Andrew Yang: Learning to Code Has Shifted from the Safest to the Worst Advice
Former U.S. presidential candidate Andrew Yang stated that "learn to code" has transformed from the safest career advice to the worst advice in just four years.
Yang expressed shock at the speed of technological change after attending the Western AI Conference, where it was claimed that changes in the next six months will surpass the total of the past decade. One company’s enterprise-level autonomous coding product saw its revenue grow 100 times in the past 12 months, significantly encroaching on technology budgets originally allocated for human programmers.
Tech companies and computer science students in the job market are facing dramatic employment changes, as AI coding tools automate and compress labor costs. Large enterprises benefit while recent computer science graduates face short-term pressure, with job market funding rapidly shifting from traditional programming roles to AI tools and higher-level supervisory positions.
Source: Public Information
ABAB AI Insight
Andrew Yang cites Anthropic CEO Dario Amodei's view that up to 50% of entry-level white-collar jobs may be automated in the coming years, with recent graduates being the first affected, as "the easiest to cut are those who haven't been hired yet." Data shows that the unemployment rate for college graduates has now exceeded or equaled that of non-graduates for the first time.
On the capital front, companies are shifting their tech budgets from hiring junior programmers to purchasing autonomous coding tools, leading to a steep decline in employment rates for computer science graduates. The motivation lies in the near-zero marginal costs brought by AI, forcing the labor market to shift from "coding equals high salary" to "understanding AI + business" as the competitive edge.
Similar to the "learn to code" craze of the 2010s, AI agents can now independently complete a large number of enterprise-level coding tasks. Yang currently places the programming profession at a turning point from a high-demand, secure track to one rapidly being replaced by AI, pushing education and career planning to transition from mere skill acquisition to AI collaboration capabilities.
Structural judgment: Essentially a case of technological substitution. AI coding tools, through exponential efficiency gains, are replacing entry-level programming jobs from human novices to machine automation. The mechanism involves a rapid shift of corporate budgets towards tool procurement, leading to a sharp reduction in job opportunities for recent graduates, forcing labor value to concentrate on AI system design, business understanding, and supervisory roles.
ABAB News · Cognitive Law
The safest advice flips the fastest.
Tools consume budgets, humans are optimized.
Entry-level positions are the easiest to be replaced by AI first.