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The biggest impact I saw was in education - overnight, schools had to rethink how to teach when students could generate essays or solve problems with a tool. Universities and schools had to change tests, evaluation methods, because the traditional way of measuring knowledge became obsolete really fast. It's not that learning disappeared, but it forced a shift toward critical thinking and actual understanding instead of just regurgitating information.

What I saw the most was a lot of office workers starting to depend on these tools to write, analyze data, and solve problems quickly - some gained time, others just got lazier. On the technical side, what always happens with new technologies happened: some sectors adapted well, others had to reinvent themselves, and there was quite a bit of unnecessary panic about machines leaving us jobless when in reality most people ended up just using this as another tool.

Over these past four years, pretty concrete things happened: tons of companies started using AI to automate repetitive tasks, but it also opened up a huge gap between those who learned to use it as a tool and those who got left behind. The real shift wasn't AI itself, but that people had to relearn how to work almost overnight - some adapted quickly, others not so much.

What nobody talks about is that the best approach is to stop seeing it as a replacement and start using it as a first draft: I generated summaries of long articles, but I always checked everything because at first it made stupid mistakes. Whoever figured this out early ended up being more productive than someone who expected the machine to do everything perfectly. In society there was panic about job losses, but the reality is more mundane: some jobs changed in nature, others disappeared, and new roles emerged. Nothing spectacular, but enough that you have to rethink what to do every five years.

I noticed the most visible change was in how people started filtering information differently, because suddenly you had access to tools that gave you instant answers instead of spending hours searching. What's interesting is that a lot of people didn't realize they now needed to develop new skills to ask these machines the right questions, because a poorly phrased question gives you garbage. A trick I saw working across several fields is using these tools as a starting point to think better, not as a replacement for thinking - for example, asking it to draft an analysis for you and then you question each point instead of just swallowing whatever it gives you on the first go.

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