AI Labor Impact — Knowledge Engine

Karpathy scored 342 BLS occupations from 0-10 on AI exposure, finding an average score of 5.3 -- suggesting the majority of the labor market faces meaningful AI disruption (from karpathy ai job exposure scores)
Screen-based knowledge work dominates high exposure: software developers 9/10, general office clerks 9/10, medical transcriptionists 10/10, lawyers 8/10 (from karpathy ai job exposure scores)
Jobs scoring 7+ on AI exposure represent $3.7 trillion in annual wages, quantifying the economic magnitude of AI-driven labor displacement (from karpathy ai job exposure scores)
The heuristic "any screen-based job is in trouble" serves as a simple proxy for AI exposure -- if the work product is primarily digital text, code, or data manipulation, LLMs can automate significant portions (from karpathy ai job exposure scores)
Karpathy deleted the original GitHub repo quickly after publishing, suggesting sensitivity around concrete AI job displacement predictions even from prominent researchers (from karpathy ai job exposure scores)

Companies building primitives for an economy where AI agents are the primary users -- digital AI coworkers that combine email, phone, browsing, memory, payments, and search tools will look increasingly human-like (from an economy of ai coworkers)

AI-native companies are replacing the traditional PM role with a "product builder" archetype that combines product, design, and engineering skills into a single IC role (from cpo role vanishing)
The standalone CPO role is predicted to vanish within five years as it creates coordination tax when IC roles are already blending (from cpo role vanishing)
Career implication: stop aspiring to become a CPO; instead develop a panoply of product development skills across product, design, engineering, and analytics (from cpo role vanishing)
The human role in programming shifts to high-level direction, judgement, taste, oversight, and iteration rather than implementation (from karpathy coding agents paradigm shift)