Agent Era Pricing Skill

Seat pricing quietly assumed the user was a human who logs in. Agents break the assumption from both sides: your customers need fewer seats (one operator, ten agents), and your product gets more usage than ever. This skill redesigns the model around a value metric that survives non-human users — without torching existing revenue on the way.

What This Skill Produces

• A value-metric decision: what you charge for when seats stop proxying value
• Agent-tier design: how agent/API usage is packaged, fenced, and priced
• Cannibalisation math: what happens to current revenue under the new model, computed on real cohorts
• A phased migration plan for existing customers, with the grandfathering decision made explicitly

Required Inputs

Ask for (if not already provided):

• Current model: plans, price points, seat definitions, current API/automation pricing if any
• The evidence of pressure: seat contraction, API traffic growth, customer asks, competitor moves
• Unit economics: cost to serve a seat vs an API call/agent action (rough is fine, labelled)
• 3-5 representative customer profiles with seat counts and usage (the cannibalisation test set)