The problem with analogy-based programming is the lack of determinacy. There are no guarantees when it comes to abstract, knowledge-based inference. And so many concepts in modern programming would have to be abandoned to make this shift. Unit tests, for instance, would lost value dramatically.
In the end, an analogy-based approach seems inevitable though, especially once natural language-based inexact. grow popular. Everyday speech is littered with ambiguities, and programming "languages" need to handle these. They can't throw compilation errors upon each inexact command.
With any improvement in programming language technology, we narrow the disparity between human and computer representations of logic. In it's simplest form, this is the premise of language designers.
The biggest difficulty with current languages is their reliance on absolute determinacy. Programmers must express in exact form what computations ought be performs, and the languages possesses no intelligence in themselves. I think this needs to change. Inference should have applications outside type declaration, and the vast knowledge base that is the Internet should be taken into account.
At this point, there are two promising pursuits that I've seen. First is Wolfram Language, which you've all heard of. The other is Escher, which enables "programming in analogies". It's on early stages right now, but I'd encourage you to check it out at https://github.com/gocircuit/escher.
This a surprisingly promising list of ideas, especially for an incubator to suggest. Things like internet infrastructure, ideally, are in the non-profit sector. And though YC does fund non-profits, I can't imagine they'd be happy with a swarm of unprofitable applicants coming in next round.
In the end, an analogy-based approach seems inevitable though, especially once natural language-based inexact. grow popular. Everyday speech is littered with ambiguities, and programming "languages" need to handle these. They can't throw compilation errors upon each inexact command.