Software quality is often discussed as if it were mainly an engineering preference: developers want cleaner code, more tests, better architecture and additional time before releasing. From the business side, this may look like a conflict between quality and speed.
In my experience, the real conflict is usually between predictable delivery and accumulated uncertainty.
A poorly structured system may still deliver features quickly for some time. The cost becomes visible later, when engineers cannot confidently explain what a change will affect, integrations start breaking in unexpected places, releases require manual verification, and relatively ordinary product requests turn into investigations.
Good engineering does not remove all these risks, and it certainly does not mean pursuing some abstract perfection. It means keeping the system understandable enough that changes can be made with a known level of risk.
In one SaaS backend, we built more than 600 unit, integration and end-to-end tests around business workflows, APIs, database behaviour and integrations. The coverage figure itself was never the main value. The useful result was that subscriptions, domain rules and external integrations could be changed without rediscovering the entire system every time.
The same applies to explicit API contracts, clear domain boundaries, database constraints, idempotency and observable failure modes. None of them is valuable merely because it represents a recognized engineering practice. They are valuable when they reduce uncertainty around future changes and make delivery more repeatable.
Software quality has an immediate cost, but poor quality keeps charging the business whenever the product needs to evolve. For a product expected to live beyond its next few releases, predictability may be the most practical business value that engineering quality provides.