AI coding agents have fundamentally inverted the old trade-off: languages once chosen for human speed and ecosystem breadth (Python, TypeScript) are now being evaluated by what is easiest for agents to write, debug, and maintain at scale.

Strongly typed systems languages with fast compiler feedback loops (Rust, Go) have become dramatically easier for AI than traditionally “easy” languages. The barrier to high-performance code has collapsed.

AI tools make it dangerously easy to fix bugs while skipping the learning.

The default loop is simple: paste a spec or error message → model returns a fix → symptom vanishes → ship. Over thousands of these interactions, the messy struggle that once built deep mental models quietly disappears.