There's a tweet making the rounds from Nat Eliason that nails something I've been feeling for months: "Nearly every ambitious person I know who has dived into AI is working harder than ever, and longer hours than ever." He adds that he's never worked this hard, or had this much fun.
I get it. I really do. But let's sit with that observation for a moment, because there's something hiding inside it that most people are glossing over.
The intoxication of infinite output
For the first time in most of our careers, our tools can genuinely keep pace with our imagination. That's an extraordinary shift. If you've spent years bottlenecked by implementation (writing boilerplate, configuring pipelines, wrestling with CSS that refuses to centre a div), the sudden removal of that friction is intoxicating.
You think it, you describe it, and something usable appears. Of course you're going to work longer hours. The feedback loop that used to take days now takes minutes. It's like someone handed you a fire hose and said: "go build."
And so we build. And build. And build some more.
Here's where I want to pump the brakes. Not on AI itself, but on the assumption that more output automatically equals more progress.
Speed without direction is just velocity
When the cost of producing something approaches zero, the bottleneck shifts. It moves away from can we build this? toward should we build this? That's a fundamentally different question, and it requires a fundamentally different skill set.
I've seen it so many times in the composable tech space: teams adopt shiny new tools, ship features at breakneck speed, and end up with a bloated product that solves problems nobody actually has. The tools weren't the issue. The lack of a clear destination was.
AI amplifies this pattern. It doesn't just let you build faster; it lets you build wrong faster. And the fun of building, that dopamine hit of seeing things materialise, can mask the fact that you're sprinting in circles.
The case for taste
If output is cheap, what becomes expensive? Taste. The ability to look at ten possible directions and choose the one that actually matters. The instinct to say "no" to nine good ideas because one great one deserves your full attention.
Taste isn't some abstract aesthetic sensibility. In practice, it's a combination of domain expertise, user empathy, and the hard-won judgment that comes from having shipped things that failed. AI can't give you that. It can generate options all day long, but it can't tell you which option your users will love, which one aligns with your strategy, or which one you'll regret building six months from now.
In other words: AI is an incredible how engine. But what and why remain profoundly human questions.
The rest nobody wants to talk about
There's another dimension to Eliason's observation that gets conveniently ignored. If ambitious people are working harder and longer than ever, that trajectory has a ceiling. And it's not a productivity ceiling. It's a human one.
The most valuable insights I've had in my career didn't come while staring at a screen. They came in the shower, on a walk, or halfway through a conversation that had nothing to do with work. Rest isn't the absence of productivity. It's the condition that makes taste possible.
When you're exhausted and hyperstimulated from twelve hours of AI-assisted building, your judgment deteriorates. You start shipping because you can, not because you should. The quality of your decisions, the very thing that differentiates you in an age of abundant output, degrades precisely when you need it most.
Simply put: if your competitive advantage is taste, and taste requires a rested mind, then rest is a strategic investment.
The real flex
I'm not arguing against enthusiasm. The energy around AI right now is earned. Building with these tools is genuinely exhilarating, and the people leaning in are going to shape what comes next.
But the people who will shape it best aren't the ones who work the most hours. They're the ones who pair relentless curiosity with the discipline to step back. The ones who use AI to explore ten directions in an afternoon, then sleep on it before committing to one.
The real flex in 2026 isn't how much you can produce. It's the restraint to produce only what matters.
When output is cheap, your greatest leverage isn't how much you build. It's the taste to know what's worth building, and the rest required to see the difference.
Frequently asked questions
What is the main argument of this article?
The article argues that in an era where AI makes output cheap and fast, the real competitive advantage is no longer how much you can build but whether you choose the right things to build. Taste—rooted in domain expertise, user empathy, and experience—and adequate rest become critical, because they enable better judgment about direction, not just speed.
How does AI change the way we should think about productivity?
AI shifts productivity from a question of "can we build this" to "should we build this." Since AI drastically lowers the cost and time of implementation, simply producing more is no longer impressive or strategically sound. Instead, the focus must move to deciding which ideas are truly valuable, sustainable, and aligned with user needs and long-term goals.
Why does the author emphasize rest in the context of AI and output?
The author emphasizes rest because high-quality judgment—and therefore good taste—requires a rested mind. Overworking, even with powerful AI tools, leads to deteriorating decision-making, where people ship features just because they can. Rest creates the mental space where insights emerge, helping you distinguish between noise and the few ideas that genuinely matter.
