I’ve probably interviewed a thousand people for technical roles in my career. Maybe more. After you’ve seen that many candidates, you start to see patterns. The biggest pattern? Most founders are absolutely terrible at hiring AI talent.
They look at the wrong signals. They ask the wrong questions. They optimize for credentials from big-name companies and universities, and they end up with a team of smart people who can’t ship product. They’re building a fantasy football team, not a real one.
I’ve had two successful exits. RemoteTeam was acquired by Gusto, and MovieLaLa was acquired by Gfycat. I’ve invested in over 200 companies, including some you might have heard of like Anthropic, OpenAI, and Scale AI. I didn’t get here by hiring people with the most impressive resumes. I got here by finding the hidden gems. The people who have a fire in their belly and a deep, intuitive understanding of how to build things people want.
And I do it by asking questions that are designed to cut through the noise. Questions that reveal a person’s true character, their problem-solving ability, and their potential to grow into a leader.
The Resume is a Lie
Let’s get one thing straight: the resume is the least interesting thing about a candidate. It’s a curated, polished, and often exaggerated document that tells you very little about what a person can actually do. I’ve seen candidates from Google and Facebook who were brilliant on paper but couldn’t code their way out of a paper bag. I’ve also hired self-taught engineers from the middle of nowhere who have become some of the most valuable people on my team.
So, what do I look for instead? I look for evidence of passion. I want to see what they build in their spare time. What are their side projects? What does their GitHub profile look like? Are they contributing to open-source projects? Are they writing a blog? Are they active in any online communities? These are the things that tell me who they are and what they care about.
I’m looking for people who are obsessed with building things. The kind of person who will stay up all night to fix a bug because they can’t stand the thought of something being broken. The kind of person who is constantly learning and experimenting with new technologies because they are genuinely curious.
The Three Pillars of an AI Gem
When I’m interviewing a candidate, I’m looking for three things:
Technical Depth: This isn’t about knowing the latest buzzwords or frameworks. It’s about having a deep understanding of the fundamentals. I want to know if they understand how the algorithms work, not just how to call a library. I want to know if they can reason about trade-offs between different approaches. I want to know if they can write clean, efficient, and maintainable code.
Product Sense: This is the ability to see the big picture. Can they understand the business context of what they are building? Can they think from the user’s perspective? Can they make smart decisions about what to build and what not to build? I’m not looking for someone who just wants to be told what to do. I’m looking for a partner who will challenge my assumptions and help me build a better product.
Grit and Curiosity: This is the most important one. I want to know if they are a fighter. Are they going to give up when things get hard? Or are they going to dig in their heels and find a way to win? I also want to know if they are a learner. Are they constantly trying to improve their skills? Are they open to feedback? Are they willing to admit when they don’t know something?
My Go-To Interview Questions
So, how do I test for these things? Here are a few of my favorite questions:
1. “Tell me about a project you started but never finished. Why did you stop?”
This is my all-time favorite question. It tells me so much about a person. It tells me about their ability to self-assess, to prioritize, and to be honest. A great answer is not “I just got busy.” A great answer is a thoughtful story about why the project wasn’t the right thing to work on, or how they hit a roadblock they couldn’t overcome, and what they learned from the experience. I’m looking for someone who is not afraid to fail, and who can learn from their mistakes.
2. “Explain [a complex AI concept] to me like I’m a 10-year-old.”
This is a classic for a reason. It’s a brilliant test of a person’s understanding of a topic. If you can’t explain something simply, you don’t understand it well enough. I’m not looking for a textbook definition. I’m looking for an analogy, a story, or a simple example that demonstrates a deep and intuitive understanding of the concept. This also tests for communication skills, which are critical for anyone who is going to work on a team.
3. “What’s a widely-held belief in the AI community that you think is wrong?”
This question is designed to test for independent thinking. I’m not looking for a contrarian for the sake of being a contrarian. I’m looking for someone who can think for themselves and who is not afraid to challenge the status quo. A great answer is a well-reasoned argument that is backed up by evidence. It shows me that they are paying attention to what is happening in the industry and that they have their own point of view.
4. “Tell me about a time you had to cut corners to meet a deadline. What was the situation, what corners did you cut, and what was the outcome?”
This is a great question to test for pragmatism and judgment. In the real world, you can’t always build things perfectly. Sometimes you have to make trade-offs to get things done. I want to know if they can make smart decisions about when to cut corners and when to hold the line. A great answer is a story about a time they made a tough call, and they can explain the reasoning behind their decision. I’m looking for someone who can be a good steward of the company’s resources.
5. “What are you learning right now?”
This is a simple question, but it’s a powerful one. It tells me if they are a lifelong learner. The field of AI is moving so fast that if you’re not constantly learning, you’re falling behind. I want to know what they are passionate about, what they are curious about, and what they are doing to improve their skills. A great answer is a specific example of something they are learning, and why they are excited about it.
The ‘Sell’ From Day One
Here’s the thing that most founders don’t get. You don’t just “sell” your company. You engineer the exit from day one. And the most important part of that engineering process is hiring the right people.
The people you hire are the ones who are going to build the product, the technology, and the culture that will make your company valuable. They are the ones who are going to be in the trenches with you when things get tough. They are the ones who are going to make the difference between a small exit and a life-changing one.
When I’m interviewing someone, I’m not just thinking about whether they can do the job today. I’m thinking about whether they can grow with the company. I’m thinking about whether they have the potential to be a future leader. I’m thinking about whether they are someone I want to be in business with for the long haul.
Because a great exit is made, not found. It’s a long-term game of strategy and relationships. And it all starts with finding the hidden gems.
So, the next time you’re hiring, I want you to do me a favor. Throw out the resume. Stop asking the same old boring questions. And start looking for the things that really matter. Look for passion, for grit, for curiosity, and for a deep and intuitive understanding of how to build things people want. If you can do that, you’ll be well on your way to building a company that is not only successful, but also built to last.
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.
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.
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.