Ask HN: What is it like being in a CS major program these days?
AI tools and a weak job market are reshaping what it feels like to study computer science today. Students and professors report heavy reliance on large language models for assignments, rising cheating, and falling real understanding, while curricula remain largely focused on traditional theory and “classical” programming. Many argue that core CS fundamentals and math are now more important than ever—both to remain employable alongside AI and to avoid graduating a generation of developers who can’t work without it.
Impact of AI on CS Education
- AI tools (ChatGPT, Claude, Cursor, Gemini, etc.) are widely used by students to complete assignments, labs, reports, and even exams.
- Many feel AI makes coding “too easy,” undermining deep learning; others see it as the best tutor they’ve ever had.
- Professors are divided: some ban AI for core courses, others encourage it in practical/project courses, many allow it but worry about learning loss.
- There’s broad uncertainty about what now counts as a “hard” or “complex” programming assignment, given rapidly improving tools.
Curriculum, Fundamentals, and Pace of Change
- Most programs’ core content (math, theory, data structures, algorithms, architecture, compilers, OS, networking) has changed little; many see this as appropriate and “timeless.”
- Recurrent theme: CS should teach fundamentals, not the framework/language of the month or “prompt engineering.”
- Some programs are adding many ML/AI courses or even stand‑alone AI degrees, but degree-change processes are slow and often lag current capabilities.
- Several posters argue real value comes from “struggling” through building things by hand (e.g., malloc, compilers, filesystems) before leaning on AI.
Student Behavior and Academic Integrity
- Many students heavily rely on AI, leading to homework averages near 100% but falling exam performance and weaker independent coding/writing skills.
- In some places, cheating (including AI‑assisted) on exams is described as “widespread,” with specific phone/LLM workflows.
- Some faculty are tightening assessment: more oral exams, in‑class coding, version‑control history checks, multimodal evaluation, zero‑width “AI canaries” in prompts.
Job Market and Career Anxiety
- Strong sense of doom among students about internships and new‑grad jobs; big‑tech campus recruiting appears reduced in some regions.
- Hedges: some still land roles at large tech firms and finance/quant companies; others see outsourcing and wage pressure, especially outside the US.
- Debate over whether AI will mainly wipe out junior roles or most developer roles altogether; no consensus.
Motivations for Studying CS
- Split between people driven by curiosity/“nerd” interest in computing and those driven primarily by high salary expectations.
- Several argue CS is becoming more like math/physics: best suited to those who genuinely like the subject, not just the pay.