I completely ignored Anthropic’s advice and wrote a more elaborate test prompt based on a use case I’m familiar with and therefore can audit the agent’s code quality. In 2021, I wrote a script to scrape YouTube video metadata from videos on a given channel using YouTube’s Data API, but the API is poorly and counterintuitively documented and my Python scripts aren’t great. I subscribe to the SiIvagunner YouTube account which, as a part of the channel’s gimmick (musical swaps with different melodies than the ones expected), posts hundreds of videos per month with nondescript thumbnails and titles, making it nonobvious which videos are the best other than the view counts. The video metadata could be used to surface good videos I missed, so I had a fun idea to test Opus 4.5:
同样,主打健康监测的RingConn智能戒指,通过搭载大模型提供个性化健康建议,构建情感与信任依赖。这类硬件售卖的是“解决方案”与情绪价值,溢价自然也能上去。2025年6月,RingConn以57%的市场份额稳居中国智能戒指市场第一。
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