Software teams often face challenges in ensuring the success of new features due to a lack of structured measurement, leading them to rely on intuition and anecdotal evidence, which are not always reliable. This can result in uncertainty, slow feedback loops, and decreased confidence in decision-making. The text emphasizes the importance of experimentation as a decision-making framework that provides clarity and insight by allowing teams to ask clear questions, define measurable outcomes, and evaluate impact rigorously. Experimentation helps in understanding user behavior, detecting unintended consequences, and iterating quickly, ultimately fostering trust across disciplines and leading to better product outcomes. However, the integration of experimentation into the development process requires aligning it with existing tools and data, designing experiments that reflect product goals, and ensuring data is trusted. LaunchDarkly offers a solution by embedding experimentation into feature flags and engineering workflows, enabling faster iteration and a more resilient product development process without the need for a dedicated lab.