App Development with Kotlin Multiplatform | Abdullah Zaiter & Urs Peter | Beyond Coding #187

AI Learning

AI tools can simplify learning for those with strong foundational knowledge, but they pose risks for newcomers. Patrick Akil expresses concern that new software engineers might rely too heavily on AI, potentially leading to a superficial understanding of technologies. Urs Peter agrees, noting that without a solid foundation, developers may become overly dependent on AI-generated code, which can be misleading 1. Abdullah Zaiter shares a humorous anecdote about AI's limitations in coding, highlighting the need for human oversight:

It's insane. Like ChatGPT would never accept not capturing the variable inside that loop.

--- Abdullah Zaiter

The discussion underscores the importance of maintaining a balance between leveraging AI and understanding the underlying principles of programming 2.

   

AI Frameworks

AI's ability to assist with new frameworks is limited, especially when technologies are rapidly evolving. Urs Peter points out that AI struggles with providing accurate advice for new frameworks like Kotlin Multiplatform (KMP) due to frequent changes and lack of extensive code examples 3. Patrick Akil adds that AI is more effective with established languages like JavaScript or Python, where it can draw from a wealth of examples. However, newer technologies present challenges for AI assistance, requiring developers to rely on their own understanding and adaptability.

If something new as KMP comes out and I don't really know how to pick up a new technology because I identify only with a certain specific one, then it's going to be more challenging.

--- Patrick Akil

Abdullah Zaiter emphasizes the need for developers to cross-check AI-generated solutions to avoid unnecessary complexity and ensure project relevance 4.