Democratizing Software Development: A Review of Generative AI’s Impact on Freelance Engineering and Code Security
DOI:
https://doi.org/10.5281/zenodo.19918284Keywords:
Generative AI, Software Engineering, Freelance Economy, Code Security, LLM Vulnerabilities, GitHub Copilot.Abstract
The software engineering landscape is currently navigating a pivotal transformation driven by the integration of Large Language Models (LLMs) and Generative AI (GenAI) into the development lifecycle. This review article examines the dual impact of these technologies on the freelance economy and software security. While industry data from 2024–2025 indicates that GenAI tools can accelerate coding tasks by up to 45%, they simultaneously introduce significant risks, including the propagation of vulnerable code patterns (such as CWE-787 and CWE-89) and the erosion of entry-level opportunities. We analyze how the role of the freelance developer is shifting from manual syntax construction to "AI-assisted system architecture," necessitating a fundamental re-evaluation of computer science education and freelance business models. This paper argues that while the barrier to entry for coding has lowered, the barrier to competence regarding security and architecture has risen.
References
Stack Overflow, "AI vs Gen Z: How AI has changed the career pathway for junior developers," Stack Overflow Blog, Sep. 10, 2025.
A. Minkiewicz, "The Impact of Generative AI on Software Engineering Activities," U.S. Department of Homeland Security Report, Dec. 2024.
MIT Sloan, "How generative AI affects highly skilled workers," MIT Sloan Ideas Made to Matter, Feb. 2024.
Endor Labs, "The Most Common Security Vulnerabilities in AI-Generated Code," Endor Labs Research Blog, Aug. 2025.
Y. Zhang et al., "Security Attacks on LLM-based Code Completion Tools," Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI-25), 2025.
CIO Magazine, "Demand for junior developers softens as AI takes over," CIO.com, Sep. 2025.
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Copyright (c) 2025 Mr. Tayabur Rahman Laskar (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain copyright. Licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/4.0/ (CC BY 4.0 deed)
