Ok, but why did they chose Sonnet in the first place? Couldn't they have chosen Haiku or GPT Luna or maybe even some small cheap Chinese model?
If you think the former is a likely hypothesis, then why did you even click on TFA?
As for your question, seeing what others are doing helps one decide both what to do and what not to do.
I tried this with an AI subtitle translator thing I built for myself. Mid-tier models were considerably cheaper but "reasonably good" doesn't cut it in translations, the output language was too janky or used the wrong words. I had to bump it to Sol level (at the time) to get "good / very good" output, which was enough for something I intended to use once.
After that, I'm guessing it was just fairly low priority to update a working system. Amazon's net income last quarter was >$20B. Saving millions is huge on the scale of one or two engineers spending a week tackling it, but it's too small for the organization to make it a big initiative. By the time engineers decided to update it, decision models like Jev were popular and are naturally a better fit for the task than an LLM.