Two Paths to Mastery | Generated by AI
Both approaches are valid, but they suit different people, goals, and stages of learning. Neither is universally “better”—they represent two ends of a spectrum: intrinsic motivation/enjoyment-driven exploration vs. discipline/grinding/deliberate hard work.
1. Enjoyment-Driven Learning (exemplified by yinwang.org / Wang Yin style)
Wang Yin (王垠) is a prominent Chinese programmer and writer (former Google engineer) who strongly criticizes rote, exam-oriented education (especially the Chinese system). He emphasizes:
- Deep understanding of fundamentals
- Learning through curiosity, beauty, and personal interest
- Thinking independently rather than memorizing or doing endless practice problems
Strengths:
- Sustainable long-term → Less burnout
- Leads to genuine mastery and creativity
- Better retention and ability to apply knowledge in novel ways
- More enjoyable, so you stick with it for decades
Weaknesses:
- Can be inefficient or slow if you only study what feels fun right now
- May struggle in highly competitive, structured environments (admissions, certifications, certain jobs)
- Requires strong self-discipline anyway— “just follow interest” often fails without structure
2. Grinding / Discipline-Driven (the MIT PhD journey style, e.g., from ordinary Chinese high school → top undergrad → MIT PhD)
This represents the classic high-achiever path many successful people (especially in competitive fields like CS, physics, math from Asia) take:
- Long hours of deliberate practice
- High-volume problem solving
- Systematic preparation for exams (Gaokao, GRE, research output, etc.)
- Pushing through when it’s not fun
Examples include many MIT/Stanford/CMU PhDs from non-elite backgrounds who succeeded through extreme work ethic.
Strengths:
- Extremely effective for measurable, competitive goals (admissions, competitions, publications)
- Builds resilience, time management, and raw technical skill
- Deliberate practice (focused, repetitive, with feedback) is proven to be the main driver of expertise (see Anders Ericsson’s research on deliberate practice)
- Opens doors that pure “interest-based” learning often cannot (top programs are hyper-competitive)
Weaknesses:
- High risk of burnout, mental health issues, loss of intrinsic motivation
- Can lead to shallow understanding if it’s pure memorization without reflection
- Not enjoyable → harder to sustain after the external goal (PhD, job) is achieved
My Overall View
- The best path is usually a combination: Use grinding/discipline to build a strong foundation and achieve thresholds (e.g., get into good programs, master core skills), while cultivating genuine interest and enjoyment for long-term growth and creativity.
- Many “enjoyment” advocates like Wang Yin succeeded partly because they had enough talent or early foundation to afford following their curiosity. For most people starting from average backgrounds in competitive systems, some grinding is unavoidable.
- Pure grinding without any developing interest often leads to regret or quitting later.
- Pure enjoyment without discipline rarely reaches elite levels in competitive fields.
Individual differences matter a lot:
- Some people naturally enjoy deep technical topics → they can learn more via the first way.
- Others need external structure and goals to push themselves → grinding works better initially.
In practice, highly successful people (including many MIT PhDs) often combine both: they grind hard on the required material while finding pockets of enjoyment or deeper meaning in parts of it.
What are your own goals (e.g., competitive admissions, self-learning for fun, career in tech/research)? That would help determine which approach (or mix) fits you better.