1.Set Clear Goals: Focus on high-impact areas that will yield the greatest benefit. 2.Automate Testing: Implement unit, integration, and end-to-end tests to safeguard against regressions. 3.Use CI Pipelines: Catch issues early with continuous integration to maintain code quality. 4.Collaborate: Involve QA, product, and design teams to ensure well-rounded improvements. 5.Refactor Incrementally: Make small, focused changes to manage risk and keep morale high. 6.Clean as You Go: Update dependencies, remove deprecated code, and document changes. 7.Stay Lean: Keep the codebase flexible, minimizing future technical debt.

When dealing with technical debt, our focus is on teamwork, learning, and making steady progress. We treat refactoring as a chance to improve, not a burden. Here's how we keep quality high: We start with small wins, fixing critical areas first so it doesn’t feel overwhelming. Testing gives us confidence—automated tests let us catch issues early and build safely. Code reviews let us share insights and keep our standards strong, learning from each other as we go. Instead of seeing technical debt as a setback, we view it as an opportunity to create cleaner, better code together. It’s a step-by-step journey, but each step makes our codebase and our skills stronger.

To manage technical debt while refactoring, start by prioritizing high-impact areas and ensure thorough testing (unit and integration) to validate functionality. Use incremental changes with code reviews to maintain quality and track improvements.

To ensure quality while refactoring, prioritize unit tests, refactor in small, manageable steps, and validate functionality after each change to prevent introducing new issues.

Before you refactor, consider re-imagining. This means harnessing your skills as a software designer rather than reimplementing the existing design. The problem with technical debt is that it exists in software design too, not just in code implementation. These days refactoring is easier than ever, because the language barriers of idiomatic coding have been lifted by large language models which can generate snippets of idiomatic code. While it may be tempting to pick this now low hanging fruit (refactoring, simplified by code generation), the value of refactoring is lower than it once was. Rather than simply refactoring the code base to make coding more "maintainable", make the UI, UX, and end-to-end application performance more graceful.