Natural-language-to-SQL unlocks data for everyone—when it’s designed with care. Anchor the system on a semantic layer that defines metrics, joins, and filters; map synonyms and business terms to columns and tables. Constrain generation to certified schemas, and pre-validate queries for dangerous patterns (Cartesian joins, unbounded scans). Offer clarifying prompts when intent is ambiguous, and return citations and sample rows so users can verify results. Collect feedback on the usefulness and correctness of models to retrain and refine synonyms over time. Finally, prioritize security by enforcing row-level policies, redacting sensitive fields, and logging queries for audit purposes. Done right, NL to SQL enables speed of insight without sacrificing governance or performance.