AI & Machine Learning

From "this is broken" to a fix PR I merge by hand

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A new open-source system called Mushi Mushi aims to bridge the gap between user-reported bugs and actual code errors, which often don't surface in traditional error tracking. The system leverages LLMs like Claude and GPT to categorize, prioritize, and even automatically generate potential fixes for user issues, significantly streamlining the debugging process. While the system automates much of the workflow, a human still reviews and merges code changes to ensure accuracy and prevent unintended consequences, highlighting the continued importance of human oversight in AI-driven development.

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