I wrote this piece to explore how tech debt accumulates and why it often undermines scaling efforts if left unresolved.

Two points stood out during my analysis: first, that debt isn’t inherently bad—it’s a trade-off that enables speed, but compounding interest appears when teams skip foundational fixes. Second, systemic failures emerge when architectural shortcuts stack, making later feature work exponentially harder.

In practice, addressing debt early often means pausing new development to refactor core data models, testing harnesses, or CI/CD pipelines.

For those here who’ve scaled fast-growing systems, how do you balance debt repayment against product velocity?