In a recent episode of the Monetizely channel, pricing strategy experts Akhil and Ajit discussed a controversial email from Anthropic introducing usage restrictions for Claude AI users. The video "Claude Limits Usage: Anthropic's Pricing Dilemma EXPLAINED" explores how Anthropic is navigating the challenges of scaling an AI business while managing costs in its competitive battle with OpenAI.
The Email That Stirred the AI Community
Akhil opened the discussion by sharing an email he received from Anthropic that announced upcoming restrictions on Claude usage. This notification immediately raised concerns, with Akhil noting, "I thought there are already many restrictions on usage with Claude."
The email essentially informed users that Anthropic would be implementing usage limits that would affect approximately 5% of users—primarily power users. This move sparked significant discussion within the AI enthusiast community, with many users feeling targeted.
As Ajit explained: "Fundamentally what they are saying is… AI companies have to be very careful. Just a small fraction of overusing customers can completely change the profitability dynamic."
The Unique Economics of AI SaaS vs. Traditional SaaS
A key insight from the discussion is how fundamentally different AI SaaS economics are compared to traditional software services. According to Ajit:
"When you have a regular SaaS product, regular application layer SaaS product, think of your Salesforce CRM… these products have 90-95 plus percentage gross margin on their product. The cost to deliver on a per customer basis is one or $2 or $3 per unit time."
In contrast, AI companies like Anthropic face substantial ongoing costs that scale with usage. As users engage with more sophisticated models like Claude Opus, the costs grow even higher. This creates a significant economic challenge when offering flat-rate subscription plans.
Credit-Based Systems: The Industry Standard Anthropic Isn't Following
The discussion highlighted that most generative AI companies employ credit-based systems to manage the variable costs of AI usage. Ajit pointed out:
"Most generative AI companies such as 11 Labs or other companies that bring generative products will have a credit based system and they will sell credit bundles."
This approach allows companies to tie usage directly to costs while giving users clarity about what they're paying for. However, Anthropic and OpenAI have chosen a different path for their consumer-facing products:
"Companies like OpenAI, companies like Anthropic and others, they cannot directly for their frontline products give you this credit based system… because they are trying to capture a large market right now."
Strategic Considerations: The Mass Market vs. Power Users
One of the most interesting aspects of the conversation was the discussion about Anthropic's strategic priorities. Ajit suggested that Anthropic is making a calculated decision to potentially alienate power users in favor of capturing the broader market:
"They don't care about Ajit and Akhil. We want to capture and change user behavior from the large market who just like us and they use us little bit because they're trying to capture the whole consumer segment and they're going against OpenAI."
Akhil added a crucial point about Anthropic's revenue structure: "Unlike OpenAI, most of their money comes from API. 85% of their revenue comes from API, which is anyways already transparent, pay-per-use and clear."
The User Experience Problem
Beyond the business strategy, Akhil emphasized the poor user experience created by opaque usage limits:
"I really do not like the opacity that exists in their consumer facing product. As in, I just have to believe them, trust them when they say that you have over exceeded your limit… Completely black box."
This opacity creates psychological friction for users. As Akhil explained: "Even if I am not in the five percent that is impacted and this is very psychological… There are very few people in this world who will receive this email and immediately believe that, yes, I will not be impacted because that is not how the mind works."
The "Communism Model" of AI Access
In a particularly colorful metaphor, the hosts described Anthropic's approach as a "communism model" of AI access:
"This is why it's a communist sort of, and you have overused the commons. And now you must go to the AI Gulags," joked Ajit.
This highlights the tension between providing equal access to AI capabilities while managing the economic realities of delivering those capabilities.
The AI War Context: Massive Losses and Valuations
To understand Anthropic's decisions, it's important to consider the broader context of the "AI war" with OpenAI. As Ajit noted:
"Open AI, I believe lost three to five billion dollars last year, according to Marimilka's report. This year, OpenAI would have lost even more net amount of money, even though they are growing users at cetera break neck pace."
With Anthropic valued at approximately $170 billion after raising $5 billion, these companies are making strategic decisions based on a long-term vision where, as Ajit puts it, "this thing becomes the internet, maybe in a year."
Looking Forward: The Future of AI Access
The conversation concluded with reflections on how AI is becoming increasingly integrated into everyday life. Akhil observed how his seven-year-old daughter doesn't say "let me Google this" but instead asks to "ask ChatGPT"—showing how AI has "gone from a verb to a person."
This humanization of AI tools creates stronger user connections, which makes pricing changes all the more sensitive. As Akhil concluded, "If you want Sonnet and only Sonnet works, which we have reached through trial and error… we will pay."
Key Takeaways for SaaS Executives
For executives watching the AI pricing landscape evolve, this discussion offers several valuable insights:
- Traditional SaaS economics don't apply to AI products where costs scale significantly with usage
- Credit-based systems provide transparency but may create friction in consumer adoption
- Strategic priorities may require sacrificing power users to capture the mass market
- Opacity in usage limits creates psychological uncertainty for users
- AI companies are playing a long game, willing to sustain massive losses for market position
As AI continues to transform into an essential utility, finding sustainable pricing models that balance accessibility with economic viability remains one of the industry's biggest challenges.