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That's my experience too. I've found OpenAI really quite generous with tokens. I sometimes wonder how some people manage to run out of them really. Do they just type prompts that much faster than me or use the highest reasoning mode for everything just because they can? Idk.

I generally agree with those reasons, although using a single thread may be less of an issue than it seems because of context compacting which should happen automatically when you're near the limit.

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My use cases are iterative and sometimes require reading a lot of code or reevaluating work.

Token efficiency is near meaningless when the workload is input-heavy. It can't always just choose to read less, depending on the task.

I can have cheaper agents do the reading but it's not appropriate for all use cases because they'll misjudge and choose the wrong things to emphasize, summarize, extract for the bigger model.

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Many threads.

I use new threads if relevant old one is uncached. (Often using a skill or doc for handoff instead of requiring full context gathering again.)

I get involved in architecture and specific implementation direction. The codebase is 8 years old and mostly handwritten.

Mostly coding. Some QA.

No cron/CI agents.

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