Signals and Threads

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 do the exercise for you. Along the way, they consider the underrated power of a live lecture; why the text editor is still the software engineer's home base; using editor telemetry to find out how AI is actually changing developer workflows; and how Jane Street rebuilt its intern curriculum around testing, design, and code review now that producing the code is the easy part.
You can find the transcript for this episode on our website.
Some links to topics that came up in the discussion:
Foldit and AlphaFold
Carleton College Computer Science
Flipped classroom, active learning, mastery learning, and cognitive load
"The Pen Is Mightier Than the Keyboard" — Mueller & Oppenheimer on handwritten vs. typed notes
Merlin and ocaml-lsp
ecaml — writing Emacs extensions in OCaml
Bonsai — Jane Street's OCaml web UI library
OxCaml
Claude Code output styles — the "learning" mode Aaron describes (note: Anthropic has since moved this to a plugin)
Jane Street's tech internship

"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 negative price and the systems that broke as a result; the years when the commodities desk's risk system was one very large Excel spreadsheet; the hard question of what a company even is; and why better ML models raise the value of careful data engineering.
You can find the transcript for this episode on our website.
Some links to topics that came up in the discussion:
Figgie
Adverse selection
2020 Russia–Saudi Arabia oil price war
Dual-listed company
"LAMBDA: The ultimate Excel worksheet function"
Trino
The Bitter Lesson
Learn more about Jane Street’s internship program.
Apply for Data Engineering roles at Jane Street

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 support wide-ranging analytical queries while transactional writes stream in at the speed of trading systems? And what’s it like when your first design doc leads to an eight-figure hardware purchase? After building Superstore Jacob has since gone back to his roots, thinking about schemes for bidding on compute time as he works to optimize usage of the Hive, Jane Street’s massive compute cluster for research.

You can find the transcript for this episode on our website.

Some links to topics that came up in the discussion:

Mechanism design, second-price auction

MapReduce, BigTable, Google File System

Vertica

Apache Parquet

CockroachDB

Paxos

BitTorrent

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 workloads are reshaping the networking layer; and the success Jane Street has had using an early Internet protocol, BGP, together with a more declarative high-level specification language.

You can find the transcript for this episode on our website.

Some links to topics that came up in the discussion:

P4 (Programming language

Lenses (bidirectional transformation)

OpenFlow

Kleene algebra with tests

NetKAT

End-to-end principle

Border Gateway Protocol

“Stable Internet routing without Global Coordination,” aka the Gao-Rexford conditions

Unison file synchronizer

Barefoot Networks

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” but also property-based testing, fuzzing, chaos testing, type systems, and formal methods. How do you blend these techniques to find the subtle, show-stopper bugs that will otherwise wake you up at 3am? As Will has discovered, making testing less painful is actually a tour of some of computer science’s most vexing and interesting problems.

You can find the transcript for this episode on our website.

Some links to topics that came up in the discussion:

Antithesis, Will’s company

FoundationDB’s deterministic simulation framework

QuickCheck — the original Haskell property-based testing library, by Koen Claessen and John Hughes

Hypothesis — property-based testing for Python, created by David MacIver

QuviQ — John Hughes’ company commercializing QuickCheck, including automotive testing work

Netflix Chaos Monkey

Goodhart’s law — “When a measure becomes a target, it ceases to be a good measure”

CAP theorem — the impossibility result for distributed systems that FoundationDB claims to have in some sense violated.

Paxos — the consensus algorithm FoundationDB reimplemented from scratch

Large cardinals, an area Will studied before abandoning mathematics

Lyapunov exponent — measure of chaotic divergence

Chesterton’s fence

The Story of the Flash Fill Feature in Excel

Building a C compiler with a team of parallel Claudes

Barak Richman, “How Community Institutions Create Economic Advantage: Jewish Diamond Merchants in New York”