The behaviour you described is what happens when you have small context windows. Perhaps you're feeding the models with more tokens than you think you are. I have enjoyed loading large codebases into AI Studio and getting very satisfying and accurate answers because the models have 1M to 2M token context windows.
Concat to a file but it helps to make an ascii tree at the top and then for each merged file out its path and orientation details. I’ve also started playing with adding line ranges to the ascii tree hoping that the LLMs (more specifically the agentic ones) start getting smart enough to jump to the relevant section.
