Something Is Changing in the Unit Economics of Software

gist

Nicolo argues that AI removes software’s historical near-zero marginal cost by attaching an inference bill to each user interaction. That makes product quality, gross margin, and usage intensity interdependent: better models cost more, power users cost far more than casual users, and falling inference prices may invite enough new consumption to absorb the savings. The result is a different operating playbook built around unit economics, model routing, usage-aware pricing, and growth funded by durable margins.

ideas

• Inference makes usage a direct cost. Each model call adds compute expense to the core experience, weakening software’s historical ability to serve another customer for almost nothing.
• Model choice couples quality and margin. Cheaper models protect gross margin while more capable models can improve the product at a higher per-interaction cost.
• Flat pricing hides unequal consumption. When power users generate far more inference work than casual users, usage-based pricing better aligns revenue with cost to serve.
• Efficiency may increase total demand. Falling inference prices can fund deeper integration, more calls, and background agents instead of becoming retained margin.
• The SaaS growth assumption no longer holds automatically. Founders need viable unit economics before scale because additional customers may carry persistent costs that growth does not erase.

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