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The article examines practical challenges of using AI in software development, focusing on three main issues: the effort required to properly prompt AI (ranging from detailed specifications to high-level requests), the limitations of AI context windows that prevent it from processing large codebases or datasets effectively, and the need for domain-specific expertise and information compression. The author argues that while AI eliminates traditional coding time, it shifts the workload to system design, specification writing, and refinement, requiring developers to become effective communicators rather than merely reducing overall development effort.
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