>>938969513
The majority of these issues are best managed on the basis of token inversion and concept understanding. Being able to identify a respective model and sampler's management of these things is something that requires technical knowledge. Without that knowledge everything is trial and error. E.g. you wouldn't try to use a new model of an unknown base with random prompts. You would experiment to understand the base first, then work from there. In reality all models have a known base, so you should be able to determine what data blocks are being used and what weights they have to best use the model.
Older gens using more "rudimentary" models can far exceed the output of modern models if their strengths are being played. Improper use of the best models will still produce slop.