#career

Richard Hamming’s legendary Bell Labs seminar on doing first-class research.

• Why working on important problems, cultivating emotional courage, and communicating clearly define impactful scientific careers.

Yong Zheng-Xin’s candid breakdown of interviewing across industry AI research labs.

• Covers job talk preparation, system design rounds, and choosing research teams.

John Schulman’s personal reflections on problem selection, experimental iteration speed, and developing technical taste in machine learning.

• Highly practical advice on research notebook discipline and avoiding premature optimization.

Michael Nielsen on developing scientific intuition, active note taking, spaced repetition for research mastery, and sustained deep exploration.

Andrej Karpathy’s timeless reflection on navigating graduate school, handling imposter syndrome, running fast experiments, and writing papers.

Max Liani’s meditation on why software craftsmanship, engineering taste, and deep systems understanding matter more than ever in the era of code generators.

Vlad Feinberg’s concrete roadmap for preparing for systems and infrastructure roles at OpenAI, Anthropic, and DeepMind.

• Focuses on CUDA profiling, distributed networking primitives, and hardware failure recovery.