At the end of this summer, I had a final call with a second-year college student who interned with me. I expected us to review his work. Instead, the conversation became something more personal.
He asked how I knew I was a product person. He asked which internships would help him grow. Then he asked a larger question. If I were his age today, where would I begin?
I have been answering that question for a month, mostly to myself.
He is entering a field where the thing I spent my early career learning to do, turning an idea into working software, now takes a few days. That is not a threat to him. It is a change in what the years at university are for.
AI changes what students can make. It does not remove the need to understand why something matters. That difference will shape how this generation learns, builds, and leads. What follows is what I told him.
Curiosity comes before certainty
I became a product person before I understood the title.
My older brother became an architect. He built buildings. I built computers. Both of us wanted to understand how separate parts could become something useful, and that curiosity followed me into my career. I studied products, industries, customer behavior, and organizations. I learned through good decisions and painful ones. Over time, that experience became judgment.
I told our intern that product thinking does not begin with a job title. It begins with curiosity, and it shows up when someone looks at an ordinary product and starts asking questions. Why was it designed this way? Who does it help? What else could it become? Someone at Apple asked that last question about an object millions of people already had in their ears, and AirPods became a hearing aid.
AI can help answer these questions. Students must first care enough to ask them.
Building is easier, but judgment still takes time
AI has reduced the distance between an idea and a prototype. Students can now create software, explore hardware, and test ideas without waiting for a large team. That access is real, and so is the responsibility that comes with it.
The hardest question is no longer "Can I build this?" The harder questions are "Should I build this?" and "Who will it help?"
AI can offer options. It cannot take responsibility for the outcome.
I felt this while building Revolv the week before he left. Information about one person had become three separate records. One held an email, one held a phone number, one held the meeting history. The tools had built quickly on a weak assumption, and the fundamentals of how data represents a person were what caught it. That is the pattern. AI builds fast on whatever you believed when you asked. A person still has to notice when the belief was wrong.
Students still need to test assumptions, understand people, and decide when a product provides real value. AI coding tools will not tell them when they are spinning. The tools are relentlessly encouraging. Somebody has to be calm enough to disagree.
Paul Graham recently wrote about how universities should prepare founders. He argues that universities should help students become capable builders and encourage independent projects. I agree. Students learn differently when they build something because it interests them. A personal project creates ownership, and it turns failure into information instead of a final grade.
But students should not have to develop alone. They also need experienced people who will listen, question their assumptions, and remain involved after the first project fails.
The right experience changes how someone thinks
My first internship included many hours at a photocopier. I wanted to understand how an organization worked. People gave me documents to copy instead.
That experience shaped how I work with interns today. I want them in real conversations. I want them to see how decisions develop, and to understand how their work reaches customers, colleagues, and the larger organization.
An internship should give someone more than a company name. It should leave that person with stronger questions, better judgment, and more confidence in their ability to contribute.
During our final call, the intern said he had learned how products work. He also said he had gained some understanding of how I think. That was the most meaningful result of the summer for me. My reward was not a completed assignment. It was knowing that his curiosity had expanded.
What I would tell every university student
If I were starting university today, I would focus on four things:
- Learn the fundamentals that help you understand your tools.
- Build projects that interest you, even when they look small.
- Use AI to explore, but keep responsibility for every decision.
- Find people who will support your development beyond one program.
Students do not need to pick one permanent career path immediately. They need room to try, fail, reflect, and try again. They also need relationships with people who understand their progress over time.
Knowledge matters. Experience matters. Context connects them.
The conversation I am bringing to Carnegie Mellon
I leave for Carnegie Mellon University this week as part of my innovation work. I will speak with professors, students, founders, and investors, and I want to understand how each group sees this period.
I also want to explore what becomes possible when different generations build together. Experienced leaders bring knowledge, context, and relationships. Students and recent graduates bring new perspectives, technical fluency, and fewer assumptions about what technology must become. Neither group holds the complete answer. Together they hold most of it.
That belief sits at the center of the Revolv Network. We are building a network where experience can find emerging talent, and emerging talent can find continued support. The goal is not a single introduction or a temporary mentorship. The goal is a relationship that develops through shared work, trust, and understanding.
When our internship ended, I told the student that our conversations did not need to end. He could contact me about a difficult class. He could show me a project. We could discuss his next decision. One day, I hope he provides that same support to someone else. That is how a strong network grows.
The next generation deserves our confidence
I left our final conversation optimistic.
The students and graduates entering technology today have tools my generation could not imagine. They also face important decisions earlier in their lives. They deserve more than warnings about what AI might replace. They deserve our attention, our experience, and our confidence in what they can create.
We should not try to provide every answer. We should help them develop the judgment to find their own.
To professors, students, founders, investors, and experienced operators who share this belief: join the Revolv Network. The next generation is ready to build. We should be ready to build with them.
