Technical debt is reframed as a capacity problem rather than a code quality issue. Drawing on Deloitte's 2026 study, Accenture's 2024 analysis, and CISQ data, it estimates technical debt consumes 21–40% of IT spending and has accumulated to $1.52 trillion in the US alone. For mid-stage SaaS companies, debt manifests as slower onboarding, brittle deploys, and missed roadmap commitments rather than catastrophic outages. Generative AI is identified as both a potential remedy and a new source of debt. Practical tracking approaches are recommended: debt-to-capacity ratio, feature lead-time inflation, and explicit remediation budget allocation (targeting ~15% of IT spend). The core advice is to treat debt as a portfolio decision and prioritize reducing debt in systems that block the highest-value work.
