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Managing Technical Debt Without Losing Velocity

Shane Barron

Shane Barron

Laravel Developer & AI Integration Specialist

Technical debt is inevitable in any software project. The question is not whether you will have it but how you will manage it. Letting debt accumulate unchecked eventually brings development to a crawl, but addressing all debt immediately prevents shipping features. Balance is key.

Making Debt Visible

You cannot manage what you cannot see. Create a technical debt registry—a backlog of known issues, shortcuts, and areas needing refactoring. Include the impact of each item and rough effort estimates. When stakeholders see the accumulated debt, conversations about allocation become easier.

The Boy Scout Rule

Leave code better than you found it. When working on a feature, take a few extra minutes to clean up surrounding code. Rename a confusing variable. Extract a method. Fix a warning. These micro-improvements compound over time without requiring dedicated refactoring sprints.

The 20% Rule

Many successful teams allocate roughly 20% of their capacity to technical debt and infrastructure improvements. This is not a sprint-by-sprint commitment but a quarterly average. Some sprints might be all features; others might be heavy on debt reduction. The average maintains balance.

Strangler Fig Pattern

For legacy systems, the strangler fig pattern allows gradual replacement. Build new features in a new, cleaner system while the old system continues operating. Over time, traffic shifts to the new system, and the old one can be retired. This avoids big-bang rewrites while steadily reducing debt.

Debt Sprints

Sometimes you need focused effort. A dedicated debt sprint every quarter can address accumulated issues that are too large for incremental improvement. Use these strategically—perhaps before a major new initiative or when velocity has noticeably degraded.

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Shane Barron

Shane Barron

Strategic Technology Architect with 40 years of experience building production systems. Specializing in Laravel, AI integration, and enterprise architecture.

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