generative AI

Explore how MCP elicitation transforms AI tool interactions by gathering missing information upfront.

This guide offers five essential tips for writing effective GitHub Copilot custom instructions, covering project overview, tech stack, coding guidelines, structure, and resources, to help developers get better code suggestions.

Learn how GitHub Copilot’s evolving models and infrastructure center developer choice and power agentic workflows.

Delegate coding tasks to Copilot and track progress wherever you are on GitHub. Copilot works in the background, creates a pull request, and tags you for review when finished.

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 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).

AI agents in GitHub Copilot don’t just assist developers but actively solve problems through multi-step reasoning and execution. Here’s what that means.

Reduce context-switching, minimize manual work, and accelerate resolution times with these new AI-powered features.

Get insights on the latest trends from GitHub experts while catching up on these exciting new projects.

Learn how to go from curious coder to AI wizard—with a little help from GitHub.

An introduction to the three distinct modes of GitHub Copilot and a practical guide for integrating them effectively into your workflow.

Get insights on the latest trends from GitHub experts while catching up on these exciting new projects.

What to look for with each model and how to test them in your workflows—with tips, tricks, and pointers.

Ever wondered which AI model is the best fit for your GitHub Copilot project? Here are some things to consider.

We’ve tested integrating OpenAI o1-preview with GitHub Copilot. Here’s a first look at where we think it can add value to your day to day.