Why can I not know what my AI workflow will cost before it goes live?
Opportunity
Enterprise AI inference spend jumped 3.2x in 2025 even as per-token prices fell roughly 1,000x, driven by agentic loops, context window inflation, and always-on monitoring agents. A misbehaving agent at $0.06 per call retrying 1,000 times per minute generates $86,400 of spend in a single day. Existing cloud FinOps tools do not apply because inference cost is a function of semantic input length, tool call amplification, and loop depth, none of which are known at planning time. There are no standard tools for pre-production cost estimation of LLM workflows, and CFOs cannot model AI inference as a predictable budget line.
Why it matters
Without a cost model you can trust before shipping, every AI product is a budget lottery rather than a business.
How I score the opportunity
The Opportunity Score is my own read, not a measurement: how much it hurts, how often it bites, and how little exists to solve it today. Higher means I think it is more worth building.
How much pain it causes when it shows up.
How often people actually run into it.
How little good tooling exists for it today.
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