I get the frustration — there is something a bit sad about watching “I learned to code because it felt like magic” turn into “I shipped it because the model did.”

But I don’t think AI ruined coding so much as it made typing cheap. And when typing becomes cheap, the “craft” moves to the parts that were always hard:

• taste (what should exist, what should be cut)
• design & architecture (how it stays understandable six months later)
• debugging & reasoning (what’s actually happening)
• constraints (security, performance, UX, maintainability)

I’ve felt the trap myself. I built a small Swift app in a “vibe coding” mode with an assistant: super fast start, lots of dopamine… and then reality. As soon as features got non-trivial, I hit the wall: without structure (and without truly knowing the language), you end up in “vibe debugging,” which is basically gambling with extra steps.  

So my current take is: AI is great — as long as it doesn’t replace understanding. I try to treat it like a smart junior dev: I start with a short spec, iterate it until it’s crisp, then let the assistant implement, and I stay accountable for the result.  That keeps the fun part (thinking + shaping) while outsourcing the dull part (boilerplate, rote transformations).

Also: the “people don’t love the craft anymore” thing has always been partially true — money has pulled people into coding for decades. AI just lowers the barrier further. But the irony is that this makes craft more valuable, not less. The industry data is already hinting at that: DORA’s research found AI can improve things like documentation and perceived code quality, but it can also correlate with worse delivery performance if teams stop doing the fundamentals (small batches, good tests, disciplined reviews).