Can we talk about the model drift that tanked my support bot at 2am on a Tuesday?
Honestly, I woke up to 47 angry tickets because my fine-tuned support bot started giving made-up refund policies overnight. The training data looked fine when I checked it on Sunday, but by Tuesday the model was confidently wrong on about 30% of replies. I rolled back to the previous checkpoint on Thursday and banned auto deploys without a canary test first. Ngl it was rough, has anyone here set up drift alerts that actually fire before users notice the mess?
Oh man, been there. What finally worked for me was tracking the spread of the bot's replies each day and setting an alert for when it starts sounding too sure of itself, that caught the drift a good day before users did.