Benchmarking Coding Agents on New vs Legacy Codebases — Denys Linkov, Wisedocs

Refactoring a legacy AI pipeline from multiple repositories into a single monorepo significantly enhances shipping velocity and developer engagement. At Wisedocs, this six-month initiative addressed critical issues, including slow performance and unmaintainable code, ultimately enabling the team to support larger files and accelerate feature delivery. While modern AI coding tools drastically reduce the time required for such refactors, they demand rigorous human oversight to prevent errors and ensure alignment with technical specifications. Balancing technical debt requires a strategic approach, weighing the immediate business value of new features against the long-term costs of complexity. As AI agents continue to evolve, the ability to execute large-scale refactors will become increasingly efficient, provided teams maintain clear mental models and robust verification frameworks to manage the inherent risks of autonomous code generation.