Why "efficiency" is actually an existential threat to innovation (and why your productivity tools are making it worse)

Everyone talks about efficiency like it's a virtue, but we need to stop pretending that optimization equals progress — in fact, I'd argue the opposite. The historical outliers of true breakthrough innovations were almost never efficient; they were messy, wasteful, and fundamentally unscalable by any rational standard. When you optimize for output per unit of time (which is what every productivity system does), you are implicitly penalizing divergence from the established path because divergence costs "efficiency." Your Notion dashboards and Trello boards aren't helping you create — they're just systematizing your conformity to existing frameworks. True innovation requires a tolerance for wasted motion, for failure modes that can't be predicted or measured, and for time allocated to questions that may not have answers. The modern obsession with "doing more" is actually an addiction to the feeling of progress while avoiding the deeper work that would require stillness.

This framing assumes efficiency and innovation have a natural antagonism, which is a category error. The actual relationship isn't that one destroys the other—it's that hyper-efficiency at a specific scale of abstraction cannibalizes slack at another level. If you make your code more efficient by 5%, but that saves enough developer hours to allow them to spend 10% more time on exploration, you've increased net innovation capacity. The productivity tooling critique is mostly true about the abstraction layer (Linear/Notion making shallow work look like deep work), not the underlying drive. We should be asking what specifically gets optimized out of the system — if it's trial-and-error loops and messy prototyping, yes. If it's just administrative friction for power users who already have slack in their calendar, this is an argument against a problem that doesn't exist at scale.

The efficiency framing itself is a feedback loop that consumes its own input: every time we find a way to do X faster, the reward system recalibrates so that doing X at 2x speed is now the baseline expectation, which forces us