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1:36:37EN
Jane Street· 23. Sept. 2026Aaron Bauer on Teaching Software Engineering in the Age of AIYaron Minsky, Aaron Bauer · Jane StreetHow learning goals, active practice and editor design shape engineering education when models can generate the code.
1:00:15ENJane Street· 17. Dez. 2025Arjun Guha on How Language Models Represent Code and How People Prompt ThemArjun Guha · Northeastern UniversityExperiments with activation steering and student-written prompts reveal how programming models behave—and why evaluating them requires more than a single benchmark score.
2:53ENJane Street· 1. Juli 2025Jane Street Interns on Projects, Mentorship and LearningDylan · Jane StreetFormer interns and staff describe the learning, open-ended projects and relationships that shaped their internship experience.
2:50ENJane Street· 16. Okt. 2024Inside Jane Street’s 2024 Internship ProgramSanemi, Brian, Xavier, Abby, Marcus, In Young Cho · Jane StreetInterns and staff describe an 11-week program built around learning, collaboration and hands-on projects across several disciplines.
4:24ENJane Street· 10. Mai 2023Lars on Trading and Learning at Jane StreetLars · Jane StreetA London trader describes the mix of research, monitoring and coding, and what new hires learn on the job.
3:10ENJane Street· 11. Jan. 2023Sergei on Quantitative Research and Collaboration at Jane StreetSergei · Jane StreetA Jane Street researcher describes long-running quantitative projects, working with traders and developers, and the value of continued learning.
2:13ENJane Street· 8. Nov. 2022Interns Describe Jane Street's 2022 Internship ProgramElla, Sandor Lehoczky · Jane StreetParticipants reflect on learning, project ownership, colleagues, and discovering possible career paths during their internships.
10:32ENJane Street· 17. Juli 2020Real Numbers: Expected Time Between Exams and a Half-Court Shot ChallengeSawyer · Jane StreetSawyer solves an exam-scheduling problem in several ways, then asks how many basketball attempts it takes to make one shot or two in a row.
6:16ENJane Street· 10. Juli 2020Indicator Variables: Marching Bands and SnowboardsSawyer · Jane StreetSawyer uses linearity of expectation to count in-step rows, then poses a six-snowboard challenge.
9:40ENJane Street· 7. Juli 2020Real Numbers: A Marching Band Challenge, Expected Damage, and Bayes’ RuleSawyer · Jane StreetSawyer introduces a marching-band expected-value puzzle and uses linearity and Bayesian updating to solve a monster-attack problem.
10:08ENJane Street· 3. Juli 2020Expected Damage and a Golden-Ratio Window PuzzleSawyer · Jane StreetSawyer introduces expected value with an unknown video-game monster, then uses geometry to solve a painting-through-a-window problem.
7:55ENJane Street· 30. Juni 2020The Art Thief’s Window and a Toy Boat’s Return JourneySawyer · Jane StreetSawyer poses a geometric window puzzle and solves the previous episode’s river-crossing problem in two ways.
5:39ENJane Street· 16. Juni 2020A Snow Cone Geometry Puzzle and a Piggy Bank ProbabilitySawyer · Jane StreetSawyer poses a cone-design challenge and solves a conditional probability problem in two ways.
7:23ENJane Street· 9. Juni 2020Bayes' Theorem and a Driver's Test Probability PuzzleSawyer · Jane StreetSawyer derives Bayes' theorem, poses a question about test-takers who studied, and solves an earlier card-game probability puzzle.
8:03ENJane Street· 6. Juni 2020Real Numbers: A Taxi Challenge and Two Ways to Calculate a Sleep ProbabilitySawyer · Jane StreetSawyer poses a consecutive-taxi puzzle and solves a five-night dog-sitting problem with a probability table and a counting argument.
6:50ENJane Street· 6. Juni 2020The Perils of Dogsitting: A Probability Warm-UpSawyer · Jane StreetSawyer introduces a five-night dogsitting puzzle and reviews independence, overlapping events and complements with coins and dice.
1:10:18ENJane Street· 28. Feb. 2018Shriram Krishnamurthi on Designing Computing Curricula for Real ClassroomsShriram Krishnamurthi · Brown UniversityThe Bootstrap project treats curriculum design as an engineering problem: start with goals and constraints, then support teachers and measure learning.