The Rabbitory
Every AI tool's pricing page shows the same story: a generous free tier, then a monthly fee that looks reasonable until you actually ship something.
The real costs show up elsewhere: retries on failed generations, context windows that balloon with every added feature, and rate limits that force you onto a higher tier long before you hit the advertised usage cap.
Where the budget actually goes
Teams that track this closely usually find that a small number of high-context requests account for the majority of spend — not the steady trickle of small ones.
The sticker price is never the real price. Budget for the retries, not just the requests.
Three ways teams keep costs sane
- Cache aggressively — repeated prompts shouldn't hit the API twice
- Route cheap tasks to cheap models, and save the frontier model for what needs it
- Set hard per-user or per-session limits before launch, not after the first bill
None of this is exotic — it's the same cost discipline every infrastructure team already knows. AI tooling just makes the bill arrive faster.