Learning to program in a given language requires a non-trivial amount of time. This seems to be agreed upon as a good use of LessWrongers' time.
Each language may be more useful than others for particular purposes. However, like e.g. the choice of donation to a particular charity, we shouldn't expect the trade-offs of focusing on one versus another not to exist.
Suppose I know nothing about programming... And I want to make a choice about what language to pick up beyond merely what sounds cool at the time. In short I would want to spend my five minutes on the problem before jumping to a solution.
As an example of the dilemma, if I spend my time learning Scheme or Lisp, I will gain a particular kind of skill. It won't be a very directly marketable one, but it could (in theory) make me a better programmer. "Code as lists" is a powerful perspective -- and Eric S. Raymond recommends learning Lisp for this reason.
Forth (or any similar concatenative language) presents a different yet similarly powerful perspective, one which encourages extreme factorization and use of small well-considered definitions of words for frequently reused concepts.
Python encourages object oriented thinking and explicit declaration. Ruby is object oriented and complexity-hiding to the point of being almost magical.
C teaches functions and varying abstraction levels. Javascript is more about the high level abstractions.
If a newbie programmer focuses on any of these they will come out of it a different kind of programmer. If a competent programmer avoids one of these things they will avoid different kinds of costs as well as different kinds of benefits.
Is it better to focus on one path, avoiding contamination from others?
Is it better to explore several simultaneously, to make sure you don't miss the best parts?
Which one results in converting time to dollars the most quickly?
Which one most reliably converts you to a higher value programmer over a longer period of time?
What other caveats are there?
Learning ideas has better ROI than learning tools. It's easy to pick up tools as needed for work, but recognizing ideas/patterns is both a more transportable kind of knowledge and harder to acquire. Also key ideas behind computation do not have a "half-life," whereas tool/tradeschool type knowledge does.
Exactly, it's all about the concepts underlying the tool and recognizing situations when a certain tool has a better ROI than some other one at solving a problem at hand.
But, sometimes it can be hard to make a fair judgement on whether you really know something or just think that you know. So, it might definitely be useful to know a few other techniques/tools of doing the same thing in order to foolproof yourself.