How to Integrate Multiple AI Generation APIs Without Rebuilding Your Architecture Every 6 Months

AI generation APIs are moving faster than any other part of the stack right now. A model that doesn't exist in January is the production standard by June. A model that leads every benchmark in Q1 is deprecated by Q3. If you're building an application that depends on AI video, image, or art generation - and you've integrated directly against a single model API - you've built a dependency that will require architectural intervention within months, not years. I know because I built that architecture first. Then rebuilt it. Then rebuilt it again. Eventually I stopped rebuilding and built the abstraction layer that makes rebuilding unnecessary. This is what that abstraction layer looks like, why each decision was made, and the specific patterns that prevent AI generation API churn from becoming a permanent engineering liability. The Problem With Direct Model Integration Direct integration against a single AI generation API looks like this: // Direct integration - brittle const response = aw