Abstract

Prompt Architecture represents a novel and systematic approach to the design and optimization of prompts within Conversational AI systems. This literature review synthesizes key developments, methodologies, and insights in the field, drawing from historical influences, recent advances, and current challenges. The review begins with an examination of early influences, such as Weizenbaum's ELIZA chatbot and Minsky's Frames Paradigm, and proceeds to explore modular prompting strategies, optimization techniques, and evaluation methods. Attention is given to innovative approaches, applications in conversational systems, user-centered design, knowledge representation, and ethical considerations. The review identifies existing gaps in the field, including the need for standardized benchmarks, inclusiveness, and ethical oversight. It concludes with a set of recommended actions for further research and development. The insights and recommendations provided in this review contribute to the maturation of Prompt Architecture as a robust and ethical methodology, with potential implications for the broader field of language model interaction and design.

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