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:
2025 年，DataWorks 的核心优势聚焦两大方向：一是 AI + 大数据深度融合，通过集成 Spark、Ray 等 AI 友好引擎与 Copilot 智能开发能力，支持从数据准备、特征工程到大模型推理的端到端 pipeline；二是湖仓一体架构升级，全面兼容 Paimon、Iceberg、Delta Lake 等开放湖格式，实现结构化与非结构化数据统一存储、统一元数据管理与统一治理，构建高性能、低成本、可扩展的新一代数据基础设施。
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that actually did the accounting.
5️⃣ 归并排序 (Merge Sort)