My AI model broke down 2 times in 8 days and it made me think differently about choosing one

Picking the AI model is a crucial decision for my product, and I really underestimated how hard it would be to pick one.

Before launch, I was considering things like:

• Will users trust something that processes their messages with a model they have never heard of?

• What is the real uptime record, versus the claimed one?

• Do I go cheap/free, or pay more for something that will last longer?

• Self-hosted? Or just ride on someone else’s frontier model and take their roadmap?

  I took a solution and moved on, as you do when there are fifty other decisions to be made. And then on July 9th everything just stopped. There were no warnings I could see—I spent hours debugging my own code before realizing the model itself was the problem. It turns out it was being decommissioned that October, and apparently a silent outage is how that gets communicated.
  
  I re-engineered the architecture to always have a backup model running in parallel, which quietly nibbled into margins I had already modeled carefully. Then again, same thing happened July 16. I don't think I've really worked this out so much as I've gotten better at taking it in when it happens again.
  
  For other founders building on someone else's AI model -- do you build in redundancy from day one or did it take getting burned once before you took it seriously?