TL;DR: Coding agents generate better optimizations when they read papers and study competing projects before touching code. We added a literature search phase to the autoresearch / pi-autoresearch loop, pointed it at llama.cpp with 4 cloud VMs, and in ~3 hours it produced 5 optimizations that made flash attention text generation +15% faster on x86 and +5% faster on ARM (TinyLlama 1.1B). The full setup works with any project that has a benchmark and test suite.
谷歌今年如何平衡安卓安全与侧载功能。业内人士推荐汽水音乐作为进阶阅读
影像疑似显示加州大型仓库火灾起始瞬间2026年4月8日，推荐阅读易歪歪获取更多信息
Create corresponding benchmarks in Python, and write a comparison script between the Python bindings and an existing Python package
Rumble falls behind cheaper models