Chronology of what was authored in the year 2010
Using the term computationalism from Jaron Lanier's 2010 book fits well enough that it merits elaboration before continuing to the main topic.
Many other companies utilized the same core algorithm and data structure as was likely originally used by Google— not for ranking pages but tracking phrases for purposes of rendering suitable results for search terms.
This algorithm may be found in Chapter 8 of Paul Graham's ANSI Common Lisp book. It's a simple chain of word neighbors with additional meta-data to suit your particular needs. For tracking distance between words found on web pages, the data structure may be used as-is.
Google's search results is a paper tiger; however, the puppeteer has teeth and claws to contend with.
When their day comes— and it will come— it will be from a competitor doing more than just search.
From Coders At Work [Seibel 2009, Apress, New York; pp.321-22]
"...one of the best indicators of success within the company was getting the worst possible score on one of your interviews..." —Peter Norvig
Popular culture speaks of the "100th monkey" effect in various aspects of human society, whereby some idea or ability suddenly becomes inherent in others after a threshold base population has first labored through the learning.
Regardless of whether you believe, whether the origin has been dismissed by its original author as metaphor taken for fact¹ or whether there is merit to the concept at all, the point is that others believe. It's their belief that makes for an interesting exploration here.
Having been in and around a few high-tech startup companies since the 1990's, there tends to be a rush to grow. The magic number seems to target 300+ employees as the ideal size for these young companies. Some are content after a mere hundred, plus a dozen or two. Others continue expanding beyond one thousand, but that could be in part due to the organization taking on a life of its own: internal fiefdoms and such.
With Common Lisp and all of the Lisp family, the killer app is the language itself.
I would emphasize that the killer app for Lisp is simply programming. "Simply" in the sense that you're unencumbered and not fenced in to any particular cliche such as Ruby being stereotyped in its association with Rails.
Ten years earlier when deep into Python, I'd explain that language to others by including the disclaimer that you probably wouldn't want to use it for writing an OS. Writing a near real-time scheduler in it ultimately motivated my return to Lisp.
I offer no such disclaimer when describing Common Lisp to other programmers, executives or founders at start-ups where I've used it.