One of my favorite software solutions that I came up with was “human learning” powered. A few years ago I was working as the engineering manager at a small company. I had 8 other people who I was in charge of and we had moved to a new office in the middle of this. Our team took up two rooms in the office and I had to figure out who would be sitting where. I had some preconceived notions of who would be productive together, who would annoy each other, etc., but there were enough possible combinations to make this a large enough search space.
So I wrote a very simple python script that would randomly generate layouts of who would sit in each room and next to whom. Every time it gave me a result I scanned it for conditions that would make it not work and add a rule to skip such configurations. After about six such edits I got a layout I thought was acceptable. The team as far as I know was happy and nobody questioned it for the entire time we were there. This saved me time because I didn’t have to pre-program all the conditions, only add ones I had already seen not work. Saved both CPU and brain cycles, so to speak.
So I wrote a very simple python script that would randomly generate layouts of who would sit in each room and next to whom. Every time it gave me a result I scanned it for conditions that would make it not work and add a rule to skip such configurations. After about six such edits I got a layout I thought was acceptable. The team as far as I know was happy and nobody questioned it for the entire time we were there. This saved me time because I didn’t have to pre-program all the conditions, only add ones I had already seen not work. Saved both CPU and brain cycles, so to speak.