As we learned in the prior chapter, the flow graph API is remarkably versatile, allowing us to construct graphs that incorporate loops, utilize nodes such as multifunction_node to generate multiple messages for each incoming message, and introduce parallelism in various ways. This level of flexibility enables us to represent the same application in numerous forms, ranging from highly efficient to less efficient implementations. While each approach can produce correct results, they may differ significantly in terms of complexity and overhead. Therefore, in this chapter, we explore strategies that help us develop flow graph applications that optimize execution efficiency.