Reason 1: Custom AI Doesn’t Scale

Key Concepts

• AI Agency Model: A business model offering AI-powered solutions to clients.
• SMMA (Social Media Marketing Agency): An agency focused on managing social media marketing for clients.
• IP (Intellectual Property): Creations of the mind, such as inventions, literary and artistic works, designs, and symbols, names, and images used in commerce.
• Scalability: The ability of a system or business to handle increasing amounts of work or clients.
• Leverage: Using something to maximum advantage.
• Infrastructure: The basic physical and organizational structures and facilities needed for the operation of a society or enterprise.

The Broken Scalability of the AI Agency Model

The core argument presented is that the current “AI agency” model is fundamentally flawed due to inherent scalability issues. Unlike traditional agency models, building custom AI solutions doesn’t lend itself to efficient scaling. The speaker asserts that the AI agency model is “completely broken for these two main reasons.”

The Lack of Standardized Output & Project Variability

The primary reason cited for this broken model is the lack of standardized output. Traditional agencies, such as Social Media Marketing Agencies (SMMA) or web design agencies, operate on repeatable processes. The speaker explains, “In any other type of an agency…the outputs that your team produces are always roughly similar. So you go through the same process for every client every single time.” This allows for efficiency and predictable resource allocation.

However, AI projects, even those appearing similar during initial sales conversations, diverge significantly upon implementation. The speaker emphasizes, “Once you actually start building, you realize it's a completely different project.” This stems from diverse client requirements, including the need to integrate with disparate systems. Larger clients frequently demand deployment on their own, unique infrastructure, further complicating the process. This constant customization prevents the development of reusable Intellectual Property (IP) or leverage.

The Impact of Scale on Margins & Role Definition

The speaker contends that scaling an AI agency worsens the problem, rather than improving it. “Scaling makes this worse, not better, because more clients just means more issues and more people to manage.” This is a direct contrast to other agency models where increased client volume typically leads to improved margins due to economies of scale.

The consequence of this lack of scalability is a shift in the agency’s role. Instead of building a scalable product or service, the agency effectively becomes a team of full-time developers or project managers. The speaker states, “You end up either as a full-time developer or a project manager with a normal job.” This fundamentally alters the value proposition of an “AI agency” and negates the potential for high-margin, scalable growth. The speaker directly links this to the fact that “your margins don't automatically improve with scale.”

Logical Connections & Synthesis

The argument is logically structured: the inherent variability of AI projects prevents the creation of standardized processes and reusable IP. This, in turn, hinders scalability and prevents the agency from achieving the margin improvements typically associated with growth. The core takeaway is that the current approach to building and delivering custom AI solutions within an agency framework is unsustainable and ultimately leads to a business resembling a traditional development or project management firm, rather than a scalable AI-powered agency.