Technical debt is the accumulated cost of shortcuts, compromises, and deferred work in software development — first articulated by Ward Cunningham in 1992 as a financial metaphor to explain the trade-off between speed and perfect design. It exists in every codebase and isn't inherently bad; prudent, deliberate debt can accelerate time-to-market and validate ideas quickly. The critical challenge is visibility and prioritization — teams that treat technical debt as a managed backlog item rather than hidden friction consistently ship faster and maintain higher quality over time. Understanding the different types of debt (code, design, architecture, test, documentation, infrastructure, security), how to measure it quantitatively, and how to prioritize remediation using frameworks like WSJF or cost of delay modeling is what separates teams that scale from those that collapse under their own complexity.