bts

Here's an explanation of Quadratic Funding from their website[1], which I guess they now refer to as "Plural Funding":

  Plural Funding (also known as Quadratic Funding or QF) is a more democratic and scalable form of matching funding for public goods, i.e. any projects valuable to large groups of people and accessible to the general public.
  
  “Matching funding” is a model of funding public goods where a fund from governments or philanthropic institutions matches individual contributions to a project. Plural Funding optimizes matching funds by prioritizing projects based on the number of people who contributed. This way, funds meant to benefit the public go towards projects that really benefit a broad public, instead of things that only have a few wealthy backers. In Plural Funding, [total funding] for a proposal is [the square root of each contribution to it → summed up, then squared.] Plural Funding strongly encourages people to make contributions, no matter how small, and ensures a democratic allocation of funds meant to benefit the public.

If you read a bit more about them, I think you will be surprised to see the breadth of what these abstractions can be used for. To start, they've been used to build a new compositional foundation for game theory[1], and they can be used to model gradient-based learning in machine learning[2].

As for their simpler applications as getters and setters, they are programmable in the sense that you can think of lens/prism types as interfaces that can be implemented arbitrarily. So you can create your own lenses and combine them like legos to construct new, "bigger" getters and setters from the smaller components.

This StackOverflow post[1] is a good starting point for understanding comonads. It points out that they can be used to model cellular automata (like Conway's Game of Life), sequences, streams, etc.