The Boundary (https://github.com/sasa1977/boundary) thing is interesting. It seems logical to want to put dividing lines within a monolith like this, but I'm super curious as to what problems they faced that spurred them to bring it in in the first place? Like, were internal APIs changing so fast that it kept breaking dependants? Wouldn't/shouldn't test coverage help with that? Or did it have more to do with tooling/DX? (e.g. speeding up compile times or something)
I empathize! These kinds of shifters are SUPER hard to put back together. Quite literally, so many moving parts in such a tight space. If you inadvertently bend the springs or coils too much, you could end up ruining the whole thing.
I had a similar situation happen to on a Shimano Deore shifter, which is even less complex than the SRAM you mention.
For others who have never had this "joy", it looks like there's at least one video at least partially showing what the OP had to go through: https://www.youtube.com/watch?v=nrfKQfXJgd0 Jump to ~2:00 to get a sense of how finicky this stuff is.
For those intrigued by Systems Thinking but want to explore it in context of startups (or business in general), consider reading Scaling Lean by Ash Maurya [1]. The whole Customer Factory [2] is based on a causal loop diagram of McClure's Pirate Metrics (AARRR); Ash also incorporates a lot of Theory of Constraints into the book. Highly recommended.
Systems Thinking was also part of Intel's culture under Andrew Grove (at least at the leadership level, from what I can tell). You can see evidence of that in his super-acclaimed book, High Output Management [3], especially the first couple of chapters (though he doesn't refer to it directly). Rich Jolly, another executive @ Intel, actually has a PhD in Systems Science and also wrote a book, Systems Thinking for Business [4], although it's definitely a bit more advanced and more theoretical than the others listed here.
And, I whole-heartedly agree - Meadows' book is simply an AMAZING treatise of Systems Thinking. It's a great place to start regardless of your background (the beauty of ST is that it is applicable to a broad range of fields and disciplines).
As an aside, does anyone know of any good/free/open source tools for drawing causal loop diagrams, or better yet, running simulations?
