Episode Details

Two diagrams show the same AI workflow: one as a sequential chain, one as a parallel fan-out. But the real difference isn't the shape — it's what happens when results come back. We dig into when parallelization actually wins, when it secretly costs more, and why the join node is where workflows live or die. Plus: where does the loop actually live in a graph, and why most diagrams get it wrong.