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Signals and Threads

Jane Street

Listen in on Jane Street’s Ron Minsky as he has conversations with engineers who are working on everything from clock synchronization to reliable multicast, build systems to reconfigurable hardware. Get a peek at how Jane Street approaches problems, and how those ideas relate to tech more broadly. You can find transcripts along with related links on our website at signalsandthreads.com.

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23 episodes
Avg 1 hr 10 min
English

Episodes 23

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#31
October 16 · 1 hr 48 min
The Changing Craft of Programming with John Crepezzi
John Crepezzi has spent his career building tools for other programmers—at Tumblr, at Square, and then at GitHub, where he worked on the merge queue and the early versions of Codespaces. He came to Jane Street to build a code search engine for OCaml. A week into the job, ChatGPT came out, and he’s been working on AI tooling ever since. In this episode, Ron and John talk about how a three-day prototype grew into a firmwide platform for agentic coding, how AI can break the social contract around c
#30
September 23 · 1 hr 36 min
Learning Goals and the Goals of Learning: Teaching in the Age of AI with Aaron Bauer
Aaron Bauer is a software engineer and one of Jane Street's few developer educators—a role that splits his time between writing code and teaching other people how to write it. Before joining the firm, he taught computer science at Carleton College, including four straight terms online during the pandemic. In this episode, Ron and Aaron discuss what it takes to teach engineering inside a company with its own language, its own version control, and its own editors, and what changes when an LLM can
#29
September 2 · 1 hr 25 min
Wrestling the world into rows with Eric Mannes
"Alternative data" is Wall Street's name for information that comes from non-traditional sources: satellite photos of parking lots, credit card panels, weather forecasts. Eric Mannes has spent over a decade at Jane Street, first as a commodities trader and now helping lead the firm's alternative data team. In this episode, Eric and Ron talk about what it takes to turn messy external data into datasets a trading strategy can rely on. Along the way, they cover the day oil futures settled at a nega
#28
June 24 · 1 hr 34 min
Building a data warehouse from scratch with Jacob Baskin
In university Jacob Baskin studied at the intersection of computer science and economics, thinking about systems that incentivize people to express their true preferences. He put those ideas into practice at Google, where he worked on ad serving, before joining Jane Street’s database infrastructure team. In this episode, Ron and Jacob discuss Superstore, a distributed columnar database now central to Jane Street’s tech stack that Jacob began building practically the day he started. How do you su
#27
June 1 · 1 hr 34 min
The Network as a Program with Nate Foster
Nate Foster is a professor at EPFL in Switzerland in the Networked Systems Abstractions Lab, and a visiting researcher at Jane Street on the Networking team. In this episode, he and Ron consider what happens when you bring a software mindset to network engineering. Can you use programming language theory and formal methods to realize the dream of software-defined networks? Along the way, they discuss how hyperscalers have shaped networking hardware; the return (or not) of multicast; the ways ML
#26
March 17 · 1 hr 48 min
Why Testing is Hard and How to Fix it with Will Wilson
Will Wilson is the founder and CEO of Antithesis, which is trying to change how people test software. The idea is that you run your application inside a special hypervisor environment that intelligently (and deterministically) explores the program’s state space, allowing you to pinpoint and replay the events leading to crashes, bugs, and violations of invariants. In this episode, he and Ron take a broad view of testing, considering not just “the unreasonable effectiveness of example-based tests”
#25
Sep 3, 2025 · 1 hr 12 min
Why ML Needs a New Programming Language with Chris Lattner
Chris Lattner is the creator of LLVM and led the development of the Swift language at Apple. With Mojo, he’s taking another big swing: How do you make the process of getting the full power out of modern GPUs productive and fun? In this episode, Ron and Chris discuss how to design a language that’s easy to use while still providing the level of control required to write state of the art kernels. A key idea is to ask programmers to fully reckon with the details of the hardware, but making that wor
#24
Jul 25, 2025 · 58 min
The Thermodynamics of Trading with Daniel Pontecorvo
Daniel Pontecorvo runs the “physical engineering” team at Jane Street. This group blends architecture, mechanical engineering, electrical engineering, and construction management to build functional physical spaces. In this episode, Ron and Dan go deep on the challenge of heat exchange in a datacenter, especially in the face of increasingly dense power demands—and the analogous problem of keeping traders cool at their desks. Along the way they discuss the way ML is changing the physical constrai
#23
May 28, 2025 · 1 hr 19 min
Building Tools for Traders with Ian Henry
Ian Henry started his career at Warby Parker and Trello, building consumer apps for millions of users. Now he writes high-performance tools for a small set of experts on Jane Street’s options desk. In this episode, Ron and Ian explore what it’s like writing code at a company that has been “on its own parallel universe software adventure for the last twenty years.” Along the way, they go on a tour of Ian’s whimsical and sophisticated side projects—like Bauble, a playground for rendering trippy 3D
#22
Mar 12, 2025 · 59 min
Finding Signal in the Noise with In Young Cho
