AI agents are rapidly transforming software development and knowledge work, but their impact on professions requiring physical robotics, like surgery or auto repair, is on a much longer timeline. The AI revolution is arriving in phases, with the digital world being upended first and the physical world to follow later.
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The most immediate AI milestone is not singularity, but "Economic AGI," where AI can perform most virtual knowledge work better than humans. This threshold, predicted to arrive within 12-18 months, will trigger massive societal and economic shifts long before a "Terminator"-style superintelligence becomes a reality.
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.
To predict AI's future impact on the broader economy, observe its current capabilities in software development. AI models are consistently about a year ahead in coding ability compared to other domains, providing a reliable preview of the automation coming to other knowledge-work sectors.
Brendan Foodie predicts that as AI automates digital roles, the displaced workforce will shift to physical world jobs (from robotics data creation to therapy). He argues this is because physical automation progresses much slower than digital automation, which benefits from rapid, self-reinforcing feedback loops.
Software engineering is a prime target for AI because code provides instant feedback (it works or it doesn't). In contrast, fields like medicine have slow, expensive feedback loops (e.g., clinical trials), which throttles the pace of AI-driven iteration and adoption. This heuristic predicts where AI will make the fastest inroads.
The future of software isn't just AI-powered features. It's a fundamental shift from tools that assist humans to autonomous agents that perform tasks. Human roles will evolve from *doing* the work to *orchestrating* thousands of these agents.
Industries with fixed demand (accounting) will see job losses as AI handles the necessary workload. Sectors with expandable demand (software engineering) may absorb AI's productivity gains by creating vastly more output, thus preserving jobs for a longer period.
Contrary to popular belief, highly compensated cognitive work (lawyers, software engineers, financiers) is the most exposed to AI disruption. If a job can be done remotely with just a laptop, an advanced AI can likely operate in that same space. Physical jobs requiring robotics will be protected for longer due to cost and complexity.
Unlike COVID, which universally and immediately affected everyone, AI's disruption is gradual and highly sector-specific. A surgeon's job isn't changing this month, but a software engineer's is. The comparison creates misplaced urgency for many outside of tech.
While AI moves fast in the world of bits, its progress will be constrained in the world of atoms (healthcare, construction, etc.). These sectors have seen little technological change in 50 years and are protected by red tape, unions, and cartels that resist disruption, preventing an overnight transformation.
