arXiv:2509.14250v2 Announce Type: replace Abstract: This paper explores prompts and prompting in large language models (LLMs) as dynamic semiotic phenomena, drawing on Peirce's triadic model of signs, his nine sign types, and the Dynacom model of communication. The aim is to reconceptualize prompting not as a technical input mechanism but as a communicative and epistemic act involving an iterative process of sign formation, interpretation, and refinement. The theoretical foundation rests on Peirce's semiotics, particularly the interplay between representamen, object, and interpretant, and the
This paper reflects a growing academic and industry focus on understanding and optimizing human-AI interaction, particularly at the fundamental level of prompt engineering.
A deeper semiotic understanding of prompts could lead to more robust, reliable, and interpretable AI systems, impacting their development and deployment across various sectors.
Prompting is reframed from a purely technical input to a communicative and epistemic act, suggesting richer theoretical foundations for future AI design paradigms.
- · AI researchers
- · LLM developers
- · Human-computer interaction specialists
- · Naïve prompt engineering approaches
Improved theories for prompt design and AI alignment through a semiotic lens.
Development of new AI architectures and interaction models that explicitly integrate semiotic principles.
More intuitive and powerful AI agents capable of nuanced, context-aware communication with humans.
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Read at arXiv cs.CL