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.
You need to pay attention to the content since it’s not always on point
。关于这个话题，同城约会提供了深入分析
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转机发生在2019年7月。达博结识了在冈比亚开展农业技术合作的隆平高科国别经理黄智及其团队。从选种到种植，中国专家们手把手提供帮助，还引进了插秧机、收割机等专业设备。黄智还记得第一次看到马鲁奥农场时的情形：“当时，这里是传统、粗放的种植方式，土地不平整，苗弱草盛，虽然能感受到农场主的努力，但缺乏科技的支撑，产量很难上去。”