While correlation doesn’t imply causation, being able to tell the difference is essential in software engineering, where systems often involve complex interactions between variables. Causal inference offers a principled approach to uncovering true causal relationships and supports more accurate debugging, optimization, and decision-making. Nonetheless, applying these methods in practice is challenging due to the dynamic and complex nature of software environments. At the same time, core software engineering practices, like testing and verification, can inform and improve causal inference techniques. This tutorial aims to bridge these two areas. We provide an accessible introduction to causal inference, explore how it can be applied to real-world software engineering tasks like debugging and testing, and highlight the two-way synergy that emerges when these fields come together. With case studies and practical examples, we illustrate how causal thinking can enhance software development, and how engineering insights can in turn advance causal analysis.