Ex Valve dev on CS:GO’s codebase
One of the best, and first, things we did when starting our machine learning platform was to design it using a plugin architecture. There's a lot of scar tissue and horrible experience through our previous ML products we built for enterprise.Namely, it was extremely hard to onboard new developers to work on the product. They had to understand the whole thing in order to contribute.Changing something was also hard, since it was intertwined. Adding a feature or removing a feature was hard. Especially given the fact we were not designing to spec, and the domain experts we were building for could not give feedback. That was a constraint outside of our control, so we were building for users we never met based on what we thought would make sense.The first commits on our own platform were to establish a plugin architecture. There's a core, and there are plugins. We could add or remove functionality changing a config file. Applications are plugins and onboarding is easy and smooth, since a junior developer can start working on one plugin and then expand their knowledge.We're reaping the rewards of that.