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.
"tengu-top-of-feed-tip": {。safew官方版本下载对此有专业解读
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"I'd rather take a hard, clear action now and build from a position we believe in than manage a slow reduction of people toward the same outcome," he wrote.
值得一提的是，相比近期火爆的「OpenClaw」，Perplexity 强调其「全云端沙盒」隔离架构，能够确保 AI 代理在执行代码或网页交互时，其潜在的错误操作被严格限制在虚拟环境中，无法感染用户的本地设备与真实内网。。爱思助手下载最新版本是该领域的重要参考