Have you ever pasted a JSON payload into ChatGPT and asked it to generate a TypeScript interface or Go struct? Usually, it works. But sometimes, it decides to be "helpful" and changes your user_id to UserId , or completely forgets an optional field. In a production CI/CD pipeline, this kind of AI hallucination is a nightmare. I got tired of this, so I built TypeFlow : A developer tool that converts JSON, SQL, or YAML into 16+ languages instantly. But the real secret isn't just AI—it's a Hybrid Architecture . The Problem: AI is smart, but unpredictable When dealing with Data Transfer Objects (DTOs), schemas, and type definitions, you need 100% deterministic output . If an AI "guesses" a type wrong, your app crashes. Legacy tools like QuickType are fully deterministic but feel outdated and struggle with broken syntax. Modern devs just use AI, but sacrifice reliability. The Solution: The Hybrid "TypeFlow" Engine I wanted the absolute reliability of a compiler, mixed with the "magic" of an LLM.…