Research and Analysis of Prompt Engineering Technology Systems Based on Large Language Model Generation Tasks

Abstract

Due to the rapid development of artificial intelligence, prompt engineering technology has become a key technology for the development of Large Language Models in the field of generation tasks. Although the existing reviews have listed various technologies in detail, they still lack an analysis of the inherent logic and evolution laws among the technologies. Therefore, this article classifies the core issues that the technology solves, namely the functional goals, establishes the connection between the technology and the core issues, and presents the development path of the technology. First, let’s introduce the basic prompt class to achieve something from nothing and solve the problem of task understanding. Then elaborate on how structured reasoning classes deal with logical reasoning problems. In this category, it is further divided into two subcategories: linear reasoning and nonlinear reasoning. Then, it discusses how the hallucination-correcting category overcomes the problems of knowledge deficiency and hallucinations. Finally, it explores how the automation optimization category can focus on the efficiency of manual design and promote the evolution of technology towards scale and industrialization. In the future, engineering technology will move towards a more intelligent direction, achieving a paradigm shift in human-computer interaction.