Everyone seems to be an AI expert these days. You can't throw a rock in Silicon Valley without hitting someone who's "building the future of AI." But here's the thing: most of it is just noise. I've been in the trenches for over a decade, building and investing in AI companies. I've seen the hype cycles come and go. And I've learned that the real winners aren't the ones making the most noise. They're the ones quietly solving real problems.
I'm not a theorist. I'm a builder. I co-founded RemoteTeam, which was acquired by Gusto, and MovieLaLa, which was acquired by Gfycat. I've also been fortunate enough to be an early investor in over 200 companies, including some of the biggest names in AI like Anthropic, OpenAI, Scale AI, and Hugging Face. I've seen what works and what doesn't. And I'm going to share 7 of the most important lessons I've learned along the way.
1. Your AI is only as good as your data.
This is probably the most important lesson I've learned. Everyone is obsessed with algorithms and models. But the truth is, the model is a commodity. The real differentiator is the data. If you have a unique, proprietary dataset, you have a real competitive advantage. It's your moat. For example, at RemoteTeam, we had a unique dataset of global payroll and HR data. That's what allowed us to build a better product than our competitors. We weren't just another payroll company. We were a data company. We could see trends and patterns that no one else could. That's what made us valuable.
I see so many startups that are trying to build an AI company without a data advantage. They're just using the same public datasets as everyone else. That's a recipe for failure. You need to have a plan for how you're going to acquire and use data in a way that no one else can. That's the secret to building a defensible AI business.
2. Solve a real problem, not a fake one.
This sounds obvious, but you'd be surprised how many AI companies are solutions in search of a problem. They have a cool piece of technology, but they don't know how to apply it to a real-world problem. I get pitched these companies all the time. They'll say something like, "We've built a new type of neural network that can do X, Y, and Z." And I'll say, "That's great, but who is going to pay for that?"
The best AI companies start with a real problem. They talk to customers. They understand their pain points. And then they figure out how to use AI to solve that problem. For example, one of the companies I invested in, Scale AI, started by solving a very real problem for autonomous vehicle companies: data labeling. It was a huge bottleneck for the industry. And Scale AI built a platform to solve that problem. They didn't start with a cool piece of technology and then try to figure out what to do with it. They started with a real problem and then built the technology to solve it.
3. Focus on the user experience.
Even the best AI is useless if it's not easy to use. I've seen so many AI products that are incredibly powerful, but they have a terrible user experience. They're confusing. They're hard to navigate. And as a result, no one uses them. It doesn't matter how smart your AI is if no one can figure out how to use it.
This is something we obsessed over at RemoteTeam. We wanted to make our product as simple and intuitive as possible. We spent countless hours on user research and design. We wanted to make it so easy to use that you didn't even need a manual. That's the bar you should be aiming for. Don't let your engineers design the user interface. Hire a great designer. And listen to your users. They'll tell you what they want.
4. Build a great team.
This is another one that sounds obvious, but it's so important. You can have the best idea in the world, but if you don't have the right team to execute it, you're going to fail. I've seen it happen time and time again. A brilliant founder with a great idea, but they can't attract or retain top talent. And as a result, their company slowly withers and dies.
Building a great team is hard. It's one of the hardest things you'll do as a founder. You need to be able to sell your vision. You need to be able to convince people to take a risk on you. And you need to be able to create a culture where people can do their best work. At MovieLaLa, we were a small team, but we were a great team. We were all passionate about movies and technology. And we were all committed to building a great product. That's what allowed us to compete with much larger companies.
5. Don't be afraid to pivot.
The path to success is never a straight line. There will be twists and turns along the way. And you need to be able to adapt. Don't be so in love with your original idea that you're not willing to change it. The market will tell you what it wants. And you need to be able to listen.
We pivoted multiple times at RemoteTeam. We started out as a tool for remote companies to manage their teams. But we quickly realized that the bigger opportunity was in global payroll. So we pivoted. It was a scary decision. But it was the right decision. It's what allowed us to build a $100M+ business. If we had stuck with our original idea, we would have been a much smaller company. Don't be afraid to change course. It might be the best decision you ever make.
6. Think in terms of ROI.
AI is not magic. It's a tool. And like any tool, it needs to have a positive return on investment. If you're going to invest in AI, you need to be able to measure the impact it's having on your business. Are you saving money? Are you making money? Are you improving customer satisfaction? If you can't answer those questions, you're not ready to invest in AI.
I see so many companies that are just throwing money at AI without any real plan for how they're going to get a return on that investment. They're just doing it because everyone else is doing it. That's a terrible reason to do anything. Before you invest a single dollar in AI, you need to have a clear understanding of what you're trying to achieve and how you're going to measure success. Otherwise, you're just gambling.
7. Don't believe the hype.
The AI industry is full of hype. There are a lot of people who are making a lot of noise, but they're not actually building anything of value. Don't get caught up in the hype. Focus on the fundamentals. Solve a real problem. Build a great team. And don't be afraid to be different.
The most successful AI companies are not the ones that are getting the most press. They're the ones that are quietly building great products and delighting their customers. They're the ones that are focused on the long term. They're the ones that are building real, sustainable businesses.
So there you have it. Seven things I've learned building a $100M AI business. I hope you found them helpful. If you're a founder who is building an AI company, I'd love to hear from you. You can find me on Twitter at @sahinboydas.
Frequently Asked Questions
How were these items selected?
Each item on this list comes from direct experience, either from building my own companies or from patterns I've observed across the 200+ startups I've invested in. I prioritize practical, actionable items over theoretical concepts.
Can I implement all of these at once?
I'd strongly recommend against it. Pick the 2-3 items that resonate most with your current situation and focus there. Trying to do everything simultaneously is a recipe for doing nothing well.
Which item on this list has the highest impact?
It depends on your stage and context, but in my experience, the items near the top of the list tend to have the broadest applicability. That said, sometimes the less obvious items create the biggest breakthroughs for specific situations.
Are these recommendations still relevant in 2026?
Absolutely. While specific tools and tactics change, the underlying principles remain consistent. I update my thinking regularly based on what I'm seeing in the market and across my portfolio companies.