GitHub AI: Using AI in Your Development Workflow (video)

Use AI with GitHub: Copilot, code scanning, and third-party quality tools. Privacy, permissions, and human review of generated code.

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GitHub AI: Using AI in Your Development Workflow. Here's the short version.

“GitHub AI” can mean GitHub’s own AI features (such as Copilot and security scanning) or third-party tools that connect to GitHub repositories.

GitHub-native AI and security features. GitHub Copilot provides AI-assisted completion in supported editors. Always verify feature names and limits on https://docs.github.com — product names change over time.

Third-party AI and quality tools on GitHub repos. IDE assistants editing code locally, then pushing to GitHub. CI workflows running linters and tests on pull_request events. Hosted static analysis (e.g. CodeInspector) after connecting GitHub or scanning public URLs. PR comment bots — evaluate privacy and signal quality before enabling.

Permissions and privacy. Grant minimum OAuth scopes. Understand whether code leaves your tenant for model inference. Review generated code before merge. Use branch protection and required checks where appropriate.

Want to find these issues in your own code? Connect your GitHub repository to CodeInspector. You'll get findings with the file, line, severity, and a recommended fix, plus HTML and PDF reports for your team. Start free at codeinspector.app.

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