I once burned out building an AI product. I’m talking 100-hour weeks, sleeping under my desk, the whole nine yards. We had a team of brilliant engineers, the latest models, and a beautiful UI. We launched, and… crickets. Nobody cared. The product was a technical marvel that solved a problem nobody had. That failure taught me a lesson that no amount of success ever could: building great AI isn't about the tech. It's about the people.
For years, I approached AI roadmaps the way most of Silicon Valley does. We’d start with the technology. “What can we build with this new model from OpenAI?” or “How can we use diffusion models to disrupt X industry?” We were so obsessed with the “how” that we forgot to ask “why.” We were a hammer looking for a nail, and we ended up building a lot of things that nobody wanted to pay for.
My turning point came during a late-night conversation with a mentor. I was complaining about my latest failure, and he just listened patiently. Then he drew a simple 2x2 chart on a napkin. It was so simple, so obvious, that I almost dismissed it. But it stuck with me. That one chart completely changed how I think about building AI products.
The Chart That Changed Everything
The chart my mentor drew was a simple 2x2 matrix. On the x-axis, he wrote “Technology Novelty,” and on the y-axis, he wrote “User Value.” It looked something like this:
| Low Technology Novelty | High Technology Novelty | |
|---|---|---|
| High User Value | The Low-Hanging Fruit | The Holy Grail |
| Low User Value | The Obvious Dud | The Trap |
This simple chart provides a powerful framework for thinking about AI roadmaps. Let’s break it down.
The Trap: High Tech Novelty, Low User Value
This is where my failed product lived. It’s the siren song of the engineer-led startup. We get so excited about the latest and greatest technology that we build something just because we can. We create a solution and then go looking for a problem. These products often get a lot of buzz in the tech press, but they rarely find a sustainable business model. It’s a trap that I’ve seen countless startups fall into, including my own.
The Obvious Dud: Low Tech Novelty, Low User Value
This quadrant is pretty self-explanatory. These are the uninspired, me-too products that nobody wants. They don’t push the boundaries of technology, and they don’t solve a real problem for users. Thankfully, most teams are smart enough to avoid this quadrant.
The Low-Hanging Fruit: Low Tech Novelty, High User Value
This is where the magic happens. These are the products that solve a real, painful problem for users with existing, proven technology. It’s not as sexy as building with the latest and greatest AI, but it’s a lot more likely to be successful. My first company, RemoteTeam, was a perfect example of this. We used simple automation and integrations to solve the headache of managing remote teams. It wasn’t the most technically challenging product, but it solved a real problem for a lot of people. That’s why it was acquired by Gusto.
The Holy Grail: High Tech Novelty, High User Value
This is the ultimate goal. These are the products that change the world. They combine cutting-edge technology with a deep understanding of user needs to create something truly new and valuable. Think about what OpenAI did with ChatGPT or what Scale AI is doing with data labeling. These companies didn't just build cool tech; they found a way to apply that tech to a massive, unsolved problem. This is the quadrant we should all be striving for, but it’s also the hardest to reach. It requires a level of technical expertise and user empathy that is incredibly rare.
Putting the Framework into Practice
So how do you use this framework to build a better AI roadmap? It starts with a shift in mindset. Instead of starting with the technology, start with the user. Obsess over their problems, their workflows, and their pain points. Once you have a deep understanding of the problem, then you can start thinking about the technology.
Here are a few practical tips:
- Talk to your users. A lot. I can’t stress this enough. Get out of the building and have real conversations with the people you’re trying to help. Ask them about their problems, their frustrations, and their goals. The more you understand your users, the better you’ll be at identifying high-value problems to solve.
- Start with the low-hanging fruit. Don’t try to build the Holy Grail on day one. Start by solving a real problem with existing technology. This will help you build momentum, generate revenue, and learn more about your users. Once you have a solid foundation, then you can start to explore more innovative solutions.
- Build a balanced roadmap. A good AI roadmap should have a mix of projects from different quadrants. You should have some low-hanging fruit to drive short-term results, and you should have some moonshots that have the potential to be transformative. The key is to have a clear understanding of the trade-offs and to make conscious decisions about where you’re investing your time and resources.
A Real-World Example
At MovieLaLa, my second company, we used this framework to build a product that was eventually acquired by Gfycat. We started with a simple problem: it was hard to find out where to watch a movie online. We could have tried to build a sophisticated recommendation engine using the latest machine learning algorithms. But instead, we started with a simple, low-tech solution. We built a search engine that aggregated data from all the different streaming services. It wasn’t the sexiest product, but it solved a real problem for a lot of people.
