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