Over-reliance on AI and auto-complete tools leads to a lack of understanding of underlying concepts and potential errors in code

Signals over time

2 observed signals across 1 sources, tracked for 5 days. Confidence: low.

What people are saying Observed

• “Alas, I think we (collectively) either are, or will be soon. There will be people who keep 100% knowledge of the code in their projects, but I don't think there will be any monetary reward for that, nor reputational outside of their own niche. And I say that from a position of really wanting to be wrong about it. I recently started using Claude to write an app. I was going to write it by hand but was having trouble getting motivated, and I knew I had to "up my game" in the vibecodery anyway. So far it's been a lot of back and forth, I keep the leash pretty short because I don't want The Claude AI you see everywhere now. But even with good intentions and the short leash, I find myself saying "yeah, whatever, it looks like it did what I told it to do" and not actually reading all the code. Some yes, all no. And this is for my own project, nobody is my boss here, and it's nothing I couldn't have done by myself. Now imagine the incentives for someone who's doing it for money, whose boss is pushing them to do more AI and not less, who probably doesn't actually know how to do all the things the AI is doing for them, who looks around ”

  Hacker News · frustration

• “I can compare this to my early days. At first I was using Visual Studio like everyone else and relying on auto-complete and built-in symbols to figure out how to make something, or I would just copy and paste examples from the internet, and then tweak until something works. But what actually made me understand what I was doing was switching from an IDE to a simple code editor. Because then I couldn't use auto-complete as a crutch, I had to actually read the documentation, understand how a library is structured, which methods are supported, what the parameters are. This helped me slow down, learn the concepts, instead of blindly throwing things at the problem and seeing what sticks. And I'm having a similar experience with the AI now, it's easier to just prompt continuously, feels productive, but then I find a bug or bad logic and trace it down to a prompt where the LLM made a mistake that I wasn't aware of, and this happens a lot. The solutions it provides are rarely optimal and it's easy to fool yourself that it handles everything.”

  Hacker News · frustration