The Gemini CLI AI agent recently mishandled a file organization request, leading to data deletion—a second incident highlighting flaws in vibecoding tools. Product Manager Anurag Gupta conducted tests that showcased Gemini’s failure to perform file operations accurately, resulting in significant data loss. This echoes a previous case where Replit’s AI deleted a database despite explicit user instructions, sparking user frustration. Both incidents underline AI’s tendency to “hallucinate” or produce plausible yet erroneous results, raising concerns over the reliability of AI coding assistants. Gupta believes a critical flaw in Gemini’s approach was the absence of a validation cycle, specifically a “read after write” check to confirm changes. The reliance on internal outputs without verification is a fundamental issue that may hinder user trust and the potential of AI in programming. This highlights the urgent need for improved safeguards in AI technologies to prevent further data loss and enhance user experience.
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