GitHub Copilot

GitHub Copilot is an AI coding assistant and agentic development tool built into the GitHub ecosystem, popular IDEs, and the command line. It targets professional developers, teams, and enterprises that want to speed up coding, code review, and operations without leaving their existing tools. Rather than being a generic chatbot, it focuses specifically on software development workflows.

You interact with Copilot through your editor (VS Code, Visual Studio, JetBrains IDEs, Xcode, Neovim, and more), within GitHub itself, and via a dedicated CLI for the terminal. According to GitHub’s materials, you can choose from several large language models (including Haiku 4.5, GPT-4.1, GPT-5 mini, and models from Anthropic, Google, and OpenAI) and use built-in GitHub Copilot agents, your own custom agents, or third-party agents. Getting started is done via a GitHub account and installing the appropriate extensions or integrations.

Copilot positions itself as an “AI accelerator for every workflow,” moving beyond inline suggestions to more autonomous behavior. It can take GitHub issues, write code, create pull requests, and respond to feedback in the background, and it can plan and execute complex terminal workflows using your repository context. For teams, features like Copilot Spaces and enterprise agent management aim to turn it into a shared project expert with centralized governance.

GitHub Copilot is notably more agentic than traditional code-completion tools: it doesn’t just suggest lines of code, it can be assigned issues, draft implementations, open PRs, and iterate based on review comments. The terminal integration can plan and run multi-step shell workflows using natural language, which is powerful if you’re already committed to GitHub-based development. The wide IDE support and model choice are strong points, and enterprise features like audit logs, MCP server controls, and a dedicated trust center show a focus on governance and security.

However, Copilot is tightly coupled to GitHub and developer workflows; it’s not a general-purpose personal assistant and won’t be useful outside software engineering contexts. Details like exactly how long context is retained, how custom agents are configured, and the depth of project "expert" behavior in Spaces aren’t fully clear from the public marketing page. Privacy, data handling, and responsible AI practices are documented separately in the GitHub Copilot Trust Center, so you’ll need to review that if compliance is a concern. Non-developers, teams not using GitHub, or organizations that require fully on-premise or open-source solutions may find this tool a poor fit.