CircleID

Let me pose what may be a complementary problem. Google certainly is dominant, but I do use other search engines. 
My background goes back to 1970-vintage search engines, which used a very formal, Boolean query language, often with controlled vocabulary. That was certainly not as user-friendly as Google, Jeeves, Yahoo, etc., but it was expert-friendly.
I'm usually extremely fast at finding information with current search engines, but my chief problem is getting too much information.  I miss the ability to run several searches, and then use Boolean logic among the multiple retrieved sets. I miss the ability to specify the context for strings, and to exclude metatags not part of text.
My ideal application could go to several search engines, return sets of hits, and even go and retrieve these sets in the background, so I can do context-based searching.
Perhaps some of this old-time background is helpful in finding information with modern tools. It mystifies me, however, why I can often find answers much faster than many of my colleagues.
A classical rule of expert systems was to use extremely proficient people as domain knowledge models.  We may need more of that when search engines are going to be used by other than casual users. I'm also of the belief that there is a niche for front-ends to the general search engines, for tools that provide more complex searches and analysis than can be done by the engine. Capabilities like this were present in several front-ends to MEDLINE, 20 or 30 years ago.
Now, some of the advanced medical databases are exploring knowledge representations such as semantic networks.  It's probably unreasonable and economic to put these in the basic search engine, due to the skill needed to use them.
To respond to Karl's comment, it may be there, but, with present tools, it may not be possible to find it.  More often, it's my experience that the information is there but hard to find in a mass of irrelevant hits, than that the information isn't there at all.