For some kinds of forecasting it doesn't need to be exactly accurate - eg say you are forecasting traffic for how to scale a load balancer, it can be a bit off it will just cost you a little and you can adjust after - a lot of feedback systems dont need full accuracy. You wouldnt use this to forecast whether to buy shares. It basically replaces various traditional curve fitting tools. If you need a really good forecast yes you are going to build a domain model. At least this is my understanding...

Agree on the share-buying point. I keep a side project that tracks about twenty published bitcoin price models side by side and grades each one on its own forecast record. Two lessons carried over to any time-series benchmark for me. First, freeze every forecast as it stood the day it was made; refitting on later data flatters everything. Second, put the naive baseline (tomorrow looks like today) in the same table. The best-known model in my set, stock-to-flow, sits more than 100% off over the past year, and it looked brilliant in backtests. A 0.03 gain means little to me until I see it next to persistence.