Now do it with knowledge or causal graphs

Causal graphs are interesting, but in my experience, the bottleneck isn't the representation; it's getting the model to actually follow through on weak signals instead of moving on to the next topic. A graph won't help if the system doesn't know what to do when it hits a node that doesn't resolve cleanly. What's your experience been with them?