A software engineer reflects on integrating LLMs into their coding workflow over the past year, noting initial reluctance but eventual gains in output and development speed. However, they found that LLM-generated code often requires significant revision and can detract from the creative aspect of programming. Citing data from Harvard University and Jellyfish, the engineer points to research suggesting LLMs do not yield productivity gains or reduce staff numbers, raising concerns about the quality of code produced by less experienced users. AI
IMPACT Raises questions about the actual productivity benefits of LLMs in software development, potentially influencing adoption strategies.
RANK_REASON The item is a personal reflection and opinion piece on the use of LLMs in coding, referencing external research but not presenting new findings or a primary release.
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