AI is increasingly contributing to software development, but many teams struggle with quality assurance as their processes haven't adapted. The core issue isn't the AI's capability, but the lack of a robust engineering framework around AI agents. This includes insufficient specifications, limitations, independent testing, security checks, and reliable artifact pipelines. AI
IMPACT AI code generation requires robust engineering processes to ensure quality and prevent vulnerabilities.
RANK_REASON The cluster summarizes a webinar presentation about the challenges of maintaining code quality when using AI in software development.
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