AI 痴迷症：自动化可能制造灾难机器

说的真对啊，摘抄两段 “现在有很多公司已经陷入严重的 AI 痴迷状态” “可以把系统自动化成一台看起来很稳健的灾难机器。局部指标看上去一切正常，但全局却变得越来越难以理解。bug 报告可能下降了，...

说的真对啊，摘抄两段 “现在有很多公司已经陷入严重的 AI 痴迷状态” “可以把系统自动化成一台看起来很稳健的灾难机器。局部指标看上去一切正常，但全局却变得越来越难以理解。bug 报告可能下降了，但潜在风险却在爆炸式增长。测试覆盖率可能上升了，但对系统的真正理解却在下降。变化太快，以至于没人注意到底层架构正在悄悄腐烂。” 未来程序越来越多的黑盒，能看懂的人越来越少，全靠机器来修复，真的要进入蠢蛋进化论 Idiocracy 那部电影的世界。 Mitchell Hashimoto @mitchellh I strongly believe there are entire companies right now under heavy AI psychosis and its impossible to have rational conversations about it with them. I can't name any specific people because they include personal friends I deeply respect, but I worry about how this plays out. I lived through the great MTBF vs MTTR (mean-time-between-failure vs. mean-time-to-recovery) reckoning of infrastructure during the transition to cloud and cloud automation. All those arguments are rearing their ugly heads again but now its... the whole software development industry (maybe the whole world, really). It's frightening, because the psychosis folks operate under an almost absolute "MTTR is all you need" mentality: "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!" We learned in infrastructure that MTTR is great but you can't yeet resilient systems entirely. The main issue is I don't even know how to bring this up to people I know personally, because bringing this topic up leads to immediately dismissals like "no no, it has full test coverage" or "bug reports are going down" or something, which just don't paint the whole picture. We already learned this lesson once in infrastructure: you can automate yourself into a very resilient catastrophe machine. Systems can appear healthy by local metrics while globally becoming incomprehensible. Bug reports can go down while latent risk explodes. Test coverage can rise while semantic understanding falls. Changes happens so fast that nobody notices the underlying architecture decaying. I worry. 🔗 View Quoted Tweet 💬 0 🔄 0 ❤️ 1 👀 342 ⚡