How to Build an AI FinOps Function Before Your CFO Forces You To
Most AI FinOps functions get built after a CFO gets a surprise bill. Here's how to build it proactively — structure, ownership, charter, and tooling.
Most AI FinOps functions get built after a CFO gets a surprise bill. Here's how to build it proactively — structure, ownership, charter, and tooling.
RAG pipelines look cheap per call — until you account for embedding, re-indexing, and context stuffing. Here's where the real costs actually live.
Comparing GPT-4o to Claude Sonnet on price per token is a trap. Benchmark at the task level — the only comparison that actually matters.
Cursor is $20/month per seat. Underneath that is BYOK API usage and background agents that bypass the seat fee. Here's the real cost math.
Shadow AI audits fail when they go top-down. Here's a collaborative playbook that finds what's running without driving tools further underground.
AI bill shock isn't a budgeting failure — it's a visibility failure. The spend happened days ago and nobody had a signal. Here's how to fix that.
Cloud FinOps teams are the natural owners when AI spend appears. Here are the five structural mistakes they make when they apply their cloud playbook to AI.
No one in your org sees the complete picture of AI vendors running. Here's a step-by-step guide to finding them all without creating new bureaucracy.
A practical guide to standing up AI FinOps from inside engineering: who owns what, what meetings matter, and what tooling exists today.
Cloud FinOps gave us tagging, reserved instances, and rightsizing. None of it maps cleanly to AI spend. Here's what breaks and what to do instead.
Token costs are not what you think. A deep look at tokenizer differences, output vs. input pricing, context window economics, and why cost-per-token misleads.
Shared API keys are convenient and financially opaque. No attribution, no accountability, no optimization signal. Here's what that actually costs you.