I asked an AI for restaurant recommendations. It gave me five perfect options. I picked one, ate, had a fine meal. When a friend asked what I’d eaten, I couldn’t remember the name of the place.
The experience wasn’t bad. It was frictionless. And it left almost no trace.
The gap wasn’t inefficiency — it was where memory, judgment, and understanding used to form.
This isn’t about nostalgia for a harder time. It’s about a pattern we’ve normalized: we’ve built tools that eliminate the gap between want and satisfaction, question and answer, curiosity and resolution. We call it seamlessness. We’ve assumed it’s progress. But what if removing the friction is making us less capable — not more?
Think about the last time you used an AI assistant. It answered before you finished your question. It completed your sentence. Efficient, yes. But it also interrupted the process of figuring out what you actually wanted to ask. It prevented you from discovering what you were trying to say.
Researchers at Harvard and MIT found something unsettling: when radiologists used AI assistants, their diagnostic accuracy improved. But when the AI wasn’t available, their unaided performance had declined. They had become dependent — faster with the tool, worse without it.
Coding assistants show the same pattern. Developers complete tasks faster. But they write more buggy code than those who did the same tasks unaided — and struggle to fix bugs without the AI. They’ve outsourced the reasoning, not just the typing.
Now consider therapy. A good therapist doesn’t rush to make you feel better. They sustain the conditions under which you can do the work — and that requires a specific kind of silence. The pause where something might form. Collapse that silence with reassurance or advice, and you interrupt the process. The distress might drop. But the integration doesn’t happen.
What happens when AI enters that space? A person in distress at 2am opens a chatbot. The distress decreases. But the question that was forming — the real material for the next session — was answered before it crystallized. The tension that, held until morning, might have produced insight: resolved, and gone. Not all relief is therapeutic. Most platforms aren’t designed to know this.
Cities show the same pattern. When planners over-optimize — separating uses, eliminating ambiguity, programming every space — the city becomes efficient and sterile. It stops generating the unplanned encounters where culture and solidarity form. Jane Jacobs knew this. The modernist housing project Pruitt-Igoe was designed with efficiency in mind: clean lines, separated functions. Within two decades, it was demolished. The design eliminated the productive tension that makes a city livable.
Education is where this hurts most. EdTech companies know that difficulty is not an obstacle to learning — it’s the mechanism. The ‘generation effect’: information is better remembered when you generate it yourself. ‘Desirable difficulty’: learning improves with effort. But instant feedback, no uncertainty, no struggle — students score better on immediate tests. They retain less, transfer less, struggle more with novel problems. They have the answer. They don’t have the capacity.
This is the pattern: across AI, therapy, cities, education — removing friction makes things faster. It also weakens the capacities it touches.
Byung-Chul Han speaks of a ‘burnout society’ where excessive positivity eliminates resistance and produces exhaustion. Hartmut Rosa describes ‘social acceleration’ — if you don’t speed up, you fall behind — and the result is alienation.
Here’s the twist: the tools we build shape us. And the shape we’re choosing — seamless, frictionless, instant — may be making us faster at consuming and slower at thinking, feeling, and becoming.
We can design differently. AI that occasionally asks ‘What do you mean by that?’ instead of answering. Therapeutic tools that preserve silence instead of filling it. Cities that keep their edges rough, their uses mixed, their future open. Education that defends the struggle instead of removing it.
The question is not whether we can build this way. It’s whether we should. And if we’re honest — if we’ve felt the exhaustion of being constantly predicted, preemptively satisfied, algorithmically managed — we already know the answer.
Stop optimizing for seamlessness. Start designing for the gap. That’s where you become human.
FAQ
Q: Aren't you just romanticizing difficulty? Tools are supposed to make life easier.
A: Making life easier isn't the same as making life better. The problem is when ease eliminates the productive struggle that builds capability. A tool that does the thinking for you isn't a tool — it's a crutch that atrophies your skills.
Q: So I should stop using AI? What's the practical takeaway?
A: No, use AI — but deliberately. Choose tools that slow you down when you need to learn, that ask questions instead of giving answers, that preserve the gap. The practical takeaway: design your own friction. Don't let the algorithm decide when you think.
Q: Seamlessness works for many things. Why is it suddenly bad?
A: Seamlessness is great for routine tasks (like booking a flight). The problem is when we apply it to domains where the process matters — thinking, learning, therapy, community. The same logic that optimizes a supply chain can destroy a classroom. Context matters.