** Separate registration is required for CppCon Academy Classes. **Class Page
In a previous conference talk, I demonstrated building a complete OPRA feed handler without writing a single line of code by hand. Over the two days of this workshop, you’re going to do something even more difficult.
We’re building a matching engine. Not a toy, one that conforms to IEX specifications, with the kind of IPC infrastructure you’d actually deploy: lock-free queues, seqlock arrays, a sequencer pattern. The works. And you won’t write a single line of code yourself.
Every line comes from Claude Code. You prompt, you guide, you review, you course-correct, but your fingers don’t type C++. By the end, you’ll have a working matching engine and a visceral understanding of what AI can and can’t do with a serious C++ project.
We will first cover the foundations: how agentic loops work (condensed review), and why C++ is uniquely challenging for AI assistants. Compilation latency breaks the fast-iteration feedback loop. Header/source splits multiply context requirements. Templates generate error novels. The agent can write code that compiles but has undefined behavior. We’ll develop strategies for each problem, then begin building.
We will build the necessary pieces: lock-free queues, seqlock arrays, order books, matching logic, end-to-end integration. Everyone codes with their own Claude instance. Results will diverge, but that’s also a great opportunity for learning.
You don’t need previous experience with trading infrastructure.
We are choosing this project, because it is not a toy example, yet modern AI techniques are fully capable of building a functioning system that is at least on par with something that a team of junior engineers could build.
The goal is to learn how to use the AI tools, not write production-grade trading software.
By spending two days in an intense lab setting, attendees gain hands-on experience building real C++ software systems using generative artificial intelligence.
