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A potential new job category involves humans acting as a common-sense filter for superhumanly intelligent AI. Because AI models lack a comprehensive world model for obvious things, humans will be needed to provide simple, obvious inputs and context, much like a servant assisting a brilliant but absent-minded professor.

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The integration of AI into human-led services will mirror Tesla's approach to self-driving. Humans will remain the primary interface (the "steering wheel"), while AI progressively automates backend tasks, enhancing capability rather than eliminating the human role entirely in the near term.

As AI agents become reliable for complex, multi-step tasks, the critical human role will shift from execution to verification. New jobs will emerge focused on overseeing agent processes, analyzing their chain-of-thought, and validating their outputs for accuracy and quality.

Emerging AI jobs, like agent trainers and operators, demand uniquely human capabilities such as a grasp of psychology and ethics. The need for a "bedside manner" in handling AI-related customer issues highlights that the future of AI work isn't purely technical.

As AI agents take over routine tasks like purchasing and scheduling, the primary human role will evolve. Instead of placing orders, people will be responsible for configuring, monitoring, and training these AI systems, effectively becoming managers of automated workflows.

AI models lack access to the rich, contextual signals from physical, real-world interactions. Humans will remain essential because their job is to participate in this world, gather unique context from experiences like customer conversations, and feed it into AI systems, which cannot glean it on their own.

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.

The fundamental economic shift is not just job automation but an inversion of roles. AI, as pure intelligence, will become the employer, hiring humans as contractors for physical tasks it cannot perform, like visiting a warehouse or collecting brochures. Intelligence becomes a cloud commodity, while physical presence becomes the service.

Even powerful AI tools don't produce a final, polished product. This "last mile" problem creates an opportunity for humans who master AI tools and then refine, integrate, and complete the work. These "finisher" roles are indispensable as there is no single AI solution to rule them all.

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.

The emerging job of training AI agents will be accessible to non-technical experts. The only critical skill will be leveraging deep domain knowledge to identify where a model makes a mistake, opening a new career path for most knowledge workers.