Vol. 3 No. 1 (2023): January−June 2023
Short Articles

Redefining Software Architecture: Challenges and Strategies for Integrating Generative AI and LLMs

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  • Aditya S Shethiya
Aditya S Shethiya
University of Bridgeport, Connecticut, USA

Published 2023-02-15

Keywords

  • Generative AI,
  • Large Language Models,
  • Software Architecture,
  • Intelligent Systems,
  • Prompt Engineering

How to Cite

Shethiya, A. S. (2023). Redefining Software Architecture: Challenges and Strategies for Integrating Generative AI and LLMs. Spectrum of Research, 3(1). Retrieved from https://spectrumofresearch.com/index.php/sr/article/view/22

Copyright (c) 2023 Spectrum of Research

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

The rise of generative AI and large language models (LLMs) is reshaping the fundamentals of software architecture. Unlike traditional deterministic systems, LLM-integrated applications require architectural patterns that accommodate probabilistic reasoning, context-aware interactions, and dynamic adaptability. This paper explores the evolving landscape of software engineering in the age of generative intelligence, highlighting the unique challenges in model integration, system reliability, data management, scalability, and ethical governance. Through a detailed analysis of architectural shifts, it presents strategic frameworks and best practices that balance innovation with control, offering actionable insights for designing intelligent, secure, and future-ready systems.

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