AI-generated JSON often looks valid but fails semantically, structurally, or logically in production. After 50,000+ generations, the author outlines a multilayer validation stack—required fields, type-specific checks, semantic rules, forbidden-content filters, and error-aware retries—that raises reliability from ~85% to 95%+ and prevents user-facing failures.
Why Your AI JSON Always Breaks (And How to Fix It) | HackerNoon
