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At a glance
WHAT IT’S REALLY ABOUT
Why hands-on, foundational learning outlasts fast AI-driven shortcuts today
- Yeh’s “AI by Hand” approach uses drawing and handwriting to demystify AI models and help learners truly internalize concepts rather than just obtain answers.
- He explains that teaching and learning slow (e.g., on a blackboard) enforces human-paced progress, increases attention, and improves focus compared with slide-driven or tool-driven speed.
- He emphasizes “evergreen” foundations—like linear algebra and matrix multiplication—that repeatedly reappear across waves of computing (graphics, big data, ML, AI, quantum), while specific tools trend and fade.
- Using a palace rebuilt on an unburned rock foundation as a metaphor, he argues that strong fundamentals let you rebuild skills whenever technologies change without starting from scratch.
- He critiques the “AI-native” mindset and AI-enabled cheating as symptoms of deeper incentive problems, stressing that hiring and education should prioritize problem-solving, ethics, and teamwork because AI won’t change a person’s character.
IDEAS WORTH REMEMBERING
5 ideas“Having the answer” is not the same as understanding.
Yeh argues that AI can produce outputs instantly, but real learning is demonstrated by internalization and the ability to reconstruct reasoning; ownership grows with the time and effort invested.
Slow, manual work creates a built-in learning speed limit that helps comprehension.
Writing on a blackboard or by hand forces instruction to move at a human pace and makes it easier for students to follow, reducing the cognitive “firehose” effect of rapid slides or instant tooling.
Handwriting supports attention and engagement, not just note-taking.
When students are copying by hand, they’re less likely to multitask on devices; the physical act becomes a focus mechanism and a “human connection” to the material.
Foundations outlast tools; trends come and go.
He highlights matrix multiplication as a recurring pillar across multiple eras (CGI, big data, machine learning, today’s AI, and potentially quantum), while specific tools (e.g., whichever model is popular this month) may quickly fade.
Build a “rock foundation” so you can rebuild skills when technology shifts.
Like a palace reconstructed on a surviving foundation, strong fundamentals let you adapt to new frameworks and model families without repeatedly starting over from scratch.
WORDS WORTH SAVING
5 quotesWhat is the purpose of learning? Having the answer doesn't mean you know it.
— Tom Yeh
One is that I can only go at the humanly possible speed of my writing. I cannot go any faster than I write.
— Tom Yeh
So you see this, a, a trend that every time there's something, that tool keep changing, but it's always something that's core and foundational that doesn't change, it's evergreen.
— Tom Yeh
If you keep focused on the surface features, the tools, then forget about foundation, you just have to keep rebuilding your houses.
— Tom Yeh
AI cannot change people, only you. But you can change AI.
— Tom Yeh
SPEAKERS
Tom Yeh
guestProfessor of computer science at the University of Colorado Boulder and founder of AI by Hand.
High quality AI-generated summary created from speaker-labeled transcript.
