Holdback experiments are a strategic approach to validating long-term effects by exposing a small user segment to the original experience while rolling out improvements to the majority. This method allows for safe decision-making on compounding metrics like retention without delaying immediate business gains. When significant results take time, an uneven split, such as 95% to the preferred option and 5% as a holdback, ensures most users benefit from improvements while enabling measurement of long-term impacts. The approach is especially relevant when changes aim for immediate gains in business-critical metrics but require confirmation of longer-term effects, like customer satisfaction on retention. Although maintaining two versions can be challenging, holdbacks provide a more accurate measure of the long-term impact by comparing a small cohort against the rest. It's crucial to manage technical debt by engaging engineers and operational managers in the process, emphasizing the value of experimentation for long-term objectives. The holdback pattern, paired with tools like Split for feature management and experimentation, aids in reducing risk, enhancing deployment visibility, and ensuring continuous improvement through data-driven insights.