Nature, Published online: 26 February 2026; doi:10.1038/d41586-026-00158-y
但對於那些沒有單一正確答案的開放式任務，角色扮演是有效的（例如建議、腦力激蕩、創意或探索性的問題解決）。如果你對求職面試感到緊張，讓聊天機器人模仿招聘主管的語氣練習可能是一個不錯的主意——只是要記得同時參考其他資源。
。业内人士推荐Line官方版本下载作为进阶阅读
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В России ответили на имитирующие высадку на Украине учения НАТО18:04
It’s Not AI Psychosis If It Works#Before I wrote my blog post about how I use LLMs, I wrote a tongue-in-cheek blog post titled Can LLMs write better code if you keep asking them to “write better code”? which is exactly as the name suggests. It was an experiment to determine how LLMs interpret the ambiguous command “write better code”: in this case, it was to prioritize making the code more convoluted with more helpful features, but if instead given commands to optimize the code, it did make the code faster successfully albeit at the cost of significant readability. In software engineering, one of the greatest sins is premature optimization, where you sacrifice code readability and thus maintainability to chase performance gains that slow down development time and may not be worth it. Buuuuuuut with agentic coding, we implicitly accept that our interpretation of the code is fuzzy: could agents iteratively applying optimizations for the sole purpose of minimizing benchmark runtime — and therefore faster code in typical use cases if said benchmarks are representative — now actually be a good idea? People complain about how AI-generated code is slow, but if AI can now reliably generate fast code, that changes the debate.