Modern companies are increasingly automating routine tasks with AI to reduce costs and increase efficiency. However, as systems grow more complex, the cost of communication errors and misinterpretation of requirements rises. Automated systems can scale both correct solutions and errors present in the initial task setup.
To simplify internal interactions, organizations often combine multiple functions into single roles. While this theoretically reduces coordination costs, it leads to constant context switching. According to neurobiological research, the human brain is not designed for multitasking, as frequent switching between complex tasks consumes cognitive resources and reduces work quality.
Economic history demonstrates that productivity growth is driven by specialization rather than universalization. Modern industry relies on clear role distribution, such as developers, testers, and analysts, to manage system complexity and localize responsibility. Blurring these boundaries often results in disorganized processes and a lack of clear accountability.
The author tested claims that AI could clone complex corporate products in two weeks. A test involving a complex analytical platform showed that an initial iteration of a system clone was produced within 48 hours.
