You can add more workers, more servers, or more processing power and still have a slow system. Sometimes the real limitation is dependency. Imagine a process with five steps, where each step needs the result of the previous one before it can begin. No matter how much capacity you add, those steps still have to wait for each other. That creates a different engineering question. Instead of asking: “How can we process more things at once?” I ask: Which parts actually depend on each other? Which work can happen independently? Are we forcing tasks to wait when they do not need to? Can the critical path be shortened? This matters because unnecessary dependencies increase response time, reduce throughput, and make scaling more expensive. Sometimes the best performance improvement is not adding more resources. It is redesigning the workflow so independent work can happen independently. Scaling is not only about adding capacity. It is also about removing unnecessary dependencies that prevent the capacity you already have from being useful.