Learn how to use AI Guardrails to secure your AI-assisted development workflow.
Learn about tool-specific configuration files for AI assistants.
Automated quality checks that run before every commit.
GitHub Actions for security scanning, testing, and quality validation.
Scripts to enable/disable hooks and CI jobs, manage configuration.
Multi-layer security strategy: AI rules, pre-commit hooks, and CI scanning.
Single source of truth approach and formatting standards.
Prevent context loss and circular debugging with WORKLOG.md implementation tracking.
AI coding assistants like Cursor, Claude, and GitHub Copilot are powerful productivity tools, but without proper guardrails, they can introduce security vulnerabilities, inconsistent code, and technical debt. AI Guardrails provides a comprehensive framework to ensure AI-generated code meets professional engineering standards.
Never commit secrets, enforce proper credential handling
Automatic formatting, linting, and validation
Clear, up-to-date documentation standards