The new value architecture of the AI-native SaaS era

This excerpt proposes new financial and operational KPIs for AI-native software businesses, centered on credit-based pricing and usage: revenue composition metrics (committed vs. burndown ARR, credit utilization, burn velocity, effective price per credit); margin measures that separate inference costs (credit margin, inference-adjusted gross margin, compute leverage, AI-adjusted Rule of 40); and behavioral/value signals (time-to-first outcome, workflow/agent adoption, net credit retention). It argues legacy SaaS metrics should be retired or recalibrated as AI changes unit economics and investor valuation approaches.