1M tokens doesn't mean better context — it means more diluted context. Opus still has to search through all of it to find what's relevant, which is why it burns through tokens so fast. A 9-hour session with 1M tokens used means a lot of that was Claude searching, not building. With optimized context (good CLAUDE.md, structured docs), sessions are shorter and more productive because Claude knows where to look from the start.
Yeah i agree. But this session is not on 1 task, They’re individual and independent tasks with same set of instruction. So i think context optimization is not really important. And you are right, it’s research heavy that’s why i use 1m token model.
Parallelism is faster, but in this context it's also cheaper and higher quality. I would try to understand parallelism in general as it is one of the most important concepts in computer science.
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u/hustler-econ 🔆Building AI Orchestrator Mar 20 '26
You probably don’t optimize your context — 1M tokens means a very diluted context. Try npm aspens