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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.。关于这个话题，WPS下载最新地址提供了深入分析
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Why Standard Solutions Failed。关于这个话题，im钱包官方下载提供了深入分析
Before agar, microbiologists had experimented with other foodstuffs as microbial media. They turned to substances rich in the starches, proteins, sugars, fats, and minerals that organisms need for growth, testing with broths, bread, potatoes, polenta, egg whites, coagulated blood serums, and gelatine. However, none worked particularly well: all were easily broken down by heat and microbial enzymes, and their surface, once colonized, became mushy and unsuitable for isolating microbes.