Opinions expressed by Entrepreneur contributors are their own.
Key Takeaways
- AI startups don’t just need engineers — they need experienced founders who know how to build businesses.
- Even after 40 years of startups, building in AI can make seasoned founders feel like beginners.
- Technology may change, but fundamentals like customers, margins and execution still decide success.
I started my first company at the age of 21 and have launched 9 more over the last 39 years. That’s a total of 10, and I just turned 60 this year.
I have had multiple exits — including acquisitions by venture capital and private equity firms.
I have also failed multiple times and lost everything once. I have consulted for public companies, and I was elected to public office, lost a state senate race, written two Wall Street Journal bestselling books and spoken on 3 TEDx stages.
After 4 decades of startups, you develop a pattern. You see the opportunity, you build the team, you grind through the first year, you hit a rhythm and you either scale, fail or exit. I have lived this story my whole life.
Restaurants, insurance, media, marketing, consulting — every business I started was in an industry that I did not know or understand when I started. That was actually normal. I understand the business side and the economics. I knew how to manage money and risk so I moved forward.
Then I decided to build an AI company. And everything I thought I knew went sideways. I was now a non-tech founder.
Why AI is a different animal
In a restaurant, your product is food. In insurance, your product is a policy. You can sell specific benefits. In marketing, we sold leads.
In AI, however, your product is a language model’s ability to simulate human conversation, grounded in someone’s actual personality, delivered through a real-time video avatar that looks and sounds like a real person.
I have to be honest; I have no idea how that works, and 6 months ago, I didn’t even know AI could do it. It’s like magic to me.
I am not an engineer. I do not write code. I spent the first three months of this company just learning what was possible and finding someone who did understand it so we could build it. I would love to tell you that I now know what a RAG pipeline is, or how vector databases work, and why retrieval-grounded generation is different from a chatbot. I wish I could tell you all those things, but I can’t.
I’m still working on getting my emails to show up on both my phone and my computer at the same time. What I can tell you is that I know my limitations, so I brought someone in who does understand it, and I got out of their way.
To be fair, I have to become conversationally fluent in technology. Just enough that I can talk about our products and then refer you to engineering for the tough questions.
What has stayed the same
The fundamentals of building a company are all the same, even in AI.
You still need a problem worth solving. You still need a team that can execute. You still need to find customers and you need to tell a story that makes investors want to listen.
The technology is different, but the business inside the business is the same. Margins matter. Customer acquisition cost matters. Retention matters.
The founders who are going to win in AI are not the ones with the best models — they are the ones who understand that technology is a tool, not a strategy and the best technology will still fail if you don’t know how to run an actual business.
The advantage nobody talks about
Now here is the scary part: there is an unspoken bias in Silicon Valley that AI companies should be founded by 25-year-old engineers and be based in the valley.
But too often, the younger founders don’t understand operations or money management. Too often, they are on a quest to build technology that is looking for a problem.
I have spent 30 years understanding customers, sales cycles, distribution channels, and how to build something people will actually pay for. I did not have to learn how to run a business. I had to learn the technology and, more specifically, the AI side of the new world. That is a much shorter learning curve than the reverse. (Now I say that because our Chief Architect has a PhD in computer science and robotics with 6 patents to his name. I don’t need to understand his world. He has that covered.)
If you are an experienced entrepreneur looking at AI and thinking you are too late, too old or too non-technical, I’m here to tell you that you are wrong. The market is not short on engineers. It is short on experienced founders who know how to build companies, and there has never in the history of the world been a better time to do that.
What scares me
Every company I have built before, I could see the finish line. I knew what success looked like.
The potential ceiling here is so much higher than anything I have ever done before. That is what’s truly interesting and a little intimidating. We are not building a restaurant chain or an insurance brokerage, or even a lead-gen company where the outcomes and product are specific. We are building AI-driven technology that could fundamentally change how humanity preserves its memory.
That sounds grandiose. I know. But when you watch someone have a conversation with an AI version of their father and see their reaction, it stops being grandiose and starts being real.
And I think that is exactly why it is worth building.
Key Takeaways
- AI startups don’t just need engineers — they need experienced founders who know how to build businesses.
- Even after 40 years of startups, building in AI can make seasoned founders feel like beginners.
- Technology may change, but fundamentals like customers, margins and execution still decide success.
I started my first company at the age of 21 and have launched 9 more over the last 39 years. That’s a total of 10, and I just turned 60 this year.
I have had multiple exits — including acquisitions by venture capital and private equity firms.
I have also failed multiple times and lost everything once. I have consulted for public companies, and I was elected to public office, lost a state senate race, written two Wall Street Journal bestselling books and spoken on 3 TEDx stages.



