AI coding assistants excel in tasks like generating boilerplate code, simple functions, documentation, and debugging, but have limitations in complex coding scenarios. While 63% of developers leverage AI for productivity, reliance can increase technical debt and produce quality issues. AI performs best with straightforward code and popular libraries but struggles with novel or complex projects. Engineering leaders must understand AI's strengths and weaknesses to avoid pitfalls, as improper use can lead to wasted time and debugging challenges. Overall, AI tools are rapidly evolving, promising increased software development efficiency but requiring careful oversight.
https://www.infoworld.com/article/3973969/knowing-when-to-use-ai-coding-assistants.html