When was that? In 2008, the candidates who were good at leet code kind of questions were generally unusually smart and skilled: nobody at the time was grinding these problems to prepare, so people who could offhandedly solve them without any special preparation were extraordinary. Now, 10-15 years later, everyone is grinding Leetcode, and as a result, being good at it is not indicative of all that much. When a measure becomes the goal, it often ceases to become a good measure.

I interviewed in 2007-2009 and there was a lot of preparation as well. It wasn't as widespread as later, but anyone that did 'programming contest' style problems had a huge advantage at interviews.

I had something like an 80% offer rate because of this. Ironically I didn't actually get a Google offer though (not sure why, I did solve the problems).

Nobody was literally solving them offhand in the sense that they had no background in algorithmic problem solving. Those who didn't explicitly "prepare" were the people who liked competition programming and solving these problems for fun in their spare time. Though I'd agree those candidates were probably better quality on average than those who just grind problems solely for the interview

1. What types of questions did they ask instead?

2. Did you get an offer? Did you accept?

Yes. These days onsites have at least three categories of interviews: leetcode style, system design and behavioral. For L5 level (senior) and above, the latter two tend to weigh more heavily.

It's also more common now to have two coding sessions, and even two system design ones, under the rationalization that it reduces interviewer bias.

Google explicitly links to leetcode/hackerrank/etc as suggestions for practice resources in their pre-interview email, implying that practicing artificial DS&A quizzes is now table stakes.

I would be curious as to whether these changes have been data driven, or whether the bar is being increased purely out of necessity to weed out candidates more strictly.

I certainly have seen my share of candidates that do fine in leetcode sessions but then go on to fail in the other sessions for various reasons that allegedly correlate to work performance.