4 articles
AI is reducing the value of junior knowledge work faster than the need for senior judgment. Firms are cutting entry-level hiring, weakening the pipeline that produces experienced professionals. The resulting cohort deficit will emerge most sharply in law, audit, consulting, banking, and software during the 2030s.
Economic AGI is not a singularity or an ontological state — it is a factor-substitution threshold. Frontier models have crossed expert parity on standardized professional work at a fraction of human cost, and the threshold has been crossed for low-tail functions like customer support and content production. The remaining gap is autonomy, reliability, integration, and liability — not raw reasoning.
The key variable is feedback-loop generation time, not loop gain. The central question is whether AI removes bottlenecks faster than new ones emerge.
Open-weight foundation models have collapsed the intelligence generation layer to near-zero marginal cost. The structural bottleneck is migrating to the verification layer — where search engines, financial data aggregators, and content publishers are converting their historical indexing moats into paid API tollbooths. This is not a single monopoly rent; it is a fragmented patchwork of metered, unevenly-priced access gates whose integration complexity is the real constraint.