While a perfectly reasonable point, and one which might benefit other readers, I think it’s worth adding that the article seems fairly clear that it’s demonstra

While a perfectly reasonable point, and one which might benefit other readers, I think it’s worth adding that the article seems fairly clear that it’s demonstrating a proof of concept that can be built upon. I certainly didn’t take it to suggest that I should go write a convoluted setInterval to implement GC in WASM. Amusingly (to me), I’ve been working on a variety of performance-focused efforts—professionally on directly deliverable tasks, professionally on exploratory spikes for more holistic future improvements, and in pet personal projects. I find myself deliberately writing throwaway code that’s just as painfully suboptimal quite a lot. At worst it helps me quickly iterate on the actual bottleneck without focusing on the things I’m not trying to optimize. It can be more helpful than that though, when it reveals sometimes unexpected JIT perf characteristics. Sometimes it reveals that a hot loop optimization isn’t going to bear much fruit because the JIT is going to optimize the baseline code better than anything I have in mind. Other times it reveals cases where I see dramatic benefits from an initial JIT pass that vanish because other factors cause a deoptimization. Granted I think it’s still good to slap a big warning like this on obviously suboptimal code! But I also think people working on performance sensitive code in a dynamic JIT/GC environment should be encouraged to write weird suboptimal throwaway glue code around their perf focal point. You can learn a lot if you’re profiling!