As much as I love systems, in terms of having a pre-defined set of instructions to carry out, I'm also wary of defaulting too much on them to the point that I become the machine instead of the man operating the machine.
Much of the work of being an operator is optimizing for efficiency and other related metrics like speed, cost, scale etc.
They say faster, cheaper, and better is the trinity that drives progress and competitive advantage in almost any field.
The main premise is of course that you can't optimize all three simultaneously without trade-offs, which I think is where my source of wariness comes from.
In the modern world, optimization is a very gamed metric, in that it often incentivizes superficial improvements or even detrimental shortcuts, as long as the numbers look good.
When numbers are loosely tied to practical reality and there's a veil of sorts between why the system was built and what it does then you have perfect ground for Goodhart's Law to take effect.
The measure becomes the target and loses its value as a measure.
I think this divorce of metrics from meaningful outcomes is why it's not always a bad idea to take modern optimization frameworks with a pinch of salt and also not get too fixated on performance indicators, lest we lose sight of the original purpose and become slaves to our own measurements.
A vivid example of this that I always seem to get reminded of is the rise of clickbait journalism.
Article quality is sacrificed for engagement metrics like "clicks" and "shares," which always down the line brings about a proliferation of misinformation and sensationalism.
Perhaps, this is also one of the unintended consequences of our data-driven culture or rather Silicon Valley's obsession with growth metrics that has proliferated all over the world.
But if the cost really comes with a profound loss of human agency, then we need to ask whether we're still solving human problems or just feeding the machine.
I find myself caught in this tension a lot more lately.
As mentioned above, part of me craves the clarity that systems provide such as the relief of knowing exactly what to do next and the satisfaction of checking boxes and seeing progress bars fill up.
But there's another part that adamantly rebels against this and prefers to color outside the lines, so to speak.
One of the seeds of this concern for me is having a glimpse on how subtle this transformation can be.
You don't wake up one day having become a machine. It happens gradually, one optimized process at a time. First you automate the simple decisions, then the complex ones, until you realize you've outsourced your judgment entirely.
I've watched myself become incredibly efficient at tasks that no longer serve any real purpose, like elaborate performance reviews that I hardly ever read again after writing them.
The irony is that in our quest to become more efficient, we lose the very qualities that made us effective in the first place.
The time spent wandering down interesting rabbit holes gets labeled as "waste", which seems grossly unfair when we've already optimize for productivity but lose serendipity, and I'm not sure that's a fair trade itself.
Maybe this is why I find myself increasingly drawn to deliberately inefficient practices as of late too.
Efficiency is inherently bad.
However, maintaining some inefficient spaces in life could be the only way to preserve whatever makes us human operators as we enter the era of human-shaped machines.
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