Introduction: AI Project helped with College Admissions Most high school applicants today list GitHub on their résumé but very few understand it. Admissions readers have learned to separate surface familiarity from systems-level thinking. Cloning repositories, pushing commits, or contributing to small issues no longer registers as meaningful differentiation. What does  stand out is when a student treats GitHub itself as a dataset, a system, and a decision surface. That’s why

Introduction: AI Product Finder: How Building a Recommendation System helps with College Admissions Product discovery looks simple from the outside. You type what you want, a system suggests options, and you choose. Because of this familiarity, many student-built product recommendation systems feel shallow. They retrieve items, rank them loosely, and stop there. Admissions officers are not impressed by that. What they evaluate instead is whether a student understands why  rec

Is it truly "too early" for sophomores to take AI seriously, or is this belief subtly costing competent students time they can never get back? I observe the same pattern in every admissions cycle. Silicon Valley sophomores excel academically, are interested in technology, and live in an innovative environment. However, many put off doing significant AI work until their junior year because they believe universities won't value their earlier efforts. Students who already have d

What would happen if the busiest summer of your life proved to be a waste of time? Many of San Jose's best students have to deal with this unsettling concept. During their final summer, they pack their schedule with camps and classes, only to arrive at senior year with an application that looks like a haphazard grocery list with lots of ingredients but no meal. The goal for this summer is not to achieve "more," but to make everything make sense. Admissions officers don't want

Introduction: Common AI Project Mistakes In the last post, we talked about how scattered projects can slowly become a real portfolio how choosing a few meaningful builds and reflecting on them can turn effort into something coherent. Once that picture becomes clearer, a new worry often replaces the old ones. “I worry that even if I build an AI project, I might accidentally do it the ‘wrong’ way and ruin my chances without realizing it.” That fear isn’t about laziness or lack

Introduction: Turn AI Projects Into a Portfolio In the last post, we talked about something that often surprises students: AI projects don’t have to feel like school to matter. They can be personal, creative, even fun. But once you’ve built a few projects that way, a new kind of uncertainty usually appears. “I’ve built a few AI projects, but I don’t know which ones actually matter or how they become a ‘portfolio’ instead of just random experiments.” This confusion is very nor