Scaling Multi-Provider AI Platforms: A Three-File Architecture Pattern

This pattern solves a key challenge for multi-provider AI platforms: adding new LLM providers without code rebuilds or application changes. By combining database-driven architecture with offline fallback content, teams can scale to dozens of providers while maintaining reliability and simplifying maintenance. The approach is immediately valuable for AI education tools, comparison platforms, and any application supporting multiple AI services.