Beyond Prompt Engineering: The Evolution of Reasoning in Advanced Large Language Models

Author(s)	Nan Wu
Country	United States
Abstract	This paper explores the evolving role of prompt engineering as large language models (LLMs) develop enhanced intrinsic reasoning capabilities. Initially essential for effective model performance, explicit prompting techniques are becoming less crucial with advanced models like GPT-4.5 and DeepSeek R1. Benchmark analyses indicate that intrinsic reasoning now solves most reasoning tasks efficiently, though explicit prompting still provides incremental benefits in specialized scenarios. Future directions emphasize intrinsic reasoning improvements, automated prompting strategies, and refined evaluation methods, marking a fundamental shift in leveraging LLMs.
Keywords	Prompt Engineering, Intrinsic Reasoning, Large Language Models, Chain-of-Thought, Benchmarks
Field	Engineering
Published In	Volume 16, Issue 1, January-March 2025
Published On	2025-03-09
Cite This	Beyond Prompt Engineering: The Evolution of Reasoning in Advanced Large Language Models - Nan Wu - IJSAT Volume 16, Issue 1, January-March 2025. DOI 10.71097/IJSAT.v16.i1.3719
DOI	https://doi.org/10.71097/IJSAT.v16.i1.3719
Short DOI	https://doi.org/g9fmwd

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