Compilable Pseudocode Proposed as Fix for AI-Generated SQL Logic Errors

Developers and data analysts increasingly rely on AI tools to generate SQL queries, but the resulting code often executes without errors while producing logically incorrect results. A key concern is that syntax checkers cannot catch these semantic mistakes, forcing reviewers to manually trace through complex query logic to verify correctness. The core issue is that AI models generate code through probabilistic prediction rather than deterministic logical reasoning, meaning even well-specified prompts cannot guarantee accurate output. One proposed solution is to make specifications formal and compilable, so a deterministic compiler — rather than an AI model — handles the translation to executable code. This approach aims not to reduce hallucination rates incrementally but to eliminate the guesswork entirely by removing AI from the final code-generation step.