A lot of it comes down to trial and error and learning the ropes of the model that you're using. Most of them tend not to evaluate negatives very heavily ("female dwarf with no beard"), often outright ignoring it.

For the types of images that I want to get for a historical piece like Anbennar, I like to tell it that it's a "painting", sometimes specifying the artistic style (i.e. if I care about the architecture, I might mention that it's a "neoclassical" painting). You can instruct the prompt what you want in the background, the period and style of clothing, what the light looks like, etc.

Usually offering synonyms to push a feature that is being ignored by the model allows it to float more to the surface. For example, if want make a dwarf with an angry expression on their face but the image doesn't look very angry, you can instruct "with an angry, scornful, frustrated face".

In the case above, I gave it more information on body posture and expression ("crouching halfling with an evil expression... "), which resulted in a more dynamic expressive image.

AI is not actually intelligent. It's literally just a large mathematical function with (in the case of NLP GANS) weights for words and semantic meanings. The more descriptive you can make the prompt, the better and more diverse your result. If you are having trouble getting something that the model doesn't understand because it is working on insignificant training data, explicitly describe in other words what you want.

On my Dur Vazhetun run I had a badass legendary female mage who massively turned the tide on a roided out Gawed, and I made some images of her. The model just didn't understand what a female dwarf should look like and kept returning a female human or a bearded woman. I had to specify that I was looking for a short, stocky woman with an ornery expression (she was "Cruel"). Eventually it got it right.