How do you keep AI-generated code from falling apart when you change the database or API mid-project?

Developers building applications with AI tools like Cursor, Claude, or Lovable face challenges in maintaining code integrity as projects evolve. A key concern is preventing AI-generated code from becoming inconsistent when database or API changes occur mid-project. Strategies are needed to manage these changes effectively and ensure the AI-generated components remain functional and aligned with the updated project architecture.

This discussion uniquely focuses on the practical challenge of maintaining AI-generated code integrity when core project components like databases or APIs change, unlike broader talks on AI code generation.