AI is quietly redefining what it means to be “technical.” It used to mean memorizing syntax, knowing framework quirks, and being the person who could recall the right method or configuration from memory. Today, with tools like Claude AI, Cosine, GitHub Copilot, and Cursor, that information is almost always a prompt away. The surface layer of knowledge has become easier to access. What starts to matter more is how well you think. Can you take a messy requirement and break it into clear components. Can you define constraints before jumping into implementation. Can you explain edge cases, tradeoffs, and failure paths before writing a single line. The tools reflect the quality of the direction they are given. When your thinking is sharp, the output improves. When your thinking is vague, the output looks polished but fragile. In that sense, engineering is becoming less about recall and more about clarity. submitted by /u/Tough_Reward3739
Originally posted by u/Tough_Reward3739 on r/ArtificialInteligence
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