Outcomes-Based Pricing
by Bret Taylor • Co-founder & CEO, Sierra at Sierra
A legendary builder and executive who co-created Google Maps, was CTO of Facebook (presiding over the IPO era), co-CEO of Salesforce, and Chairman of the Board at OpenAI. He currently leads Sierra, an enterprise AI agent company.
🎙️ Episode Context
Bret Taylor shares deep insights drawn from a career spanning the most pivotal moments in modern tech history. He discusses the inevitable shift from SaaS to 'Service-as-a-Software' via AI agents, the necessity of outcomes-based pricing, and the leadership frameworks that allowed him to succeed across engineering, product, and CEO roles.
Problem It Solves
Addresses the difficulty of selling 'productivity' software where ROI is hard to prove.
Framework Overview
A pricing strategy for autonomous agents where customers are charged per successful resolution or defined outcome, rather than per seat or per token.
🧠 Framework Structure
Autonomy: The software must be able t...
Measurability: The outcome must be bi...
Alignment: Ensure the pricing model a...
Deflection vs. Containment: Measure v...
When to Use
When selling AI agents or automation software where the value proposition is replacing labor costs.
Common Mistakes
Charging for 'usage' (tokens) when high usage might actually indicate the AI is failing to solve the problem efficiently.
Real World Example
Sierra charges customers when the AI agent successfully resolves a customer inquiry without human intervention.
I think the whole market is going to go towards outcomes-based pricing. It's just so obviously the correct way to build and sell software.
— Bret Taylor