The Effort Problem
The Version of Effort That Isn't
There's a version of effort that looks like work but isn't.
It shows up as reading five articles when you could read one. Following ten discussions when you could follow three. Downloading the outline for three books when you've already read none of them. Keeping a list of resources you intend to read, a backlog of things that will fix the problem once you get to them.
The effort itself feels productive. You're doing research. You're being thorough. You're staying on top of it.
And it never ends.
Effort and progress are not the same thing. We've built an industry that rewards effort visibility. The engineer who reads more, follows more, keeps up more — who ships more Jira tickets and writes more documentation — is often the one who gets recognized. The engineer who sits quietly with a hard problem and comes back three days later with a simple answer is often the one who gets asked why they didn't do more.
What AI Made Worse
AI tools made the effort loop faster. Not better — faster.
You can generate more. Read more. Review more. Write more. Ship more. And each unit of output takes less effort, which means you can produce more units — but the relationship between effort and actual understanding hasn't changed. You can read ten AI-generated explanations of a concept in the time it used to take to understand one.
The explanation looks like understanding. The reading looks like learning. The shipping looks like productivity.
But the thing underneath — the actual model of how the system works — hasn't updated.
The Three Shapes of Fake Progress
1. The Resource Accumulation Pattern
You keep a list. The list grows. The list never shrinks.
Articles to read. Videos to watch. Courses to take. Books to finish. Topics to understand. The list is a proxy for progress — you're preparing, you're staying on top of things, you're building toward something. But the list is also a way to not be in contact with the actual difficulty of the work. Preparation is safer than production. Research is less frightening than shipping.
2. The Velocity Illusion
You shipped more this week than last week. You closed more tickets. Your AI-assisted throughput is up.
This is real — in a narrow sense. You did more. But did you understand more? Did the work get better, or just faster? Is the codebase healthier, or just more generated? Are you more capable of solving the next problem, or just more capable of describing problems to AI?
Velocity is a proxy for progress, not progress itself. And the proxy breaks down when the effort per unit of output approaches zero.
3. The Coverage Compulsion
You read the Hacker News thread. You read the two top-level replies. You read the reply to the top-level reply. You read the comment that corrected the reply to the top-level reply. You feel like you understand the conversation — you followed it all the way through.
But what you have is coverage, not understanding. You know what people said. You know the shape of the disagreement. But the underlying technical question — the one that would have taken an hour of actual thinking to resolve — is still open. The coverage is a stand-in for the understanding you didn't build.
Why the Pattern Persists
The effort problem is persistent because it's self-reinforcing.
Every unit of effort you add creates a small release of anxiety. You did something about the problem. You advanced the ball. The anxiety goes down — briefly. But it doesn't stay down, because the underlying issue isn't being addressed. The anxiety comes back. You do more. The cycle continues.
The trap isn't that effort is bad. The trap is that effort-as-relief keeps you in the loop. You do something, you feel better, you stop, the anxiety comes back, you do something. The system perpetuates itself because each action produces a real neurological reward — the reduction of the discomfort that comes from not doing anything.
The engineers who break the cycle are not the ones who try harder. They're the ones who learn to sit with the discomfort of not-yet-understanding — and let that discomfort point toward the actual work, not the surrogate work.
The Experiment
This week, try an experiment:
Notice the moments where you reach for more information instead of sitting with less. Where you open a new tab instead of thinking about what you already know. Where you add something to the list instead of asking whether the list is the point.
Not to stop reading. Not to stop learning. Just to notice whether the reading and the learning are in contact with the actual problem — or whether they're a detour around it.
The difference matters. Not because curiosity is wrong. Because the detour feels like the destination, and eventually you arrive somewhere you didn't intend to go.
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