The case for using AI to write better code more slowly

The dominant mental model for AI-assisted coding is speed: generate multi-hundred-line PRs, merge fast, iterate faster. Vibe coding as a velocity play. Nolan Lawson's post this week pushes back on that - not by rejecting LLMs, but by using them differently. "You can use them just as effectively to write high-quality code slowly." The hook is simple: LLMs are excellent at finding bugs. Anthropic's Mythos research showed agents can surface flaws in a codebase at scale. Lawson extended that insight into a practical PR review workflow - and the results are the opposite of slop.