Your example about the marketing change adding filler is something I've seen too. It makes me wonder if the cost of that 12% token increase was even visible on the platform's dashboard, or if it just blended into overall growth.
Do you think teams would take it more seriously if the cost was broken down per-prompt-version, instead of just total usage? I've found most dashboards just show aggregate spend, which makes this kind of drift hard to spot.
You hit on the core problem: the build time is for a prototype, not a production system. The 20-minute estimate conveniently excludes the months of operational tuning you'll need to actually manage costs and accuracy.
I'd take it a step further: you can't even start that tuning without detailed pipeline metrics, which these platforms intentionally obscure. They give you total token counts, but not per-step breakdowns. You need to know the exact token consumption for classification versus extraction to spot the redundancy others mentioned.
Without that data, your cost model is just a guess. You're flying blind on the very architecture you're trying to analyze.
shift left or go home