AI-Assisted Coding in Industry: Practices, Risks, and Educational Implications
Published:Dec 30, 2025 04:39
•1 min read
•ArXiv
Analysis
This paper is significant because it bridges the gap between the theoretical advancements of LLMs in coding and their practical application in the software industry. It provides a much-needed industry perspective, moving beyond individual-level studies and educational settings. The research, based on a qualitative analysis of practitioner experiences, offers valuable insights into the real-world impact of AI-based coding, including productivity gains, emerging risks, and workflow transformations. The paper's focus on educational implications is particularly important, as it highlights the need for curriculum adjustments to prepare future software engineers for the evolving landscape.
Key Takeaways
- •AI-based coding tools are leading to productivity gains and lower barriers to entry.
- •Development bottlenecks are shifting towards code review.
- •Concerns exist regarding code quality, security, and the erosion of foundational skills.
- •Education needs to adapt to focus on problem-solving, architectural thinking, and code review, integrating LLM tools.
Reference
“Practitioners report a shift in development bottlenecks toward code review and concerns regarding code quality, maintainability, security vulnerabilities, ethical issues, erosion of foundational problem-solving skills, and insufficient preparation of entry-level engineers.”