There is a surprisingly common use case for "quick and dirty univariate time series forecasts" that are basically equivalent to giving a small child a pencil, a

There is a surprisingly common use case for "quick and dirty univariate time series forecasts" that are basically equivalent to giving a small child a pencil, and asking them to draw out the trendline. The now-deprecated Prophet model from Facebook (which was just some GAM) was often used for this. Auto-ARIMA models, ETS etc are also still really commonly used. I also see people try to use boosted trees, or deep learning stuff like DeepAR or N-BEATS etc even though it's rarely appropriate for their 1k-datapoint univariate time series, just because it gives off the impression of serious methodological work. There are a lot of use cases in business were what's needed is just some basic reasonable-ish forecast. I actually think this new model is really neat because it completely dispenses with the pretense that we're doing some really serious and methodologically-backed thing, and we're really just looking a basic curve fit that seems pretty reasonable with human intuition.