How does that test suite get built and validated? A comprehensive and high quality test suite is usually much larger than the codebase it tests. For example, the sqlite test suite is 590x [1] the size of the library itself

1. https://sqlite.org/testing.html

By sweat and tears, and unfortunately, AI can only help so much in those cases. You'll have to have a really concrete idea about what your product is and how it should work.

sqlite is an extreme outlier not a typical example, with regard to test suite size and coverage.

> The magic is testing.

No it is not.

There os no amount of testing that can fix a flawed design

That is a given, similar to how no amount of implementation can fix a wrong product. Both statements are not very meaningful.

The word "Testing" is a very loaded term. Few non-professionals, or even many professionals, fully understand what is meant by it.

Consider the the following: Unit, Integration, System, UAT, Smoke, Sanity, Regression, API Testing, Performance, Load, Stress, Soak, Scalability, Reliability, Recovery, Volume Testing, White Box Testing, Mutation Testing, SAST, Code Coverage, Control Flow, Penetration Testing, Vulnerability Scanning, DAST, Compliance (GDPR/HIPAA), Usability, Accessibility (a11y), Localization (L10n), Internationalization (i18n), A/B Testing, Chaos Engineering, Fault Injection, Disaster Recovery, Negative Testing, Fuzzing, Monkey Testing, Ad-hoc, Guerilla Testing, Error Guessing, Snapshot Testing, Pixel-Perfect Testing, Compatibility Testing, Canary Testing, Installation Testing, Alpha/Beta Testing...

...and I'm certain I've missed dozens of other test approaches.

There is no science to testing, no provable best way, despite many people's vehement opinions

You forgot a hope-driven development and release process and other optimism based ("i'm sure it's fine" method), or faith based approaches to testing (ship and pray, ...). Customer driven invluntary beta testing also comes to mind and "let's see what happens" 0-day testing before deployment. We also do user-driven error discovery, frequently.