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
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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.