Solving Problems & Saving Time through Software and Crushing Entropy
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The source code to your application and/or product is a representation. It is a model of a digital world you are creating. But remember:
All models are wrong, but some are useful—George Box
All models by definition are conceptual. Until the rise of “knowledge work” models referred to something tangible, something physical in the world we could touch. Software is metaphorically compared to construction, but in construction you have physical boards, nails, screws, and steel. When completed, you have a building. Software “knowledge work” is the first time (that I am aware of at least) where we create a conceptual model of a referent we cannot touch. Well, we can, but its electricity, it hurts to touch it.
There used to be a time, long ago, in our galaxy, where source code wasn’t a model. During that historical time your source code was Assembly, an instruction set for the specific hardware chipset your code would run on. You were programming, very specifically, about the electrical binary state of memory addresses. We’ve come a long way and we don’t want to go back.
High level languages are now representational models of a conceptual digital world that doesn’t actually exist. To repeat, all models are wrong. And I don’t just mean bugs here, but truly “what you think is happening, is not what it really happening.” This truth is why the space for instrumentation, observability, and server-less (or just containers) is growing exponentially right now. We are, finally, admitting to ourselves things are complicated and we cannot simply conceptually reason our way through why N% of our distributed systems are always broken:
“We used to have an illusion that we were in control and nothing was broken. But our systems are full of emergent behaviors and are broken all the time.”— Charity Majors
Today, our languages and code is more powerful and expressive than ever before. You need fewer engineers to do more. So if you have two-pizza team (or more) you are probably solving a problem with a very large surface area. We know that the more nodes — humans — we add to a network — team — the more we will be forced to communicate.
The job of technical management is to create a shared understanding in your team of an imperfect representation. (Aside: the job of people management is to keep the humans happy, and working together well. A manager is responsible for both.) There are some additional things that make accomplishing this task tricky:
There are lots of good tools now to understand what your system is actually doing. There are lots of good tools now for understanding what your users are actually doing. But within your team(s) no one person has the big picture. Everyone has a part of the model of how things ought to work. Stitching that together repeatedly, with little margin for error, is very, very hard. There are not very many tools that are specialized for that.