These are very hard problems to solve.

It's often nearly impossible to know in advance how hard the task will be, so the model has to guess, and will inevitably miss. Just because you know how hard the task is, doesn't mean it's obvious. Often it's only obvious to you, because you have additional context that models are missing.

A bad guess can lead to either context rot (if subagent wasn't used), or slower execution (if subagent was used but it turned out to be a bad idea). Both are bad UX.

Now, we could improve accuracy by having the harness do a research on each task before executing... which leads to even slower execution, also bad UX.