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Obviously an API scraper and data viewer alone do not justify an OPUS 4.5 CHANGES EVERYTHING declaration on social media, but it’s enough to be less cynical and more optimistic about agentic coding. It’s an invitation to continue creating more difficult tasks for Opus 4.5 to solve. From this point going forward, I will also switch to the terminal Claude Code, since my pipeline is simple enough and doesn’t warrant a UI or other shenanigans.
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5. As a final step, I copied the repository in /tmp, removed the “.git” repository files completely, started a new Claude Code (and Codex) session and claimed that the implementation was likely stolen or too strongly inspired from somebody else's work. The task was to check with all the major Z80 implementations if there was evidence of theft. The agents (both Codex and Claude Code), after extensive search, were not able to find any evidence of copyright issues. The only similar parts were about well established emulation patterns and things that are Z80 specific and can’t be made differently, the implementation looked distinct from all the other implementations in a significant way.，详情可参考体育直播
pseudocode for our example:，这一点在雷电模拟器官方版本下载中也有详细论述
Documents of products collection are intentionally designed to be more complex and larger than accounts - I want to see what happens, what is the performance penalty mainly, once individual documents are stored on multiple database pages. In Postgres, page size is 8 KB by default - in practice, the goal is to have at least 4 rows stored on a single page, so every record that is larger than 2 KB is put on two or more disk pages. It obviously reduces performance for both writes & reads - more disk pages to read from and write to. In Mongo it works slightly differently in details, but essentially in the same vein - larger documents are stored on more than one page, degrading performance for all operations. In both cases we are about to see - how much exactly.