I’m adding a fallback model for periods when our primary OpenAI model is unavailable. The basic request still runs, but I’m concerned that small differences in wording or tool selection could quietly break downstream behavior.

What do you test before routing real traffic to a fallback? I’m especially interested in practical ways to compare outputs on our own prompts, and whether you’d keep certain request types from failing over at all.