GitHub Copilot transforms the developer experience. Backed by the leaders in AI, Copilot provides contextualized assistance throughout the software development lifecycle, from code completions in the IDE to code explanations in GitHub and more. With Copilot elevating their workflow, developers can focus on more: value, innovation, and happiness.

Copilot enables developers to focus more energy on problem solving and collaboration and spend less effort on the mundane and boilerplate. That’s why developers who use Copilot report up to 75% higher satisfaction with their jobs than those who don’t and are up to 55% more productive at writing code without sacrifice to quality, which all adds up to engaged developers shipping great software faster.

Copilot integrates with leading editors, including Visual Studio Code, Visual Studio, JetBrains IDEs, and Neovim, and, unlike other AI coding assistants, is natively built into GitHub. Growing to millions of individual users and tens of thousands of business customers, Copilot is the world’s most widely adopted AI developer tool and the competitive advantage developers ask for by name.

GitHub Copilot has offerings for organizations and an offering for individual developers. The primary differences between the organization offerings and the individual offering are license management, policy management, and IP indemnity.

Organizations can choose between GitHub Copilot Business and GitHub Copilot Enterprise, which is coming in February 2024. GitHub Copilot Business primarily features GitHub Copilot in the coding environment - that is the IDE and CLI. In early-2024, it will also include GitHub Copilot in GitHub Mobile. GitHub Copilot Enterprise includes everything in GitHub Copilot Business and adds an additional layer of personalization for organizations as well as GitHub Copilot integrated into GitHub as a chat interface to allow developers to converse about their codebase and action buttons throughout the platform. GitHub Copilot Enterprise can index an organization’s codebase for a deeper understanding of the customer’s knowledge for more tailored suggestions and will offer customers access to GitHub Copilot Customization to fine-tune custom, private models for code completion.

GitHub Copilot Individual is designed for individual developers, freelancers, students, educators, and open source maintainers. The plan includes all the features of GitHub Copilot Business except organizational license management, policy management, and IP indemnity.

GitHub Copilot is trained on all languages that appear in public repositories. For each language, the quality of suggestions you receive may depend on the volume and diversity of training data for that language. For example, JavaScript is well-represented in public repositories and is one of GitHub Copilot’s best supported languages. Languages with less representation in public repositories may produce fewer or less robust suggestions.

GitHub Copilot is available as an extension in Visual Studio Code, Visual Studio, Vim, Neovim, the JetBrains suite of IDEs, and Azure Data Studio. GitHub Copilot is also supported in terminals through GitHub CLI. GitHub Copilot will soon be natively integrated into GitHub web and mobile.

GitHub Copilot is powered by generative AI models developed by GitHub, OpenAI, and Microsoft. It has been trained on natural language text and source code from publicly available sources, including code in public repositories on GitHub.

No, GitHub Copilot generates suggestions using probabilistic reasoning.

• When thinking about intellectual property and open source issues, it is critical to understand how GitHub Copilot really works. The AI models that create Copilot’s suggestions may be trained on public code, but do not contain any code. When they generate a suggestion, they are not “copying and pasting” from any codebase.
• To generate a suggestion, Copilot begins by examining the code in your editor—focusing on the lines just before and after your cursor, but also information in other files open in your editor. That information is sent to Copilot’s model, to make a probabilistic determination of what is likely to come next and generate suggestions.

You can visit the GitHub Copilot Trust Center for more information on these topics.

GitHub Copilot personal data from three categories of data: user engagement data, prompts and suggestions.

User engagement data
User engagement data is usage information about events generated when interacting with a code editor. These events include user edit actions (for example completions accepted and dismissed), error messages, and general usage data to identify user metrics such as latency and feature engagement. This information may include personal data, such as pseudonymous identifiers.

Prompts
A prompt is the collection of code and supporting contextual information that the GitHub Copilot extension sends to GitHub to generate suggestions. The extension sends a prompt when a user working on a file, pauses typing, or uses a designated keyboard shortcut to request a suggestion.

Suggestions
A suggestion is one or more lines of proposed code and other output returned to the Copilot extension after a prompt is received and processed by the AI models that power Copilot.

No, GitHub Copilot does not use Prompts or Suggestions to train AI models. These inputs are not retained or utilized in the training process of AI models for GitHub Copilot.

GitHub processes user engagement data as a process to provide the service, which includes:

• To deliver functional capabilities as licensed, configured, and used by Customer and its users, including providing personalized user experiences;
• Troubleshooting (preventing, detecting, and repairing problems); and
• Keeping Products up to date and performant, and enhancing user productivity, reliability, efficacy, quality, and security.

Per Customer instruction in the GitHub DPA, GitHub processes UED as a data controller for the purposes of:

• Billing and account management;
• Compensation such as calculating employee commissions and partner incentives;
• Aggregated internal reporting and business modeling, such as forecasting, revenue, capacity planning, and product strategy; and
• Aggregated financial reporting.

Prompts

• Prompts are discarded once a suggestion is returned. Copilot Individual users may opt to allow GitHub to retain prompts.

Suggestions

• Suggestions are not retained by GitHub. Copilot Individual users may opt to allow GitHub to retain prompts.

User engagement data

• User engagement data is retained by GitHub for 24 months.