The rise of AI-driven code generation tools like GitHub CoPilot, Cursor AI, etc., have revolutionized software development by automating routine tasks and accelerating coding processes. However, a gap persists between generated code and real-world software engineering. These tools often lack domain-specific understanding and contextual awareness, leading to suboptimal solutions for real-world applications. Addressing this gap requires integrating software engineering best practices into code generation frameworks and fostering human-AI collaboration. I will discuss the challenges and potential solutions for aligning code generation with the broader demands of software engineering.

Baishakhi Ray is an Associate Professor of Computer Science at Columbia University. She works at the intersection of AI, Software Engineering, and Security. She received her Ph.D. degree from the University of Texas, Austin. She has received the IEEE TCSE Rising Star, NSF CAREER, IBM faculty, and VMWare Faculty awards. She is also an Amazon Visiting Academic. Her research has been acknowledged by many Distinguished Papers awards including FSE’17, ASE’22, ISSTA’23, the ICSME Most Influential Paper award, and has also been published in CACM Research Highlights and has been widely covered in trade media.