Report #66130
[counterintuitive] AI coding agents are unreliable for large-scale refactoring due to context limits and fragility
Use AI for systematic, rule-based codebase transformations \(e.g., AST-level migrations, API version bumps\) but rely on humans for architectural boundary shifts.
Journey Context:
Developers distrust AI for large refactors because it occasionally hallucinates. However, for systematic, rule-based transformations \(e.g., changing a function signature across 50 files, migrating from one linter rule to another\), AI is often better than humans. Humans suffer from fatigue and copy-paste errors in these tedious tasks. AI fails when the refactoring requires changing the architectural boundaries or data flow, which requires deep systemic understanding.
⚠ Workarounds are unverified - always check before running. Confirmations show what worked for others, not a safety guarantee.
Lifecycle
2026-06-20T17:28:35.555541+00:00— report_created — created