I remember the exact moment I knew we had to pivot RemoteTeam. We had built this incredible suite of tools for remote companies, and we were getting great feedback. But I had this nagging feeling in the pit of my stomach. Every time I saw a new HR tech startup pop up, my heart sank a little. We had a cool product, but did we have a real business? A defensible one?
That feeling is something a lot of founders in the AI space are wrestling with right now. You’ve built a slick feature on top of a large language model, and it’s getting a ton of buzz. But what happens when the next, more powerful model comes out? What happens when the big guys decide to build your feature directly into their platform?
I’ve been fortunate enough to have a couple of successful exits – RemoteTeam to Gusto and MovieLaLa to Gfycat – and I’ve invested in over 200 startups, including some of the biggest names in AI like Anthropic, OpenAI, Scale AI, and Hugging Face. And I can tell you this: a cool feature is not a business. A defensible business, a true moat, is what separates the shooting stars from the companies that last.
The AI Feature Trap
It’s so easy to fall into the feature trap. You see a problem, you build a solution with AI, and it works. But that’s just the first step. The hard part is building a business that can withstand the relentless pace of innovation in AI.
I’ve seen it happen time and time again. A startup builds a fantastic AI-powered copywriting tool. It’s better than anything on the market. But then, a new, more powerful language model is released, and suddenly, a dozen other startups are offering the same thing. The original startup’s advantage evaporates overnight.
This is the reality of building in the AI space. You can’t just be a thin wrapper around someone else’s technology. You have to build something that’s uniquely yours, something that’s hard to replicate. You need a moat.
What is a Moat, Anyway?
Warren Buffett famously said, “In business, I look for economic castles protected by unbreachable ‘moats’.” A moat is a sustainable competitive advantage that protects a business from being attacked by competitors. It’s what allows you to maintain your market share and profitability over the long term.
In the world of AI, there are a few key types of moats you can build:
Network Effects: This is the holy grail of moats. The more users you have, the more valuable your product becomes for everyone. Think about it: every time someone uses Waze, they’re contributing to the real-time traffic data that makes the app so useful. That’s a powerful network effect. In AI, this could be a model that gets better with every new piece of data it processes. The more users you have, the more data you have, and the better your model becomes. It’s a virtuous cycle that’s incredibly difficult for competitors to break into.
Data Moat: If you have a unique, proprietary dataset that no one else has, you have a massive advantage. This is especially true in AI, where the quality and quantity of your data can make or break your model. At MovieLaLa, we had a huge dataset of movie-related social media conversations. This allowed us to build a recommendation engine that was far more accurate than anything else on the market. We weren’t just using a generic movie database; we had a deep understanding of what people were actually saying about movies. That was our data moat.
High Switching Costs: How hard is it for your customers to switch to a competitor? If it’s a huge pain, you have a strong moat. This is often the case with enterprise software. Once a company has integrated your product into its workflows and trained its employees on how to use it, they’re not going to switch unless there’s a very compelling reason. At RemoteTeam, we built deep integrations with payroll and HR systems. Once a company was using our platform to manage its entire remote workforce, it was very difficult for them to switch to a competitor. We had become an essential part of their infrastructure.
Process Power: This is about having a unique, highly efficient process for doing something. It’s not just about having a better product; it’s about having a better way of building and delivering that product. This could be a unique way of training your models, a more efficient way of collecting and labeling data, or a better way of deploying and managing your AI systems. This is a subtle but powerful moat that’s often overlooked.
The Pivot: A Terrifying and Necessary Step
So what do you do when you realize you don’t have a moat? You pivot. The decision to pivot is one of the hardest a founder can make. It’s an admission that your original vision was flawed. It’s a leap of faith into the unknown.
When I decided to pivot RemoteTeam, I was terrified. We had a team of amazing people who had poured their hearts and souls into building our original product. We had investors who had backed our vision. And now I was telling them that we were changing course.
I knew I had to be incredibly thoughtful about how I communicated the pivot. I couldn’t just spring it on them. I had to bring them along on the journey. I started by having one-on-one conversations with every member of my team. I explained my reasoning, I listened to their concerns, and I answered their questions. I did the same with our investors. I was transparent and honest, and I laid out a clear vision for the future.
It wasn’t easy. There were a lot of tough conversations. But in the end, everyone got on board. They understood that the pivot was necessary to build a truly defensible business. And they were excited about the new direction.
Building Your Moat: A Practical Guide
So how do you build a moat for your AI startup? Here are a few practical tips:
Start with the problem, not the solution. Don’t just build a cool AI feature and then try to find a problem it can solve. Start with a real, painful problem that people are willing to pay to solve. Then, figure out how you can use AI to solve that problem in a way that’s 10x better than anything else on the market.
Focus on a niche. Don’t try to be everything to everyone. Focus on a specific niche and become the go-to solution for that market. This will allow you to build a deep understanding of your customers’ needs and develop a product that’s perfectly tailored to them.
Build a community. A strong community can be a powerful moat. If you can build a community of passionate users who are evangelizing your product, you’ll have a huge advantage over your competitors. This is something we did very well at MovieLaLa. We built a community of movie lovers who were constantly sharing their thoughts and recommendations. This not only gave us a ton of valuable data, but it also created a strong sense of loyalty to our brand.
Think about your business model from day one. Don’t just focus on building a great product. Think about how you’re going to make money. A strong business model can be a powerful moat in itself. If you can find a way to monetize your product that’s difficult for competitors to replicate, you’ll have a huge advantage.
The Long Road Ahead
Building a defensible business is not easy. It takes time, it takes patience, and it takes a lot of hard work. But it’s the only way to build a company that will last.
Don’t be seduced by the hype. Don’t be fooled into thinking that a cool AI feature is enough. Focus on building a real business with a real moat. That’s the only way to win in the long run. And trust me, the view from the other side is worth it.
Frequently Asked Questions
What are the most common mistakes when building a defensible business, not just a cool ai feature.?
The biggest mistake I see is overcomplicating things early on. Start with the simplest version that works, get real feedback, and iterate from there. Another common trap is copying what worked for someone else without understanding the context behind their decisions.
How long does it take to build a defensible business, not just a cool ai feature.?
The timeline varies depending on your starting point and resources. For most founders, expect 2-4 weeks for initial setup and 2-3 months to see meaningful results. I've seen teams move faster when they focus on one thing at a time rather than trying to do everything at once.
Do I need technical skills to build a defensible business, not just a cool ai feature.?
Not necessarily. While technical understanding helps, the most important skills are clear thinking and the ability to break problems into smaller pieces. Many successful founders I've invested in started with zero technical background and either learned enough to be dangerous or found the right technical partner.
How do I measure success with this approach?
Pick one or two metrics that directly tie to your goal and track them weekly. Vanity metrics like page views or follower counts rarely matter. Focus on metrics that reflect real engagement or revenue impact.