Once we had a user base, we started to add more advanced features. We built a recommendation engine that was based on user ratings and viewing history. We used natural language processing to analyze reviews and help people discover new movies. We slowly moved from the “Low-Hanging Fruit” quadrant to the “Holy Grail” quadrant. But we did it in a deliberate, user-centric way. We didn’t just build cool tech for the sake of it. We built it because it solved a real problem for our users.
It’s Not About the Tech
Building a successful AI product is not about the tech. It’s about the people. It’s about understanding their problems and finding a way to solve them. The technology is just a tool. It’s a means to an end, not the end itself. So the next time you’re building an AI roadmap, I challenge you to start with the user. Start with their problems. And use the simple 2x2 chart to guide your decisions. It might just save you from burning out and building a product that nobody wants.
The Investor's Perspective: How I Use This Chart
As an angel investor, I see hundreds of pitches a year. And you'd be surprised how many of them fall into the "Trap" quadrant. They come in with a brilliant team of PhDs, a novel new algorithm, and a deck full of technical jargon. But when I ask them who their customer is and what problem they're solving, they get a blank look on their faces. They're so in love with their technology that they've forgotten about the business fundamentals.
I've invested in over 200 companies, including some of the biggest names in AI like Anthropic, OpenAI, Scale AI, and Hugging Face. And I can tell you that the successful ones all have one thing in common: they started with a deep understanding of a real-world problem. They didn't start with the tech; they started with the customer.
When a founder pitches me, I'm not just looking for a cool idea. I'm looking for a founder who is obsessed with solving a problem for a specific set of users. I want to see that they've spent countless hours talking to their customers, that they understand their pain points better than anyone else, and that they have a clear vision for how to solve that problem. The technology is secondary. It's important, of course, but it's not the most important thing.
I've seen founders with mediocre tech but a deep understanding of their users build massive businesses. And I've seen founders with brilliant tech but no understanding of their users fail spectacularly. The 2x2 chart is a simple but powerful tool for cutting through the hype and focusing on what really matters: creating value for users.
Beyond the Chart: A Culture of User-Centricity
This framework is a great starting point, but it's not a silver bullet. You can't just look at a chart and know what to build. You need to build a culture of user-centricity in your organization. This means that everyone, from the CEO to the intern, should be obsessed with understanding and solving user problems.
Here are a few ways to build a user-centric culture:
- Make user research a team sport. Don't just leave it to the product managers and designers. Get your engineers, your marketers, and your sales team involved in user research. The more people who have direct contact with users, the better.
- Celebrate user love. When a user sends you a thank-you note or a glowing review, share it with the whole company. This will help everyone feel connected to the people they're building for.
- Tie your metrics to user value. Don't just track vanity metrics like page views and downloads. Track metrics that show you're actually creating value for your users, like engagement, retention, and customer satisfaction.
Building a user-centric culture is not easy. It takes time, effort, and a real commitment from leadership. But it's the only way to build a sustainable business in the age of AI. The companies that win will be the ones that put the user at the center of everything they do.
A Final Thought
That conversation with my mentor was a turning point in my career. It helped me see that I had been so focused on the technology that I had lost sight of what really matters. Building a successful company isn't about having the best tech. It's about solving a real problem for real people. It's about creating value. And that's a lesson that I'll never forget.
So, I’ll say it again. The next time you're building an AI roadmap, I challenge you to start with the user. Start with their problems. And use the simple 2x2 chart to guide your decisions. It might just save you from burning out and building a product that nobody wants. And who knows, it might even help you build the next big thing.
Frequently Asked Questions
How often is this guide updated?
I revisit and update my guides regularly as I learn new things and as the market evolves. The core principles tend to stay stable, but specific tactics and tools get refreshed based on what's working right now.
Who is this guide designed for?
This guide is written for founders and operators who want practical, actionable advice rather than theoretical frameworks. Whether you're just starting out or scaling an existing business, the principles here apply across stages.
How should I work through this guide?
Don't try to absorb everything in one sitting. Read through once to get the big picture, then go back and work through each section as it becomes relevant to your current challenges. Bookmark it and return to it regularly.
What if I disagree with some of the advice?
Good. That means you're thinking critically, which is exactly what a good founder should do. Take what resonates, test it, and discard what doesn't work for your specific situation. No advice is universal.