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.
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。关于这个话题，Line官方版本下载提供了深入分析
// 核心逻辑：当前时间 上一个车队时间 → 无法合并，是新车队
快科技报道指出，Find N6 的折痕深度将挑战行业极限，目标是在观感上接近「绝对平整」，触感过渡也更顺滑。上一代 Find N5 已将折痕压到 0.15mm 以内，而 Find N6 预计将进一步突破。