Bringing manufacturing back to the US won't mean a return of old assembly line jobs. The real opportunity is to leapfrog to automated factories that produce sophisticated, tech-infused products. This creates a new class of higher-skill, higher-pay "blue collar plus" jobs focused on building and maintaining these advanced manufacturing systems.

Amazon's plan to automate 75% of operations isn't just about job replacement; it's a fundamental workforce transformation. Future roles, even for hourly workers and managers in its facilities, will increasingly require knowledge of engineering and robotics to maintain the vast robot fleet, shifting the baseline for employment.

Industry leaders from LinkedIn and Salesforce predict that AI will automate narrow, specialized tasks, fundamentally reshaping careers. The future workforce will favor 'professional generalists' who can move fluidly between projects and roles, replacing rigid departmental structures with dynamic 'work charts.'

If AI were perfect, it would simply replace tasks. Because it is imperfect and requires nuanced interaction, it creates demand for skilled professionals who can prompt, verify, and creatively apply it. This turns AI's limitations into a tool that requires and rewards human proficiency.

Instead of fearing job loss, focus on skills in industries with elastic demand. When AI makes workers 10x more productive in these fields (e.g., software), the market will demand 100x more output, increasing the need for skilled humans who can leverage AI.

The initial impact of AI on jobs isn't total replacement. Instead, it automates the most arduous, "long haul" portions of the work, like long-distance truck driving. This frees human workers from the boring parts of their jobs to focus on higher-value, complex "last mile" tasks.

Unlike past technological shifts where humans could learn new trades, AI is a "tractor for everything." It will automate a task and then move to automate the next available task faster than a human can reskill, making long-term job security increasingly precarious for cognitive labor.

Most AI applications are designed to make white-collar work more productive or redundant (e.g., data collation). However, the most pressing labor shortages in advanced economies like the U.S. are in blue-collar fields like welding and electrical work, where current AI has little impact and is not being focused.

AI will handle most routine tasks, reducing the number of average 'doers'. Those remaining will be either the absolute best in their craft or individuals leveraging AI for superhuman productivity. Everyone else must shift to 'director' roles, focusing on strategy, orchestration, and interpreting AI output.