Stanford's Youngest Instructor Rachel Fernandez: InfoSec, AI, and the Future of CS Education
In this exclusive Q&A, we dive into the mind of Rachel Fernandez, a computer science student at Stanford who also holds the title of the university's youngest instructor. Rachel shares her journey from a small California town to organizing TreeHacks, Stanford's premier hackathon, and discusses the critical topics of computer science education, the enduring relevance of C++, and how developers can harness AI without losing their edge. She also reveals insights on catching academic dishonesty in coding competitions. This interview is packed with practical advice for aspiring developers and educators alike.
What Is the State of Computer Science Education in 2026?
Rachel explains that CS education has evolved significantly by 2026. While foundational concepts remain—like algorithms, data structures, and systems design—the curriculum now emphasizes applied AI and ethical hacking. Universities are integrating real-world projects earlier, often collaborating with industry. At Stanford, Rachel notes that courses on InfoSec and responsible AI are no longer electives but core requirements. The shift is toward teaching students how to think critically about code rather than just writing it. She observes that the best programs blend theory with hands-on labs, preparing students for a landscape where AI tools are everywhere. Yet, she warns that many institutions still lag, focusing too much on legacy languages or outdated teaching methods. The key, she says, is to equip students with adaptive skills—like reading documentation and debugging with AI assistance—while ensuring they understand the underlying principles.
Why Does C++ Still Matter in a World of Python and AI?
Rachel, who teaches C++ at Stanford, argues that C++ remains indispensable for performance-critical systems. She points out that every major AI framework—TensorFlow, PyTorch—relies on C++ under the hood for speed. Python is great for prototyping, but C++ is what powers production solutions, she explains. In fields like InfoSec, knowledge of memory management and low-level programming is crucial for understanding vulnerabilities. C++ also teaches discipline: manual memory handling forces developers to write efficient code. Rachel suggests that beginners shouldn't shy away from it, even if it's harder. She recommends using C++ for projects where performance matters, like game engines or real-time systems. While AI tools can generate C++ snippets, she warns that without understanding the language, you'll struggle to debug or optimize that code. Her advice: learn C++ to deepen your control over hardware and algorithms.
How Can Developers Use AI Without Losing Their Skills?
Rachel addresses the fear of deskilling head-on. She believes the smartest approach is to treat AI as a co-pilot, not an autopilot. For instance, when using AI for code generation, developers should review and refactor every output. This habit reinforces understanding. She also suggests using AI to explore multiple solutions instead of the first guess. For example, ask an AI tool to generate three different ways to sort data, then compare them. Rachel emphasizes that active learning is key: deliberately turn off AI suggestions when practicing algorithms. At Stanford, she encourages students to first solve problems manually, then use AI for validation. She also recommends explaining code to a peer—or even to the AI—as a way to solidify knowledge. The goal is to avoid becoming a prompt engineer who can't write code from scratch. Instead, become a developer who uses AI as a lever, not a crutch.
What Are the Best Ways to Catch Cheaters in Hackathons?
Rachel, who helped organize TreeHacks, shared some of the techniques used to detect cheating. The first line of defense is automated plagiarism detection tools like MOSS (Measure of Software Similarity). These algorithms analyze code structure, variable names, and even comment patterns. But she notes that sophisticated cheaters try to obfuscate their code—so the next step is manual review by experienced mentors. They look for identical logic in unique edge cases. Another method: interview-based validation. Teams that submit suspicious code are asked to explain their design decisions on the spot. If they can't, it's a red flag. Rachel also uses version control forensics—checking timestamps in commit histories. Cheaters often submit entire codebases in one push, whereas honest teams build incrementally. She advises hackathon organizers to set clear rules upfront and use a combination of automated and human checks. Ultimately, she says, the goal isn't to punish but to preserve the integrity of the learning experience.
What Was the Biggest Challenge Organizing TreeHacks?
TreeHacks attracted 15,000 applicants for just 1,000 spots, making selection a huge challenge. Rachel explains that the team focused on diversity and potential rather than just prior achievements. They looked for applicants who showed curiosity and problem-solving skills in their submission. Another major hurdle was logistics: coordinating a million dollars in prizes, mentors, and sponsors over a single weekend. Rachel says the key was delegation and trust. She also emphasizes the importance of creating a supportive environment—including quiet spaces and mental health resources—when participants are under intense pressure. The most rewarding part, she shares, was seeing teams from non-traditional backgrounds build impressive projects. One team, for example, created an app for translating sign language in real time using only a webcam. For Rachel, TreeHacks proved that hackathons are as much about community as they are about code.
What Advice Would You Give to Students from Underrepresented Communities?
Rachel, who was the first student from her high school to attend Stanford, offers heartfelt advice. First, she says don't let imposter syndrome hold you back. She recalls feeling out of place in advanced coding classes, but she persisted by seeking out mentors—including professors and older students. She also suggests leveraging free resources like freeCodeCamp's curriculum and open-source communities. Another tip: build a portfolio of projects, no matter how small. It's better to have a dozen tiny projects than one unfinished giant. Rachel emphasizes networking intentionally—attend local meetups or virtual hackathons to find allies and collaborators. She also recommends asking questions fearlessly; every expert was once a beginner. Finally, she reminds students that their unique perspective is an asset. Being from a low-income or immigrant background often means having resilience and creativity that others lack. Your story matters, she says. Tech needs diverse voices to build truly inclusive products.