Open source contributions are becoming congested as more developers use AI coding assistants, reducing the signal value of contributions when evaluating candidates
Job search markets face similar congestion where AI-generated applications and portfolios make it difficult for employers to identify genuinely qualified candidates
The matching efficiency of both markets deteriorates when volume increases without corresponding improvements in quality differentiation mechanisms
Both scenarios illustrate how AI adoption can paradoxically harm the very markets it was meant to improve by flooding them with similar outputs
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