Everyone gets faster. Not everyone gets more valuable (justinedwards.me)

Recent discussions around AI’s impact on productivity reveal a complex dynamic in the workforce. While numerous studies show that AI tools enhance the productivity of less experienced users—allowing novices in coding, writing, and customer support to leverage AI for quicker results—this narrative masks deeper issues. As organizations integrate AI, they see an increase in output primarily from junior workers while more seasoned professionals remain largely unaffected. The crux of the matter is not merely speed but the underlying value produced. In many cases, increased efficiency can lead to a pile-up of unreviewed work, raising the stakes and complexities involved in critical projects. This phenomenon illustrates two competing paradigms: while AI amplifies productivity for entry-level roles, it also effectively commodifies tasks that were once the domain of emerging professionals, leading to their displacement. As a result, the job market has become less favorable for junior developers while pushing up demand for experienced ones who excel in nuanced judgment and decision-making—skills AI lacks. The analysis underscores that true value lies not in merely executing tasks faster but in possessing a robust understanding of the principles driving the technology. Without this fundamental knowledge, the risk of relying too heavily on AI-generated outputs grows considerably, as users may struggle to discern when things go awry.