On December 10, 2024, Elliot Greenwald (Sierra) published the founding text of outcome-based pricing for AI agents. Pivotal thesis: AI agents executing processes autonomously make possible an unprecedented pricing model — "you pay only when the software achieves specific, valuable outcomes: outcome-based pricing."

The article unfolds a four-age genealogy. (1) Shrink-wrapped software (1980s-90s): the floppy disk/CD-ROM box at Fry's Electronics — "Whether you actually used it or not, you paid for it." (2) SaaS / seat-based: Salesforce pioneered it, followed by Google/Microsoft/Adobe; its major flaw = shelfware ("Unused seats sit idly on a proverbial store shelf"). (3) Consumption-based: AWS and Snowflake — "charged only for what you used." (4) Outcome-based: AI agents.

Canonical definition: "outcome-based pricing is tied to tangible business impacts—such as a resolved support conversation, a saved cancellation, an upsell, a cross-sell, or any number of valuable outcomes. If the conversation is unresolved, in most cases, there's no charge."

Alignment principle: "With outcome-based pricing, Sierra gets paid only when we complete a task for you. Our incentives are aligned." Greenwald highlights the structural conflict facing legacy CX vendors: their revenue depends on seat-based pricing, yet "the more effective their AI becomes, the fewer contact center seats their clients need—undermining the provider's own revenue model." An effective AI agent cannibalizes a revenue model built on seats; a pure-play vendor paid on outcome has no such conflict.

The model is granular: a distinction is drawn between simple resolutions (a single question) and complex ones (a case requiring a 20-minute L2 call); escalations generally incur no charge; a blended pricing model is possible (consumption-based for routing/greeting interactions). On the vendor side, there is a commitment to continuous optimization: "we continue to deploy concerted, directed optimizations to refine the agent's performance over time."

Scope: posed in late 2024, this post precedes and grounds the 2026 debate on the agentic economy. It supplies the vocabulary of the billing unit (the completed outcome, not the seat/usage/token) later taken up by Gupta (cost of a completed outcome, buyer-side view), Bain (outcome-based pricing shifts revenue from fixed seats to labor/operations economics, with Sierra cited as an example) and Ng (pricing anchored to the replaced salary). ⚠️ The article contains no figures (no ROI, no named client): it is a conceptual manifesto. To be used for the Cost Optimization slot (vendor-side view of cost per outcome) and the value-based positioning of agentic delivery.