Why Token Cost Became a Real Line Item I Track

Short summary

Token cost per completed task is the critical unit economics metric for AI products, now superseding gross margin for forecasting. Agentic systems make 5-10x more model calls than chatbots; falling prices don't reduce bills because task complexity multiplies costs. Semantic caching (achieving 67% hit rates) and prompt caching recover 70%+ of costs through engineering discipline—the self-hosting threshold flips at 100M tokens/month.

• •Cost per task is the new unit economics signal for AI products; gross margin alone no longer predicts health
• •Agentic workflows multiply model calls 5-10x versus chatbots, compounding costs despite token price drops
• •Semantic and prompt caching recover 70%+ of costs through engineering discipline without infrastructure scaling

Generated with AI, which can make mistakes.