For a decade (2014-2024), I was a Ruby-only developer. I worked across the Ruby ecosystem—from Rails development to Ruby’s core tooling like IRB, RDoc, and the debug gem. But while I moved around the stack, I stayed within Ruby’s boundaries. Ruby wasn’t just my primary language; it was essentially my only language.
That changed in 2025.
This year, I’ve contributed to Sorbet (C++), worked on RBS’s parser (C), and am now diving into ZJIT (Rust). A combination of factors enabled this shift—something I’d always dreamed of but was terrified to attempt. But AI coding tools like Cursor and Claude Code—both encouraged at Shopify—have been absolutely career-changing.
The Perfect Storm of Opportunity
Before diving into the AI aspect, I need to acknowledge two crucial factors that made this transition possible:
First, our Ruby DX team’s roadmap shifted to require Sorbet’s support for RBS, which meant I now had to work on projects written in C++ and C—system programming languages that require understanding concepts I’d never encountered in Ruby.
Second, Shopify’s Ruby and Rails Infrastructure team is packed with experts who genuinely love sharing their knowledge. Alexander Momchilov, Alexandre Terrasa, Max Bernstein, and many others have been incredibly generous with their time. Those pairing/tutoring sessions gave me the C/C++/JIT fundamentals I needed to even attempt this work.
But here’s the thing: great mentors and project opportunities to learn new languages have always existed. What’s different now is how AI has fundamentally changed the learning curve.
The Complexity of System Programming Projects
Let me use ZJIT, a new just-in-time (JIT) Ruby compiler, as an example (to learn more about it, check out this RailsAtScale post by Max). This project perfectly illustrates the challenge: it requires both deep conceptual understanding (how JITs and GC work) AND language/tool-specific expertise (Rust idioms, C programming conventions, Ruby’s build system). Working on ZJIT means constantly juggling:
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