Question: Can you recommend a tool that helps ensure AI-generated code meets high quality standards?

If you're looking for tools to ensure AI-generated code is of high quality, Sonar is a great option. It offers in-IDE analysis, self-managed static analysis and cloud-based analysis to ensure high-quality, secure code whether it's written by humans or generated by AI. Sonar integrates with many popular development tools like GitHub, Bitbucket, Azure DevOps and GitLab, and offers a free version with tiered pricing.

Another powerful option is SonarCloud, an online code review service that can be integrated with cloud DevOps services. It supports more than 30 programming languages and frameworks, offers automated analysis, clear go/no-go quality gates and results that are easy to understand. SonarCloud also includes developer security tools like secrets detection and static application security testing (SAST), so it can be used for technical debt and secure coding practices, including for AI-generated code.

For a more AI-centric approach, Metabob uses graph-attention networks and generative AI to improve code review, refactoring and debugging. It uses graph neural networks to spot problematic code and large language models to generate context-aware explanations and fixes. Metabob offers a free individual developer plan and customizable bug detection models, so it can be used to maintain legacy code and validate AI-generated code.

Korbit is another AI-based code review tool that can be integrated with GitHub pull requests for immediate and accurate feedback. It also offers a management dashboard for code quality insights, project status and developer performance. With its experience in reviewing pull requests and flagging problems, Korbit is designed to speed up the code review process and improve productivity, making it a good option for development teams.