Armin Ronacher on Balancing Speed and Rigor in the AI Coding Era
In a new post, Python and Rust veteran Armin Ronacher explores what he calls "fast and hard code" — the tension between writing software quickly with AI assistance and making sure that code is actually robust and correct. He argues that speed alone, now cheaply available thanks to LLM-based coding tools, isn't the goal; the real skill is combining that velocity with rigorous engineering habits like testing, clear abstractions, and careful review.
Ronacher reflects on how AI tools have shifted the bottleneck in software development away from typing speed and toward judgment: knowing what to build, when to slow down, and how to verify that fast-generated code doesn't quietly introduce bugs or technical debt.
The piece serves as a reminder to developers riding the AI coding wave that discipline hasn't become optional — it's arguably more important now that code can be produced faster than it can be understood.