Five hundred and twelve.
That’s how many new AI tools launched last week, according to Product Hunt. Five hundred and twelve. And if you’re anything like me, you saw at least thirty LinkedIn posts about why each one is “going to change everything.”
Your feed is a wall of fire. Everyone you know has apparently become an AI expert overnight. Your manager forwarded you an article about agents. Your cousin texted you about some new image generator. A guy you haven’t spoken to since college just DMed you: “Bro, have you tried this?”
Take a breath. I’m here to tell you something that an AI skills directory probably shouldn’t admit.
You can ignore most of this. And you should.
The AI FOMO Trap
Here’s what I’ve been watching happen since late 2024, and it’s only gotten worse.
Smart, competent people – the kind who were already good at their jobs – are suddenly spending their mornings reading about the latest model release instead of doing the work that got them promoted. They’ve got seventeen browser tabs open. They’re testing four different AI writing tools when the one they already had worked fine. They’re tweaking prompts for an hour when a five-minute Google search would’ve answered their question.
They’re becoming AI hobbyists on company time. And their actual output? It’s dropped.
I talked to a product manager last month who told me she’d spent the better part of a week “evaluating AI tools for the team.” She tested nine of them. Built a comparison spreadsheet. Made a Notion doc with pros and cons. You know how many the team actually adopted?
Zero.
She burned a full work week on research theater. The team went back to doing things the way they always had, and she’d lost five days she couldn’t get back.
This is what AI FOMO does. It convinces you that keeping up IS the work. It’s not. Keeping up is procrastination in a trench coat.
Everyone’s a Prompt Engineer, Nobody’s Shipping
Somewhere around mid-2025, “prompt engineering” became a personality trait. People put it in their LinkedIn bio. They started posting about “my prompting framework” like they’d invented fire.
And look, I run an AI skills directory. I literally make prompts and skills for a living. So believe me when I say: the obsession has gone too far.
The problem isn’t that prompting doesn’t matter. It does. The problem is that people are treating it like the point. It’s not. The point is the thing you’re trying to get done. The email. The analysis. The code review. The slide deck.
Nobody’s boss ever said, “Great prompting in Q4, Sarah.”
I wrote about a similar thing in The AI Hype Is Over – this pattern where the excitement about the tool replaces the discipline of using it well. The hype cycle is quieting down, but the FOMO hasn’t caught up yet. People are still chasing tools like it’s 2024.
The ones actually getting ahead? They’re boring. They found two or three things that work and they use them every day without posting about it. More on that in a minute.
Three Things Worth Caring About
Here’s a filter. When the next AI launch hits your feed (give it about forty minutes), run it through these three questions. If it doesn’t pass at least one, close the tab.
1. Does This Save Me Real Time on Something I Already Do?
Not “could it theoretically save time if I spent a week learning it and restructured my workflow.” Does it save time now, on a task you already do regularly?
If you write fifteen emails a day, an AI email skill saves real time. If you review code every morning, a code review assistant saves real time. If you take meeting notes weekly, an AI summarizer saves real time.
But if you don’t do data analysis, you don’t need an AI data analysis tool. Doesn’t matter how cool it is. Doesn’t matter if it went viral. You don’t need it.
The Lazy Person’s Guide to AI nails this – just find the handful of things you’d copy-paste and actually use. That’s the whole game.
2. Does This Make My Specific Work Measurably Better?
Not “better” in a vague, hand-wavy sense. Can you point to a specific output that improved?
A developer using an AI code review tool catches bugs they’d have missed. That’s measurable. A writer using a tone-matching skill produces cleaner first drafts. That’s measurable. A marketer using AI to A/B test subject lines gets higher open rates. Measurable.
“I feel more productive” is not measurable. “I generated 47 images today” is activity, not improvement – unless you’re a designer who needed 47 images.
3. Will I Still Use This Next Month?
This is the killer question. Because most AI tools have a half-life of about eleven days.
You discover it. You’re amazed. You show two coworkers. You use it heavily for a week. Then you quietly stop opening it. By month two you’ve forgotten the login.
Sound familiar?
Before you invest time learning anything new, ask yourself honestly: will I open this tool thirty days from now? If the answer isn’t a confident yes, you’re window shopping. That’s fine as entertainment, but don’t confuse it with work.
Permission to Not Care
Look, I know what you’re thinking. “But what if I miss the next big thing? What if everyone else learns this tool and I’m left behind?”
Here’s the thing. That fear is manufactured. It’s manufactured by the people selling you the tools, by the influencers building their audience on your anxiety, and by the algorithm that knows panic gets clicks.
The actual history of technology adoption tells a different story. The people who won with spreadsheets in the ’90s weren’t the ones who tried every new software. They were the ones who got really, really good at Excel. The people who won with the internet weren’t the ones who signed up for every social network. They were the ones who picked a platform and built something real on it.
AI is no different.
The best AI users I’ve met – and through this site I’ve talked to hundreds – are almost aggressively boring about it. They have their setup. They have their three or four go-to skills. They’ve tested them. They trust them. And they use them the same way every day, like a carpenter uses a hammer. No drama. No content about it. Just consistent work.
Nobody writes LinkedIn posts about their hammer.
The Twist: Selective Mastery Is the Actual Edge
This is the part where I’m supposed to say “so relax and don’t worry about AI.” But that’s not quite right either.
The real play isn’t apathy. It’s selection.
Think about it this way. Two marketers walk into 2026. Marketer A is using ChatGPT, Claude, Gemini, Copilot, Jasper, Copy.ai, Writesonic, and nine other tools. She’s got browser extensions on browser extensions. She knows the surface level of all of them. She can do a cool demo at lunch.
Marketer B picked Claude and one writing skill. She spent three months getting deep with it. She knows exactly which temperature settings work for her brand’s voice. She’s built custom prompts for every recurring task. She can produce in twenty minutes what used to take her a full morning.
Who’s more valuable to their company?
It’s not close. Marketer B ships more, ships faster, and her output is better because she actually understands her tool instead of dabbling in a dozen. She went deep where everyone else went wide.
That’s the edge. Not knowing about more tools. Knowing fewer tools better.
What This Looks Like in Practice
If you want a concrete system, here’s what I’d suggest:
Pick your number. For most people, two to three AI tools is plenty. One general-purpose assistant (Claude, ChatGPT, Gemini – pick one). One or two task-specific skills for things you do every week. That’s it.
Delete the noise. Unfollow the AI influencers. Mute the newsletters. Stop reading the “top 100 AI tools” roundups. If something is genuinely important, you’ll hear about it from someone you trust – not from a viral tweet.
Go deep, not wide. Spend your learning time mastering the tools you’ve chosen. Learn the shortcuts. Build templates. Develop muscle memory. The ROI on depth crushes the ROI on breadth.
Revisit quarterly. Every three months, take an honest look. Are your tools still serving you? Has something genuinely better emerged? If yes, swap. If not (which is most quarters), stay the course.
Judge by output, not by activity. The only question that matters: are you producing better work, faster? If yes, your AI setup is working. If not, adding more tools won’t fix it.
The Bottom Line
Five hundred and twelve new AI tools launched last week. You need maybe three of them. Probably fewer.
The most productive people I know have the most boring AI setups imaginable. They aren’t chasing the new thing. They aren’t posting about their workflows. They’re just… doing their jobs, a little faster and a little better than they used to.
That’s the whole secret. It’s not exciting. It won’t get you LinkedIn engagement. But it works.
So the next time someone tells you about the hot new AI tool that’s “going to change everything,” you have my full permission to nod politely, say “cool,” and go back to the three things that are already working for you.