I said that based on you saying you exhaust a million token context windows easily. I'm no expert on that, but I think the current state of LLMs works best if you are not approaching that 1M token limit, because large context (reportedly) deteriorates response quality quickly. I think state of the art usage is managing context in tens or low hundreds thousands tokens at most and taking advantage of splitting tasks across subtasks in time, or splitting context across multiple "expert" agents (see sub-agents in claude code).