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 to use GitHub Copilot on github.com: A power user’s guide

Explore how to use GitHub Copilot on github.com to automate tasks, assign agents, prototype ideas, and streamline your entire workflow — all without an IDE.

Building your first MCP server: How to extend AI tools with custom capabilities

Learn Model Context Protocol by building a turn-based game server that shows how to extend GitHub Copilot with custom tools, resources, and prompts.

GPT-5 in GitHub Copilot: How I built a game in 60 seconds

How GitHub’s new MCP server and GPT-5 are revolutionizing developer workflows — with live build examples.

How to use GitHub Copilot to level up your code reviews and pull requests

Discover practical ways GitHub Copilot streamlines code reviews, pull requests, and daily engineering tasks with real prompts, examples, and workflow tips from our engineering team.

Latest

Junior developers aren’t obsolete: Here’s how to thrive in the age of AI

The role of junior developer is evolving. If you’re at this stage in your career, here’s how to keep up and stand out.

Automate your project with GitHub Models in Actions

Learn how to integrate AI features with GitHub Models directly in GitHub Actions workflows.

Onboarding your AI peer programmer: Setting up GitHub Copilot coding agent for success

Learn how to configure Copilot coding agent’s environment, optimize project structure, use custom instructions, and extend its capabilities with MCP servers.

A practical guide on how to use the GitHub MCP server

Upgrade from a local MCP Docker image to GitHub’s hosted server and automate pull requests, continuous integration, and security triage in minutes — no tokens required.

How to build secure and scalable remote MCP servers

More context can mean more attack surfaces for your projects. Be prepared for what lies ahead with this guide.

Solving the inference problem for open source AI projects with GitHub Models

How using GitHub’s free inference API can make your AI-powered open source software more accessible.

Debugging UI with AI: GitHub Copilot agent mode meets MCP servers

Explore how I use agentic tools like GitHub Copilot agent mode and the Playwright MCP server to accelerate troubleshooting and debugging of UI issues, while revisiting the importance of clear requirements.

For the Love of Code: a summer hackathon for joyful, ridiculous, and wildly creative projects

That idea you’ve been sitting on? The domain you bought at 2AM? A silly or serious side project? This summer, we invite you to build it — for the joy, for the vibes, For the Love of Code 🧡

From chaos to clarity: Using GitHub Copilot agents to improve developer workflows

Explore how you can set Copilot coding agent up for success with custom instruction and Copilot setup steps.

Code review in the age of AI: Why developers will always own the merge button

When it comes to merging code, developers will always make the final decision. But we’re rethinking how tools like GitHub Copilot can help.

Beyond prompt crafting: How to be a better partner for your AI pair programmer

Ensuring quality code suggestions from Copilot goes beyond the perfect prompt. Context is key to success when working with your AI pair programmer.

5 ways to transform your workflow using GitHub Copilot and MCP

Learn how to streamline your development workflow with five different MCP use cases.

From idea to PR: A guide to GitHub Copilot’s agentic workflows

A practical guide to GitHub Copilot’s agentic coding agent, chat modes, and remote MCP server so you turn issues into tested PRs with clear steps (and no hype).