Go and Loops: How Music Sampling Reflects Go Development

I’ve spent my career thinking in terms of structs, interfaces, and goroutines, so I was floored when I started learning music sampling. I wasn’t just learning a new hobby; I was finding a hidden mirror of my day job as a Go developer. The process of taking an old sound and making it new feels exactly like building software. The tools are different—an MPC instead of Zed—but the thinking is identical.

In sampling, it all starts with “crate digging” for source material, like a drum break or a vocal snippet. This is 1:1 with finding the perfect Go module. Why would I write a complex HTTP router from scratch when I can import "net/http"? In both cases, you’re not building from zero. You’re standing on the shoulders of giants, taking a powerful, complete piece of work and using it as a foundation for your own new creation. The same applies to libraries and samples packs, both of which are curated collections designed to save time and spark creativity.

Once I have a sound, I load it into my sampler, which is effectively my “language” and “compiler” rolled into one. The sampler dictates the rules, giving me “constructs” like slice, pitch-shift, and filter. This is my Go toolchain. Go gives me func, struct, go, and chan—a logical system for manipulating raw ideas. The sampler simply provides its own syntax for manipulating raw audio.

The specific actions map perfectly. A “chop”—a tiny, isolated drum hit—is just a Go func: it does one thing, does it well, and is completely reusable. Arranging those chops into a sequence is my func main(), the core algorithm that calls all the pieces. The real mind-blower? Thinking about polyphony (playing multiple samples at once) as concurrency. It’s just like spinning up multiple goroutines with the go keyword to have different sounds play simultaneously without blocking each other.

The final beat is the finished application, a “compiled” product. In both worlds, you are forced to be creative within constraints, whether it’s the 12 seconds of sample time on an old MPC or managing memory and avoiding data races between channels in Go. It turns out that chopping beats and compiling code are both, at their heart, just different forms of systems thinking. And I’ve been doing, I mean, enjoying, that all along.

I’m still just focused on making my first loops, so I haven’t even thought about distributing a finished track. But I can already see the next analogy forming. I have a feeling that when I’m ready to “release” my music, I’ll find that services like DistroKid are just another form of Platform-as-a-Service (PaaS). It’ll be just like deploying a Go service to a cloud platform—packaging up my “build,” pushing it, and letting them handle the global scaling and delivery to all the “endpoints” like Spotify and Apple Music. I’m not there yet, but I’m willing to bet the parallels will hold up.