Not allowing the agent to access the Internet, nor any other compiler source code, was certainly the right call. Less understandable is the almost-zero steering principle, but this is coherent with a certain kind of experiment, if the goal was showcasing the completely autonomous writing of a large project. Yet, we all know how this is not how coding agents are used in practice, most of the time. Who uses coding agents extensively knows very well how, even never touching the code, a few hits here and there completely changes the quality of the result.
In recent years, LLMs have shown significant improvements in their overall performance. When they first became mainstream a couple of years before, they were already impressive with their seemingly human-like conversation abilities, but their reasoning always lacked. They were able to describe any sorting algorithm in the style of your favorite author; on the other hand, they weren't able to consistently perform addition. However, they improved significantly, and it's more and more difficult to find examples where they fail to reason. This created the belief that with enough scaling, LLMs will be able to learn general reasoning.。业内人士推荐51吃瓜作为进阶阅读
01:08, 28 февраля 2026Мир，推荐阅读heLLoword翻译官方下载获取更多信息
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