Here is a 1-paragraph summary of the text: Building an A/B testing platform from scratch is more complex than anticipated, with various technical and non-technical challenges arising during its development. The platform must handle aspects such as user assignment, targeting rules, data collection, metrics definition, experiment results analysis, and data quality checks to ensure accurate and reliable results. A well-designed user interface is also crucial for empowering non-technical teams to set up and monitor experiments without engineering support, while also maintaining collaboration, documentation, and real-time visibility. The complexity of building an in-house A/B testing platform can lead to errors, invalidation of entire experiments, and eroded trust in data-driven decisions, making it a daunting task that may be better handled by leveraging proven open-source solutions.