I’ve been programming for a long time, watched this presentation several times, done a bunch of other research, and still don’t know if I understand what this presentation is about. I fear that I’ve tried to apply these simple-vs-complex principles and only made my code harder to understand. My understanding now is that complexity for every application has to live somewhere, that all the simple problems are already solved in some library (or should be), and that customers invariably request solutions to problems that require complexity by joining simple systems.
> still don’t know if I understand what this presentation is about
1. The simplicity of a system or product is not the same as the ease with which it is built.
2. Most developers, most of the time, default to optimizing for ease when building a product even when it conflicts with simplicity
3. Simplicity is a good proxy for reliability, maintainability, and modifiability, so if you value those a lot then you should seek simplicity over programmer convenience (in the cases where they are at odds).
If you agree with her hypothesis, what it's basically saying is that a clean design tends to feel like much more work early on. And she goes on to suggest that early on, it's best to focus on ease, and extract a simpler design later, when you have a clearer grasp of the problem domain.
Personally, if I disagree, it's because I think her axes are wrong. It's not functionality vs. time, it's cumulative effort vs. functionality. Where that distinction matters is that her graph subtly implies that you'll keep working on the software at a more-or-less steady pace, indefinitely. This suggests that there will always be a point where it's time to stop and work out a simple design. If it's effort vs. functionality, on the other hand, that leaves open the possibility that the project will be abandoned or put into maintenance mode long before you hit that design payoff threshold.
(This would also imply that, as the maintainer of a programming language ecosystem and a database product that are meant to be used over and over again, Rich Hickey is looking at a different cost/benefit equation from those of us who are working on a bunch of smaller, limited-domain tools. My own hand-coded data structures are nowhere near as thoroughly engineered as Clojure's collections API, nor should they be.)
> I fear that I’ve tried to apply these simple-vs-complex principles and only made my code harder to understand. My understanding now is that complexity for every application has to live somewhere, that all the simple problems are already solved in some library (or should be), and that customers invariably request solutions to problems that require complexity by joining simple systems.
Simplicity exists at every level in your program. It is in every choice that you make. Here's a quick example (in rust):
fn f(i) -> i32 { i } // function
let f = |i| -> i32 { i }; // closure
The closure is more complex than the function because it adds in the concept of environmental capture, even though it doesn't take advantage of it.
This isn't to say you should never pick the more complex option - sometimes there is a real benefit. But it should never be your default.
You are correct in your assessment that customers typically request solutions to complex problems. This is called "inherent complexity" - the world is a complex place and we need to find a way to live in it.
The ideal, however, is to avoid adding even more complexity - incidental complexity - on top of what is truly necessary to solve the problem.
I think, the shift in programmer's perspective on where complexity should live is very much related to the idea of "the two styles in mathematics" described in this essay on the way Grothendieck preferred to deal with complexity in his work: http://www.landsburg.com/grothendieck/mclarty1.pdf.
