Study Guide: The Art of Doing Science and Engineering: Learning to Learn

Richard W. Hamming

By Best Books Updated June 30, 2026

This AI-generated study guide is a reading aid. The source-backed recommendation record and evidence for this book live on the book page.

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1. Work on important problems. Hamming's most famous question — "What are the important problems in your field, and why aren't you working on them?" — runs through the book. He argues that talent is widely distributed but courage to attack important problems is rare, and that the gap is what separates great careers from competent ones.

2. Compound interest on effort. Putting in consistent extra hours, reading one more paper a week, returning to a hard problem one more time — these are presented as the actual mechanism of great work. Hamming makes the math explicit: small differences in daily intensity, sustained for decades, produce enormous differences in lifetime output.

3. Style and taste matter as much as technique. Two scientists with the same skills produce radically different work because one has taste for which problems to pick, which approaches to try, and when to publish. Hamming treats taste as cultivable — by studying masters, by self-critique, by reading widely outside one's specialty.

4. The vision: a clear picture of where the field is going. Hamming insists that great work requires a coherent long-term vision of one's field, even if the vision turns out wrong. The vision lets you choose what to work on this week so it compounds into something coherent in a decade.

5. Open the door — be findable. He literally argues for working with your door open: harder in the short run, because of interruptions, but vastly more productive over a career because ideas, collaborators, and opportunities find you. The principle generalizes — visibility and accessibility are career multipliers.

6. Specific techniques across domains. The lectures cover information theory, coding, simulation, learning, AI, and engineering practice. Hamming refuses to separate the methods from the meta-lessons: each technical chapter is also an argument about how to think clearly and choose tools.

7. Communication is a first-class skill. He devotes entire lectures to writing, speaking, and formal presentations, arguing that work that cannot be communicated effectively does not exist socially. The point is not polish for its own sake but the discipline of forcing oneself to be understood.

8. Take responsibility for your career. Hamming's stance is unfashionable and bracing: nobody is going to make your career great except you. Mentors, institutions, and luck help, but the strategic choices — what to work on, who to work with, what to ignore — must be made deliberately and reviewed often.

1. Work on important problems. Hamming's most famous question — "What are the important problems in your field, and why aren't you working on them?" — runs through the book. He argues that talent is widely distributed but courage to attack important problems is rare, and that the gap is what separates great careers from competent ones. 2. Compound interest on effort. Putting in consistent extra hours, reading one more paper a week, returning to a hard problem one more time — these are presented as the actual mechanism of great work. Hamming makes the math explicit: small differences in daily intensity, sustained for decades, produce enormous differences in lifetime output. 3. Style and taste matter as much as technique. Two scientists with the same skills produce radically different work because one has taste for which problems to pick, which approaches to try, and when to publish. Hamming treats taste as cultivable — by studying masters, by self-critique, by reading widely outside one's specialty. 4. The vision: a clear picture of where the field is going. Hamming insists that great work requires a coherent long-term vision of one's field, even if the vision turns out wrong. The vision lets you choose what to work on this week so it compounds into something coherent in a decade. 5. Open the door — be findable. He literally argues for working with your door open: harder in the short run, because of interruptions, but vastly more productive over a career because ideas, collaborators, and opportunities find you. The principle generalizes — visibility and accessibility are career multipliers. 6. Specific techniques across domains. The lectures cover information theory, coding, simulation, learning, AI, and engineering practice. Hamming refuses to separate the methods from the meta-lessons: each technical chapter is also an argument about how to think clearly and choose tools. 7. Communication is a first-class skill. He devotes entire lectures to writing, speaking, and formal presentations, arguing that work that cannot be communicated effectively does not exist socially. The point is not polish for its own sake but the discipline of forcing oneself to be understood. 8. Take responsibility for your career. Hamming's stance is unfashionable and bracing: nobody is going to make your career great except you. Mentors, institutions, and luck help, but the strategic choices — what to work on, who to work with, what to ignore — must be made deliberately and reviewed often.