While it's true this is mostly justification for further investigation, correctly categorizing 12/12 people into 2 categories actually has a p-val of .000244141 = (1/(2^12)), which would easily allow you to reject the null hypothesis of random categorization. The stronger the effect, the fewer samples you need.

We consider n=12 generally underpowered only because many real-world effects are way weaker than the ability this woman demonstrated.

What makes this result meaningless? The probability of her guessing all 12 correctly at random is: 0.0002 (i.e., approximately 0.5^12). So, it is far more statistically significant than many published results.

The minimal sample size depends on the effect you try to measure. Big effects can be validated with smaller sample size.

How is it simultaneously meaningless and also a justification for further study?

Meaningless to draw large scale conclusions on. It's a "This is something we should look more closely at" not a "Send this person around the country STAT"