In a recent LinkedIn post, jessie van breugel addresses common skepticism about AI tools, particularly regarding their potential for generic output. Van Breugel details a process designed to create a highly personalized AI “engine” that learns and writes in the specific voice of a founder, distinguishing it from one-size-fits-all solutions.
The core of Van Breugel’s argument centers on the distinction between a “tool” and an “engine.” While a tool might offer a standardized solution, an engine, as described in the post, is built and customized for a specific business. This intensive customization is what allegedly prevents the output from sounding like generic AI.
“Isn’t the install just another generic AI tool with your name slapped on it?”
Van Breugel acknowledges this frequent question, stating that the team has dedicated time to answering it through a practical demonstration. They took a real founder’s business, analyzing his existing positioning, written posts, and client acquisition strategies.
Building a Bespoke AI Voice
The process, as outlined by Van Breugel, involved building the AI’s learning component “live, from start to finish” on the founder’s specific business data. The objective was to ensure the AI’s output was “unmistakably theirs instead of unmistakably AI.” This involved significant human effort and time investment.
Van Breugel emphasizes that this level of personalization is not achievable through a simple button press. “You can’t build something that specific on one business in an afternoon,” the post states. The development requires “100s of hours of building on that one business that make the output unmistakably theirs instead of unmistakably AI.” This contrasts sharply with generic tools that might provide the same output to thousands of users.
The “Install” vs. the “Tool”
The concept of an “install” is presented as a proprietary engine, deeply integrated with and learning from a single business. This is contrasted with a “tool,” which is seen as a more generalized offering.
“A generic tool gives 10,000 people the same thing. An install is built on your business, so what comes out is yours and nobody else’s.”
According to Van Breugel, the distinction lies in ownership and uniqueness. Renting a tool implies using a pre-made solution, whereas owning an engine suggests a bespoke system tailored to one’s specific needs and brand identity. This “whole gap between renting a tool and owning an engine” is a key theme explored in the post.
Demonstration and Future Rollout
To illustrate this process, Van Breugel mentions that the entire build was filmed. This content is slated for release to an email list, providing a “full breakdown of how a piece of the engine gets built on one real business.” This detailed breakdown will be available alongside an existing playbook.
“We filmed the entire build. Over the next few days it’s going out to the list — the full breakdown of how a piece of the engine gets built on one real business.”
Van Breugel invites interested individuals to join the list to access this detailed explanation, concluding with a forward-looking statement, “See you soon on the inside.” The article highlights Van Breugel’s approach to demystifying AI personalization and demonstrating a method for creating unique, business-specific AI outputs.
📝 About This Content
This article is based on insights shared by jessie van breugel on LinkedIn.
📅 Originally posted on July 18, 2026 | View original post on LinkedIn →