Yep, this is a fair take. Token usage shoots up fast when you do agentic stuff for coding. I too end up doing the same thing.

But for most background automations your might actually run, the token usage is way lower and probably an order of magnitude cheaper than agentic coding. And a lot of these tasks run well on cheaper models or even open-source ones.

So I don't think you are wrong at all. It is just that I believe the expensive token pattern mostly comes from coding-style workloads.

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kej 4 hours ago | parent [-]

I don't doubt you, but it would be interesting to see some token usage measurements for various tasks like you describe.

	▲	segmenta 4 hours ago \| parent [-]
		For example, the NotebookLM-style podcast generator workflow in our demo uses around 3k tokens end to end. Using Claude Sonnet 4.5’s blended rate (about $4.5 per million tokens for typical input/output mix), you can run this every day for roughly eight months for a bit over three dollars. Most non-coding automations end up in this same low range.