analiza aiqbench

The article argues against relying on generative AI to autonomously fix broken data pipelines, emphasizing that such tasks require deterministic logic and rigorous testing rather than probabilistic model outputs. This perspective highlights a critical boundary in current AI deployment strategies, warning that using ML for infrastructure maintenance could introduce new failure modes instead of solving them. It serves as a cautionary note for engineers integrating AI into backend systems, urging a focus on traditional reliability engineering over automation hype.