  Creating written products is essential to modern life, including writings
about one's identity and personal experiences. However, writing is often a
difficult activity that requires extensive effort to frame the central ideas,
the pursued approach to communicate the central ideas, e.g., using analogies,
metaphors, or other possible means, the needed presentation structure, and the
actual verbal expression. Large Language Models, a recently emerged approach in
Machine Learning, can offer a significant help in reducing the effort and
improving the quality of written products. This paper proposes a new
computational approach to explore prompts that given as inputs to a Large
Language Models can generate cues to improve the considered written products.
Two case studies on improving write-ups, one based on an analogy and one on a
metaphor, are also presented in the paper.
