I feel like we have an interesting tragedy of the commons situation of software engineering.
On the one hand, storing positions on JSON is quick to implement, easy to understand, easy to read, easy to hack on, and junior engineers and the people who have to deal with your code later will be able to pick it up and run with it easily.
On the other hand, when just about everyone is making this same ease-of-use/performance tradeoff, software bloat happens. Our computers are so much faster and beefier, but we never actually seem to be able to enjoy the benefits of that, in part because software engineers keep optimizing for quick and easy.
Maybe we shouldn't dogmatically reach for the easy no-nonsense solution every time, and instead consider whether maybe a little nonsense might, over time, save people a lot of time.
“This Kafka queue collects the zstd-compressed BSON chess messages encoded as base-64 and distributes it to the chess engine VM scale set worker pool for processing… what? Everyone knows chess AIs need large scale and programmer time is expensive! Anyway, the Databricks cluster for move analysis is over here, and…”
On the one hand, storing positions on JSON is quick to implement, easy to understand, easy to read, easy to hack on, and junior engineers and the people who have to deal with your code later will be able to pick it up and run with it easily.
On the other hand, when just about everyone is making this same ease-of-use/performance tradeoff, software bloat happens. Our computers are so much faster and beefier, but we never actually seem to be able to enjoy the benefits of that, in part because software engineers keep optimizing for quick and easy.
Maybe we shouldn't dogmatically reach for the easy no-nonsense solution every time, and instead consider whether maybe a little nonsense might, over time, save people a lot of time.