Fix Your AI Slop Problem by Giving Reviewers Credit (danunparsed.com)

A recent discussion highlights the challenges of code review processes in the age of AI, revealing that human reviewers often serve as mere proxies for AI evaluations. The issue stems from developers submitting code without fully understanding it, relying instead on AI tools that may overlook critical errors, as demonstrated by a recent bug involving a printer in a specific code branch. Despite the human reviewer’s role, reliance on AI can lead to overlooked issues, undermining code quality and accountability. To address this, a proposed solution encourages teams to formally recognize code reviews as tasks in sprint boards, ensuring reviewers receive credit for their efforts. This change fosters a culture that emphasizes the importance of thorough human review, as it highlights the time and effort involved in checking code. By valuing review contributions alongside feature development, organizations can improve code quality and mitigate the risks associated with automated checks, ultimately enhancing collaboration and responsibility within the AI/ML community.