The Drift Principle: why systems get worse even when they're "working"
I keep noticing a pattern across social platforms, news cycles, UX design, and now AI assistants. At some point the system starts doing exactly what it was built to do, but the experience gets worse. The Drift Principle is my attempt to describe that moment:
When a system optimizes faster than it can preserve context, fidelity to reality starts to slip.
Examples are everywhere. Social feeds tighten around whatever drives engagement, and the range of content shrinks until everything feels like a remix of itself. Customer support flows become friendlier but less helpful because the metric rewards tone over resolution. Helpful AI assistants become smoother and more cautious while quietly dropping specificity. Even individual users fall into it, once you learn what works, your online behavior slowly converges toward the safest version of yourself.
Nothing catastrophic happens. The system still functions. But the texture that made it feel real gradually thins out. You get efficiency without depth, volume without variety. That gap between what the system optimizes for and what humans actually experience is where the drift shows up.
Curious how others here think about this pattern, or whether you’ve seen better language for describing it across domains. If anyone wants the longer version of this pattern across platforms, AI systems, and culture, I tried to map it out here: https://therealitydrift.substack.com/p/the-age-of-drift-why-... One thing I keep returning to is how much of this seems tied to compression outrunning fidelity. Social feeds, news cycles, and even AI assistants optimize faster than context can stabilize, so the experience quality drops even while the metrics look better. I’m genuinely curious how others on HN see it. Especially anyone who’s worked inside systems that had strong early texture and then gradually drifted. The entropic demise. Something must come along that devours or is devoured. That is the natural progression. You have touched upon something no doubt. There is a natural rule that nothing good lasts forever, and it leaves things to those of us who will try to get a good decade in here and there. Appreciate what you have before it’s depleted. You never know who will bankrupt themselves next, or will rise from obscurity to give us just what we want and need, before that too fades to our oblivion. I think you’re describing a deeper pattern that sits underneath the Drift Principle. Systems don’t fall apart all at once; they get smoother, safer, more predictable, and in that process they lose the qualities that made them meaningful. It’s a kind of entropy disguised as progress. What’s striking today is the speed. Cultural systems used to erode over decades, now they can drift noticeably within a single design cycle. Maybe the real risk isn’t that things fade, but that they fade before we can adapt or build anything to replace what was lost. While reading this I kept thinking: this might be why mutation is essential for evolution. That’s a really interesting way to frame it. Drift almost feels like the cultural version of genetic stasis. The system keeps optimizing the current pattern until it can’t adapt anymore. Mutation or some injection of variety becomes the only thing that restores texture. In living systems that happens automatically; in engineered systems it almost never does unless someone deliberately reintroduces friction, novelty, or unused pathways. Your point makes me wonder whether part of the problem is that we’ve built platforms that suppress mutation by default, as everything converges toward the safest, most rewarded output.