elvis@omarsar0 · X一个10岁孩子想创建火箭模拟器等科学应用，却屡屡被主流AI编码工具所挫败。这揭示了当前以LLM为核心的技术短板：它们擅长在丰富训练数据框架内维护和构建现有模式，但难以灵活应对需要全新综合创造能力的边缘与生成性任务。这暴露了LLM距离实现通用人工智能（AGI）的局限，指明了未来需向更具泛化能力的原生多模态系统与世界模型等方向突破。
Every time I ask my 10-year-old to use coding agents， he gets extremely disappointed.
It turns out that all he wants is to build his own rocket simulator.
No amount of context engineering helps. No model works. All coding agents fail.
That's just one example. He has many use cases where the coding agent really suck. Learning apps and other types of science-centered simulators.
It's not like he is trying to be adversarial or break the system. I use the coding agents so extensively in my codebases that I just assumed that he would get similar results. It's not the case. And I think this is happening across all kinds of domains.
I know he is not the target user. I get all that. But if all these claims about superintelligent AI on the horizon （12-18 months） are right， then coding agents shouldn't struggle so much to build any of the things he wants.