Jane Street builds its trading systems in OCaml, relying on the type system to catch errors at compile time and avoid run-time crashes. They snapshot every successful build to train an in-house AI model, rewarding only code changes that compile and pass tests.

• Jane Street runs its trading systems almost entirely on OCaml, betting on compile-time type checking (e.g., mandatory Option handling) to prevent costly runtime bugs.
• They rejected off-the-shelf tools like Copilot and Claude in favor of an in-house AI model trained on their own workspace snapshots.
• Developer workspaces are snapshotted every 20 seconds, and reinforcement learning rewards only edits that compile and pass tests.
• This snapshot-trained system underpins infrastructure supporting roughly $40 billion in annual trading volume.

Jane Street agreed to spend $6 billion on AI cloud compute from CoreWeave and took a $1 billion equity stake at $109 per share, making it one of CoreWeave’s top five shareholders. The deal secures access to NVIDIA’s next-gen Vera Rubin GPUs and aligns Jane Street’s trading firm with the rapid expansion of specialized AI infrastructure.

• Jane Street is spending $6B on CoreWeave AI compute and taking a $1B equity stake at $109/share, becoming a top-five shareholder—valuing CoreWeave 176% above its IPO price.
• Trading firms are now becoming major direct AI infrastructure players, not just users of it, with Jane Street's $13B net income last year making the spend easily affordable.
• CoreWeave has locked in massive deals beyond this one (Meta $35B, OpenAI $12B, NVIDIA $6.3B), positioning it as a specialized alternative to AWS/Azure for AI workloads.
• Long-term compute commitments this large carry real risk if AI demand slows or cheaper architectures emerge, turning bargains into burdens for both sides.