Any text-to-SQL benchmark should address difficulties of real-world data stores

This brief article argues that current benchmarks for text-to-SQL AI models fail to account for the complexities and messiness of real-world enterprise data stores. It suggests that developers need more robust testing methods to ensure AI reliability in practical database environments.