A good programming language should have features that make the kind of people who use the phrase “software engineering” shake their heads disapprovingly.

The most powerful programming language is Lisp. If you don't know Lisp (or its variant, Scheme), you don't know what it means for a programming language to be powerful and elegant. Once you learn Lisp, you will understand what is lacking in most other languages.
When you start a Lisp system, it enters a read-eval-print loop. Most other languages have nothing comparable to read, nothing comparable to eval, and nothing comparable to print. What gaping deficiencies!

The connection between the language in which we think/program and the problems and solutions we can imagine is very close. For this reason restricting language features with the intent of eliminating programmer errors is at best dangerous.

If you try to solve a hard problem, the question is not whether you will use a powerful enough language, but whether you will (a) use a powerful language, (b) write a de facto interpreter for one, or (c) yourself become a human compiler for one.

Computer scientists have so far worked on developing powerful programming languages that make it possible to solve the technical problems of computation. Little effort has gone toward devising the languages of interaction.

But, of course, the point of a programming language is that you don't just read it; you write it, too. You make it do things for you. And this, I think, is where Ruby shines (...)

"The "space" of all possible programs is so huge that no one can have a sense of what is possible. Each higher-level language is naturally suited for exploring certain regions of "program space"; thus the programmer, by using that language, is channeled into those areas of program space. He is not forced by the language into writing programs of any particular type, but the language makes it easy for him to do certain kinds of things. Proximity to a concept, and a gentle shove, are often all that is needed for a major discovery-and that is the reason for the drive towards languages of ever higher levels."

The clarity of programming languages have several advantages over traditional languages. For example, programs in such languages are considerably shorter than the equivalent programs in imperative languages. They also encourage clear programming styles.

People are inventing new programming language all the time but I think that's not the big problem is actually writing programs. I think the big technical problem in building system is what I call "the connecting things together problem". It's a version nightmare problem. It's given things in different languages and actually connecting them together.

For twenty years programming languages have been steadily progressing toward their present condition of obesity; as a result, the study and invention of programming languages has lost much of its excitement. Instead, it is now the province of those who prefer to work with thick compendia of details rather than wrestle with new ideas. Discussions about programming languages often resemble medieval debates about the number of angels that can dance on the head of a pin instead of exciting contests between fundamentally differing concepts. Many creative computer scientists have retreated from inventing languages to inventing tools for describing them. Unfortunately, they have been largely content to apply their elegant new tools to studying the warts and moles of existing languages.

A programming language is for thinking of programs, not for expressing programs you've already thought of.

If language A has an operator for removing spaces from strings and language B doesn’t, that probably doesn’t make A more powerful, because you can probably write a subroutine to do it in B. But if A supports, say, recursion, and B doesn’t, that’s not likely to be something you can fix by writing library functions.

To me, programs are black boxes. You send a message in and you get a message out. I don't care if it's written in Scala or Haskell or Erlang or Python or Ruby. I care about this relationship between inputs and outputs.

When you see a problem or an opportunity, I want you to shift your thinking from “We need a solution for that” to “We need a system for that.” A solution is a onetime fix that requires you to keep reinventing the wheel and puts you in a reactionary place. A system is an ongoing activity that becomes duplicatable.