I like figuring out where things break and why. That curiosity is what got me into product, and it's what I spend most of my time on, whether that's at Lenovo, leading SohAI, or running point on the basketball court.
I'm a Computer Science student at Elmhurst University, currently spending my summer as a Product Management intern on Lenovo's OEM Portfolio team in Research Triangle Park. I'm also the founder of SohAI, a small AI automation business that earns $1k monthly that I started last fall while in school, and I play point guard for Elmhurst's NCAA Division III basketball team.
I have a knack for pattern recognition, noticing edge cases, and finding pain points and that's what led me to start SohAI. It's also the same instinct I bring into product work. I'm drawn to roles where I can combine that curiosity and data, and build something that moves the needle. I find that to be deeply satisfying.
My family is from Cameroon, and growing up my first language was French, with Spanish as my third. I was lucky enough to travel widely growing up, visiting countries on every continent but Asia. My favorite trip outside of visiting family in Cameroon was Patagonia. There's something about being that far from everything that puts life in perspective.
Travelling and experiencing other cultures has shown me the value of diversity and different perspectives. I've learned that the only reason I am where I am is chance, and that there are plenty of people who are just as special as I am, just without the opportunity. That drives me each day to create change and to help afford others with opportunities similar to the ones I've had. Often we judge others on decisions, but we don't always know the choices they faced. Walking through life with that lens lets me appreciate others for who they are, what they bring to the table, and the potential within them.
Outside of school, work, and basketball, I'm usually reading, journaling, or adventuring.
Patagonia, with my mother
Like I said, I've always had a knack for noticing edge cases. Where a process breaks down, where a pain point shows up, where something that looks fine on paper doesn't actually work for the person using it.
Customers don't care how advanced your technology is. They care whether it solves their problem.
Building SohAI taught me that lesson over and over. I learned it the hard way when presenting to prospective dental clients. I had built an AI receptionist and chatbot for after-hours customers, and when I walked into their office I found myself selling them on the conversational ability of the receptionist, how fast it was, how cheap it was to operate. What I learned was that they could not care less about any of that. They did not understand much of it, and honestly it did not matter. What mattered was the why. Why should we hire this product to do a job for us?
So in my next meeting, I came back explaining how not using my product was costing them and I had charts to show it. For a quick breakdown, the average dental office is open anywhere between 35-45 hours a week and closed for around 120-150hrs a week. So, during those hours, say they have four customers calling each week looking to book or with emergencies, that turns into 16 a month, which turns into 192 customers a year you’re missing by not using my services.
The best products are not the most complicated ones. They are the ones that consistently get the job done. People hire Netflix, wine, firepits, so they can have a relaxing night with friends. People hire a tool so a task gets off their plate. As long as the job gets done, reliably and consistently, that is what people pay for.
A lot of this also comes from basketball. As a point guard, I am the one running the offense, reading the floor, and making sure everyone around me is in a position to succeed. I have always been someone people depend on to get things done under pressure, and I genuinely like that responsibility. I see pressure as a privilege. That translates directly into product, where so much of the job is about understanding people, aligning everyone around a goal, and making good calls with ambiguous information.
I came into my Lenovo internship thinking PM was mostly roadmaps and features. I am learning it is really about understanding people, the jobs they are trying to get done, and making thoughtful tradeoffs so the right thing gets done.
I am currently working in Product Management at Lenovo, getting a firsthand look at how products move from an idea to a customer's hands.
One of the things I have enjoyed most is seeing how many different teams and perspectives are involved in building a successful product. Customer needs, engineering constraints, manufacturing requirements, sustainability goals, and business objectives all have to be considered at the same time, and every decision comes with tradeoffs.
Coming into this role, I thought product management was mostly about features and roadmaps. What I have learned is that great products come from understanding people, understanding the jobs people hire products to do, aligning teams, and making thoughtful decisions.
SohAI started with a simple question. How can small businesses use AI to save time and grow without needing a technical background?
Before building anything, I spent weeks talking to business owners across different industries. Through more than 20 customer discovery interviews, I learned something that changed how I think about products. Customers do not care how advanced your technology is. They care whether it solves a problem they actually have.
Those conversations helped me find a much stronger opportunity in real estate than healthcare, so I pivoted the business before investing significant development time. Within 30 days of launching, SohAI reached $1,000 in monthly recurring revenue.
Today, I have built automated content marketing systems, AI receptionist workflows, lead qualification systems, and business automation tools using Claude, OpenAI, n8n, Bland AI, and Twilio. A real estate client directly attributed five home sales to the work I have done for her.
At Move For Hunger, I worked on using data to help the organization better understand and engage its donors.
One project started with a simple hypothesis. Personalized thank you letters could improve donor retention. Using Python to analyze more than 2,000 donor records, I helped test the idea through a pilot program and found an 18% improvement in retention.
I also worked with over 5,000 donor records to find patterns among high value supporters. Using clustering techniques, I helped uncover more than 100 high potential donor prospects and improved targeting accuracy by 25%.
What I enjoyed most was seeing how data could tell a story. Numbers by themselves are not meaningful. The real value comes from turning data into decisions that help people get better outcomes.
Started with a question about late-game basketball decisions. After analyzing more than 3,000 possessions and running over 10,000 Monte Carlo simulations, I found evidence that teams could improve win probability by 8 to 10% in specific late-game situations. This research earned me a $20,000 scholarship. The biggest takeaway was not the result itself, it was learning how data can challenge assumptions that feel obvious on the surface.
Built a predictive model with 33 features that hit about 72% accuracy. The more interesting finding was that betting markets were far more efficient than I expected, which made a real edge hard to find even with a solid model. That pushed me to rethink the product entirely, away from predictions and toward helping people understand probability, decision making, and risk.
Books that have shaped how I think about products, people, and the world.
Always happy to talk product, AI, basketball, or anything in between. Feel free to reach out.