"And workers aren't using AI to be ten times more effective, he continued; instead, "they're using it to churn out their tasks with less energy spend." Worse yet, the "two people on your team that actually tried are now flattened by the slop code everyone is producing, they will quit soon." "Even when you produce work faster you're still bottlenecked by bureaucracy and the dozen other realities of shipping something real," Raad concluded."
"Using AI to accelerate tasks, it turned out, was a double-edged sword, because it led to "workload creep," forming a vicious cycle in which AI raised expectations for how fast the workers had to churn stuff out, which in turn made them more reliant on AI to keep up with the greater demands. The upshot: worker fatigue, burnout, and lower quality work; not the hallmarks of a thriving organization."
Many software organizations lack strong product ideas, and rapid code production does not substitute for conceptual quality. AI tools can speed task completion but cannot generate better underlying ideas. Employees often use AI to reduce individual effort and churn out work with less care, producing low-quality "workslop." Faster output increases expectations and creates workload creep, creating a cycle of greater reliance on AI to meet rising demands. Bureaucratic bottlenecks and other realities of shipping products remain unchanged despite speed gains. The combination of lower-quality output, heightened pace, and intensified workloads leads to fatigue, burnout, and talent attrition.
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