I worked on a small AI image tool project, and the biggest lesson I learned is: the first step really isn’t picking which model—it’s figuring out what scenario the user is in, how fast they need an image, and what kind of image they actually want.
The model is just a replaceable part in the backend. Early on, we dumped all our energy into comparing image quality across different models, but when we launched, we found out users couldn’t stand waiting thirty seconds, and they didn’t care about how detailed the output was. Later, we cut features, added caching, and made the UI dead simple—that’s when retention finally picked up. Piling on models is the last thing you should focus on first.