Technical debt, akin to financial debt, refers to the long-term costs of implementing quick or suboptimal solutions in software development, which can eventually stifle productivity and slow future development. As organizations increasingly rely on AI, continuous delivery, and cloud-native environments, managing technical debt has become crucial, with various forms like code-level, architectural, infrastructure, testing, documentation, generated code, and process debt all contributing to potential inefficiencies. This debt often accumulates unintentionally, driven by pressures to prioritize speed over quality, evolving business requirements, or inconsistent engineering practices, leading to increased security risks and reduced system resilience. Companies are encouraged to prioritize and tackle this debt by integrating it into their workflows, using agile frameworks, and leveraging tools like API gateways to manage and mitigate the complexity, thereby fostering a culture that values long-term quality alongside shipping velocity. By continuously auditing, categorizing, and addressing technical debt as a strategic effort, businesses can transform it from a hindrance into an opportunity for growth and improvement, ultimately enhancing their delivery and resiliency.