Post methodology: Claude 3.7 via custom Dust assistant @TDep-SubstackPost with the system prompt: Please read the text of the podcast transcript in the prompt and write a short post that summarizes the main points and incorporates any recent news articles, substack posts or X posts that provide helpful context for the interview. Please make the post as concise as possible and avoid academic language or footnotes. please put any linked articles or tweets inline in the text. Please refer to Podcast guests by their first names after the initial mention. Light editing and reformatting for the Substack editor.In this episode, former Outreach CEO Manny Medina discusses his new company, Paid, which helps AI companies capture more value through sophisticated pricing strategies. The conversation reveals how AI is fundamentally changing software pricing models and offers a compelling framework for companies looking to monetize their AI agents effectively.
The Hedgehog Approach Wins in AI
Manny argues that in today's AI landscape, the "hedgehog" approach is winning—companies that focus deeply on solving specific, well-defined problems are finding the most success. Rather than trying to build broad platforms, the most profitable AI applications are targeting narrow use cases with high friction and manual work.
"If you take up a very narrow problem, and then you hedgehog into it and you become the best at that one thing, that is printing money right now," Manny explains. He cites examples like Quandri (policy renewals), XBOW (penetration testing), and HappyRobot (freight booking) as companies that have found success by focusing on specific workflows where there's no clear software solution and processes are people-heavy.
This approach aligns with what Manny recently outlined in a Growth Unhinged article, where he analyzed patterns from 60+ AI agent companies and found that specialized solutions are commanding premium prices.
The Four-Stage Pricing Maturity Curve
The episode highlights Manny's framework for AI pricing models, which he describes as a maturity curve:
Activity-based pricing: Charging per token or API call (the simplest approach)
Workflow-based pricing: Charging for complete processes rather than individual actions
Outcome-based pricing: Charging based on measurable results achieved
Per-agent pricing: Charging for AI agents that replace human equivalents
Manny warns that companies stuck in activity-based pricing will face commoditization pressures. "If you stay there, somebody will come along and say, 'I'll do the same thing for cheaper,'" he cautions.
This framework has gained significant attention in the industry. As Elliot Greenwald at Sierra explains in a recent blog post, "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."
JUMP TO: The Pricing Maturity Curve
Don't Let Declining Token Costs Dictate Your Strategy
While many believe AI models will commoditize due to falling token costs, Manny offers a contrarian view. He argues that inference costs for sophisticated reasoning will likely remain significant, and companies should focus on capturing value through the full stack—including data, APIs, and other infrastructure.
"I just don't see how the token price goes down," Manny says, explaining that deeper reasoning capabilities in models will continue to command premium prices.
"The problem that we have right now in cost mode is that because everything, like all the activity of the agent goes down through this eval framework that acts as a proxy before the token goes to the LLM, you don't know who's incurring what cost," Manny explains. "This is why the margin problem is such a bear to solve."
Focus on Narrow Markets First
Perhaps the most actionable advice is Manny's emphasis on market focus. "Stay focused on a very narrow set of customers. Don't worry about TAM. Disregard VC advice about big TAMs. Small TAMs will be big TAMs as long as you deliver a superb experience," he advises.
This approach allows companies to dial in their product, pricing, and go-to-market strategy for a specific use case before expanding, creating a stronger foundation for growth.
As the AI landscape continues to evolve, Manny's insights offer a valuable roadmap for companies looking to capture their fair share of the value they create. By moving up the pricing maturity curve and focusing on specific customer segments, AI companies can build sustainable businesses that align costs with the true value their agents deliver.
BONUS ESSAY: | The Pricing Maturity Curve for Agentic AI Companies
Hosted by Pat Grady and Lauren Reeder, Sequoia Capital
Mentioned in this episode:
The Hedgehog and the Fox: 1953 essay by philosopher Isaiah Berlin that divides writers into hedgehogs, that view the world through a single defining idea, and foxes, that draw on a wide variety of ideas
Manny’s list of contemporary “hedgehog” companies in AI:
CPQ: Configure, Price, Quote
Invent and Wander: Book by Jeff Bezos and Walter Isaacson
Foundations of Statistical Natural Language Processing: 1999 book by Chris Manning and Hinrich Schütze that Manny cites as a piece of AI content every AI founder should read. (still in print, companion site here)
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