Recently, many teams are working on Text-to-SQL, ChatBI, or data analysis agents. An often underestimated issue is that SQL generated by LLMs should not be directly executed on production databases.
This article discusses a technical topic: explaining why syntactically correct SQL still requires catalog binding, name resolution, and semantic checks.
Key points:
Syntactic correctness does not guarantee semantic correctness.
Real catalog metadata is needed to resolve tables, columns, aliases, scopes, functions, and types.
This serves as a key technical bridge from SQL parsing to SQL semantic governance.
Original link: https://www.dpriver.com/blog/sql-semantic-validation-for-llm-generated-queries/?utm_source=dev&utm_medium=community&utm_campaign=ai_sql_governance_external_2026q2&utm_content=shenhuan_dev_sql_semantic_validation_for_llm_generated_queries
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