The same mistakes with AI moats sink companies over and over.
Your AI model will be copied. Your data might not be unique. I'll explain why the only durable moats are systems, not assets, and how to build a compounding flywheel of defensibility from day one.
What I've Learned From 115 Companies
A few patterns in AI moats come up again and again.
The founders who handle AI moats well understand that your team matters more than your technology.
The Counterintuitive Truth
In AI moats, the best practitioners often do less, not more.
The lesson: most founders overthink this and underspend on execution. It sounds simple. It's incredibly hard to execute.
The Numbers Don't Lie
Investing early in AI moats can be the difference between raising your next round and running out of runway.
One of my portfolio companies went from struggling to profitable in under a year after they finally got serious about this. The founder told me later that they wished they'd started sooner.
This connects to broader themes around AI talent wars, AI exit strategies, AI pitch decks, AI due diligence that I've been thinking about a lot lately.
Final Thoughts
There are no shortcuts in AI moats, but there are smarter paths.
The strongest teams treat AI moats as a competitive advantage, not a checkbox. They invest in it early, measure it obsessively, and never stop improving.
If you're just getting started with AI moats, don't be intimidated. Everyone starts somewhere. The key is to start with the right mindset and the right framework, and then execute like your company depends on it. Because it probably does.
Frequently Asked Questions
Q:What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.
Q:What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 234 startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
Q:How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
Q:Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.