Or, you can take a risk-informed approach, and understand what risks are prevalent (e.g., the risk of a bad vendor) and put the appropriate checks in place to mitigate that risk. "Learning" doesn't always mean taking the highest risk option and just rolling the dice.

Oh I totally agree, but that is a form of learning.

If you don't know what you don't know, you must find out.

If you write a spec you've got to have some process to verify your stuff meets that spec. Otherwise you just wrote a fucking dream journal.

Indeed, and one way to verify you meet the spec is to test it, which they did and found it to be deficient. Having done so, they decided to improve their process. This is the definition of learning from your mistakes

Sadly, or interestingly, that was not an engineering lesson but a human one - don't trust the supplier.

Framed this way, I'm not surprised younger Elon's company missed it.

This is an really optimistic outlook. One way to test the rocket is also to see if it fails when humans are aboard. But it may not be the best way to balance risk and what you learn.

It would have been much more economical to test a coupon of the material upon receipt, like what is considered standard practice throughout aerospace companies. Or, like you said, you can blow up a rocket and launch pad instead. Same result, different risk profiles.

I don't think anyone would argue it would have been better had they known better and done things right the first.

The question is how you transition from the state of not knowing to knowing.

If you have poor processes and a lack of knoledge, how do you get better?

In this specific instance, the root cause analysis and remediation are vastly more complicated that presented in this thread. It is not like SpaceX wasnt doing testing on incoming materials at all or ignorant of the concept.

You’re right. Like most failures of this type, it’s rarely simple and these forums are super conducive to long-form discussion. They did checks, but they were inadequate.

Regarding knowing if you have a poor process or not, it depends on the uniqueness of your problem. For proteins that are relatively common, like material checks, you can shorten your learning process by looking at other organizations that have been through it for decades. For more exotic non-standard problems, you might have to learn the hard way.

I think the distinction I'm making is that the "form" of learning you take should be proportional to the risk and that all forms are not equal in value.