What building Cameo Labs with AI taught me about business capacity

I built Cameo Labs from zero to $3 million with eight humans. AI made that possible.

The part I want other founders to understand is what changed in the work: how much I could take on across sales, operations, and delivering software-development services to our customers.

That experience is the foundation of what I teach in The AI Employee Lab.

Seeing a different way to build

I’ve spent 20 years in technology building software. When GPT-4 arrived in ChatGPT and I began exploring Midjourney, I recognized how much AI could change business.

I started to see how much business could change. After two decades building technology, I was looking at what these tools could make possible for the company itself: the work it could take on, the information it could use, and the capacity of the people running it.

About five months after GPT-4 arrived, I started Cameo Labs.

We build custom digital products and platforms and modernize software for the AI era. AI became part of how we operated the business as well as how we delivered the work.

Capacity across the business

At Cameo Labs, we use AI to research opportunities, prepare proposals, organize customer insight, and move projects forward. It expands the capacity of our human team across sales, operations, delivery, and the coordination those functions require.

For a founder, those are connected concerns. Winning work creates delivery responsibilities. Delivery creates information the business needs to understand and use. Running the company requires attention across all of it.

That is why I want leaders to look beyond a single impressive AI output. Consider what happens around it. Where did the information come from? Who will use the result? What decision does it support? What happens next?

Those questions help connect useful AI work to the way a company operates.

Design the responsibility and the handoff

The practical method I teach begins with a job the business needs done. Define the responsibility, the information required, the standard for a useful result, and the human who remains accountable.

Then work through the handoff. A proposal draft still needs someone responsible for scope and promises. Customer analysis needs someone to evaluate the findings and decide what to change. A project update needs to reach someone who can act on it.

AI can expand what people can prepare, understand, and complete. Leadership still has to decide how that capability fits into the business.

Teaching what leaders can apply

Over the last year, I’ve delivered this training inside multiple client companies, working with the people responsible for applying it to their work.

That experience sits alongside what we do at Cameo Labs. It informs how I explain the method, demonstrate an AI role, and help someone begin with their own business information.

I want founders and leaders to leave able to identify a useful responsibility, understand what the role needs, and judge whether its work is good enough to use. That is a capability they can keep applying as their business changes.

Start with a result you can inspect

In The AI Employee Lab, I’ll take you inside our human-and-AI operating model and show you an Employee being built and tested.

Then you’ll activate two supplied AI Employees using your own business context. One analyzes customer evidence; the other uses those findings to assess your website and offer. You’ll leave with useful findings and three prioritized actions.

You will have something concrete to inspect, improve, and use—and a clearer view of the next responsibility AI could help carry in your company.