Causal reasoning involves a structured decision-making approach that begins with a specific goal or outcome, followed by identifying the necessary steps and resources to achieve it. This method relies on prediction, planning, and analysis, using existing data and knowledge to create a clear path toward the desired result. It emphasizes efficiency, optimization, and control, making it suitable for environments where future events can be anticipated based on past experiences and where variables are relatively stable. In contrast, [[effectual reasoning]] is a flexible approach that starts with available resources, skills, and networks, allowing goals to emerge and evolve over time. Rather than focusing on prediction, effectual reasoning emphasizes control over what can be influenced and the ability to adapt to changing circumstances. The key difference between the two lies in their handling of uncertainty: causal reasoning relies on prediction and control while effectual reasoning focuses on adaptability and leveraging contingencies as they arise.