A lot of teams start their LLM stack with one model string in application code. That is fine for prototypes. It becomes painful once multiple products, customers, background jobs, and fallback paths all share the same AI budget.
At that point, an OpenAI-compatible gateway should not just be a convenience proxy. It should become a control plane: the place where routing, quotas, cost attribution, keys, and failover are managed consistently.
Here is the checklist I use when evaluating whether a gateway setup is production-ready.
1. Keep the SDK surface stable
Your application should not need to know every provider-specific header, endpoint, or auth detail.
