During development I encountered a caveat: Opus 4.5 can’t test or view a terminal output, especially one with unusual functional requirements. But despite being blind, it knew enough about the ratatui terminal framework to implement whatever UI changes I asked. There were a large number of UI bugs that likely were caused by Opus’s inability to create test cases, namely failures to account for scroll offsets resulting in incorrect click locations. As someone who spent 5 years as a black box Software QA Engineer who was unable to review the underlying code, this situation was my specialty. I put my QA skills to work by messing around with miditui, told Opus any errors with occasionally a screenshot, and it was able to fix them easily. I do not believe that these bugs are inherently due to LLM agents being better or worse than humans as humans are most definitely capable of making the same mistakes. Even though I myself am adept at finding the bugs and offering solutions, I don’t believe that I would inherently avoid causing similar bugs were I to code such an interactive app without AI assistance: QA brain is different from software engineering brain.
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向 AI 外包自己的意志我是一个思虑极重的人，因为惧怕风险，所以做决策前喜欢思考再三，找出问题的最优解，然后再行动。而当问题的最优解不是那么显而易见，或者根本就无法评判的时候，我就陷入了选择困难的境地，屡屡纠结各种因素和条件，始终无法行动。换句话说，我是个纠结党。这种特点几乎体现在我的所有行为上。比如「晚饭吃什么」对我来说就是一个世纪难题：食堂太腻、外卖太贵、出门太远是我永远在纠结的三要素；此外各种眼花缭乱的券、折扣、红包也在不断给我的决策增加难度。
这些新实体验证了一个反直觉的逻辑：在AGI突破的前夜，组织越小、目标越纯粹，创新势能越大。 当大厂背负营收包袱时，“分拆”出的特种部队反而能跑得更快。这对于那些试图通过不断扩招来维持创新的巨头来说，是一个巨大的警示。，推荐阅读谷歌浏览器【最新下载地址】获取更多信息
Lambda puzzles challenge: https://bntre.github.io/visual-lambda/#workspace=puzzles
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