The Subtlety of the Point
The reason this view resonates so widely is that it precisely describes many people's real experience of using AI. The simple parts—boilerplate code, first drafts, routine queries, mechanical organizing—AI dispatches in one stroke, and the barrier is leveled to the ground. But the hard parts—true system design, complex trade-offs, deep judgment, breaking down ambiguous problems—not only aren't solved by AI, but stand out more and seem more urgent precisely because the simple work has been rapidly cleared away. AI hasn't flattened the difficulty curve; it has made it steeper—the easy easier, and the hard relatively harder, and also more valuable.
The Reshaping of Work and Skills
This insight is extremely valuable for understanding the shift in work in the AI era. First, it explains why "everyone has an AI tool but overall output hasn't doubled"—speeding up the simple stage often runs into the untouched bottleneck of the hard stage, and total output is determined by the bottleneck. Second, it redefines human value: when AI makes execution cheap, human value migrates to what AI does poorly—defining problems, key judgment, and handling true complexity. Third, it's a skills warning: those who can only do the part "made simple by AI" will see their value rapidly diluted, while those who can command the hard part become scarcer. The most practical advice is to use AI to clear the simple work, and firmly redirect the freed-up energy toward the harder parts that AI can't replace.
via: Hacker News