Redefining Antenna Design Education: ChatGPT as a copilot for engineering students [Education Corner]

The integration of artificial intelligence (AI) in engineering education is rapidly evolving, presenting both opportunities and challenges. This study explores the use of ChatGPT in a graduate-level antenna design course, where students were encouraged to leverage AI for problem solving, design exploration, and performance optimization. Unlike traditional coursework, this experiment aimed to observe their natural brainstorming with AI in an open-ended engineering scenario. The findings reveal that AI is recognized as valuable for ideation, literature review, and coding support but remains limited in technical accuracy, iterative optimization, and complex problem solving. Students successfully used AI to generate antenna design insights, define technical parameters, and explore alternative configurations, but AI-generated outputs required significant validation, particularly in equation derivations, simulation workflows, and MATLAB implementations. To guide effective AI integration, this article proposes a possible definition of the large language model (LLM) persona and a decalogue of AI best practices, providing structured strategies and prompts to balance AI automation with human expertise, fostering a realistic copiloting model (human in the loop) for future AI-enhanced engineering education.