“Any sufficiently complex computer system is indistinguishable from a biological system.” -Me

So, I like to joke that I find all computer languages equally difficult[1]. The interesting corollary to this is that this also seems to apply to complex systems in general. I approach a complex computer (or other) systems in the same way that I would approach a biological system:

1) Look at the visible behaviour/symptoms/phenotype of the system[2]
2) Assume that there are some number of internal processes in the system, each doing the job they ‘think’ is correct
3) Build a mental model which describes the visible behaviour
4) If debugging a problem, this should greatly narrow down where you investigate

Steps 2) and 3) above are where I think my school training (engineering and science) were the most useful. Our engineering program seemed to focus on the fundamentals and underlying systems, so that one would have a pretty good idea of what individual system components are capable of[3] (and some idea of what the system as a whole is capable of).

The systems I understood most intuitively[4] were chemical systems, probably because my dad and his dad were both chemical engineers. You have a huge number of molecules[5], each doing its own thing, and in aggregate, they exhibit complex behaviour. When you’re dealing with inorganic compounds, you can (most of the time), simulate them in bulk, but when you’re dealing with organic compounds, the complexity explodes and all kinds of strange boundary effects become important.

At this point, you need to switch abstraction levels, also something I remember from engineering, from the micro- level to a level of slightly or substantially more abstraction. At this point, having an intuition about biological systems becomes much more useful.

I’ll use an example to illustrate. At one point, a number of years ago, I and my team were trying to debug why throughput on a system seemed to be capped at a number below the theoretical maximum. Like any flow system, there must be a number of sequential steps that your data or fluid or what have you must flow through. After we built this mental model, it was a matter of looking at readouts and logs to find the graph that had an asymptotic curve showing at which step the system was maxing out. Then we had to fix it, but that’s another story.

[1]This is probably not strictly true. I remember finding Fortran 77 more difficult than usual, and Javascript mind-bendy.

[2]I use ‘behaviour/symptoms/phenotype’, because we might be debugging a problem, or we could just be trying to better understand the system.

[3]This could be why so much of technological advancement is characterized by the advancement in materials. You can only get so far by using a specific set of building blocks. At some point, you need better blocks.

[4]There is a larger article here about how it’s important to follow the things that love the most, whether this is in hobby form or if you’re lucky, work form. You will work harder at doing them better, more importantly, working harder at understanding yourself and removing your mental blocks, which will help you in all the other parts of your life.

[5]Huge.