Dario Amodei's prediction that AI would write 90% of code within a year fell short (actual figures ~25–50%), but the deeper issue isn't code generation metrics—it's that AI automation of junior tasks eliminates the learning pathways that built engineering judgment. Research from METR and Anthropic reveals the "supervision paradox": using AI effectively requires the skills that atrophy from overuse, and teams with high AI adoption shift their bottleneck upstream to code review, where senior judgment becomes even more critical.
Strategy
The ladder is missing rungs – Engineering Progression When AI Ate the Middle
AI code generation fell short of Amodei's 90% prediction at 25–50%, but the real crisis is that automating junior tasks eliminates learning pathways; METR and Anthropic research reveals the "supervision paradox" where teams shift bottlenecks to senior code review, requiring judgment that atrophies from overuse.
Tuesday, March 31, 2026 12:00 PM UTC2 MIN READSOURCE: Hacker NewsBY sys://pipeline
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