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1:48:29ENHow AI Is Changing Programming: John Krazit and Ron MinskyRon Minsky, John Krazit · Jane StreetJane Street’s AI tooling lead and the Signals and Threads host examine agent infrastructure, security, code review and the changing experience of writing software.
1:36:37ENAaron Bauer on Teaching Software Engineering in the Age of AIRon Minsky, Aaron Bauer · Jane StreetHow learning goals, active practice and editor design shape engineering education when models can generate the code.
1:05:45ENCyrus Omar on Live Programming and a Computational Commons for Humans and AICyrus OmarA demonstration of Hazel shows how immediate feedback, structured collaboration and carefully scoped permissions could support people and AI agents working together.
1:25:00ENEric Mannes on Turning Messy External Data Into Trading ResearchRon, Eric Mannes · Jane StreetFrom commodity futures and an Excel risk system to point-in-time datasets and AI, Eric Mannes explains the domain knowledge behind data engineering at Jane Street.
1:16:29ENGrant Sanderson and Alok Puranik: Positional Encodings Through Group TheoryGrant Sanderson, Alok Puranik · 3Blue1BrownStarting with assumptions about attention, they derive matrix exponentials and connect rotations, decay and Jordan blocks to RoPE and ALiBi.
4:41ENInside Jane Street’s Internship: Projects, Mentorship and LearningCody · Jane StreetInterns and employees describe collaborative interviews, learning finance from the basics, and working on projects used by the firm.
1:34:29ENJacob Baskin on Building Superstore and Scheduling the HiveYaron Minsky, Jacob Baskin · Jane StreetThe Jane Street engineer traces the design choices behind a distributed analytical database and the challenge of allocating a growing research cluster.
1:34:36ENNate Foster: Treating the Network as a ProgramYaron Minsky, Nate Foster · Jane StreetFrom programmable switches to BGP, a programming-languages researcher explains how higher-level policies and formal models can make networks easier to change.
1:48:21ENWill Wilson on Deterministic Simulation and the Hard Problems of Software TestingYaron Minsky, Will Wilson · Jane StreetThe Antithesis co-founder explains how replayable simulations explore complex software, why properties matter and where testing meets its limits.
1:12:58ENChris Lattner on Mojo and the Search for Portable GPU PerformanceYaron Minsky, Chris Lattner · Jane StreetRon Minsky and Chris Lattner discuss the language and compiler design behind Modular’s effort to make accelerator programming both portable and fast.
1:01:23ENWill Crichton on Making Rust More UnderstandableWill Crichton · Brown UniversityOwnership visualizations, interactive trait diagnostics and program slicing illustrate an evidence-based approach to developer tools.
58:47ENDaniel Pontecorvo on Cooling Trading Infrastructure and WorkspacesYaron Minsky, Daniel Pontecorvo · Jane StreetFrom dense GPU racks to movable desks, Jane Street’s physical engineering team designs around heat, power, failure and human comfort.
1:27:41ENRon Minsky on the Saga of Multicore OCaml at Jane StreetRon Minsky · Jane StreetA production migration exposed garbage-collector regressions, led to a new pacing design, and illustrated the difficulty of turning research into reliable infrastructure.
2:53ENJane 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.
59:46ENIn Young Cho on Trading Research and Finding Signal in Financial DataRon Minsky, In Young Cho · Jane StreetIn Young Cho and Ron Minsky discuss the blurred lines between trading, research, and engineering, and why machine learning in markets is difficult.
40:33ENCharlie Marsh on uv: Python Dependency Resolution and PerformanceCharlie Marsh · AstralThe Astral founder explains universal lockfiles, Python packaging constraints, and the data structures and cache design behind uv.
1:06:23ENSylvain Gugger on Accelerating ML Models and Reproducing ResultsRon Minsky, Sylvain Gugger · Jane StreetFrom learning-rate schedules to GPU bottlenecks and noisy market data, Sylvain Gugger explains how he approaches practical machine-learning performance.
53:51ENLiora Friedberg on Solving Puzzles in ProductionYaron Minsky, Liora Friedberg · Jane StreetProduction engineering combines live incident response with software, process improvements and a culture that helps people learn from mistakes. Liora Friedberg and Ron Minsky explore the work at Jane Street.
7:17ENErik and Martin Demaine on the Mathematics of Curved-Crease SculptureErik Demaine, Martin Demaine · MITThe MIT father-and-son collaborators turn paper folding into art and research, embedding puzzles and mathematical fonts in their sculpture Solve Me.
1:03:36ENErin Murphy on Designing Tools for Expert UsersRon Minsky, Erin Murphy · Jane StreetFrom NASA scientists to Jane Street engineers, a UX designer explains how observation, drawing and collaboration reveal what complex tools need to do.
1:02:17ENPeter Bogart-Johnson on Product Management, Poetry and ListeningYaron Minsky, Peter Bogart-Johnson · Jane StreetA poet and program manager explains how to earn a team’s trust, preserve what works and coordinate change without separating engineers from their users.
59:38ENRichard Eisenberg on Dependent Types, OCaml, and AI-Assisted ProgrammingYaron Minsky, Richard Eisenberg · Jane StreetHow type systems can express correctness and performance, and why precise, readable specifications still matter when AI writes code.
37:24ENGrace and Nolen's Software Engineering Mock InterviewGrace, Nolen · Jane StreetA unit-conversion graph illustrates how Jane Street interviewers discuss design, code, errors and communication with a candidate.
5:42ENJane Street’s Trading Interview: What to ExpectMichael, Megan · Jane StreetA trader and a recruiter explain the interview stages, how to approach open-ended questions and what the firm says it looks for.
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