Coding agents shift the calculus on minor code improvements
Developer Simon Willison notes that AI coding agents make tedious multi-file refactors effectively free, raising baseline code quality.
Simon Willison, prominent open-source developer and AI tooling commentator, shared an observation on how coding agents are changing day-to-day development habits. When spotting a small readability improvement that would require updates across 20 or more locations in a codebase, he now delegates it to a coding agent rather than skipping it — because the cost in time and effort is effectively zero.
The remark points to a subtle but meaningful shift in how agentic coding tools affect software quality. Historically, minor improvements — renaming a variable for clarity, standardizing a pattern across files — are often deferred because the effort outweighs the individual payoff. When an AI agent can execute those changes on command, developers are more likely to make them, gradually raising the baseline quality of a codebase through accumulated small fixes. As coding agents become standard tooling, this friction reduction may prove as consequential as the headline-grabbing capability of generating new code from scratch.