Task length is increasing over time - and many AI labs are working on pushing it out further. Which necessitates better attention, better context management skills, better decomposition and compartmentalization and more.
Increasing task length doesn't build in an equivalent of human-capital. It's just pushing the point at which they degrade. This approach isn't generalisably scalable, because there's always going to be a task longer than the SOTA capabilities.
We really need to work on a low cost human-capital-equivalent for models.
I don't babysit them for long periods in one session. I allow them to one-shot the initial solution. Then, I thoroughly review the output, make notes of what should be improved, then either feed that into the original prompt and one-shot it again, or ask the agent to update the solution based on the notes.