Offloading implementation to AI misses a critical truth: writing code was never just execution, but the cognitive vehicle through which engineers stress-tested their architecture. By skipping the painful, hands-on debugging cycles where intuition is forged, we risk creating a dangerous junior talent debt - producing developers who lack the deep mental models required to spot subtle logic bugs or security flaws when AI output strays. In two or three years, the most valuable engineers won't be those who prompt fastest, but those with enough deep technical fundamentals to rigorously audit AI-generated code and call BS when the model inevitably goes off the rails.