I’ve noticed something interesting over the past year watching people learn and use AI tools. beginners seem to be progressing insanely fast, while experienced developers sometimes feel like they’re moving slower than before. meanwhile some experienced developers say they spend more time verifying AI output, debugging generated code, or correcting subtle mistakes than actually writing code themselves. So we’re seeing a weird dynamic like AI massively compresses the early learning curve, but the final 20% of reliability and correctness still requires deep expertise. Simply means that if beginner then intermediate has become much faster if intermediate then expert might actually be getting harder i think this creates a strange new environment where more people can build things but the complexity of systems is increasing and expertise is shifting from creating to evaluating . in some ways it reminds me of what happened when calculators became common. like basic math became easier for everyone, but understanding the underlying concepts became even more important for catching mistakes. did anyone of you noticing that AI compresses early learning but increases the importance of judgment and verification later? or do you think this is just a temporary phase while tools improve? like what do you think ? submitted by /u/Interesting_Mine_400
Originally posted by u/Interesting_Mine_400 on r/ArtificialInteligence