The Cold Start Problem in AI Personalization
A user signs up for your AI writing assistant. They type their first message. Your system has exactly one data point — and it has to decide: formal or casual? Verbose or terse? Technical depth or accessible overview? Most systems punt and serve a generic default. A few try to personalize immediately. The ones that personalize immediately often make things worse.
The cold start problem in AI personalization is not the same problem Netflix solved fifteen years ago. It is structurally harder, the failure modes are subtler, and the common fixes actively introduce new bugs. Here is what practitioners who have shipped personalization systems have learned about navigating it.
