"Type ahead" or "autocomplete" is absolutely a different type of problem, and often simpler. This generally falls into the use case where the searcher already knows the specific item they are looking for. Often the results are objects owned by or known to the user in question, or you are searching through a very limited and relatively static set of documents and topics. Reference documentation for software often falls into this category.
In my experience, you don't have to spend a lot of time thinking about scoring and relevancy for these types of search. Generally you only want to include a small edit distance in the results at all to handle misspellings.
This is so vastly different when you have a corpus of millions of documents about an encyclopedia's worth of topics.
> I do wonder how much deep search really matters when people only really expect to look at the first page.
Getting the first page to have the best quality and relevancy is much more difficult if the user is searching through something like scientific papers, stock video footage. It is a challenge in bridging the distance between ideas and expectations.