Vol. 169 高考只是个开始，Don’t Waste Your Life

Summary

This 枫言枫语 episode by Justin Yan and 自立 uses gaokao volunteer filling as a starting point for discussing College Major Choice, city and school context, university life, and AI-era learning. The hosts explicitly avoid giving tactical admissions advice, because their own 2006 and 2008 gaokao experience is outdated; instead, they frame the next four years as a period for using information, peers, projects, internships, school resources, and AI tools to discover a sustainable direction. The episode adds College Career Preparation, University Opportunity Density, Learning How To Learn, and AI As Tutor while reinforcing Graduation Anxiety, Internship As Career Exploration, AI Programming Engine Shift, AI Engineering Thinking, and Human Judgment Under AI.

Key Claims

• Old gaokao tactics are not a reliable guide for current students because admissions rules, information access, and volunteer-filling mechanisms have changed since the hosts took the exam.
• College Major Choice is important but not a one-shot life sentence; changing major, moving from engineering to design, or redirecting career focus is possible, but it costs extra effort.
• The episode warns against blindly chasing hot AI majors: students enter with today’s demand signal but graduate into a market that may have shifted or become oversupplied.
• University Opportunity Density matters because cities, companies, labs, campus recruiting, hackathons, student competitions, and peer groups lower the cost of getting real practice.
• AI-era school resources matter more when high-quality APIs, GPU access, devices, and labs are too expensive for many students to buy personally.
• College Career Preparation should be goal-dependent: GPA matters for graduate school or baoyan, while projects, internships, portfolios, and interview readiness matter more for employment.
• Preparing only for baoyan or civil-service exams can leave students exposed if they later need to enter the job market without internships, projects, or interview practice.
• Learning How To Learn, communication, expression, curiosity, and self-directed practice are treated as durable skills that matter with or without AI.
• AI As Tutor can help students bridge explanation gaps, explore unfamiliar majors, and prototype ideas, but it works best when the student supplies context, hypotheses, and judgment.
• As of the hosts’ cited June 3, 2026 time point, they do not claim programming is either safely future-proof or already obsolete; they argue that programming remains valuable for people who enjoy building things and want to understand what AI-generated systems are doing.
• The episode pushes back on using exceptional geniuses as ordinary templates; unusual Yao-class or physics-to-AI stories can inspire, but should not become generic major-selection advice.
• The “Don’t Waste Your Life” frame is not anti-practical idealism: the hosts acknowledge family responsibility and income needs while still urging students to seek work they can sustain.

Key Quotes

“高考只是个开始” — the episode’s frame for treating gaokao as the start of a four-year decision period rather than the end of choice.

“Life is short, so don’t waste it” — the Steve Jobs idea Justin uses to connect major choice, responsibility, and long-term interest.

“不要用天才特例做普通人模板” — the source’s warning against copying exceptional cases as general advice.

Connections

• 枫言枫语, Justin Yan, and 自立 — show and host context.
• College Major Choice — central decision frame around major, school, information, family, and AI uncertainty.
• College Career Preparation — GPA, internship, project, portfolio, and hiring-logic tradeoffs during the undergraduate years.
• University Opportunity Density — city, school, lab, competition, peer, and culture layer behind opportunity access.
• Learning How To Learn and AI As Tutor — AI-era learning posture that requires using AI actively without outsourcing understanding.
• Graduation Anxiety and Internship As Career Exploration — existing career-entry pressure extended backward into the gaokao and early-college period.
• AI Programming Engine Shift, AI Engineering Thinking, and Human Judgment Under AI — programming and AI-use boundary: AI lowers barriers but does not remove judgment, maintenance, or responsibility.

Contradictions

• No direct contradiction with existing wiki content. The source extends the earlier AI-coding synthesis by applying the same verification and human-judgment boundary to students choosing majors and learning under AI uncertainty.