Pricing for uncertainty in an agentic world
Blog post from Orb
As organizations increasingly combine human employees with AI agents, software pricing must accommodate uncertainty over how work will be divided between them. While hybrid models of seat-based subscriptions and consumption pricing have enabled experimentation, purchasing seats and tokens separately can force customers to make premature decisions about staffing and agent usage. GitLab and HubSpot illustrate an emerging approach in which customers can shift a shared budget between human seats and AI credits during a contract term, with HubSpot adding spend caps, reporting, and feature-pausing controls to manage risk. Supporting such flexibility requires intentional exchange rates, clear credit drawdown rules, revenue-recognition tracking, and real-time metering and entitlement systems. The central argument is that pricing should support the long transition to agent-augmented work rather than assume a future in which agents have already replaced most human activity.
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