Rachel Kang

Our monthly cloud bill went up a lot after we put a big customer support chatbot into action. This chatbot answered every message that came in using a model that wasn't optimized. We solved the problem by sending ninety percent of the questions to a smaller system that used caching before using the expensive language model. Monthly costs went down by sixty-five percent. There was no drop in how happy customers were or in how good the answers were. Always have a simple filter in front of big models to handle simple questions better. Check how tokens you use every day and save the answers that come up often. This helps keep your profits safe as more people use the service. How do you handle the costs, for your AI features?

I flip-flop on this every week. Some AI drafts are honestly better than what I'd write at 6pm on a Friday. Others sound fine but are subtly wrong, and those are the scary ones.

Stack Overflow's 2025 survey found more devs distrust AI output accuracy (46%) than trust it (33%). Feels about right for customer emails too.