It's undeniable that AI is rapidly changing the landscape, and we all need to adapt. Many find AI to be a helpful tool, and I personally have found it beneficial in my workflow, solving problems that were previously difficult or required new skills. However, I'm particularly interested in how new programmers should use AI during their learning process. How can they leverage it to learn faster without missing crucial knowledge?

There's a parallel to the past when programmers would copy code from Google without fully understanding it, resulting in functional but poorly understood code with potential implementation gaps. Now, it's even easier to fall into this trap with AI.

New programmers face a dilemma: they need to grasp the fundamentals, like building a basic to-do application or understanding JavaScript's prototype chain. Simultaneously, they could automate these tasks with AI and move on to building fully-fledged applications, potentially missing intricate errors or struggling to debug complex issues later on.

This is a complex problem I've been considering while mentoring a friend who wants to learn programming. I believe there's a sweet spot where new programmers can learn programming while using AI to enhance their debugging time and learn about the latest tools, all while mastering the basics.

This process won't be easy, and it will vary for each individual, but it's crucial to get it right.

Another consideration is that the interview process often lags behind current industry standards. A candidate who can easily solve problems with AI might struggle to do so manually, hindering their job prospects while forcing them to learn skills they might not use.

I'm curious to hear your thoughts: How are you experimenting with AI? Where are you looking for AI resources? What are your experiences with AI in learning or working with code?