I don’t work with classic prompt engineering .. so I won’t provide a prompt.
I work with dynamics myself
Indeed, I also prefer to let people think for themselves and just give them inspirations. But I will give you a concept, because you have already developed something that goes exactly in this direction
You wonder what? Try the given name “Dubhchobhlaigh”, 美智子, Barack, … or “Chastity”.
GPT-Image-2 specifically inserts a lot of text output. So a bias towards written-out names is seen.
A person’s name arbitrarily is no guarantee that the output is a picture of a person. I’ve picked from trials where we have a picture of a human along with their text, instead of greeting cards or infographics or maps of Africa.
I tried right from the start, a clause in the prompt - in this case (which is inherently not going to give what you are searching for in underlying name meanings): don’t copy the same Japanese person in every picture; give the “ko” portrait assignments uniqueness by underlying demographic usage by portrayable ethnotypes, etc.
Funny: Sakurako gets cherry blossoms, Yukiko gets snow, Ainuko: literally Ainu? etc. The model can’t help itself, like the “Bambi” or “Cherry” I showed before.