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The Honest Case For Boredom

By Nigel Guy · 2 min read

The loudest people in AI content are perpetually excited — a new feature every week, a new "game-changing" release every month, an ever-refreshing sense that you're about to fall behind if you don't try the latest thing today. That excitement is mostly performance. The people getting genuinely good results tend to be doing something much quieter.

The rule: the calmest users get the best results — boredom, not excitement, is what actually lets a workflow settle into something reliable.

Why this holds

  1. Chasing every new feature means never mastering any single one. Genuine skill with a tool comes from repetition, and repetition requires sticking with something past the point where it stopped feeling new.
  2. Excitement biases you toward novelty over fit. The newest capability is rarely the one that actually solves your most common task — but it's the one getting all the attention, which pulls focus away from the boring workflow that would actually help more.
  3. A boring, stable routine is auditable. If you use the same handful of patterns repeatedly, you notice when something breaks. If you're constantly switching approaches, every failure looks like a new, unrelated problem instead of a pattern you could learn from.
  4. Boredom is what "it just works now" looks like from the outside. People who look unexcited about their AI setup usually aren't behind — they've already done the interesting part and moved on to using it.

The mechanism

  1. Pick your core tools and workflows deliberately, then deliberately stop evaluating alternatives for a set period — a quarter is reasonable.
  2. Let genuine improvements come to you through routine use, rather than actively hunting for the next thing to try.
  3. Notice when a new feature solves an actual recurring problem you have, versus when it's just novel. Only the first is worth adopting immediately.

What to skip

Skip feeling behind because your setup isn't the newest one discussed online — being unexcited about a tool because it already reliably does its job is not the same as being behind. And skip mistaking someone else's constant tool-switching for expertise; often it's the opposite signal.

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