To learn anything, first unlearn school
- Source
- x.com
- Author
- Zara Zhang
- Date
Context
A project can give an adult learner a reason to return to difficult material. Zara Zhang describes becoming more technically literate by building products with AI coding tools and then asking AI to explain the codebase structure, the technologies used and what each file did, after earlier introductory computer science lectures had failed to hold Zhang's interest.
The proposed learning sequence starts with a concrete goal, then works backward to the knowledge it requires. AI serves as an on-demand explainer inside that process. Zhang's account supports a way to organize self-directed learning around motivation; the comparison with formal coursework reflects personal experience, not a measured study.
- The school mindset survives school by decades. Her friend, years out of the classroom, still bought grammar books and vocabulary lists because learning had to be 'systematic' — and the label 'bad at languages' was really a verdict on the method.
- Motivation is the binding constraint for adult learners, not aptitude. School supplies external accountability (exams, attendance) and a defined goal; adults have neither, so anything boring gets dropped. Only a problem you actually want solved sustains the effort.
- Her concrete AI move: ship the product first, then have the model walk you through the codebase structure, name the languages and technologies, explain what each file does, and add detailed comments everywhere. The explanation lands because it is attached to your thing.
“Do first, learn later.”
“You don’t get good and then produce output. You produce output and then get good.”
“After a few projects, I’d learned more about coding than a year of college CS lectures.”
“It’s a 24/7 world-class tutor that answers any question, as long as you know what to ask.”
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