Leo Romanovsky, a staff engineer at Datadog and former engineer at Eppo, details the architectural transformation of an A-B experimentation platform that managed 12 different SDKs with only three engineers. The initial model of manual, language-specific development led to unsustainable repetition, inconsistent feature flagging, and business risks like the "Spanish language segment" error where missing translation keys invalidated experiment data. To solve this, the team centralized logic into a unified Rust core and implemented a universal configuration schema, allowing backend-driven updates to propagate across all languages without new releases. By treating AI as a "team of interns" to generate boilerplate and validating it against a massive, cross-language test corpus, the team reduced duplicated code by 75% and increased release frequency tenfold. This shift from "keyboard hours" to automated leverage ensures that experimentation remains a reliable data-driven tool rather than a source of technical debt.
Sign in to continue reading, translating and more.
Continue