The article explores the challenges faced by artificial intelligence (AI) in creating compelling narratives, particularly focusing on the characteristics of AI-generated texts that often depict anti-heroes and begin their stories from the earliest points in chronological order. These elements hinder the functionality of AI narratives compared to human storytelling. The introduction of narrative techniques is suggested as a solution to rectify these shortcomings and improve the quality of AI-generated content.

One of the key points made is the juxtaposition of traditional narrative techniques, particularly the 'in medias res' approach, against the 'ab ovo' method commonly utilized in AI-generated stories. The author argues that while AI tends to start from the beginning, engaging storytelling often immerses the audience directly into the action or conflict, bypassing lengthy introductions about the characters and setting. By incorporating narrative art into large language models (LLMs), the article posits that the potential for more engaging storytelling can be unlocked, thereby bridging some of the gaps between human and machine-created narratives.

Ultimately, the article advocates for the integration of narrative craft into AI systems to enhance their storytelling capabilities. It reflects on the interactions between humanity and technology, highlighting the essential need for storytelling as a means of capturing the complexities of human experiences, suggesting that the future of AI storytelling lies in its ability to convey depth and resonance through improved narrative structures.