Ruby's JIT compiler, specifically ZJIT, enhances performance by compiling frequently used methods into native code while retaining their bytecode for safety and de-optimization. The article explains the mechanics of how Ruby executes JIT-compiled code, the criteria for compilation, and the reasons for falling back to the interpreter when assumptions are violated. Additionally, it addresses common questions regarding JIT functionality and performance implications.

Building a coding agent in Ruby is straightforward, requiring only a few lines of code and minimal boilerplate compared to other languages like Go. By utilizing the RubyLLM gem and implementing three essential tools—reading files, listing files, and editing files—developers can create a functional AI chat agent that can assist in coding tasks. The author successfully demonstrates this by developing an agent capable of coding a simple game in Ruby.

AI coding tools are revolutionizing the way developers transition between programming languages, enabling them to contribute to projects in languages like C++ and Rust without extensive prior knowledge. By acting as a collaborative partner rather than just a code generator, AI helps developers overcome learning barriers and enhances the coding experience, allowing for more productive contributions from the outset. This shift signifies a broader trend towards reduced specialization in programming languages.