I find myself intrigued by the level of understanding our guests possess regarding artificial intelligence. The critiques directed at AI models appear to stem from a misapprehension of their capabilities. It is essential to recognize that the generation of code from scratch by AI necessitates a contextual foundation, much like the process a developer goes through. Without access to documentation or an understanding of how various structures are intended to interact, crafting code becomes a significantly more challenging endeavor. It is my contention that, when equipped with appropriate context, AI can indeed produce code that surpasses that of many developers. My assertion is not baseless; through my personal experimentation with various Large Language Models beyond merely Copilot, I’ve observed remarkable performance in code generation tasks.

To further illustrate this point, I propose a challenge: a coding interview, comparing the problem-solving efficiency between human participants and ChatGPT 4.0. Such a comparison would not only serve as an effective benchmark but also potentially reshape our understanding of AI’s capabilities in software development.