[CSSer]

I've always wondered: Is LLM/GPT already how Google is generating answers to "People also ask" questions or are they using a prior, or unknown, ML approach for this? I ask this because the quality of answers linked to these queries is often so astoundingly awful that I can't believe this is in production.

The question is often very relevant. I'll readily admit that I have a high engagement with that accordion feature, but I can't believe how often I open it to find a disappointing text selection or even page.

And if it is, I wonder where that leaves JSON-LD schema in all of this. Schema is the perfect signal for something like this, but I'm afraid, and I believe I can speak representatively about this from an agency perspective, the trust is kind of broken for that model.

Too many people, myself included, are uneasy about how much information to give to Google since they have an insidious aim to use it to get information to users faster regardless of how much impact it has on a business' ability to remain competitive. Yet, on the other hand, I sympathize with the idea that the more Google reverses course on this and leans into embracing SEO industry-driven control they risk compromising the product. It makes me think that Google has reached a theoretically maximum level of product optimization.

[gardenhedge]

I think Google has built up a knowledge base that they query for those answers. And yes, it's embarrassingly wrong so much of the time