AI-powered frontends like V0 promise rapid development, but they create a hidden integration trap. Developers can build interfaces in minutes, yet these tools generate code assuming a perfect backend. When your API returns different field names, the entire app breaks silently. The frontend expects `seats` while the backend sends `seat_count`, causing undefined values and failed flows.

A custom backend is non-negotiable for enforcing consistent data contracts. You control the JSON structure, business logic, and security validation. AI tools cannot secure endpoints or apply domain-specific rules. Without this foundation, scaling becomes impossible as you add user roles, third-party integrations, and complex workflows. The backend must be the single source of truth.

The solution is building a Flask API that normalizes responses to match frontend expectations. Define your contracts first, then let AI accelerate the UI layer. This approach prevents subtle bugs and security holes that emerge when relying solely on generated code. Treat AI as a powerful assistant, not a replacement for architectural control.