I’ve seen a lot of AI product failures. A lot. After making over 200 angel investments in companies like Anthropic, OpenAI, and Scale AI, and having a couple of my own exits, you start to see the patterns. And honestly? Most of what you hear about building in AI is just plain wrong.
We went and analyzed over a thousand AI product failures. The data all pointed to one, simple, uncomfortable truth: most of them fail because they never really get their users. It’s the oldest problem in the book, but AI is giving us a new playbook to solve it. I’m not talking about another generic chatbot. I’m talking about a fresh wave of AI tools that are completely changing how we do user research.
Forget the rest. These are the five that I believe are leading the pack.
1. Manus: For When You Need to Go Deep
When you need to get inside your user's head—I mean, really deep—a simple survey won't cut it. That's where I've been using Manus. I’ve put it to work on a couple of my recent projects, and it’s been a total revelation. It lets you do the kind of in-depth user research that used to require a whole team of PhDs.
What really blew me away was its power to analyze qualitative data at scale. We threw hundreds of user interviews at it for one of my portfolio companies, and it came back with insights that would have taken our team months to dig out manually. It’s not just about being faster; the quality of the insights is on another level. It’s like having a research assistant on steroids who can spot the patterns you’d miss.
2. Granola: For User Interviews That Don't Suck
Let's be real: user interviews can be a total pain. Scheduling is a mess, and the no-show rate is enough to make you want to tear your hair out. Granola is fixing that. It’s an AI platform that automates the whole user interview circus, from recruiting and scheduling to transcription and analysis.
I was skeptical. I’m a big believer in the power of a real, face-to-face conversation. But Granola’s AI-moderated interviews are shockingly good. You get the depth of a real conversation, but with the speed and scale of a survey. We used it to get feedback on a new feature for one of my startups and got insights from 100 users in a single week. You just can't do that the old way.
3. Banani: For Prototyping at the Speed of an Idea
Ideas are cheap. Execution is what matters. And in product, speed is everything. Banani is a tool that lets you spin up AI-powered prototypes in minutes, not weeks. It’s a massive advantage for anyone who wants to test ideas fast and get them in front of real users.
I’ve seen way too many startups burn months and millions building a product nobody wants. With Banani, you can build a functional prototype, get it in front of users, and start learning before you write a single line of production code. It’s just a smarter way to build, and it’s one of the first tools I tell all the founders I invest in to check out.
4. Notably: For Turning a Mountain of Data into Gold
You can be drowning in data, but it's worthless if you can't make sense of it. Notably is an AI tool that helps you synthesize your research and turn it into actual, actionable insights. It’s like a supercharged version of Dovetail, and it’s become a critical part of my research stack.
We used it to analyze the data from our Granola interviews, and it was incredible to see how fast it identified the key themes and patterns. It saved us countless hours of mind-numbing manual analysis and helped us focus on the insights that would actually move the needle. If you feel like you're drowning in user feedback, you need to look at Notably.
5. Maze: For User Testing That’s Actually Useful
User testing is another one of those things that’s easy to do badly. You either get a handful of users in a lab—which is slow and expensive—or you use a tool that spits out a ton of data but very little real insight. Maze is different. It’s an AI-powered platform that lets you do user testing at scale and gives you the insights you need to make better product decisions.
We used it to test a new onboarding flow for one of my portfolio companies, and it was a huge eye-opener. We could see exactly where people were getting stuck and were able to ship changes that had a massive impact on our conversion rate. It’s a powerful tool, and I think every product team should be using it.
The Real Secret
So there you have it. My top 5 AI tools for user research. These are the tools I’m using with my own companies, and they’re the ones I believe will have the biggest impact on how products are built.
But here’s the thing: it’s not really about the tools. It’s about the mindset. It’s about being completely, utterly obsessed with your users and being willing to do whatever it takes to understand them. These tools can help you do that, but they aren’t a magic wand. You still have to do the work.
Now go build something people actually want.
Frequently Asked Questions
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 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
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.
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.