I don't know how useful this reply will be since I haven't tried Argon specifically, but with other models I've found that the best strategy for work that is shaped this way is to have the model process it in chunks and iteratively verify and build up the rules for processing. So you have it process 5 to 10 pages at a time and self-verify it's output before continuing. Every lesson gets propagated forward to the next chunk.

To get the best performance you really need to present your problem as an iterative verification loop.