Some products do only what their maker built: a fixed set of features. If you need something else, you wait.
Other products can be extended. They offer connection points where anyone can plug in a new tool, a new source of data, a new skill.
The Wall Socket
Think of a wall socket. The maker does not need to know what you plug in. But notice who holds the power. The owner of the socket decides its shape. Everyone else has to build plugs that fit.
Change the socket, and every plug has to change with it. That is why extensibility is control. Whoever defines how others connect shapes everything that gets built on top.
A Worked Example
The video gives an illustration. A closed assistant ships with 10 tools, all built by its maker. An open one ships with 10 and lets others add 1,000 more. That is 1,010 in total, which is this publication’s addition.
The second product grows without its maker doing the work, and its maker still sets the rules.
The open product grows without its maker building the tools, and its maker still sets the rules. An illustration with round numbers.
Why It Matters
This is why the strongest position is often not the best product. It is the product that everything else connects to. Leaving it means rebuilding every connection.
There is one more case. Sometimes the socket is a shared standard that no single company owns. Then a tool built once works everywhere, and the control is spread among everyone who uses it.
MCP is an example of Extensibility Is Control. MCP is a shared plug, and the extensibility lesson says whoever defines how others connect shapes what is built on top.
Extensibility Is Control builds on Switching Costs. Leaving the product everything connects to means rebuilding every connection.
The Business Engineer framework maps where each part of the AI stack sits and who holds the leverage. These pills are short lessons from the same library.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
