Cost & FinOps for AI
Unit economics per request, token accounting, reserved versus spot capacity, and attributing spend to features.
12concepts
105flashcards
90minutes of reading
- 01 Cost Variance and the Tail of Agentic Spend Why the budget for an agent workload is set by the tail of its cost distribution rather than its mean, where the multipliers in that tail come from, and the controls that bound a single run without quietly lowering success.
- 02 The Cost of Evaluation and Experimentation Why evaluation is a standing line item that can rival production inference, the multipliers that make a golden set expensive, and how to buy statistical confidence at the lowest price.
- 03 Token Accounting and Cost Attribution Why a single provider invoice cannot be allocated to teams, features or customers without instrumentation, and the tagging discipline that makes AI spend attributable.
- 04 Training Cost Estimation Before You Commit The FLOP arithmetic that converts a model and dataset size into a GPU-hour figure, why achieved utilisation is the term that decides the answer, and the overheads that turn an estimate into a budget.