I play a lot of Tetris. Cascading four-block shapes that have to be fit “just so” with one of two goals: either maximize your “points” (in which case your strategy is to build up four lines and then complete them by slotting a final piece in) or maximize the number of rows you exhaust (in which case your strategy is to complete a single line as often as possible). As you play either the cascade speeds up or impediments are put in your way to make it hard to complete rows. (FWIW, Tetris appears to be licensed out to a bunch of different entities and so your version may vary). I will play three or four rounds transitioning between “work brain” and “home brain”, a way to “accomplish” something, much the way finishing a cup of coffee and working out in the morning means I have “accomplished” something and/or doing a load of towels means I have “accomplished” something.
The thing is, as you progress in Tetris the speed and/or impediments do increase and so you rarely get nice, neat complete rows out of the gate (towards either goal). There’s always a gap and you can choose to ignore it (build nice, neat rows above it) or engineer towards it (what do I have to eliminate to get that gap addressed). If you are the type of person who likes everything “just so” you may find yourself using that second strategy and occasionally to your detriment: if you employ the “remove all gaps” strategy, you are giving up on “build up solid rows” strategy.
Of course this is like work.
I am a “Technical Program Manager” – but I expect this is observed and encountered by “Product Managers” and “Software Engineers” and pretty much any other role in which you have to coordinate sixteen things in order to deliver A Thing. Out of sixteen things, four will work perfectly well and four will work moderately well and four will be okay-ish and four will be an abject nightmare of permissions, architecture, personalities and/or randomization. (Your proportions may vary, your encounters will not). You can focus on those last four or you can work around them, but you will rarely, if ever, encounter a program or objective that does not hand you gaps through which you must strategize.
It’s frustrating. It’s also a muscle to build, because the nature of the world we live in now is that things are increasingly more intricate even while we strive to have things like AI and ML make things easier; I would posit that the development of AI and ML solutions have not been easy for those who *build* them. As our careers and technology progress, the blocks start falling faster, and the obstacles increase; and hopefully we get more agile and effective in dealing with them, because they continue.
Or we give up and go do a load of towels.
Bobbie Conti 