AI coding tools shift focus to quality and security metrics for dev teams

As AI coding tools accelerate software development, traditional metrics like velocity may become less indicative of true progress. Experts suggest focusing on KPIs that measure quality, security, and maintainability, such as Mean Time To Detect Defects, Defect Escape Rate, and Change Failure Rate. These metrics help ensure that increased code generation speed does not lead to a rise in technical debt or security vulnerabilities, emphasizing the need for robust human oversight and review processes. AI

IMPACT Shift in development team KPIs towards quality and security metrics to mitigate risks associated with AI-generated code.

RANK_REASON Article discusses implications of AI tools on development practices and metrics, offering expert opinions rather than announcing a new product or research.

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• ActiveState
• AI
• Change Failure Rate
• CodeROI
• Defect Escape Rate
• Julius Silvert, Inc.
• Mean Time To Detect Defects
• Mean Time To Remediate
• Qube Research & Technologies
• SecureFlag
• Soal Labs
• Synera

• product
• other

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