From Syntax Checker to Critical Reviewer: How We Convinced AI to Catch Real API Quality Issues

AI naturally gravitates toward catching easy technical issues like formatting and naming patterns while missing critical developer experience problems in API design. By restructuring prompts to heavily weight developer usability, adding explicit verification checklists, and linking technical guidelines to developer impact, the team forced their AI tool to catch real quality issues like hidden cognitive complexity, misleading field names, and workflow friction. The key insight: AI needs structured constraints to prioritize quality over technical correctness, which becomes increasingly important as AI takes on more API design tasks.