Technical debt has always been a necessary evil in fast-paced software development—but it doesn’t have to stay unmanaged. As projects scale and evolve, keeping track of messy code, deprecated libraries, and workaround patches becomes complex.
That’s where AI tools step in.
This article walks through:
How machine learning algorithms assist in detecting code smells.
Which AI-powered code review platforms are saving engineering hours.
Examples of how AI is helping to reduce time spent on refactoring and legacy cleanup.
Why proactive debt detection using AI dashboards can give engineering managers a clearer roadmap.
🔧 Featured tools: Codiga, DeepCode, Sourcery, and a few more.
AI-powered tools are no longer just add-ons—they’re becoming part of the foundation of sustainable development practices.
👉 Read the complete guide here: AI Tools for Technical Debt Management