A starting diagnostic. If you can't confidently check all ten, you have exposure.
- [ ] A hard organization-level spend cap is configured and active.
- [ ] Per-user and per-API-key limits are set, not just an org ceiling.
- [ ] Budget alerts fire at defined thresholds (e.g. 50% / 80%) to a human who acts.
- [ ] A real-time cost dashboard exists and someone owns watching it.
- [ ] Spend is attributed by team, feature, and use case — not a single undifferentiated total.
- [ ] Routine, high-volume tasks run on a small/cheap model by default; the flagship is opt-in.
- [ ] Repeated context (system prompts, knowledge bases, code) uses prompt caching.
- [ ] Non-urgent workloads (evals, nightly jobs, bulk generation) run through batch processing.
- [ ] Every autonomous agent has a max-iteration limit and a per-task token budget.
- [ ] A documented AI spend policy exists and maps to your governance framework (ISO 42001 / NIST AI RMF).
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