The Truth About AI's Token Economy: It Eats Profits Faster Than You Can Scale
- Jude Temianka
- 6 days ago
- 4 min read
The tech scene loves a good shortcut.
Right now, that shortcut is the "AI Wrapper Business"—a glossy user interface layered over a powerful, off-the-shelf Large Language Model (LLM). It feels like genius: outsource the hard part (building the model) and focus on the wrapper (distribution and design). Low overhead, high potential. What could possibly go wrong?
During my time in venture building in Berlin, I’ve seen this flaw up close. I’ve both witnessed and personally experienced the hard way that the cost of utility, when dealing with complex, high-stakes services, quickly outstrips the revenue model.
The prevailing wisdom is flawed. The truth is, the AI token economy is a silent, insidious cost driver that will eat your margins faster than you can scale, and often, the only solution founders attempt is to charge a price their product simply hasn't earned.
The $50 Fix: When Price Tries to Mask Fragility
Many early-stage founders try to circumvent the inevitable cost of token consumption by charging premium subscription costs—often $50 per month or higher—for their wrapper product.
The idea is simple: if the core cost is high, inflate the price to maintain a margin. This tactic works temporarily, but it reveals a fundamental lack of defensibility and commercial acumen.
A high price point forces the customer to ask a critical question: Am I paying $50 a month for information I couldn't already get by paying $10-20 a month for a general-purpose AI subscription (GPT, Claude, Perplexity, Abicus), and spending ten minutes crafting a good prompt?
If your wrapper product can't answer "yes" to that question, your business isn't defensible—it's just a temporary cash grab built on a feature, not a foundation.
The Wrapper Fatigue: Where Specialisation Falls Flat
This year, I've been pitched countless ideas that follow this exact flawed playbook, illustrating a lack of strategic depth:
The Case Study Generator: An AI platform that generates case studies for creative agencies. Ask yourself: Are creative agencies, who live and breathe innovation, not already using the latest OpenAI or Anthropic products within their creative and software development processes? Is your solution, running on the latest GPT-4o mini, truly providing value they couldn't generate themselves? The defensible value is zero.
The Life Coach App: An app designed for mental health check-ins and life coaching conversations. Can't someone already converse with GPT, Claude, or Perplexity about their problems? The high-capability base models are already phenomenal conversational partners. Unless your wrapper includes certified human therapists, unique proprietary mood data, or a scientifically validated framework baked into the model architecture itself, your utility vanishes.
The "Boyfriend/Girlfriend" App: A relationship companion app. OpenAI's latest capabilities even suggest LLMs are heading toward entertaining highly conversational, even erotic, interactions. The line between a general-purpose conversationalist and your specific, high-priced wrapper product is non-existent.
The Meeting Manager: An app that debriefs you on upcoming meetings and lets you reschedule them via messaging. One word: Co-pilot. Large enterprises are already adopting platforms where this is a deeply integrated, non-AI cost feature.
These products are not value propositions; they are convenience taxations. You are asking customers to pay a premium for a minor convenience over the core tools they already own.
The Token Trap: Why Context Creep Kills Margins
The high price tag often serves to hide the single biggest strategic flaw in the wrapper model: Context Creep.
For a complex, high-value service—such as advanced advisory support (something I’ve been working on lately) —the AI cannot operate on simple, transactional queries. It must maintain a vast, long-running context, constantly referencing past interactions and proprietary documents (often through a RAG system).
Crucially, every new user input requires the model to re-ingest this entire context to maintain accuracy. This means:
Input Token Consumption explodes exponentially with every user turn.
If you use a high-intelligence model (which you must to justify the $50/month price), the output cost is high. For a demanding customer using a powerful model, a budget of 1 million tokens for the month can easily become 5 million tokens or more after a few conversations.
Based on premium model pricing, your cost of goods sold (COGS) for that single user can easily jump from a few pounds to $50 or $60 per month.
When your cost to serve one user potentially exceeds their subscription fee, your business is technically and financially unscalable. You are scaling revenue while accelerating towards zero profit.
Defensibility Requires More Than A Glossy Interface
If you want to build a business that provides enduring value and doesn't rely on continuously hiking the price, or running from competition, you must build a defensible moat that the LLM cannot cross.
Instead of focusing on the AI wrapper, strategists must pivot to an AI-enabled value chain:
Proprietary Data Moat: The AI is simply a tool for uncovering insights from unique data (unique means self-generated, not reusing publicly accessible data), irreplaceable, and constantly refreshed (e.g., proprietary financial transaction data, exclusive legal precedents, or highly curated, real-time market sentiment feeds).
Workflow Moat: The AI is deeply embedded into a system where it is harder to leave than to stay—think integration into legacy enterprise software or a regulated process. The value is in the integration, not the intelligence.
Human/Community Moat: The AI handles 80% of simple tasks, freeing up a unique human expert or community to deliver the 20% of high-stakes, high-touch support. The price is justified by the human outcome, not the token cost.
My recent strategic pause confirmed that real innovation isn't about the technology you deploy; it's about the commercial and strategic context you build around it. Let's build businesses that truly provide value, not just expensive versions of what we already have!
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