How to use GitHub Code Quality to ship reliable code

GitHub introduces GitHub Code Quality (now generally available) and shows how CodeQL analysis plus AI-assisted findings and Copilot Autofix can surface and fix issues directly in pull requests, with rulesets to enforce quality gates at merge time.

Overview

The video covers GitHub Code Quality and how it helps teams catch reliability issues before they reach production by combining:

• Deterministic analysis with CodeQL
• AI-assisted findings
• Copilot Autofix suggestions proposed directly in a pull request

It also highlights using rulesets to enforce quality standards at the merge boundary.

Key capabilities mentioned

CodeQL-based analysis

• Uses CodeQL for deterministic analysis to identify issues.

AI-assisted findings

• Adds AI-assisted findings alongside CodeQL results to improve issue detection for software health and reliability.

Copilot Autofix in pull requests

• Copilot Autofix proposes corrections directly in the PR.
• Developers can review and commit fixes without leaving the pull request context.

Rulesets for quality gates

• Configure rulesets to enforce quality standards at the merge boundary.

Links

• GitHub Code Quality feature page: https://github.com/features/code-quality
• GA announcement (changelog): https://github.blog/changelog/2026-07-20-github-code-quality-is-now-generally-available/