[nostrademons]

Yeah, I went through the learn-every-programming-language-possible stage in late college and the couple years afterwards. I eventually decided that no language is going to boost your effectiveness as much as knowing your problem domain very, very thoroughly. There's a lot of depth in specialized algorithms that isn't visible to someone in college or a web shop, yet many of the most lucrative startups come from specialized algorithmic knowledge.

[strlen]

In violent agreement with you. Specialized knowledge is how you make your way out of the enterprise/web ghetto and onto much more fascinating problems, including in the greater enterprise/web industry: you can think of most of what Amazon does as enterprise software, yet they've used e.g., distributed systems expertise to their advantage; where most saw "class ShoppingCart extends StatefulSessionBean" (and a big fat check for WebLogic and Coherence) they saw http://www.allthingsdistributed.com/2007/10/amazons_dynamo.h...

However, I remember a comment you've posted once on this site (don't have the URL) saying there are no shortcuts to being a programmer: i.e., you should learn several programming languages and you should be a competent algorist. Some languages also force you to think differently about algorithm design (e.g., purely functional data structures), which is always a good thing.

[nostrademons]

Another interesting thing: virtually all the really high-level programmers I know have either a PL or OS background. Jeff Dean worked on Cecil. Urs Hoezle worked on Self. Lars Bak worked on Beta, Self, and HotSpot. Peter Norvig worked on Lisp. Many of the other senior guys at Google - the ones who actually understand how all the search engine works, that people go to when there's a tough problem - worked on languages like Dylan, Python, and HotSpot.

Most of them aren't working on languages now, but there's this blip in the past of a surprisingly large number of them. I wonder if it's causation or correlation.