Production AI economics guides
Measure the decision before you optimize it.
Practical methods for finding the real unit cost of an AI workload, comparing alternatives, and verifying whether a change improved the business outcome without crossing its operating constraints.
01 / Foundations
Start with a defensible unit metric.
Cost per token is useful for checking a provider bill. Cost per successful outcome is more useful for comparing production decisions.
How to calculate AI cost per successful outcome
Choose a denominator, include retries and human review, separate operating cost from implementation expense, and work through an illustrative comparison.
Read the guide Guide · 11 minute readProduction LLM cost-optimization checklist
Trace calls, context, output, retries, caching, batching, and routing in the order needed to turn a rising bill into a testable change.
Use the checklistHow these guides work
Useful before the private data arrives.
The guides explain reusable methods with visible assumptions and illustrative examples. They do not claim that a modeled saving is a verified production result.
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