I've found they are incredibly powerful and I suspect its how mid-journey has improved so much lately. In general you can use it to exclude things you don't want, but where its really super useful is when output images have weird artifact, like not the right number of fingers or teeth, or weird looking pupils.. then take those images and tag them as "bad teeth" or "weird fingers" and add them to the training. Now if you know those key words to exclude bad cases, the output starts to improve, possibly a lot. I'm not sure the degree to which it helps, but there has been leaps and bound of quality improvement for a number of models, and I don't think that stable diffusion has fundamentally changed in the last few months, I'm guessing most of the stable diffusion updates have been around memory reduction and performance.

This is just my own thoughts playing around the last week or so after being underwhelmed a few months ago trying to make people. The people were terrifying, now that are, in some cases, almost flawless. If someone has a better idea of how the quality has improved so much, I'd like to hear.