The Problem We Were Actually Solving We were actually trying to solve the problem of high-latency API queries, which were causing delays in our users' experience. Since our Treasure Hunt Engine relied heavily on real-time data, we knew we needed to optimize our API queries. Our operator framework was designed to abstract away the complexity of API queries, making it easier for our engineers to build and manage them. However, in our haste to deliver the system, we overlooked some critical details that would come back to haunt us. What We Tried First (And Why It Failed) We initially implemented the operator framework using a monolithic approach, where each query was a separate module that handled everything from data processing to caching. We thought this would make it easier to manage and scale, but what we got was a system that was infamously prone to errors. Our engineers would often introduce subtle changes to one query, which would then cascade and cause issues in other parts of the system.…