It has been said that all problems in computer science can be solved by adding another level of indirection, except for performance problems, which are solved by removing levels of indirection. Compilers are our tools for removing levels of indirection automatically. However, we do not trust them when it comes to systems building. Most performance-critical systems are built in low-level programming languages such as C. Some of the downsides of this compared to using modern high-level programming languages are very well known: bugs, poor programmer productivity, a talent bottleneck, and cruelty to programming language researchers. In the future we might even add suboptimal performance to this list. In this article, I argue that compilers can be competitive with and outperform human experts at low-level database systems programming. Performance-critical database systems are a limited-enough domain for us to encode systems programming skills as compiler optimizations. In a large system, a human expert's occasional stroke of creativity producing an original and very specific coding trick is outweighed by a compiler's superior stamina, optimizing code at a level of consistency that is absent even in very mature codebases. However, mainstream compilers cannot do this: We need to work on optimizing compilers specialized for the systems programming domain. Recent progress makes their creation eminently feasible.