AI Fatigue? Yea I Know. Here's How I Set Boundaries That Actually Hold

I hit a wall around month three of "AI for everything." Every tool promised 10x. Every morning brought three new products to evaluate. I was spending more time managing AI tools than doing the work they were supposed to accelerate. Sound familiar?

AI fatigue is real, and it's not a motivation problem. It's a signal that your tooling has outpaced your workflow. Here's what actually helped.

I set a rule: no new AI tool enters my rotation unless it replaces something I already use. Not "complements" — replaces. This killed 90% of my tool churn overnight. The bar isn't "is this good?" It's "does this make my current setup obsolete?"

The tools that stuck all share one trait: they handle the tedious edges of my work, not the core. Autocomplete for boilerplate. Summarizing long threads. First-draft outlines I'll rewrite anyway. The moment AI touches the part of the work where I actually think — architecture, trade-offs, the judgment calls — it slows me down because I'm reviewing instead of building.

I used to read AI news daily. Now I do one weekly pass. Nothing important breaks in 24 hours. The tools that matter are still there in a week, and they're better documented by then.

My default stack is boring and it works: one model for drafting, one for code, the editor's built-in completion. I only pull out something special when a task genuinely warrants it. Most tasks don't.

A lot of AI fatigue comes from tools that are fun to try and painful to depend on. The best test isn't the demo — it's whether you'd notice if it disappeared tomorrow. If the answer is no, it's not part of your workflow, it's a subscription.

What's your boundary? I'm curious what rules other people have found that hold up past the honeymoon phase.