As Import AI reports, the kernel-writing feat is a technical milestone, but its broader significance hinges on a questionable premise: that automating discrete, benchmarked tasks like kernel optimization directly translates to autonomous, end-to-end AI R&D. In our view, the leap from writing efficient code to independently formulating research questions and designing novel architectures is vast. The more immediate, and perhaps more telling, signal comes from the companion report on the Remote Labor Index, which suggests AI's capability expansion in economically valuable tasks may be outpacing human adaptation. The critical question isn't whether AI can write a kernel, but whether the systems using those kernels will create more jobs than they automate.