I've been using quite a few AI tools lately.
At first, it was exciting. Some tools genuinely helped. They saved time, reduced friction, and improved my workflow.
But after a point, I noticed something. I was spending more time managing the tools than doing the actual work. Tweaking outputs, reworking formats, figuring out how to make them fit into my process when often, doing it myself would have been quicker and clearer.
That was when I took a step back.
I started looking at the tools I use not just what they do, but why I'm using them. What problem are they really solving? Are they improving my day-to-day, or just adding more layers to manage?
And then, there's LinkedIn.
Every day, I see posts introducing yet another AI tool. One that writes. One that codes. One that promises to think for you. I try to stay curious and explore them all, but honestly, it's easy to feel overwhelmed. The line between value and noise is getting thinner.
It feels like many tools are being adopted just to look modern, not because they solve meaningful problems.
Simon Sinek's idea from "Start With Why" comes to mind.
Most teams know what tools they’re using. Some understand how to use them. But very few stop to ask why they need them in the first place.
Often, AI is layered on top of broken systems instead of fixing what’s underneath. Instead of more productivity, we get more fragmentation. More tools to manage, less clarity in how we work.
So now, before adding a new tool, I ask myself a few questions. What specific problem is this solving for me or my team? Is it making things better, or just busier? Is it helping us think better, or just move faster?
If the answer isn’t clear, maybe the tool isn’t what needs fixing.