How to Manage FOMO in the AI Era

A few years ago, AI was theoretical. Now it’s relentless. Every morning brings news of a new model, a new benchmark, a new framework that promises to change everything. And underneath it all, a constant drumbeat: if you’re not keeping up, you’re falling behind. (AI is already everywhere, often in ways organizations don’t fully realize.)

It’s exhausting. And it’s also largely unnecessary.

---

The Speeds-and-Feeds Era

Right now we’re in the speeds-and-feeds era of AI. It’s the same pattern we saw with early personal computers, digital cameras, and smartphones. Back then, value was measured in megahertz, megapixels, and gigabytes. Bigger numbers meant better products, or so we were told.

Today it’s benchmark scores. You hear that Claude beat Gemini, which just overtook ChatGPT, because one model scored 2% higher on some reasoning test. The headlines make it sound like everything that came before is now obsolete.

For most people using AI in their work, that’s noise.

---

What Actually Matters

What matters isn’t which model won the benchmark. What matters is whether the tool does the job you need it to do. I use Claude’s Sonnet model for most of my API work. It’s far less “capable” than Opus, and it costs a fraction to run. For what I’m doing in individual API calls for workflows, it’s perfect. The fact that a more powerful model exists doesn’t change that. (For the full picture of how I’m using AI right now, I wrote about my setup in detail.)

This is where the hype cycle does real damage. It creates a FOMO that convinces you to chase the newest thing, even when what you have works fine. It’s the same logic that tells you last year’s iPhone is suddenly inadequate because this year’s model benchmarks 20% faster. Maybe that’s true in a lab. But does it make your email app run better? Does it justify spending another $1,000? Probably not.

---

The Faster Cycle Problem

The AI world is worse because the cycle is faster. Every week there’s a new capability, a new tool, a new company promising to revolutionize your business. Many of them were invented last week. They have no track record. But the marketing is loud, and the implication is clear: if you’re not adopting this, you’re behind.

Here’s a better filter: does this solve a problem you actually have? And is the value it adds worth the real cost of learning it, integrating it, and maintaining it? Especially when you know there will be another “game-changing” tool six minutes from now.

---

Commit and Use

Once you commit to something, the key is to actually use it. That’s where you have to guard against FOMO again. If it’s working, let it work. Don’t rip it out just because something shinier appeared.

I use the Nano Banana Pro image model all the time. I love the results. Other models have launched since. I try them. But my workflow will stay the same until I hit a wall, either because the tool can’t do something I need or because another option is so much better that switching is worth the friction.

---

The Real Goal

That’s how I manage FOMO. Not by ignoring innovation, but by being deliberate about what I let in. The goal isn’t to keep up with AI. The goal is to make AI keep up with the work that matters.