For me, one signal has been whether the problems remain interesting even when progress is slow.
When working on complex systems (like anything involving long-running automation or agents), most of the real work happens in areas that don’t show up in demos: defining “done”, handling partial failures, and keeping behavior predictable.
If those problems are still worth thinking about after repeated failures, I take that as a sign the work itself is worth continuing.