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ai-pricing-model-picker

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Use this skill when the user is deciding how to price an AI agent product — "how should we price our agent," "per seat or per outcome," "usage-based vs outcome-based," "what do we charge for this agent." Input is what the agent does plus the target budget it displaces; output is a recommended pricing model (per agent, per action, per workflow, or per outcome), a tier structure, and defensible pricing anchors. Built on Manny Medina's four-model framework from analyzing pricing across 60+ AI agent companies at Paid.

skills/manny-medina/ai-pricing-model-picker/SKILL.md

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Oct 20, 2026
License
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Use when the user needs to pick or defend a pricing model for an AI agent product. Produces a recommended model, tier structure, and pricing anchors grounded in the budget the agent actually displaces.

## Profile the agent first

Before recommending anything, get four answers — ask the user or infer from their product description, then confirm:

1. **Breadth of responsibility.** Does the agent cover a comprehensive job function, or discrete tasks?
2. **Workload predictability.** Consistent volume, or wildly variable?
3. **Attribution.** Can a completed outcome be cleanly credited to the agent? Is autonomy high (agent finishes work alone) or low (copilot suggesting actions)?
4. **Budget displaced.** Headcount, BPO/outsourcing spend, tools budget, or a performance line item? Headcount budgets run roughly 10x larger than tool budgets — this answer moves price more than any other.

## Map to the model

| Model | Fits when | Watch out |
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