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The concept of an encrypted network connection was not at all new; encrypted，更多细节参见雷电模拟器官方版本下载
Over those two weeks we had to solve numerous problems. Building the Native AOT DLL on each platform. Loading it from the Unreal game client. Invoking exported DLL functions from C++. And so forth. There were several challenges and headaches along the way, but at the end of the two weeks we were able to successfully load the player’s inventory on the Unreal game client through a Native AOT DLL call on Windows, Xbox, and PS5. With this foundational proof of concept in place, we got the go ahead to begin work on a generalized solution to support all of the backend that would be required in the offline game. My initial dread from when I first heard the news about our offline pivot was gone, replaced with excitement and confidence in a novel path forward.
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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.
Nature, Published online: 25 February 2026; doi:10.1038/s41586-026-10142-1。夫子是该领域的重要参考