Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review

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Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models (2024, background): “Prompt engineering refers to the process of designing and refining the input given to an AI system, particularly in the context of generative models, to achieve specific or optimized outputs [84, 85, 86].”
A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT (2023, background): “…Section III describes 16 prompt patterns that have been applied to solve common problems in the domain of conversational LLM interaction and output generation for automating software development tasks; Section IV discusses related work; and Section V presents concluding remarks and lessons learned.”
A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications (2024, unknown): “The notion of prompt engineering was initially investigated and popularized in the LLMs [Liu et al. , 2023], [Tonmoy et al. , 2024], [Chen et al. , 2023] later extended to VLMs [Wu et al. , 2023], [Bahng et al. , 2022].”
AutoSurvey2: Empowering Researchers with Next Level Automated Literature Surveys (2025, unknown): “Collectively, these design strategies ensure that the generated survey maintains scholarly rigor, stylistic consistency, and factual reliability across all components of the automated writing pipeline (Chen et al., 2023c; Li, 2023).”