Lambda: the ultimate polymath

Thinking back over the last couple of years, I’ve had to know quite a bit about a few different topics to be able to write good software. Those topics:

  • Epidemiology
  • Architecture
  • Plant Sciences
  • Histology
  • Education

Not much knowledge in each field, though definitely expert-level knowledge: enough to have conversations as a peer with experts in those fields, to be able to follow the jargon, and to be able to make reasoned assessments of the experts’ suggestions in software designed for use by those experts. And, where I’ve wanted to propose alternate suggestions, enough expert-level knowledge to identify and justify a different design.

Going back over the rest of my career in software:

  • Pensions, investments, and saving
  • Mobile Telecommunications
  • Terry Pratchett’s Discworld
  • Macromolecular crystallography
  • Synchrotron accelerators
  • Home automation
  • Yoga
  • Soda drinks dispensers
  • Banks
  • Quite a bit of physics

In fact I’d estimate that I’ve spent less than 40% of my “professional career” in jobs where knowing software or even computers in general was the whole thing.

Working in software is about understanding a system to the point where you can use a computer to make a meaningful and beneficial contribution to that system. While the systems thinking community have great tools for mapping out the behaviour of systems, they are only really good for making initial models. In order to get good at it, we have to actually understand the system on its own terms, with the same ideas and biases that the people who interact regularly with the system use.

But of course, because we’re hired for our computering skills, we get to experience and work with all of these different systems. It’s perhaps one of the best domains in which to be a polymath. To navigate it effectively, we need to accept that we are not the experts. We’re visitors, who get to explore other people’s worlds.

We should take them up on that offer, though, if we’re going to be effective. If we maintain the distinction between “technical” and “non-technical” people, or between “engineering” and “the business”, then we deny ourselves the ability to learn about the problem we’re trying to solve, and to make a good solution.

About Graham

I make it faster and easier for you to create high-quality code.
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