Improving token efficiency in GitHub Agentic Workflows
Agentic workflows that run on every pull request can quietly accumulate large API bills. Here’s how we instrumented our own production workflows, found the inefficiencies, and built agents to fix them.
Agent pull requests are everywhere. Here’s how to review them.
A practical guide to reviewing agent-generated pull requests: what to look for, where issues hide, and how to catch technical debt before it ships.
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