GitHub Copilot is an AI-powered coding assistant that integrates into IDEs and GitHub, offering code completions, chat support, and agent-driven automation to streamline coding. Built by GitHub with OpenAI and Microsoft, it’s trained on public code and text, delivering context-aware suggestions that (dramatically) boost productivity. For instance, developers at companies like Shopify and Mercado Libre use it to cut through repetitive tasks, with studies showing up to 55% faster coding without quality loss. It supports Visual Studio Code, JetBrains, and GitHub’s own platform (obviously), making it versatile for solo coders and teams alike.

The tool’s strength lies in its features. Next Edit Suggestions tracks how code changes affect your project, ensuring consistency across files. The agent mode handles issues by planning, coding, and testing, producing pull requests via GitHub Actions. Copilot Spaces organizes project context, like docs and code, for tailored suggestions. The chat interface, powered by models like GPT-5 and Claude Opus 4.1, answers coding questions or explains code in real time. Code review catches bugs and vulnerabilities before submission, a feature that rivals like JetBrains’ AI Assistant don’t match in scope.

Compared to competitors, Copilot shines for GitHub users. Tabnine offers similar completions but lacks the agent mode and deep platform integration. Copilot’s free tier includes 2,000 completions and 50 chats monthly, while Pro and Pro+ plans unlock unlimited use and premium models. Pricing feels competitive, especially for teams already on GitHub, though enterprise plans add customization for larger organizations.

The tool isn’t perfect. Suggestions for niche languages like Rust can be less accurate due to limited training data, as noted in recent Reddit threads. The free tier’s limits may frustrate heavy users, and the chat interface requires some practice to use effectively. Some developers on X report occasional irrelevant suggestions, which can disrupt flow. Still, the code referencing filter helps mitigate risks of matching public code, a concern GitHub pegs at under 1% of suggestions.

A standout feature is Autofix, part of GitHub Advanced Security, which flags vulnerabilities like SQL injections with fix suggestions. This adds real value for security-conscious teams. Copilot’s ability to switch between models for speed or depth is another plus, though non-English prompts may yield weaker results due to English-heavy training data.

To get started, try the free tier to test compatibility with your workflow. Enable the code referencing filter for peace of mind, and use Copilot Spaces to boost suggestion accuracy. Experiment with the chat feature for quick code explanations, but always review suggestions manually. For teams, explore the Enterprise plan for codebase indexing. Copilot is a powerful ally, just keep your coding instincts sharp.