In Young Cho thought she was going to be a doctor but fell into a trading internship at Jane Street. Now she helps lead the research group’s efforts in machine learning. In this episode, In Young and Ron touch on the porous boundaries between trading, research, and software engineering, which require different sensibilities but are often blended in a single person. They discuss the tension between flexible research tools and robust production systems; the challenges of ML in a low-data, high-noi
#21
Oct 14, 2024 · 1 hr 6 min
The Uncertain Art of Accelerating ML Models with Sylvain Gugger
Sylvain Gugger is a former math teacher who fell into machine learning via a MOOC and became an expert in the low-level performance details of neural networks. He’s now on the ML infrastructure team at Jane Street, where he helps traders speed up their models. In this episode, Sylvain and Ron go deep on learning rate schedules; the subtle performance bugs PyTorch lets you write; how to keep a hungry GPU well-fed; and lots more, including the foremost importance of reproducibility in training run
#20
Oct 7, 2024 · 53 min
Solving Puzzles in Production with Liora Friedberg
Liora Friedberg is a Production Engineer at Jane Street with a background in economics and computer science. In this episode, Liora and Ron discuss how production engineering blends high-stakes puzzle solving with thoughtful software engineering, as the people doing support build tools to make that support less necessary. They also discuss how Jane Street uses both tabletop simulation and hands-on exercises to train Production Engineers; what skills effective Production Engineers have in common;
#19
Jul 12, 2024 · 1 hr 3 min
From the Lab to the Trading Floor with Erin Murphy
Erin Murphy is Jane Street’s first UX designer, and before that, she worked at NASA’s Jet Propulsion Laboratory building user interfaces for space missions. She’s also an illustrator with her own quarterly journal. In this episode, Erin and Ron discuss the challenge of doing user-centered design in an organization where experts are used to building tools for themselves. How do you bring a command-line interface to the web without making it worse for power users? They also discuss how beauty in d
#18
Nov 28, 2023 · 55 min
Performance Engineering on Hard Mode with Andrew Hunter
Andrew Hunter makes code really, really fast. Before joining Jane Street, he worked for seven years at Google on multithreaded architecture, and was a tech lead for tcmalloc, Google’s world-class scalable malloc implementation. In this episode, Andrew and Ron discuss how, paradoxically, it can be easier to optimize systems at hyperscale because of the impact that even miniscule changes can have. Finding performance wins in trading systems—which operate at a smaller scale, but which have bursty,
#17
Aug 15, 2023 · 1 hr 2 min
A Poet's Guide to Product Management with Peter Bogart-Johnson
Peter Bogart-Johnson was one of Jane Street’s first program managers, and helped bring the art of PMing—where that “P” variously stands for “project,” “product,” or some blend of the two—to the company at large. He’s also a poet and the editor of a literary magazine. In this episode, Peter and Ron discuss the challenge of gaining trust as an outsider: how do you teach teams a new way of doing things while preserving what’s already working? The key, Peter says, is you listen; a good PM is an anth
#16
May 18, 2023 · 59 min
The Future of Programming with Richard Eisenberg
Richard Eisenberg is one of the core maintainers of Haskell. He recently joined Jane Street’s Tools and Compilers team, where he hacks on the OCaml compiler. He and Ron discuss the powerful language feature that got him into PL design in the first place—dependent types—and its role in a world where AIs can (somewhat) competently write your code for you. They also discuss the differences between Haskell and OCaml; the perils of trying to make a language that works for everybody; and how best a co
#15
Sep 12, 2022 · 1 hr
Swapping the Engine Out of a Moving Race Car with Ella Ehrlich
Ella Ehrlich has been a developer at Jane Street for close to a decade. During much of that time, she’s worked on Gord, one of Jane Street’s oldest and most critical systems, which is responsible for normalizing and distributing the firm’s trading data. Ella and Ron talk about how to grow and modernize a legacy system without compromising uptime, why game developers are the “musicians of software,” and some of the work Jane Street has done to try to hire a more diverse set of software engineers.
#14
Apr 20, 2022 · 1 hr 12 min
State Machine Replication, and Why You Should Care with Doug Patti
Doug Patti is a developer in Jane Street’s Client-Facing Tech team, where he works on a system called Concord that undergirds Jane Street’s client offerings. In this episode, Doug and Ron discuss how Concord, which has state-machine replication as its core abstraction, helps Jane Street achieve the reliability, scalability, and speed that the client business demands. They’ll also discuss Doug’s involvement in building a successor system called Aria, which is designed to deliver those same benefi
#13
Jan 5, 2022 · 1 hr 22 min
Memory Management with Stephen Dolan
Stephen Dolan works on Jane Street’s Tools and Compilers team where he focuses on the OCaml compiler. In this episode, Stephen and Ron take a trip down memory lane, discussing how to manage computer memory efficiently and safely. They consider trade-offs between reference counting and garbage collection, the surprising gains achieved by prefetching, and how new language features like local allocation and unboxed types could give OCaml users more control over their memory.
#12
Nov 3, 2021 · 1 hr 1 min
What Is an Operating System? with Anil Madhavapeddy
Anil Madhavapeddy is an academic, author, engineer, entrepreneur, and OCaml aficionado. In this episode, Anil and Ron consider the evolving role of operating systems, security on the internet, and the pending arrival (at last!) of OCaml 5.0. They also discuss using Raspberry Pis to fight climate change; the programming inspiration found in British pubs and on Moroccan beaches; and the time Anil went to a party, got drunk, and woke up with a job working on the Mars Polar Lander.

Showing 1–20 of 23 episodes