Steve Jobs: Pioneering AI in Software Engineering

Authors

  • Priyadharasini M Assistant Professor, Computer Science and Engineering, SRM Valliammai Engineering College Kattankulathur, India. Author
  • Sriram S N UG Student, Computer Science and Engineering, SRM Valliammai Engineering College Kattankulathur, India. Author
  • Sudhar Aathith T UG Student, Computer Science and Engineering, SRM Valliammai Engineering College Kattankulathur, India. Author
  • Vigneshwaran N UG Student, Computer Science and Engineering, SRM Valliammai Engineering College Kattankulathur, India. Author

DOI:

https://doi.org/10.47392/IRJAEH.2024.0116

Keywords:

Natural language processing, Software Engineering, AI, Agile model, Waterfall model, LLM, SDLC

Abstract

"STEVE JOBS: Pioneering AI in Software Engineering" presents a revolutionary approach to software development, integrating large language models (LLMs) into traditional methodologies. This paradigm, inspired by the visionary leadership of Steve Jobs, leverages LLMs to streamline the software development lifecycle (SDLC), incorporating both the waterfall model and agile methodology. The implementation involves the orchestration of software agents, representing various roles in the development process, fostering collaborative dialogue through natural language communication. This innovative framework, inspired by the principles embodied by Steve Jobs, facilitates efficient decision-making and enhances productivity across all stages of software development. Moreover, empirical studies demonstrate the versatility and effectiveness of this approach, highlighting its potential to transform the software engineering landscape. By pioneering AI integration in software engineering, "STEVE JOBS" opens doors to new possibilities, heralding a future where technology and human ingenuity converge to drive unprecedented innovation.

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Published

2024-04-17

How to Cite

Steve Jobs: Pioneering AI in Software Engineering . (2024). International Research Journal on Advanced Engineering Hub (IRJAEH), 2(04), 823-829. https://doi.org/10.47392/IRJAEH.2024.0116

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