Introduction
In a recent freeCodeCamp podcast episode, Quincy Larson sat down with Rachel Fernandez, a computer science student at Stanford University who also holds the distinction of being the youngest instructor on its faculty. Fernandez, who recently co-organized TreeHacks—Stanford's annual hackathon that received 15,000 applications for just 1,000 spots—shared her insights on the evolving landscape of computer science education, the enduring relevance of C++, and practical advice for developers to leverage artificial intelligence without losing core competencies.
Fernandez's journey to Stanford is remarkable. Growing up in Westminster, a small Californian town where 70% of high school students qualified for free lunches, she became the first student from her school to gain admission to Stanford in years. Her story underscores the transformative power of accessible education and mentorship.
The State of Computer Science Education in 2026
Fernandez offered a candid assessment of where CS education stands today. She noted that while institutions have expanded access to coding courses, the curriculum often lags behind industry needs.
Key trends she highlighted include:
- Emphasis on project-based learning – Hackathons like TreeHacks, which challenged participants to build projects over a single weekend for a million-dollar prize pool, are becoming critical for developing problem-solving skills.
- Integration of AI into the curriculum – Many schools now teach machine learning fundamentals, but Fernandez stressed the importance of also teaching when to use AI and when to rely on traditional algorithms.
- Bridging the gap for underrepresented students – Fernandez's own background as a first-generation Stanford student from a low-income community informs her belief that personalized mentorship and early exposure can level the playing field.
Why C++ Remains Essential
As an instructor teaching C++ at Stanford, Fernandez defended the language against those who consider it outdated. She pointed out that C++ provides a foundational understanding of memory management, performance optimization, and system-level programming that high-level languages abstract away.
Her reasoning includes:
- Performance-critical applications – From game engines to financial trading systems, C++ remains the go-to when speed and control matter.
- Foundation for learning other languages – Mastering C++ sharpens a developer's ability to reason about data structures and algorithms, making it easier to pick up languages like Rust or Go.
- Continued industry demand – Despite the rise of Python and JavaScript, C++ is still widely used in robotics, embedded systems, and large-scale infrastructure.
Using AI Without Deskilling Yourself
Fernandez offered practical advice for developers navigating the AI revolution. She warned against over-reliance on code generation tools, which can lead to what she calls "deskilling"—loss of ability to write code from scratch or debug effectively.
Her tips include:
- Use AI as a learning accelerator, not a crutch – Ask tools to explain code or suggest alternatives, rather than generating entire functions automatically.
- Practice deliberate complexity – Regularly challenge yourself to write code without assistance on projects that stretch your skills.
- Understand the underlying logic – Before integrating an AI-generated snippet, take time to trace through its execution and modify it for your specific use case.
For developers seeking structured guidance, Quincy Larson mentioned the freeCodeCamp handbook on AI-Assisted Coding, which outlines methods to maintain and improve coding skills while using AI tools.
Resources for Continued Learning
In addition to the podcast discussion, freeCodeCamp has published several resources that align with the themes Fernandez touched on:
- Automation for Beginners Course – Learn to build a Model Context Protocol server to connect productivity apps and agents.
- Data Quality Handbook – Understand how bad data enters systems and how to implement validation across frontend, backend, database, and business logic layers.
- AI Governance Handbook – Four hands-on Python projects covering model cards, bias detection, audit trails, and human-in-the-loop systems.
Conclusion
Rachel Fernandez's story—from a small-town high school to becoming Stanford's youngest instructor—serves as an inspiration for aspiring developers everywhere. Her perspectives on CS education, the lasting value of C++, and responsible AI use offer actionable insights for anyone looking to grow in the field. As AI continues to reshape the tech landscape, Fernandez's advice to stay grounded in fundamentals while embracing new tools is more relevant than ever.