Last year, I used Copilot for the first time, and it was a bit shocking. It auto-completed a few lines of code and made writing a tool script incredibly satisfying. I thought to myself, "In the future, everyone will be about the same; with AI, who isn't an engineer anymore?" Looking back now, that thought seems a bit naive. The reality is: AI has not only failed to level the playing field but has actually widened the gap between programmers. Previously, the difference between top-tier programmers and average ones was 10 times, now it could be 100 times or even 1000 times. Why? Because AI has exposed the shortcomings of average programmers. If you used to get by writing for loops, CRUD operations, and connecting interfaces, AI can finish that in seconds. Your value is directly diminished. But those who are already good at system breakdowns and architecture find AI to be a tailor-made tool for them. Especially with the support of Cursor and even Claude Code, providing clearer intentions, AI can write functions and refactor modules in seconds, working together like long-time partners. The key is: the more precise your instructions, the stronger the feedback; if you're unclear, AI can only help you go in circles. In the past, writing code was "think 1, write 9"; now it has become "think 9, write 1". If you can't figure it out, you'll still get stuck; if you can think clearly, your efficiency will explode. Moreover, this isn't just a simple issue of learning prompts; it's about whether you have the system modeling ability to know "what method should be used here". Whether you're writing code or designing systems will be infinitely magnified in front of AI. In an era where tools are getting smarter, the real gap will only shift to one place: how much "irreplaceable judgment" a person's mind holds. AI has taken care of the "how to do it" for you, but the part of "what to do + why to do it" will only become more valuable.